Alexis C. Madrigal | The Atlantic

Diagramming the Pacific Circuit

2025-03-18T06:00:00-04:00

Sometimes, riding my bike around Oakland, California, on a cold morning—bumping over abandoned railroad tracks, through the shadows of new towers, under leafy trees, past the encampments—I try to imagine all the money flowing in and through the place. In high-school physics, we had to sketch diagrams that laid out all the different forces acting on an object. What if I could do the same, but for the economic pressures on a place?

The Bay Area sits between the manufacturing economies of Asia and the consumer economy of the United States. In recent decades, it has been profoundly reshaped by the system of trans-Pacific trade, in which American corporations import manufactured goods from Asia through port cities strung along the West Coast, from Seattle to Long Beach. It’s a system I call the “Pacific Circuit,” and I’ve spent the past nine years trying to understand it.

For technology companies and their executives, this system has proved incredibly lucrative. For the communities like Oakland through which the goods travel—designated by mid-century urban planners as environmental-sacrifice zones—the story has been very different. Sketch a force diagram for Oakland, and you’ll see large vectors representing the technology industry and the containerization of cargo tugging at the city, pulling it apart.

Look around Silicon Valley today, at the gleaming buildings filled with white-collar workers sitting at their desks, and it can be hard to remember that electronics is actually a manufacturing industry. Few people today see Silicon Valley as a postindustrial landscape, but it once held so many factories that it had more Superfund cleanup sites than anywhere else in America. Only some of the production occurred in the valley itself; the electronics industry also pioneered the outsourcing of production, which ultimately hollowed out manufacturing in much of the country.

This article has been excerpted from Alexis Madrigal’s new book, The Pacific Circuit.

Outsourcing was integral to the rise of the electronics industry from its beginning, as it split its labor among three workforces. The engineers and researchers, overwhelmingly white men, had groovy offices and competitive work cultures. At the same time, firms employed huge numbers of factory workers in the United States, right there in Santa Clara Valley. Nearly all of them were women, and many were from countries that had been destabilized by Cold War intrigues. Hiring managers praised “fast fingered Malaysians”; this was not a proud era of American corporate life. Finally, these companies had assembly plants throughout Asia. In Malaysia, the island of Penang became known as “Silicon Island.” Semiconductor companies there established grotesqueries such as the Miss Free Trade Zone competition. This supply chain was notable to people all around the world because it was new and important.

[From the March 2024 issue: Meet me in the eternal city]

“In California’s Silicon Valley, for example, research and development work is carried out by well paid, usually male scientists and engineers. Circuits are then photographically etched onto layers of silicon in nearby assembly plants by women—50% of whom are Asian or Latin—for low wages in a highly pressurized environment,” wrote the British sociologist Diane Elson for a 1983 conference, Women Working Worldwide. “The new stage is relocated to Southeast Asia where the silicon slices are cut up, bonded onto circuit boards, sealed in ceramic coating and tested. From there components are sent to other third world countries to be assembled into watches, etc., or sent back to the U.S.”

Fairchild Semiconductor, which spawned so many chip companies—including Intel—that they became known as the Fairchildren, began outsourcing parts of its production process to Hong Kong in 1963. By the early 1980s, labor activists at the Women Working Worldwide conference estimated that 50 percent of the people in Asia’s free-trade and export zones were working for electronics companies. And in the years since, the industry’s production has shifted ever more abroad.

Americans at the time noticed these changes, and were troubled by their implications. In the early 1970s, Huey Newton, the Black Panther leader, lived in sight of the Port of Oakland. He wrote an essay titled “The Technology Question,” arguing that the United States didn’t need to occupy and run Korea or Malaysia as colonies. Instead, it could direct the development of such countries from afar, so that they would provide the labor and consumers that the U.S. sought. Newton had a crucial realization about distributed supply chains: Because they dispersed the ethical responsibility for violence, no one even had to buy into the military-industrial complex’s aims. “The U.S. capitalist has been able to spread out his entire operation. You put together his machinery in parts,” he wrote, “thus you are not building a bomb, you are building a transistor.”

Newton told the story of the writer Alex Haley visiting Africa. Haley saw “an old man walking down the road, holding something that he cherished to his ear. It was a small transistor radio that was zeroed in on the British broadcasting network.” The man had a product containing the fruits of Silicon Valley’s R&D, playing the mass media of the empire that had colonized his country. People liked the outputs of this technological system, and its downsides—which might have horrified them—were quite deliberately obscured from view.

For decades, San Francisco was the most important port on the West Coast. Cargoes were loaded and unloaded on finger piers that surrounded the city like a crown. But containerization changed all that. Holding the containers offloaded from ships until they could be taken by semitrucks to their eventual destinations required more land than the warehouses that had once housed such cargo had occupied. Finding hundreds of acres of storage in downtown San Francisco was impossible.

Instead, cargo operations moved across the Bay, where the once-sleepy Port of Oakland bet heavily on containerization. Capturing more of the trade from Asia had long been Oakland’s goal. In 1952, the city released a report on developing its shoreline. “The industrialization of China and the rest of the Orient is late in arriving. Because of its magnitude it will inevitably produce fundamental modifications in the world’s economic and political structure,” the report declared. “No one can say exactly what the impact of the industrial revolution in Asia will be on the economy of the Pacific Coast; the potentialities are beyond imagination.”

The report was not wrong, but delivering on the potentialities took some technological development. From the perspective of men who worked on the docks, there were two components. “Containerization is the technological underpinning of the global economy,” the longshoreman (and political scientist) Herb Mills told a San Francisco historian in 1996. “Because you can bet your sweet ass if all them transmissions was being hand-handled out of the hold of a ship and put on a pallet board and sent ashore, rather than twenty tons of transmissions being in a goddamn container box, transmissions would still be built in Detroit.”

Along with the second component—“computers, rapid communication, inventory control, and all that stuff,” Mills argued—containerization “is why jobs have flowed out of the United States.” Silicon Valley created the technology to make global supply chains work, and containerization made them practical. The Bay Area’s manufacturing jobs flowed overseas, and manufactured goods flooded back through Oakland.

[From the October 2014 issue: Made in America, again]

Of course, goods don’t move themselves, even in a container. That takes a diesel truck. And if thousands of boxes are suddenly coming into a port, that means thousands of trucks will be too.

In Oakland, the neighborhood that had to absorb the influx of trucks to move the goods was overwhelmingly Black and quite poor. Since the 1930s, the city of Oakland had been trying to push out the mixed-race residents of the neighborhood to make way for industrial development. The city-planning engineer I. F. Shattuck recommended two strategies. One: Racially segregate the area by building a highway. That was largely successful. And two: Continue to site heavy industrial facilities in the area near the port to crowd out the residents. That was only half successful. The industry came, but the people stayed, despite deteriorating conditions. When more Black people came to Oakland during World War II for wartime jobs, many found themselves confined to the neighborhood by discrimination.

Beginning in the late 1950s, under the guise of urban renewal, the city bulldozed huge chunks of the area’s main commercial strip, Seventh Street, destroying the commercial base of the Black community. It never recovered. The city of Oakland had declared chunks of the area blighted using a supposedly race-blind formula. In retrospect, it was more of an index statistic of environmental racism. The city’s elites had found a way to declare the areas where 98 percent of Oakland’s Black residents lived to be blighted, which, as the legal scholar Wendell Pritchett has argued, robbed everyone of all races who lived in those areas of their property rights. Versions of the same story played out in other Black neighborhoods that were adjacent to ports.

The Pacific Circuit has one more link. As the U.S. pushed countries to develop export-oriented economies, many of those countries found it advantageous to hold dollar-denominated assets. One reason that Americans have been able to take on debt is that many other countries have been more than willing to hold mortgage-backed securities and other financial instruments. With so much juice flowing through our real-estate system, it’s no wonder that prices have spiraled upward.

In the years after the Great Recession, rising real-estate prices in urban areas led many white Americans to buy homes in Black neighborhoods—in places like West Oakland. That is to say, the Pacific Circuit helps underpin gentrification, which has upended our cities in ways that we’re still figuring out.

The share of wealth held by the bottom 50 percent of Americans has not increased in the past 40 years. Many of our indicators of Black-white inequality are as high as they were in the mid-1960s, just a few years after the legal dismantling of Jim Crow. In America’s port cities, the professional classes have gained high-paying jobs, abundant credit, and appreciating home values. At the same time, the working classes have seen their jobs go overseas and their neighborhoods become unaffordable.

Oakland has a way of concentrating the power and problems of our country. As I worked on my book over the years, I couldn’t help but notice a bifurcation in my experience of this place. Many of my affluent neighbors are coming to see themselves more as nodes in a network of deliveries and pickups than as citizens of a specific place. Apps are making all kinds of services better and more convenient, even as they deepen our dependency on far-off companies and countries. But all this convenience comes at a steep cost. Oakland is struggling to provide essential public services, the kind that can’t be ordered up on an app. The superstar cities that once seemed immune to the emptying out of Main Streets across the country are now experiencing their own version of what happened to rural areas during Walmart’s expansion. Take a trip around Oakland’s downtown, and you’ll see the vacant storefronts.

After 50 years, the Pacific Circuit has become so powerful that it is breaking our cities. Many city officials and local entrepreneurs keep waiting for the effects of the pandemic to wear off, for the streets to refill and for the old normal to return. It might not. The pandemic pulled forward a structural alteration in the urban economy. Each DoorDash order that gets delivered or Amazon package that gets left on a doorstep makes running a local business that much harder. The old spatial order of the city is now overlaid by a digital one that’s linked to the global economy through companies such as Temu and Uber and Apple. What might be wonderful for an individual (so convenient!) has generated a collective crisis of the city.

Will Donald Trump’s tariffs change all this? I doubt it. Perhaps some other countries and trading partners will benefit, but the realities of the labor arbitrage that the longshoreman Mills observed remain. Even our most successful domestic manufacturers now rely on components manufactured all over the globe.

Could we, as consumers, simply stop using the logistical apps that have burrowed their way into our hearts and habits? I’m reminded of the man Alex Haley met. We love the outputs of the Pacific Circuit, despite their negative effects on the places we live.

In the 2010s, only one coffee shop stood on the west end of Seventh Street. Sometimes it seemed to be called the Seventh Street Cafe, other times the Revolution Cafe. If it was open, jazz was usually playing. The walls were adorned with old Black Panthers paraphernalia, a Malcolm X poster, an Aztec god, and the symbol for the artist formerly known as Prince. The café was attached to a big open lot filled with old furniture and little improvised structures on the verge of collapse.

The café, however, had almost nothing for sale. One time I went in and found a black-beanie-wearing Katrina refugee named Cedric tending the place. He was serious, smart, and had the sort of dark view of America you might expect from someone who got out of New Orleans because he thought the levee was going to break. I told him about the book I was working on. “Technology always gonna have a downside,” he said. He compared it to sci-fi shows. “It’s like when they go out in space and shit and they be looking for stuff and then they bring it back here and the people say, ‘We didn’t want that shit! Why you go out looking for that shit?’”

No one asked for this world, and yet here we are. Trucks rumbled by. I was the only customer. I wanted to support the place, so I tried to order food, but despite the extensive menu on the wall, all they actually had was coffee and day-old coffee cake. So that’s what I bought.

This is how local businesses work. You buy something for a few dollars—cake, coffee—and then you sell it, maybe, for a few dollars more than you bought it for. Do it a few times, and you can pay Cedric. Do it a few more times, and you can keep the doors open. This is the economy as we like to imagine it.

But this is not how everyone makes money. Private equity firms, hedge funds, and venture capitalists take in money from public and private pension funds, Middle Eastern sovereign wealth funds, insurance companies, huge asset managers, university endowments, and banks. In 2023, the world’s largest asset managers had more than $113 trillion under management, and they are willing to scour the earth to increase their returns.

While places like the Revolution Cafe have to rely on individual residents of West Oakland to come in and spend $3 so they can make 50 cents, companies such as Alphabet or Meta are not constrained by geography. They can show ads to the entire world, extract money from the internet, and pull the bulk of it to their headquarters.

Or take Uber, which took in billions of dollars of investment in the 2010s, a large chunk of it through the Japanese SoftBank, which itself drew funds from Saudi Arabia’s sovereign wealth fund. Uber was deliberately losing money to keep fares low to juice its growth; in a very real sense, when you took an Uber ride, the cost of your fare was subsidized by pumping oil out of the ground in Ghawar province of eastern Saudi Arabia. How can a regular cab company compete with that?

Even the companies operating out of the Port of Oakland have almost no relationship to the neighborhood economy anymore. The shipping and stevedoring outfits are headquartered in Asia or Europe. The goods they import and export almost all come from somewhere else. Oakland captures some tiny trickle of funds, but the big money flowing through the port exists on another plane of economic existence, inaccessible to anyone in West Oakland except through the very narrow conduit of dockwork, where the longshoremen who remain capture a tiny percentage of the value of the goods passing through as wages.

[Read: Corner stores are the new darlings of the global tech industry]

Battles over urban change tend to take on a cultural cast—coffee shops and dog walkers replacing barbecue joints and barbers. The real disagreement, though, is not over lattes but over whether a rising tide lifts all boats. And in city after city, the rising tide looks more like a flood. It is more than metaphor that the homeless encampments, filled with flotsam and jetsam, look like the remnants of a natural disaster. They are testament to our emergency. If you’re poor, there’s little you can do to stem the forces reshaping cities except wait and watch for the signs of change, disturbances in the wind or the tastes of the air that say Get out now.

We need a new way of talking about what’s happening in cities, one that faces the realities of the world that the pandemic accelerated into being. We might like to think that our individual behavior is separate from the decisions made by the technology companies, the flow of global supply chains, the dynamics of the real-estate system, or the racial history of cities—but it is not. City dwellers, rich and poor alike, are stuck in a set of systems that are generating ever rising housing costs, mass homelessness, displacement, and an attenuated urban life.

The fates of the residents of superstar cities are more connected to Main Street America and its workers than many think. And in that realization lies the potential for a different political coalition that can make a different set of choices.

The Polish theorist Zygmunt Bauman argued that we now live under conditions of “liquid modernity,” by which he meant that power no longer has handles that regular people can grab onto. Power and capital, when confronted, simply move, flowing to less challenging, less democratic places with cozier tax structures. To slightly paraphrase Bauman, we now live in a world where it often feels as if anything can happen but nothing can be done.

But some people have figured out ways to get a hold on power. All these liquid systems have to make contact with the physical realm at some point, and such chokepoints can have an outsized effect. Longshoremen’s power derives from controlling labor, and the ILWU has organized all the ports on the West Coast, creating a network that accounts for liquid power. The anti-fossil-fuel activists of the No Coal in Oakland coalition have stymied the creation of a bulk-export terminal in West Oakland. Climate change is a global issue, but it’s local activists who have kept coal in the ground in Utah.

Similarly, organizations such as the East Bay Permanent Real Estate Cooperative are pulling land, housing, and commercial properties out of liquid real-estate markets. They are separating property’s role as an asset from its role as a vital component of civic life, be it a roof over your head, a wildlife corridor, or a legacy business.

These organizations are acting locally, but their interventions take into account the nature of global power. That’s the lesson from the ports and docks. Liquid power and capital eventually have to touch the land, and when local action takes place in those places, the activists and reformers can use the circuits that supercharge our economy to scale their own impact.

This article has been excerpted from Alexis Madrigal’s new book, The Pacific Circuit.

Getting Back to Normal Is Only Possible Until You Test Positive

2021-11-09T06:00:00-05:00

Updated on Sunday, November 14, 2021 at 5:27 p.m. ET

When I first received the invitation to the wedding where I would eventually get COVID, I was on the fence about attending at all. My best friend had gone through a tough divorce and was remarrying. I was thrilled for him. His wedding had been put off repeatedly because of COVID, and this was the couple’s second try at a real ceremony. As a bonus, the wedding would take place in New Orleans, where my friend lives. I hadn’t seen him since before the pandemic. New Orleans is a miraculous place, and my favorite city to visit in America. The notion of a trip there shone out of the fog and dreariness of this whole era of history.

The downside, of course, was the risk of exposure to COVID. Sure, I’m vaccinated—two shots of Pfizer—and the wedding’s other attendees would all be vaccinated too. But breakthrough cases happen, and we’d be in New Orleans in October, a place where cases were still high and vaccination was inconsistent. One could not expect to not get exposed to COVID.

But then I reasoned both with myself and with my wife. COVID was unlikely to kill me, a vaccinated 39-year-old endurance athlete. I would be fine, and even if I gave the coronavirus to any of my family members, they too would almost certainly be fine. My wife is vaccinated, and our young children’s risk of serious illness, while not nonexistent, is very low.

I went back and forth, looking at flights and realizing that I’d probably have to travel through Las Vegas and have a considerable layover. I put off RSVPing one way or the other, and thought I would end up passively not going, the slow slide into a never-booked flight.

But for some reason, one morning in early October, I got the “last call” email about the wedding and I revisited the prospect. Everything was beginning to seem more and more normal. The radio station where I host a show was encouraging people to come back into the office. I saw laughing, maskless people in my social-media feeds and in restaurant windows. The Delta-variant surge was easing in most places. Cases were coming down. The really vulnerable were getting boosters. Kid vaccinations were on the horizon. Filled with a surge of love for my friends and New Orleans and a sense that, you know what, I’m ready to nose out into a new tier of risk, I booked a flight; I’d be going solo.

[Read: How easily can vaccinated people spread COVID?]

As the day approached, my wife and I had not run through every scenario. I still was not precisely sure how the wedding would work, COVID-wise. My friend is a doctor, and I knew the crowd would mostly be New York and California people. There would be no anti-vaxxers among the guests, and the invitation said they’d follow the local public-health protocols. And I think I didn’t want to know too much. If I’m honest with myself, once I decided to go, it felt like I’d committed to taking on some risk. At the same time, my wife and I had been in lockstep on COVID stuff for so long that I don’t think I had the courage to really say: Hey, I want to go to this wedding, and it’s probably going to be maskless and … are we really okay with that? I don’t think she wanted to be the one to say no to seeing such good friends, if I was willing to do it.

And so I boarded my flight without the kind of real conversation and—as important—return plan that we should have made. I spent hours in an N95 mask in the Las Vegas airport and on planes before arriving in Louisiana and heading to the welcome drinks.

I walked in and saw that people were all inside, fairly densely packed in a big room. No one was wearing a mask. Everyone was celebrating like people who haven’t seen one another for a long time, ready for a wedding weekend in the greatest city in America. For some reason, I was shocked.

I don’t know why I didn’t expect it to look like that. Maybe I thought we’d be in a garden under some nice string lights, mostly keeping masks on, in that maybe it helps way. I almost turned around and begged off the night of drinks, figuring that the next day would be less risky. But I’d come all that way. Here were my friend’s family and closest friends, the woman he’d fallen in love with. I just couldn’t do it. And all the everyone is vaccinated reasoning started to play in my head. I ordered a tequila and soda, pushed breakthrough infections out of mind, made some new friends, and had a great time.

The wedding was maskless too. But in a huge, airy, gorgeous building. There was a second line through the streets, and people danced and waved white handkerchiefs with the names of the bride and groom. We wore tuxedos and listened to old-time music at Preservation Hall and made jokes and got a little drunk, mostly hanging around outside. When that part ended, a bunch of people went next door to a huge party spot, but I left as soon as I saw the piano-bar-and-club scene there.

My wife was rightfully getting worried. It seemed not unlikely that I’d get exposed to COVID. Had we really been thinking clearly? Had we really wanted to take on that level of risk? Honestly, once I’d been in the situation, the realness started to unfurl. Outside the wedding events, I’d followed our protocols from home, staying outside, masking inside, etc. But attending the wedding was much riskier than I’d wanted to admit before I’d done it.

Walking back across the city, the energy of wanting things to be normal was thick. I felt it too. After spending so much of my time studying COVID, being a part of the response with the COVID Tracking Project, and writing many stories about the pandemic, I was over it. I was done. I don’t know that I could have admitted that to myself, but I just wanted it all to go away. And there in New Orleans, for a few days, it seemed like it had. Just look at all those people singing at the piano bar, dancing to Lizzo, arm in arm with friend and stranger alike.

[Read: Don’t be surprised when vaccinated people get infected]

The next day, away from the wedding and visiting with my best friend, it became more and more obvious. My wife and I needed a plan for my return. I’d do a rapid PCR test at the airport. At least that would get me somewhere.

My kids were so happy to see me, and after my negative result came back, to hug me. Was I actually safe? No, I knew I was not. I should have quarantined. But I had stuck my wife with the kids for four days, and I wanted to get back in the mix and help. That seemed like the right thing to do.

On Monday, I felt fine, but I took an antigen test anyway (negative). I scheduled a PCR test for the next day. By the time my appointment arrived, I’d started to have some postnasal drip and what felt like a possibly psychosomatic tickle in my throat. Tuesday night—four days after the wedding—my PCR result came back negative, and despite having what felt like a cold, I figured I was pretty close to being in the clear.

The next day, my symptoms were about the same. I did an intense Peloton workout and it felt fine, though maybe my legs were a little slow. I wasn’t eager to test again; a negative PCR test seemed good enough. But my wife heard me cough—one of only maybe 20 coughs throughout my whole sickness—and said, “Couldn’t you take another antigen test?”

I was on the phone with a young geographer, talking about doing research at Bay Area libraries, and kind of absentmindedly did the swabbing. When I looked down a few minutes later, I had tested positive. Maybe a false positive? I immediately took another antigen test and the little pink line was practically red, it was so dark. Wrapping up the call, I packed my things quickly, texted my wife the result, walked outside with an N95 mask on, and waited for all hell to break loose.

I was able to find a long-term rental on our block thanks to an angelic neighbor. I set my bags down inside and tried to figure out what I had to do. The worst-case scenario that I’d imagined was that I’d get sick, mildly, as I did. I ended up taking one day off from work, and even that was more of a precaution. I felt pretty sick, like when you have a cold, but I’ve probably been sicker 15 times as an adult. As someone who has thought so much about COVID science, it was almost interesting to experience: Oh! That’s what losing your smell is like.

[Read: Your vaccinated immune system is ready for breakthroughs]

But the real worst-case scenario was everything that happened to the people around me. My kids had to come out of school and isolate with my wife. A raft of tests had to be taken by everyone I’d had even limited contact with. (I was one of at least a dozen people at the wedding who got sick.) I had been with several older people, including my mother-in-law. For my wife and children, the tests went on for days and days, each one bringing a prospective new disaster and 10 to 14 more days of life disruption or worse.

But for me, the very worst part was my children. They knew, cognitively, that I was vaccinated and unlikely to get really sick. That said, COVID-19, for them, is a terrible thing. The past year and a half of their lives has been disrupted by this virus. They take precautions every single day not to have this happen.

They reacted in different ways. My 8-year-old could barely look at me—maybe out of anger, maybe out of fear. My 5-year-old daughter proved her status as the ultimate ride-or-die kid. She brought a chair down the street so she could sit 20 feet away from me outside in her mask, as I sat on the porch in an N95. I’m not sure which reaction was more heartbreaking. It was as if one never wanted to see me again and the other didn’t want to let me out of her sight.

These vaccines are amazing. I was and am fine. But as The Atlantic’s Sarah Zhang described in her recent article “America Has Lost the Plot on COVID,” we have developed the least logical system around them. “The least vaccinated communities have some of the laxest restrictions, while highly vaccinated communities … tend to have some of the most aggressive measures aimed at driving down cases,” Zhang writes.

In the communities where ignoring the pandemic is the norm, COVID testing may not be standard—and even when testing takes place, the required isolation and quarantining procedures are sometimes ignored. As I’ve found, you really are on your own to set the limits of what you do. And given the requirements and difficulties of isolating, I can imagine that few people are willing and able to follow the letter of the law.

A positive test sets in motion huge hassles and anxieties for anyone you’ve been in contact with. This is how we slow the spread, right? It makes sense. And also, families and businesses and schools and event venues are trying to return to normal. Perhaps the risks of going into an office every day are far less than those of going to a wedding in New Orleans. But in the course of actual normal life in the places that have fought this virus the hardest, there will be more positive tests. Just in the past few weeks, I’ve seen more and more of them around me here in the Bay Area.

For people pondering edging back into normal life, or trying to jump in headfirst as I did, it’s easy to do the risk calculation only about physical health; that’s really what this was about for so long. But the vaccines changed that, and we need to update our mental spreadsheets. The life disruption—the logistical pain you cause those around you—is now a major part of any bad scenario. As I write this, I’m now 10 days past my first symptoms, but I continue to test positive on antigen tests, and so I have not returned home. I haven’t hugged my kids for 10 days. They missed a whole week of school, and my wife’s work life got turned upside down—even though they never tested positive or got sick. I blame no one but myself for this. We cannot will this pandemic to be over. Lord knows I tried.

I understand that my scenario is far better than could or would have played out in a pre-vaccination world. So many communities were hit hard. I have enjoyed tremendous privilege to keep my risk low before now. We got lucky that I didn’t infect anyone vulnerable. I’m so grateful my wife insisted that I take just one more test.

In social worlds like mine, though, where most people do work from home, where people have minimized risk and gotten vaccinated, we’re at a weird moment. Things aren’t likely to change that much for quite some time. Even after however many kids get vaccinated, there will still be breakthrough infections. Other variants could spread. Maybe we’re in this space for another year or two or three. One way to put the question of endemicity is: When do we start treating COVID like other respiratory illnesses?

[Read: The coronavirus is here forever. This is how we live with it.]

I don’t know the answer. And I’m not even sure who should be trying to answer the question. There are many outstanding mysteries about long COVID. There are still so many unvaccinated Americans, and that number seems unlikely to shift a lot anytime soon.

Right now most policies appear designed to make life seem normal. Masks are coming off. Restaurants are dining in. Planes are full. Offices are calling. But don’t be fooled: The world’s normal only until you test positive.

The Messiest Phase of the Pandemic Yet

2021-08-15T07:30:00-04:00

The numbers are remarkable. More than 100 million people in the United States have likely been infected by SARS-CoV-2 and 167 million people are fully vaccinated. Yet despite this huge population of people with at least some level of immunity, the Delta variant has sent case and hospitalization numbers soaring. Florida is on its way to having twice as many people hospitalized now than during any previous wave, when essentially no one was vaccinated.

One way to think about it, as the epidemiologist Ellie Murray has laid out, is that if Delta is as transmissible as the CDC thinks, we need a much higher percentage of our population vaccinated for immunizations and natural infection alone to cause the virus to peter out. Even when the huge majority of people in a given place have gotten the coronavirus or a shot, there might still be outbreaks, as the Brown University public-health expert Ashish Jha fears will happen in South Dakota after the Sturgis Motorcycle Rally.

These realities have already smashed the more optimistic projections of late spring, including my own. Having stared at these numbers for months and months with the COVID Tracking Project at The Atlantic, I never thought that we’d see hospitalization numbers higher than they were during the winter peak in any state. But here we are.

It’s time for a data-driven reset on the basic knowns and unknowns of this pandemic, a task that must be undertaken with great humility. The virus keeps changing, and so does our understanding of the social and biological components of the pandemic. But in exploring both the knowns and the unknowns, we can see how complex the pandemic has become—and that we’re still lacking crucial data because of the failings of state and federal government.

The Knowns

1. The vaccines work very well to reduce the likelihood of an individual being hospitalized or dying from COVID-19.

Let’s begin with the best bit of good news. Based on the available data, all the vaccines given in the United States appear to confer a solid level of immunity against severe outcomes such as hospitalization and death. Over a three-month period this summer, the CDC recorded 35,937 deaths from COVID-19—but just 1,191 of those who died were fully vaccinated. In other words, 96.7 percent of deaths this summer have been in the unvaccinated. Hospitalization data look similar, with few fully vaccinated people requiring hospitalization.

The CDC’s data mirror what other institutions have found. The New York Times was able to compile data from most states on the percentage of people with breakthrough cases who were hospitalized. Although the proportion of breakthrough patients varied by an order of magnitude from as low as 0.2 percent of total hospitalizations in Texas to 4.7 percent in Arkansas, in every state more than 95 percent of hospitalized people were unvaccinated. This is also consonant with data from the United Kingdom, which, because of its National Health Service, has better data than exist in the U.S. Many other, smaller studies in various states show very similar results.

In Israel, data showed that fully vaccinated patients who were hospitalized were much more likely to have comorbidities such as hypertension, diabetes, and heart failure.

So this is known: At this moment in the pandemic, fewer than 5 percent of the people being hospitalized and dying are fully vaccinated.

2. Even high levels of vaccination in local regions are not enough to prevent the spread of the Delta variant.

Although the randomized controlled trials on vaccine efficacy indicated that the vaccines conferred substantial protection from symptomatic infection—with efficacies touted at about 95 percent for the mRNA vaccines—their real-world performance is almost certainly lower, though to what extent is not exactly clear. (More on that in a minute.)

At the same time, more and more evidence suggests that some people with breakthrough infections can transmit the virus. Combine those two facts with Delta’s extremely high transmissibility, and we’ve found ourselves in a world where even well-vaccinated communities can see quick growth in cases. Back in the pre-variant days of the pandemic, 70 percent vaccination was seen as a rough goal to achieving herd immunity, the point at which viral growth could no longer be sustained in a community. Yet San Francisco, which has 70 percent of its population vaccinated, has nonetheless seen a similar case surge to the one in Maricopa County, home to Phoenix, Arizona, where only 43 percent of residents are vaccinated.

Although, statistically, counties and states with higher vaccination rates have lower case counts and hospitalization rates, they have still become areas with high levels of community spread.

There are probably different transmission dynamics within these cities. Young, unvaccinated people are likely responsible for a good deal of transmission. There are, after all, still 50 million kids under 12 who are not eligible for the vaccines. But it’s also likely that older, vaccinated people are responsible for some spread as the amount of virus increases in the community.

In a number of places, this has not caused major increases in hospitalizations, but that’s not universally true. Perhaps the most startling example is The Villages, in Florida. Centered on a retirement community, this metropolitan area has close to 90 percent of its over-65 population immunized, yet it has seen a surge of cases and hospitalizations.

3. There is still a lot of randomness to where the worst outbreaks occur.

Although, again, statistically, places where more people are vaccinated are faring better than places where fewer people are vaccinated, there is enormous variability lurking in the numbers. Some of it may be explainable by policy decisions and political allegiances. But some of it is also just luck.

Back in the spring, when the variant we were most worried about was called Alpha, Michigan and almost Michigan alone got absolutely torched, matching its peak for hospitalizations from the winter. This didn’t happen anywhere else, though some epidemiologists expected it to, based on the experience of European countries. Alpha just kind of went away, and it seemed like the U.S. might be in the clear.

Enter Delta. In this surge, a piece of Missouri began to take off before the rest of the country. Would it be like Michigan? As we all now know, the answer was no. The southeastern United States is now experiencing huge outbreaks as many states come close to matching or surpassing their pandemic peaks in cases and hospitalizations.

The health-care system in north Florida is under pressure that few places have seen at any time during the entire pandemic. Why there? Why not somewhere else with similar vaccination rates and political opposition to viral countermeasures? No one knows with total certainty, and we’re unlikely to ever find out.

4. Kids remain at the lowest risk of any group for hospitalization and death. And kids are at higher risk of hospitalization now than ever before in the pandemic.

One of the rare blessings of the pandemic has been that children have proved uniquely able to deal with the attacks of SARS-CoV-2. Their risk of serious illness has always been very, very low. And the available evidence suggests that this has not changed. COVID-NET, which is a CDC sample of hospitals, shows that the rate of hospitalizations for kids has varied in the pandemic from about 0.3 hospitalizations per 100,000 to 1.5 hospitalizations per 100,000. That rate is rising quickly now, but it remains within the historical envelope of the pandemic in the United States—at about one hospitalization per 100,000 children. Similar trends hold true for age subgroups such as 0–4, 5–11, and all under 18. And hospitalization rates for children younger than 18 remain considerably lower than the peak hospitalization rates of adults 18–49 (10 in 100,000), 50–64 (28 in 100,000), and 65 and older (72 in 100,000).

That said, the CDC’s COVID-NET data do not cover the whole country—they pull data from 99 counties across 14 states, representing about 10 percent of the U.S. population. And they have no data from hospitals in the worst-hit state, Florida.

If we look at the pediatric hospital admissions gathered by the Department of Health and Human Services, we can see that they are at record highs now, surpassing the worst day of the winter surge and still headed straight up. Although the overall numbers are still low—the seven-day average of hospital admissions is fewer than 300 per day—children in the Southeast are being hospitalized at almost double the rate as at any other time in the pandemic. Some states are seeing two or even three times as many admissions of kids as at any time in the pandemic.

It’s important to note that there could be multiple reasons why we’re seeing this increase in pediatric hospital admissions. Taken alone, the increases do not mean that the average Delta-variant infection is more severe in children than previous SARS-CoV-2 strains. In an early Scottish study, the data were worrisome, but the bigger problem is that almost all the data available for school decision makers are from before the Delta wave. The nation’s children will be back in the classroom before we’ll definitively know whether Delta hits kids harder than previous variants.

Still, the kids’ numbers are tracking quite closely with their adult numbers—and it’s not totally clear whether this is a meaningful shift compared with earlier stages of the pandemic.

And what all the data taken together seem to suggest is that there is an absolutely monster wave of coronavirus circulating in the South, and that our current case numbers do not come close to capturing the true number of infections in that region of the country.

5. Vaccinated people can be infected with and transmit the virus.

Breakthrough infections for vaccinated people were always going to happen. No vaccine provides perfect immunity, and the immune system is strange and somewhat unpredictable.

But there was some logic to the hope that maybe these infections wouldn’t transmit the virus forward. Because the large majority of vaccinated people have mild symptoms, the thinking went, perhaps they would have lower viral loads, and therefore be less likely to spread the virus.

How well the vaccines protect against any infection (not just symptomatic infection, hospitalizations, or death) is a hotly disputed topic. A variety of data suggest that vaccination does help prevent exposures to the virus from becoming infections, and that, obviously, helps slow the spread of an outbreak.

But it’s also become clear that vaccinated people who do get infected can spread the virus. The most recent piece of evidence came when American scientists were able to culture virus from samples taken from vaccinated people who’d gotten infected. Those same people showed similar viral loads to unvaccinated people. And yes, even those with asymptomatic infections.

Although that’s bad news, there is some good news too: Breakthrough infections appear to be significantly shorter than infections in the unvaccinated. That would reduce the amount of time that people with breakthrough infections could spread the virus.

There will undoubtedly be many more studies along these lines, and the papers cited above are preprints, meaning that they have not yet been peer-reviewed. But the data, including unpublished studies cited by public-health officials, are pointing in the same direction: Breakthrough infections are happening. And when they do, those people can spread the virus.

The Unknowns

1. How many people have had COVID-19? That is, how many people have some immunity, from vaccination or prior infection?

We already know that we’ve been undercounting the true number of infections over the course of the pandemic. Sure, we have a tally of cases, but that count is almost entirely of cases confirmed by a positive test result. And as the conditions of the pandemic have changed, the relationship between that case count and the actual number of infections has varied. It’s such a basic question that it seems absurd to ask, and yet we simply don’t know how many Americans have had COVID-19.

This is not a purely academic question. Natural infection should confer some level of immunity, though whether natural immunity is as protective as the vaccines is unclear. Regardless, it’s important to know how many naive immune systems are out there for the virus to get at. We know the number of fully vaccinated people with reasonable precision—call it a bit shy of 170 million people. But how best to estimate how many people have been infected? The CDC has done some testing of the levels of antibodies in the U.S. population, but the data are incomplete and imprecise; you could not simply multiply the percentages of people with antibodies by the number of people in the country and get an accurate number.

Through hospitalization and death data, we know the rough shape of the infection waves. There was a large New York–centric wave in spring 2020; a smaller, southern-focused summer wave; then last winter’s massive nationwide wave. In 2021, there was a small spring wave centered on the upper Midwest, and now there’s the current massive summer wave in the Southeast.

One can add up all the cases from those waves and find roughly 36 million confirmed cases. But for each era of the pandemic, there has been varying testing availability and usage—not to mention a large pool of asymptomatic infections. That’s led to very different and still-unknown case-detection rates through time. Public-health officials know they severely undercounted in the beginning of the pandemic, a problem that improved through the year. But in 2021, the availability of at-home tests and COVID-19 denialism—particularly in the less-vaccinated right-wing areas where the virus is flourishing—among other factors, may have driven down the number of cases that we’re confirming. Vaccinated people with mild cases may also have less incentive to get tested, because they know they are unlikely to have major complications. The CDC itself initially did not recommend that fully vaccinated people get tested after exposure, before changing that guidance in late July. Some institutions also dropped testing regimes for vaccinated people, and some testing sites scaled back their services. All of this is to say: Both interest and access may be lower than earlier in the pandemic.

[Read: The vaccine scientist spreading vaccine misinformation]

The CDC does make an estimate of the total number of infections. That number was 120 million with a range from 103 million to 140 million before the Delta wave. How many people have been infected since June 1? The CDC has counted about 3 million cases, but who knows what the relationship of that number is to the true number of infections.

Then there is one final unknown regarding immunity: What is the overlap between the people who have been infected and the vaccinated? The U.S. does not have these data, but they’re a pretty important component of our current situation. If there were no overlap between the 170 million vaccinated, and there have been 150 million infections, we’d be looking at 320 million people with some immunity, nearly the whole country.

But it’s likely that there is a good deal of overlap. And the more overlap, the more dry tinder there is to keep this pandemic going. When everyone in the United States has been vaccinated or infected, it won’t mean that the pandemic is over, but our collective immune systems will have become a more formidable opponent for the many strains of SARS-CoV-2.

2. How well do the vaccines work to prevent infection?

As noted, all available data show that the vaccines remain remarkably effective at reducing the risk of hospitalization and death from COVID-19. But past that very important outcome, the data are much murkier.

So the effectiveness of the vaccines is a matter of perspective. What people might refer to as vaccine effectiveness can have different meanings, and therefore the nature of their data and calculations can vary. If we want to talk about vaccine effectiveness precisely, we need to specify effectiveness against an outcome (infection, symptomatic disease, hospitalization, death). We also need to define the temporal parameters: across how long of a time period? When were the vaccines administered? We need to break out the different vaccines. We need to have a rough understanding of the variants in circulation when a given study was done. And finally, we need to specify which population is under discussion—young, old, immunocompromised, health-care workers, etc.

Sure, all these factors can be rolled up, and had to be rolled up during the vaccine approval process, into a single number to determine vaccine efficacy. That number came out to 95 percent in the original trials for the mRNA vaccines.

Effectiveness is what comes from empirical observations. As these results have been released, what we’ve usually heard is something like this from the CDC vaccine-effectiveness page: “mRNA COVID-19 vaccines offer similar protection in real-world conditions as they have in clinical trial settings, reducing the risk of COVID-19, including severe illness, among people who are fully vaccinated by 90 percent or more.”

But here’s the thing. Change one of the crucial variables, and the picture changes. That’s led to the publication of multiple conflicting studies. A New England Journal of Medicine study found Pfizer’s effectiveness against symptomatic disease from the Delta variant to be 88 percent. That’s great!

But a preprint paper working with Mayo Clinic data found much lower effectiveness against infection, especially for the Pfizer vaccine, which the authors contend had an effectiveness of just 42 percent against infection after Delta became prevalent in the populations that they studied. These findings are both surprising and disconcerting.

There is wide variability in international studies as well. In slides prepared by the CDC for the expert panel that provides recommendations on vaccines, we can see the same kind of difficult-to-explain results. Pfizer looks great in the English/Scottish and Canadian data, even against infection and symptomatic disease, but Israeli and Qatari data do not show the same performance.

It may be that these data can be reconciled in some way. For example, the NEJM study looked at symptomatic disease, while the Mayo Clinic paper may have picked up more asymptomatic disease. But even that would not be too reassuring at a population level because, as noted above, it now seems likely that vaccinated people with asymptomatic infections can spread the virus, at least sometimes. And the Israelis, at least, didn’t seem to show a major difference between vaccine effectiveness in preventing infection and symptomatic infection.

There are many other possible explanations. Could the effectiveness of the vaccines fade more quickly than hoped, so those with less recent vaccinations are more likely to get infected? Could there be a problem with the distribution of some of the Pfizer doses, which require the most intense cold storage of any of the immunizations? Maybe the way that the studies picked their subject populations or did the data work pushed the results one way or another. And none of this touches on the effectiveness of the Johnson & Johnson vaccine, which had a lower efficacy in trials.

For the time being, it seems prudent to assume that it’s possible that one or more of the vaccines will be found to have substantially lower real-world performance in preventing Delta infection and/or symptomatic disease.

3. Why have so many more people been hospitalized in the United States than in the United Kingdom?

After a glorious June, when cases in the U.S. fell to their lowest levels since the beginning of the pandemic, more virus began to circulate around the country. The United Kingdom had just seen a surge, but it did not result in an accompanying surge of hospitalizations or deaths. That seemed to portend good things for the United States.

On June 1, when the Delta wave began to take off in the U.K., approximately 40 percent of its population had been fully vaccinated. The wave ran high—reaching 80 percent of the case peak from the winter—but hospitalizations reached only 15 percent of the winter peak before the wave began to recede. This was fantastic news from a British perspective.

Fast-forward a month and cross the Atlantic Ocean. When the Delta wave began to take off in early July in the U.S., roughly 47 percent of the U.S. population was fully vaccinated. But in the American context, hospitalizations have not only risen to 50 percent of their pre-pandemic peak but continue to rise. Several southern states are seeing their all-time peaks in hospitalizations, despite three previous waves of infection and millions of vaccinated residents.

Florida had a larger share of its population vaccinated at the start of the American Delta wave than the U.K. did when it saw the variant’s exponential rise. Yet, in Florida, the state now has nearly double the number of COVID-19 patients in hospitals than it has ever had during the pandemic.

It will take a long time to tease out the different factors between the U.S. and the U.K. Obviously, for example, the United States is a much larger country with distinct types of urban structures.

But there are several other immediate pathways for thinking about why things are playing out so unlike in the U.S. The U.K.’s vaccination strategy was substantially different from the American one, despite the overall similarity of vaccination rates. It could also be that American unvaccinated people were spread more unevenly through the country than the unvaccinated in the British context, with different epidemiological effects.

Looking at Florida, though, one thing stands out. For reasons few epidemiologists could understand, the state had not been hit as hard as neighboring places with similar populations and politics. Look at almost any metric before the Delta wave, and Florida fared pretty well relative to New York, California, or Illinois. Not until the current Delta wave has Florida experienced a surge comparable to those seen in other big states.

The U.K., by contrast, was hit with two massive COVID-19 waves in which the death rate was nearly twice what it was in the U.S. That suggests that a much greater percentage of the U.K. contracted the virus, giving them some natural immunity. The virus may have run out of bodies to attack.

Perhaps, in Florida, the state’s good fortune in previous waves—along with the political opposition to societal countermeasures—could be one of the factors driving this gigantic increase in COVID-19.

4. What percentage of infections are we confirming as “cases”?

Positivity rates—as my colleagues at the COVID Tracking Project argued over and over—are a fraught metric, especially when used as a threshold for crucial decisions. However, as a coarse measure of whether testing is adequate, they do help tell the story of the case numbers that are coming out of the American South.

Note that the goal for positivity rate in most states was under 3 percent. In the Florida panhandle and adjacent counties in Alabama and Georgia, the positivity rate in many counties is greater than 25 percent. That’s comparable to many jurisdictions in the days of highly constrained testing supplies during the first wave of the pandemic. Not coincidentally, these areas are also seeing massive increases in hospitalizations, and because severe illness is largely occurring in unvaccinated people, we will also see a rise in deaths.

On its face, elevated positivity rates have historically meant that public-health surveillance was missing a greater share of the infections in a community. But there’s more evidence that this is what’s happening. Relative to previous waves, the ratio of cases to hospitalizations is lower. Last winter, we confirmed 12 million cases in December and January. This wave, we’ve confirmed fewer than 3 million cases since July 1. Last winter, we peaked at more than 120,000 COVID-19 patients in the hospital at one time. Right now, we’re already over 64,000. So we are showing 25 percent of the cases and 50 percent of the hospitalizations.

In addition, at-home tests such as the Abbott BinaxNOW and other types of testing in institutional settings like schools may not be getting reported to authorities. It’s really all a mess.

There are more precise ways to look at these data in particular hospital systems and areas, but the upshot is that either Delta is making people sicker—which, as noted above, is a real possibility—or our case-detection rate has fallen. Or, just to muddy things, maybe both.

5. How many people will die?

For people in countries with access to vaccines, the good news is that it seems almost certain that fewer people will die in this wave of COVID-19 than in the winter surge. Fewer both in absolute terms and in the percentage of COVID-19 infections as the vaccines make many more people less vulnerable to severe illness. This is an unmitigated good (and one that is a moral imperative to extend to the rest of the world).

But millions of unvaccinated people are still getting infected. And for them, the old mathematics of COVID-19 will hold. Older people who get sick are more likely to die. The more comorbidities an infected person has, the more likely they are to die.

Here, again, on a national level, there is good news. The most vulnerable group—people older than 75—are being infected at about 10 percent of the rate at the winter peak. That’s a major decline.

But in specific areas, which is to say, yet again, Florida, that trend is not holding. There, the rate of hospital admissions is up for every single age bracket, from young people to those older than 80. And people who are between 50 and 79 years old are being admitted to the hospital at higher rates than ever in the pandemic. Some of those people are going to die, and the numbers will not be small.

There is also hope that better therapeutics and improved care practices will push the death rate down. But there is pressure in the other direction too. With the hospitals in hard-hit areas under tremendous burden, they are less likely to be able to provide the highest standard of care.

Florida is already reporting a seven-day average of more than 150 deaths a day, a number that seems likely to rise as the statistics work their way through the system. Florida’s peak over the winter was about 180 deaths a day.

The big question in all this, then, is: Does Florida portend what’s likely to happen in the rest of the country? That’s not yet clear, and let’s hope not.

6. What are the risks of long COVID?

This section is more a list of questions than it is of answers. There’s so much that we don’t know about the risks of long COVID. For example, how susceptible are adults with mild infections to long COVID? How about kids? How about breakthrough infections? And asymptomatic infections?

Post-viral syndromes have long been understudied. Long COVID is a bundle of the unexplained aftereffects of a virus that we’ve never encountered before. That’s an especially hard thing to study. Yet, pushed by patient advocates, scientists are trying to get a handle on the depth of the problem.

According to one meta-analysis of research, at least some symptoms persist longer than two weeks for 80 percent of COVID-19 patients. An English survey found that more than 10 percent of people who had COVID-19 said the disease’s effects were still having a “significant effect on my daily life” 12 weeks after infection. Another found only 2 percent of people experiencing symptoms 12 weeks after infection. And another found 38 percent of post-COVID people with at least one symptom 12 weeks out. Many research studies and anecdotal stories speak to the prevalence of these problems. But the specifics are really hard to pin down, as are the risk factors.

And what of post-vaccination infection? Will the immunizations prove effective at reducing long COVID too? One small study of health-care workers found extended symptoms in some people with breakthrough infections. If the Delta variant really begins to move across the whole country, there will be a lot of breakthrough infections.

If you are relatively young and healthy, you could always bet that you’d probably come out of a COVID-19 infection just fine, neither hospitalized nor dead. That’s doubly true for the vaccinated. But long COVID is the big, spinning question mark in all the risk calculations that human beings must continue to make.

Dave Luo and Lindsey Schultz contributed reporting to this story.

The Threat That COVID-19 Poses Now

2021-04-02T15:36:57-04:00

After more than a year of pandemic, after months of an aggressive vaccination campaign, the United States should finally be better positioned to protect itself against the coronavirus. Nearly all of our long-term-care residents are vaccinated. Tens of millions of other people have been vaccinated, and tens of millions more have some level of immunity from previous infection. With more people protected, a new surge could behave differently, but early signals from the states with rising case numbers suggest that this will not universally be the case.

Just look at Michigan, the leading edge of this new surge. Cases are going up quickly, and hospitalizations are moving in lockstep—just as they have in past surges. This is a bit of a surprise. Given that so many older, more vulnerable people have been vaccinated, one might expect a divergence in the number of cases and hospitalizations. For the immunized, this disease is essentially harmless. Washington State, for example, has reported just 100 cases and as few as eight hospitalizations among its 1.2 million fully vaccinated people. But for the vulnerable and unvaccinated, COVID-19 is as devastating as it has always been.

The United States is entering a new phase of the pandemic. Although we’ve previously described the most devastating periods as “waves” and “surges,” the more proper metaphor now is a tornado: Some communities won’t see the storm, others will be well fortified against disaster, and the most at-risk places will be crushed. The virus has never hit all places equally, but the remarkable protection of the vaccines, combined with the new attributes of the variants, has created a situation where the pandemic will disappear, but only in some places. The pandemic is or will soon be over for a lot of people in well-resourced, heavily vaccinated communities. In places where vaccination rates are low and risk remains high, more people will join the 550,000 who have already died.

Cases are rising sharply in several different cities, but the patterns look different. In Michigan, some smaller, whiter counties have vaccination rates twice as high as in Detroit, where rising cases are concentrated and the vaccination rate among the city’s mostly Black population is still low. According to national survey data, in line with political divergences over masks and social distancing, vaccine hesitancy is now highest among Republicans and white evangelical Christians. In Philadelphia, zip codes that are relatively whiter but have lower educational attainment have experienced the most case growth over the past 30 days. Baltimore’s outbreak is growing too, but the data are messy.

In these places, and in other hot spots around the country, the rise in cases is an acute crisis that public-health officials should battle with all the available tools, as my colleague Zeynep Tufekci noted this week. CDC Director Rochelle Walensky spent her weekly press conference on Monday pleading with the American people, noting “the recurring feeling I have of impending doom.” She asked the country to “work together to prevent a fourth surge,” and compared the pandemic’s path here to the experience of Germany, Italy, and France, where cases have spiked dramatically in the past few weeks.

But the United States might chart its own, very unequal track in the coming weeks. Three distinct factors are now shaping this country’s pandemic experience.

First, the United States did a terrible job preventing transmission of the disease. The country's level of excess death—the margin over the number of deaths expected in a typical year—has been high, signaling that the pandemic's true toll has been even steeper than the officially tabulated COVID-19 deaths. Most other countries did not experience the same levels of consistent transmission. A year of unchecked spread means that our 30 million reported cases are a fraction of the total number of people who have been infected. Most estimates place the number closer to 100 million, and possibly tens of millions more.

So unlike in Germany, for example, which fairly effectively suppressed the virus, tens of millions of people in the U.S. have some level of immunity. While reinfection may be more common with some current or future variants, it has been rare so far. That high level of past infection should now help reduce transmission of the virus via population immunity.

Second, the U.S. is vaccinating people quite efficiently. It has given out the largest absolute number of doses in the world, and trails only a few much smaller countries (Israel, the U.K., and Chile among them) in the percentage of the population that’s been vaccinated. Almost three-quarters of the U.S. population over 65 has received at least one dose of the vaccine, with nearly half now fully inoculated. On a percentage basis, the U.S. has immunized nearly three times the number of people that Germany, Italy, and France have, and in two months, the U.S. will almost certainly have a very large percentage of vaccinated adults.

Third, the virus has had staggeringly unequal effects on the American population. For a person of a given age, the risk for certain racial and ethnic groups is several times that of a white person. Native American, Latino, Pacific Islander, and Black communities have suffered large and deadly outbreaks across the country. Our heterogeneous population and racialized economic hierarchy have exposed many people of color to higher levels of risk at home and at work. The same factors—as well as, perhaps, distrust of the medical establishment—are holding down vaccination rates in poorer places with less access to care. So some communities have both higher risk and fewer fully protected people.

This all makes for an extremely messy and volatile near-term situation. The first two factors mean that some places will see the pandemic’s worst pressures fade. The timing is great for those places, such as California, because they will have a chance to get more and more people vaccinated. But where the virus is already spreading quickly, the danger is still high, and the days are running out to slow transmission via vaccination.

In these places, it’s still unclear if previous disease or new vaccination will shift the pandemic’s darkest pattern. In every previous surge, a rise in deaths has lagged behind a rise in cases by a few weeks. Perhaps this time deaths will not rise to the level that they did in the past. Or low vaccination rates combined with possibly more deadly variants could mean that in some communities, the toll of this surge will match that of the winter’s.

In Michigan, both hospital admissions and cases are moving swiftly toward the height of the winter peak. So far, the fatality numbers have not turned upward. Now we can only wait to see if deaths will follow hospitalizations at the pace of past surges—or if something has changed.

Why the Pandemic Experts Failed

2021-03-15T15:19:36-04:00

A few minutes before midnight on March 4, 2020, the two of us emailed every U.S. state and the District of Columbia with a simple question: How many people have been tested in your state, total, for the coronavirus?

By then, about 150 people had been diagnosed with COVID-19 in the United States, and 11 had died of the disease. Yet the CDC had stopped publicly reporting the number of Americans tested for the virus. Without that piece of data, the tally of cases was impossible to interpret—were only a handful of people sick? Or had only a handful of people been tested? To our shock, we learned that very few Americans had been tested.

The consequences of this testing shortage, we realized, could be cataclysmic. A few days later, we founded the COVID Tracking Project at The Atlantic with Erin Kissane, an editor, and Jeff Hammerbacher, a data scientist. Every day last spring, the project’s volunteers collected coronavirus data for every U.S. state and territory. We assumed that the government had these data, and we hoped a small amount of reporting might prod it into publishing them.

Not until early May, when the CDC published its own deeply inadequate data dashboard, did we realize the depth of its ignorance. And when the White House reproduced one of our charts, it confirmed our fears: The government was using our data. For months, the American government had no idea how many people were sick with COVID-19, how many were lying in hospitals, or how many had died. And the COVID Tracking Project at The Atlantic, started as a temporary volunteer effort, had become a de facto source of pandemic data for the United States.

After spending a year building one of the only U.S. pandemic-data sources, we have come to see the government’s initial failure here as the fault on which the entire catastrophe pivots. The government has made progress since May; it is finally able to track pandemic data. Yet some underlying failures remain unfixed. The same calamity could happen again.

Data might seem like an overly technical obsession, an oddly nerdy scapegoat on which to hang the deaths of half a million Americans. But data are how our leaders apprehend reality. In a sense, data are the federal government’s reality. As a gap opened between the data that leaders imagined should exist and the data that actually did exist, it swallowed the country’s pandemic planning and response.

The COVID Tracking Project ultimately tallied more than 363 million tests, 28 million cases, and 515,148 deaths nationwide. It ended its daily data collection last week and will close this spring. Over the past year, we have learned much that, we hope, might prevent a project like ours from ever being needed again. We have learned that America’s public-health establishment is obsessed with data but curiously distant from them. We have learned how this establishment can fail to understand, or act on, what data it does have. We have learned how the process of producing pandemic data shapes how the pandemic itself is understood. And we have learned that these problems are not likely to be fixed by a change of administration or by a reinvigorated bureaucracy.

That is because, as with so much else, President Donald Trump’s incompetence slowed the pandemic response, but did not define it. We have learned that the country’s systems largely worked as designed. Only by adopting different ways of thinking about data can we prevent another disaster:

1. All data are created; data never simply exist.

Before March 2020, the country had no shortage of pandemic-preparation plans. Many stressed the importance of data-driven decision making. Yet these plans largely assumed that detailed and reliable data would simply … exist. They were less concerned with how those data would actually be made.

So last March, when the government stopped releasing testing numbers, Nancy Messonnier, the CDC’s respiratory-disease chief, inadvertently hinted that the agency was not prepared to collect and standardize state-level information. “With more and more testing done at states,” she said, the agency’s numbers would no longer “be representative of the testing being done nationally.”

When we started compiling state-level data, we quickly discovered that testing was a mess. First, states could barely test anyone, because of issues with the CDC’s initial COVID-19 test kit and too-stringent rules about who could be tested. But even beyond those failures, confusion reigned. Data systems have to be aligned very precisely to produce detailed statistics. Yet in the U.S., many states create one sort of data for themselves and another, simpler feed to send to the federal government. Both numbers might be “correct” in some sense, but the lack of agreement within a state’s own numbers made interpreting national data extremely difficult.

The early work of the COVID Tracking Project was to understand those inconsistencies and adjust for them, so that every state’s data could be gathered in one place. Consider the serpentine journey that every piece of COVID-19 data takes. A COVID-19 test, for instance, starts as a molecular reaction in a vial or lab machine, then proceeds through several layers of human observation, keyboard entry, and private computer systems before reaching the government. The pipelines that lead to county, state, and federal databases can be arranged in many different ways. At the end of the process, you have a data set that looks standardized, but may actually not be.

Yet the federal pandemic response was built on the assumption that those data were fundamentally sound, and that they could be fed into highly tuned epidemiological models that could guide the response. Inside the government, the lack of data led to a sputtering response. “What CDC is not accounting for is that we have been flying blind for weeks with essentially no [testing],” Carter Mecher, a medical adviser at the Department of Veterans Affairs, wrote to an email list of federal officials on March 13. “The difference between models and real life is that with models we can set the parameters as if they are known. In real life, these parameters are as clear as mud.”

We now know that early case counts reflected only a small portion of the true number of cases. They were probably 10 or even 20 times too small, according to later academic studies. The government missed the initial explosion of COVID-19 cases because, despite its many plans to analyze data, it assumed that data would simply materialize.

2. Data are a photograph, not a window.

By late spring of last year, the COVID Tracking Project’s Peter Walker had developed a simple way to visualize the sweep of the pandemic—four bar charts, presented in a row, showing tests, cases, hospitalized patients, and deaths. This chart has since aired on dozens of local news stations, and has been used by state and federal officials to view COVID-19’s path over time.

The charts seem authoritative, comprehensive. Yet the work of producing these data has taught us that every metric represents a different moment in time. You aren’t really looking at the present when you look at these charts—you’re looking at four different snapshots of the past.

The COVID Tracking Project’s research, led by Kara Schechtman and Michal Mart, has found that the data travel “at different speeds.” Take case and test data—the two factors that go into the “test-positivity rates,” which officials have used to trigger lockdowns, reopenings, and other pandemic policy measures. Case numbers can move quickly; negative test results flow more slowly. Combine them, and the dates of tests and cases may not match up. Individual states can make adjustments for this kind of problem, but comparisons across states remain difficult. Worse, while negative test results lag, test-positivity rates will look higher than they actually are, keeping schools and businesses from reopening.

The death data are also shaped by reporting systems in ways that few people—even top officials—seemed to understand. Although the CDC estimates that the median death is reported to state authorities about 20 days after the person has actually died, a huge range exists. About a quarter of deaths are reported less than six days after they have occured; another 25 percent are reported more than 45 days after. And the lags are simply not constant, as the epidemiologist Jason Salemi has shown with Florida data. These reporting quirks make it very difficult to assess the death toll for an outbreak until many weeks after the surge has ebbed.

There are other invisible problems in the data. For one, we have no idea how many antigen tests have been conducted in the United States. A recent government document estimated that 4 million of these rapid tests are now being conducted a day—more than twice the number of slower, but more accurate, polymerase-chain-reaction, or PCR, tests. Yet states report nowhere near that volume of antigen tests. Tens of millions of tests are going unreported. Where are they happening? How many are coming out positive? No one has any idea.

The data set that we trust the most—and that we believe does not come with major questions—is the hospitalization data overseen by the Department of Health and Human Services. At this point, virtually every hospital in America is reporting to the department as required. We now have a good sense of how many patients are hospitalized with COVID-19 around the country.

This has allowed the federal government to target aid, deploying health-care personnel, medicine, and personal protective equipment to the hospitals that need it most—a clear example of how accurate pandemic data can help policy makers.

3. Data are just another type of information.

Data seem to have a preeminent claim on truth. Policy makers boast about data-driven decision making, and vow to “follow the science.” But we’ve spent a year elbow-deep in data. Trust us: Data are really nothing special.

Data are just a bunch of qualitative conclusions arranged in a countable way. Data-driven thinking isn’t necessarily more accurate than other forms of reasoning, and if you do not understand how data are made, their seams and scars, they might even be more likely to mislead you.

This problem has hampered the pandemic response from the start. By early March, it was evident that the virus should have been spreading in the U.S. Yet the CDC’s stringency about who could be tested and the lack of clear testing data meant many federal leaders simply didn’t acknowledge that reality.

Today, these issues somehow remain. In a press conference on March 1, 2021, the new CDC director, Rochelle Walensky, cautioned the public about new coronavirus variants. Cases and deaths were both rising nationwide, she warned, potentially implying that the mutated versions of the virus were to blame. But at the COVID Tracking Project, we knew this narrative of a variant-driven surge didn’t hold. If deaths were rising now, that meant cases had risen a month ago. This didn’t add up—a month earlier, cases had been falling, precipitously.

Instead, we knew from following the data closely that many states were reporting huge backlogs as they examined death certificates. At the same time, Texas and several other states had been crushed by a winter storm. This sent their reporting plummeting—deaths dipped faster than they should have, and then shot back up, when work fully resumed. Since Walensky spoke, the average number of deaths a day has fallen by almost 25 percent.

In other words, it wasn’t that the pandemic in those states had gotten worse in February, but that the peak straddling December and January had been even more damaging than we knew at the time. Public-health officials continue to believe that the data in front of them can be interpreted without sufficient consideration of the data-production process.

And so deep problems with the data persist. The COVID Tracking Project has shown that at least five states have disturbingly incomplete testing data. In some states, 80 percent of tests are missing from the equivalent federal data set. Yet the CDC is referring leaders of those states to its own test-positivity-rate data—which are calculated from these inaccurate data—when they consider reopening their schools.

Because of the painstaking labor of its more than 550 contributors, the COVID Tracking Project was among the first to identify virus surges in the Sun Belt and the Midwest; it determined the outsize importance of nursing homes in driving COVID-19 deaths; and it found widespread evidence of overwhelmed hospitals during the harsh winter surge. Our data have been used by The New York Times, Johns Hopkins University, and two presidential administrations.

Data are alluring. Looking at a chart or a spreadsheet, you might feel omniscient, like a sorcerer peering into a crystal ball. But the truth is that you’re much closer to a sanitation worker watching city sewers empty into a wastewater-treatment plant. Sure, you might learn over time which sewers are particularly smelly and which ones reach the plant before the others—but you shouldn’t delude yourself about what’s in the water.

The scientists at the CDC clearly have far more expertise in infectious-disease containment than almost anyone at the COVID Tracking Project or The Atlantic. But we did spend a year grappling with the limitations of the system that Walensky and President Joe Biden now depend on. Perhaps no official or expert wants to believe that the United States could struggle at something as seemingly basic as collecting statistics about a national emergency. Yet at the COVID Tracking Project, we never had the luxury of that illusion. We started with a simple mission—to count tests nationwide—and, in pursuing it, immediately found ourselves enmeshed in the problems of defining and standardizing tests, cases, hospitalizations, and deaths. In the cracks of federalism, where the state and national governments grate against each other, we found alarming levels of chaos, but lurking within the chaos was the truth. We saw, in that dark place, how our public-health systems actually worked, not how we wished they would.

To avoid another data calamity, our public-health system must expend as much energy on understanding the present as it does on modeling the future. Governing through a pandemic—or any emergency—is about making the least-bad decisions with the best information available. That information can take many forms; it doesn’t have to be data. But if you do look at the data, then you must understand how each point, each cell, was made; otherwise, you’re likely to be misled.

Our leaders should also put some faith in the capabilities of those whom they govern. The COVID Tracking Project clung to one principle: We told people the truth as we could discern it. We didn’t say what we wanted to be true, nor what we hoped would engender a specific public response.

Working on the COVID Tracking Project has been the honor of our lives. For a year, every day, dozens of volunteers—programmers, librarians, high schoolers, a former hotel manager—came together to make an honest account of one of the most horrifying ordeals that any of us had ever experienced. This team of former strangers, united by concern and curiosity, salvaged something useful from the din. We held fast to one another, and we made sense of the world as we could.

A Simple Rule of Thumb for Knowing When the Pandemic Is Over

2021-02-23T17:59:09-05:00

In the middle of January, the deadliest month of the pandemic, one day after inauguration, the Biden administration put out a comprehensive national strategy for “beating COVID-19.” The 200-page document includes many useful goals, such as “Restore trust with the American people” and “Mount a safe, effective, and comprehensive vaccination campaign.” But nowhere does it give a quantitative threshold for when it will be time to say, “Okay, done—we’ve beaten the pandemic.”

A month later, it’s time to get specific. The facts are undeniable: The seven-day average of new cases in the United States has fallen by 74 percent since their January peak, hospitalizations have gone down by 58 percent, and deaths have dropped by 42 percent. Meanwhile, more than 60 million doses of vaccine have gone into American arms. At some point—maybe even some point relatively soon—the remaining emergency measures that were introduced in March 2020 will come to an end. But when, exactly, should that happen?

The problem is that the “end of the pandemic” means different things in different contexts. The World Health Organization first declared a “public health emergency of international concern” on January 30, 2020, holding off on labeling it a “pandemic” until March 11. The imposition (and rescinding) of these labels is a judgment made by WHO leadership, and one that can reflect murky, tactical considerations. Regardless of what the WHO decides (and when), national governments—and individual states within the U.S.—have to make their own determinations about when and how to reopen their schools and loosen their restrictions on businesses. I reached out to prominent public-health experts to find out which epidemiological criteria ought to be met before these kinds of steps are taken.

The most obvious interpretation of “beating COVID-19” would be that transmission of the coronavirus has stopped, a scenario some public-health experts have hashtagged #ZeroCOVID. But the experts I spoke with all agreed that this won’t happen in the U.S. in the foreseeable future. “This would require very high levels of vaccination coverage,” said Celine Gounder, an infectious-disease specialist at NYU who served on Joe Biden’s coronavirus task force during the transition. The U.S. may never reach vaccination rates of 75 to 85 percent, the experts said.

[Read: The good news of COVID-19 is sticking for now]

“The question is not when do we eliminate the virus in the country,” said Paul Offit, the director of the Vaccine Education Center and an expert in virology and immunology at the Children’s Hospital of Philadelphia. Rather, it’s when do we have the virus sufficiently under control? “We’ll have a much, much lower case count, hospitalization count, death count,” Offit said. “What is that number that people are comfortable with?” In his view, “the doors will open” when the country gets to fewer than 5,000 new cases a day, and fewer than 100 deaths.

That latter threshold, of 100 COVID-19 deaths a day, was repeated by other experts, following the logic that it approximates the nation’s average death toll from influenza. In most recent years, the flu has killed 20,000 to 50,000 Americans annually, which averages out to 55 to 140 deaths a day, said Joseph Eisenberg, an epidemiologist at the University of Michigan. “This risk was largely considered acceptable by the public,” Eisenberg said. Monica Gandhi, an infectious-disease specialist at UC San Francisco, made a similar calculation. “The end to the emergency portion of the pandemic in the United States should be heralded completely by the curtailing of severe illness, hospitalizations, and deaths from COVID-19,” she said. “Fewer than 100 deaths a day—to mirror the typical mortality of influenza in the U.S. over a typical year—is an appropriate goal.”

The “flu test” proposed here is not a perfect apples-to-apples comparison. Deaths attributed to COVID-19 are directly reported to public-health authorities, while the mortality numbers from seasonal flu are CDC estimates based on national surveillance data that have been fed into statistical models. But researchers believe that the straightforward counts of influenza deaths—just 3,448 to 15,620 in recent years—are substantially too low, while direct counts of COVID-19 deaths are likely to be more accurate. One big reason: Far more COVID-19 tests are done in a single day than flu tests in an entire year, and flu tests have a greater tendency to return false negatives.

In any case, we are nowhere near 100 COVID-19 deaths a day. Since last spring, states have not reported fewer than 474 deaths a day, as measured by a rolling seven-day average at the COVID Tracking Project at The Atlantic. Right now, the country as a whole is still reporting close to 2,000 deaths a day, and just two weeks ago that number was more than 3,000. So, if we’re going by the flu test, we still have a very long way to go.

[Read: The most likely timeline for life to return to normal]

Some experts were even more conservative. Crystal Watson, a health-security scholar at Johns Hopkins University, suggested a threshold of 0.5 newly diagnosed cases per 100,000 people every day, and a test-positivity rate of less than 1 percent. That would translate to fewer than 2,000 cases a day in the U.S., compared with the current 60,000 or more. We’d also want to log at least one month of normal hospital operations without staff or equipment shortages, she said.

While every proposed threshold remains far below what we’re seeing right now, the researchers I spoke with believe that if vaccine uptake is high enough, those numbers can be reached. Watson suggested a target of 80 percent coverage for populations older than 65, and 70 to 80 percent for everyone else. For the latter, “perhaps 60 percent is more realistic,” she said.

So far, no state has reached those vaccination levels in any population. It is possible, however, that in specific, high-risk subpopulations, targeted efforts could drive vaccination rates to very high levels. Our best example is in long-term-care facilities, which have been linked to 35 percent of total COVID-19 deaths in the U.S. The federal government’s vaccine rollout made residents and staff in these facilities a priority and provided specific funds and operational help to vaccinate these people beginning in December. At the COVID Tracking Project, we’ve seen the share of deaths attributed to long-term-care facilities drop by more than half over the past six weeks, which suggests the vaccines are working.

The large number of Americans who’ve already been infected will also be crucial for reaching transmission-slowing levels of immunity. The CDC estimates that more than 83 million Americans have been infected with COVID-19, far more than the official, confirmed case total of 28 million. Forty-four million Americans have received at least one dose of a vaccine. Even assuming some overlap between the previously infected and the vaccinated, perhaps 100 to 120 million Americans have some level of immunity. That’s roughly one-third of the population.

It could take months for the size of this group to reach a point where the number of COVID-19 deaths a day falls below 100. Until then, we’ll be confronted with a different sort of risk: that, for some, the pandemic feels like it’s over long before it actually is. Just as the country has never taken a unified approach to battling COVID-19, we may very well end up without a unified approach to deciding when it ends. That’s why public-health experts are desperately urging Americans to hold firm even as the pandemic seems to be receding. “We’re lifting mitigation measures too soon,” warned Gounder, the infectious-disease specialist at NYU. “We’re taking our foot off the brake before putting the car into park.” If enough people ignore that message and decide the pandemic is over for them, it may very well put off the moment when we can say that the pandemic is over for everyone.

America’s Most Reliable Pandemic Data Are Now at Risk

2021-01-18T21:00:34-05:00

When a hospital is in trouble, the signs are unmistakable. The number of COVID-19 admissions rises quickly. The number of patients who remain hospitalized grows steadily—and the bar to be admitted gets higher. The percentage of patients in intensive-care units increases. Supplies run low. As an ICU nears capacity, sick people get less care than they would have. More people suffer, and more people die. Right now, in Alabama, Arizona, and California—Los Angeles, especially—this is exactly what’s happening. We know this because of the data system that’s now in place.

But until recently, we did not have this national picture. Who had the most COVID-19 patients? Which hospitals’ ICUs were overrun? Who had staffing shortages? No one could say. Even assuming that the federal government could have executed a competent pandemic response, it couldn’t know where help was needed.

The government needed a national hospital-data system. So multiple teams scrambled to build one. In a short time, control over this hospitalization data became one of the most hotly contested elements of the American response, as fears of Trump-administration meddling cast doubt on the Department of Health and Human Services. Now the Biden administration is poised to take over as the country faces the worst surge yet, and hospitalization data may be the most important information it will have in the fight to save lives. The administration must decide where those data will live.

Since July, these data have been routed through the Department of Health and Human Services, but some officials inside the CDC are trying to regain control. It might seem obvious that the CDC, the traditional repository of infectious-disease information, should win this intragovernmental battle, but the reality is much more complicated. The current, HHS-run system works—unlike so much else in the response—and with these data flowing in, the federal government can dispatch help to hospitals that need it. If the new administration changed that system, it would be setting aside the best available data about the pandemic, and gambling that it could build a better system when it cannot afford to lose.

Since March, I’ve run the COVID Tracking Project with Erin Kissane, dozens of staffers, and hundreds of volunteers. We have pieced together national data sets on tests, cases, hospitalizations, and deaths by compiling the information that states publish. The hospitalization data that we’ve pulled from the states became the de facto national standard for the majority of the pandemic. Our team has made hundreds of contacts with local, state, and federal officials to clarify what the numbers on all those dashboards actually mean. And through that work, we’ve been able to compare what states say is happening with whatever the federal government publishes.

Hospitalization data reveal the condition of the country’s hospitals: COVID-19 admissions, currently hospitalized patients, ICU availability, and access to personal protective equipment and other supplies. In July, the Department of Health and Human Services directed hospitals to send information directly to an HHS database, bypassing the CDC, which prompted a series of articles in The New York Times casting doubt on the HHS system. There was reason to worry: HHS officials had tried to pressure infectious-disease experts, including Anthony Fauci, to echo President Donald Trump’s misleading public messaging about the pandemic. And Secretary Alex Azar and Deborah Birx, the White House’s coronavirus-response coordinator, were seen as beholden to Trump. Anonymous CDC officials said the change had been a surprise, and insinuated that perhaps the data would be manipulated.

But what really happened is widely, wildly misunderstood. Although the CDC did not respond to multiple requests for comment on this story, internal communications show that the agency agreed to the change because of the limitations of its own system. And while the switch was rocky at first, over time the HHS system has become the most reliable source of federal pandemic data.

“I’m not going to pretend that the data wasn’t messy at first, but the aspiration was valuable, and particularly over the last few months, you could see the data getting better and better,” David Rubin, the director of the PolicyLab at Children’s Hospital of Philadelphia, who has worked extensively with COVID-19 data, told me. “I think it would be a grave mistake to throw it out and go back to what we were doing before.”

At the COVID Tracking Project, we were initially dismayed by the HHS changeover, but we watched closely as the system stabilized and began to become more reliable. In a series of analyses that we ran over the past several months, we came to nearly the opposite conclusion of other media outlets. The hospitalization data coming out of HHS are now the best and most granular publicly available data on the pandemic. This information has changed the response to the pandemic for the better.

“Hospitals are now beginning to see how folks from Operation Warp Speed are using the data to identify specific shortages of specific supplies and reach out: ‘Are you okay? Can you get them from your supplier? Or can we help you in some way?’” Nancy Foster, the vice president for quality and patient-safety policy at the American Hospital Association, told me.

Amid the United States’ overall failure to contain the pandemic, the small data team at HHS did a good thing. Biden’s team did not respond to a request for comment on this story, but starting on Wednesday his administration will have the power to choose what happens to this hospital data. Disrupting the flow now—when 124,000 people are hospitalized with COVID-19 and more than 3,300 people are dying each day—is a risk the country doesn’t need to and should not take.

Pieces of data do not simply exist. They must be extracted from reality and processed into usable forms. From the molecules of the virus on up, measurements have to be taken and facts tabulated. These numbers have to flow from labs and medical examiners, hospitals and public-health departments, into larger systems, where they then get summarized into statistics.

For example, most states identify most cases electronically, based on lab results. But not every state’s electronic reporting is equal. Some use advanced electronic-case-reporting protocols, while others rely at least in part on forms sent via fax. America’s system is incredibly decentralized, with thousands of different sources of data, and it is rife with idiosyncrasies and potential points of failure. Its complexity and heterogeneity are key weaknesses in U.S. public-health surveillance.

It didn’t have to be this way. Years ago, the CDC prioritized data modernization as part of a plan to be ready for a possible pandemic, and the agency appeared to be making good progress. In 2019, a group of public-health experts even ranked the United States No. 1 out of every country in the world for pandemic preparedness, including data collection. We now know that the CDC and the rest of the federal government were not ready to confront the real thing.

“As a country, we are really underprepared for large, real-time data collection and sharing,” Nahid Bhadelia, an infectious-disease physician at Boston University School of Medicine, told me. “And real-time outbreak analytics? Well, that’s like asking a Model T to compete on the Autobahn.”

In the chaotic early days of the coronavirus crisis, the United States probably confirmed only 10 percent—or perhaps as little as 5 percent—of cases, though no one will ever know for sure. Even now some deaths are being reported weeks after they actually occur. Media outlets and government officials often say, as shorthand, “3,000 people died from COVID-19 yesterday,” but that actually means 3,000 deaths were reported yesterday. Though we usually don’t know exactly, the people represented by that number may have died two, five, 15, or 50 days ago.

Hospital data began in even worse shape than testing, case, or death data. COVID-Net, a system for estimating hospital strain, drew on a network of only about 250 hospitals in 14 states. It did not provide granular national data.

Beginning in March, different pieces of the federal government tried to stand up hospital-data systems. The CDC took a system created for tracking infections transmitted in hospitals, the National Healthcare Safety Network, and jerry-rigged it to take in COVID-19 patient data. HHS contracted with a small health-care-IT firm, Teletracking, to create a similar system. And Deborah Birx’s team worked with FEMA’s National Response Coordination Center, HHS, and the CDC to contract with Palantir, which built software called HHS Protect.

Hospitals or their intermediaries—such as state hospital associations—could send information to any of the three systems, and eventually that data would drop into HHS Protect.

Much has been made of the decision to use Palantir for HHS Protect, not least because one of Palantir’s co-founders, Peter Thiel, is a high-profile Trump supporter. The concern was reasonable enough. But HHS officials say they went with the company because the CDC already worked with Palantir. In fact, HHS Protect is an offshoot of another system Palantir produced, known as DCIPHER Cloud, which began under President Barack Obama. “It was really about using what was already in-house,” Kevin Duvall, the deputy chief data officer at HHS, told me.

Throughout the spring, hospitals and states worked to create systems for reporting data to the federal government. States published their own accounting, too, which we gathered at the COVID Tracking Project. Those state hospitalization data did not match what we saw the federal authorities reporting. When we looked at May and June, we could see the CDC estimates for hospitalizations bouncing up and down. They look like a seismograph during an earthquake. Given that the states were reporting fairly smooth curves, we concluded that the fluctuations in the CDC data did not reflect reality, but were artifacts of the reporting process. If fewer hospitals reported to the CDC, then it could push down the number of hospitalizations, even if there were still sick patients in those facilities. It was impossible to know for certain, but the state data were almost certainly more reliable.

In mid-July, as the Sun Belt teemed with infections, members of the White House Coronavirus Task Force realized that they needed to ask hospitals a new question: How much remdesivir did they have on hand? (Clinical trials had shown that the drug was more effective when administered earlier in the course of a COVID-19 infection, not later, after more severe illness had set in.) According to correspondence obtained by The Atlantic from a source who requested anonymity because they were not authorized to speak about the communication, the Data Strategy and Execution Workgroup at HHS—the team tasked with providing data for the federal coronavirus response—requested that the CDC add a single data field about remdesivir to the National Healthcare Safety Network (NHSN), its hospital-data-collection system. This is what you might think of as a new column in a spreadsheet, but officials ran into a problem: The CDC staff said that change would take more than three weeks, at a time when hospitalizations were approaching the highest levels of the pandemic to that date.

NHSN was an old system, snapped together from other IT components in 2005 to track infections spreading in hospitals. Hospitals were familiar with it, and it came with a preexisting $60 million contract with a major federal contractor, Leidos, to keep it running. But it had not been built for the kind of flexible emergency response that this unprecedented pandemic required. The request to add the data field went all the way to Sherri Berger, chief operating officer of the CDC. But the word came back: The field could not be added faster. So the CDC gave the team within HHS the go-ahead to change the reporting system itself.

This switch to HHS Protect was rushed—hospitals had just five days to figure out the new system before it went live—and hospital reporting fell rapidly, according to a dashboard HHS maintains. The change caused hiccups in state data, too, and the COVID Tracking Project noticed major reporting problems right as hospitalizations were peaking in hard-hit regions.

There were other ominous signs of malfunction, or worse: A previously public dashboard showing hospital capacity blinked offline. A big story ran in The New York Times suggesting that the changeover had surprised the CDC and focusing on the possibility of political interference with the data. A CNBC headline read, “Coronavirus Data Has Already Disappeared After Trump Administration Shifted Control From CDC.” No one seemed to believe what the CDC’s director, Robert Redfield, said at a press conference: “In order to meet this need for flexible data gathering, CDC agreed that we needed to remove NHSN from the collection process.”

The idea that the Trump administration would try to suppress COVID-19 data was not far-fetched, but the HHS staffers I spoke with said that public perception was misguided. The people on the team were not Trump-administration loyalists, but civil servants from across the federal government. Its leader, Amy Gleason, came from the U.S. Digital Service, a signature achievement of the Obama administration that brings technologists into the government from private industry.

“It’s truly interagency,” Gleason said. “Every day I work with people from 13 different agencies and components, side by side.”

As outside pressure mounted, they were scrambling to build a complicated system in a moment of national crisis.

“I know there have been lots of stories written about the relationship of CDC to HHS. But I will say this: We weren’t prepared from the data perspective for the challenge that awaited us,” said Rubin from the Children’s Hospital of Philadelphia. “The systems for influenza based on sentinel surveillance were not sufficient for a pandemic of this magnitude, so creating a public-health war room is a noble goal. The question is why we didn’t have something like this previously.”

Immediately after the switch-over to HHS Protect, the discrepancies between the federal data and state data really could be enormous. On some days in late July, HHS reported 200 percent more hospitalized patients than some jurisdictions themselves were reporting. While this was disturbing, an overcount of hospitalizations, making the pandemic seem more severe, was also a sign that the problems were unlikely to be purely political in nature.

As the HHS data became public, we at the COVID Tracking Project found that news organizations and many public-health professionals were continuing to rely on our hospitalization numbers, even though an official government entity now provided similar data. HHS had major logistical problems to deal with. After the changeover, the team had essentially no hospitals reporting all of the data requested every day for the month of July. Many hospitals were unhappy that there had been disruptive changes. But Nancy Foster credited Amy Gleason with putting a moratorium on tweaks to the system. She also built a troubleshooting team with hospital liaisons drawn from staff at the CDC, HHS, and other parts of the federal government. “It was really under Amy Gleason’s leadership that the folks from HHS started to work with states and other data intermediaries between hospitals and HHS Protect to understand where there were glitches in their processes and to help the states straighten those out,” Foster said.

Jim Jirjis, the chief health-information officer at HCA Healthcare, which runs 185 hospitals across the country, considers the HHS effort highly competent. “The fact that there was listening and the ability to pivot and change was very, very reassuring that our government can do a really good job of modifying in the middle of a pandemic,” Jirjis told me.

The improvements didn’t happen all at once. The federal government still had not released the granular data that it was receiving from hospitals and that underlay the state statistics. Civil servants across the government might have been striving to understand the spread of COVID-19 with great specificity, but their work was not reaching the public.

At the COVID Tracking Project, we were keenly aware of how little information the public was receiving. And we, like many other people, worried that HHS officials would attempt to influence the data. While hospitalization data were trickling out, other information remained locked up inside the government.

“As soon as COVID became a political issue, the administration willingly withheld data that showed how severe COVID was spreading in our communities,” says Ryan Panchadsaram, the former deputy chief technology officer of the United States under Obama and a co-founder of COVID Exit Strategy, which tracks the government’s response. “While internal reports were highlighting the ‘red zones’ and ‘areas of concern,’ the president and vice president continued to share that the reaction to COVID was ‘overblown.’”

So at the end of the summer, we decided to look for signs of cooking the books in the federal hospitalization data. First, we simply looked to see if there were obviously political patterns in the data—say, red states with lower hospitalization numbers than anticipated, or overall depressed numbers. We didn’t see anything like that. Then we ran statistical tests looking at the variance in data from different states.

What we found surprised us: The data that were flowing through HHS were much less spiky than what had flowed primarily through NHSN. In fact, at least on initial inspection, the HHS data looked a lot like our patchwork of data from states, which for the most part was not riddled with weird jumps or unexplained phenomena that were obviously not reflective of reality. When cases rose, hospitalizations did shortly thereafter. As the HHS data came to resemble the state data, we began to suspect that perhaps the HHS data had, as we put it in an internal report on August 20, “enormous potential to be the Federal numbers we’ve always wanted.”

Stitching together state reporting into a national data set is an incredibly research-intensive way to produce those statistics. We have to figure out precisely what information 56 states and territories are reporting, and even then, we cannot guarantee perfectly comparable data. HHS, for its part, simply asked states to report all confirmed and suspected COVID-19 hospitalizations in the same way, creating a consistent and standardized data set. Once hospitals learned the system, the data solidified. Jason Salemi, an epidemiologist at the University of South Florida, described the changes as “amazing improvements.”

“For a long while, there was very little help from federal data—it was a massive disappointment and failure to serve the public at a time when such information was direly needed,” Salemi told me. Since then, HHS “has stepped up to the challenge in a major way.”

Some critiques of the HHS-generated information have called its accuracy into question. There are many data sets in HHS Protect that originate in many different places, so we cannot speak to all of them. However, the COVID Tracking Project can check HHS against the state reports. In late November, we found that the data had come to match almost perfectly. Not all states report precisely the same way, and the COVID Tracking Project runs one day behind HHS, but after we took those factors into account, we found that HHS and state data were now falling within 2 percent of each other. If the HHS data were off, then the data produced by every state were also off.

For the week of December 28, the most recent data available, 96 percent of hospitals reported every data point to HHS every day. The interagency team led by HHS has done what had seemed impossible: gotten every hospital in America to tell the federal government what’s going on.

“This pandemic shined a bright light on the data gaps we had in our understanding of the magnitude, spread, and burden of disease, across each community, county, city, and state,” Irum Zaidi, the White House coronavirus-response coordinator and chief epidemiologist, told me. “The system we needed and have set up makes every patient visible across the U.S. in order to provide the limited resources such as remdesivir, supplies, and staffing to every rural and urban hospital.”

As the data improved, they became more and more available to the public. First up, HHS published the “metadata” about how facilities were reporting. This let us see for the first time how many hospitals were reporting. Then it released staffing-shortage details. Bit by bit, as the fall turned to winter, HHS published much of the crucial data that critics of the administration had been asking for. The capstone came last month, when HHS released data for every hospital in the country, exactly the kind of granular information that is necessary to understand where hospital systems are being overwhelmed. And given the general disaster of COVID-19 in America, there are many places that desperately need help from the federal government to secure supplies and shore up staffing.

This data set is not perfect—no data set is—but it is the best available. “I am heartened to see facility-level [information] because we can also get a sense of how the same facilities are doing over time,” BU’s Nahid Bhadelia said. “This level of granularity also allows researchers to create a better evidence base for policy recommendations.”

Examining the COVID Tracking Project’s map of the HHS release, one can zoom in on Dallas, say, and find data about how full any given hospital’s ICU is that week. It provides an unprecedented look at precisely how much pressure COVID-19 places on our health-care systems. The White House’s Coronavirus Task Force is now using this kind of information to dispatch medical support teams to hard-hit areas.

This week, a new administration will take control of the HHS system, and is facing public pressure to change it once again. Switching back to the National Healthcare Safety Network, at this point, would likely undo the progress the HHS data team has made in the past six months, at the worst moment of the pandemic so far. “Going forward, it’ll be important for the next administration to pick up the baton and build off of what’s been created for this response,” Ryan Panchadsaram told me. “Is it perfect? No. But it is better than what we had before.”

“My feeling is do not make any changes unless they are absolutely necessary,” Foster said. “Change is disruption.”

America Has Not Fixed Its Deadliest Pandemic Errors

2020-12-31T10:32:31-05:00

As the pandemic enters its second year, the coronavirus has remade everyday life in the United States. More than 19 million Americans have been diagnosed with COVID-19 since March, and at least 330,000 Americans have died of it, according to the COVID Tracking Project at The Atlantic. Yesterday, 3,903 Americans were reported to have died of the virus, the highest death toll since the pandemic began.

Yet the U.S. is still making the same two deadly mistakes that have defined its response since the pandemic began, our ongoing investigation has found. The nation still does not have enough tests to combat the pandemic. And it is still allowing the virus to rampage through nursing homes and other long-term-care facilities.

[Read: Where year two of the pandemic will take us]

After an early failure in February left the country with growing caseloads and too few COVID-19 tests to track the outbreak, the U.S. has never caught up. By the middle of December, the country tested about 1.8 million people a day for the virus, which was close to an all-time high. But to begin fighting the virus through testing—by, for instance, identifying infected people before they pass the virus to others—the U.S. must test at least 4.4 million people a day, according to the Harvard Global Health Institute. Ideally, given the scale of the pandemic, the country would run 14 million tests a day, the institute posits.

By our count, the U.S. has conducted more than 248 million tests since the pandemic began, a staggering total. But the virus is now so widespread that if America were meeting that ideal testing target, it would run about that many tests every two and a half weeks.

The U.S. has never tested as many people as it needs to in order to keep the pandemic in check. It has gone weeks at a time—from late July to mid-September, most strikingly—without increasing the number of people tested every day. At moments when infection has been especially widespread, companies have taken days or even weeks to process test results. Federal regulators have been slow to approve rapid virus tests that could be used at home without a prescription, similar to pregnancy tests.

This has compounded a second crucial failure. In the spring, the country learned that the virus is deadliest in long-term-care facilities such as nursing homes. Though these facilities house less than 1 percent of America’s population, they have seen at least 38 percent of the nation’s COVID-19 deaths, our data show. (Some states report incomplete data for these facilities, meaning that this number likely undercounts the true toll originating in these settings.)

The Trump administration has claimed that saving lives at such facilities is core to its pandemic strategy. Scott Atlas, a neuroradiologist who advised Donald Trump on virus policy for much of the summer and fall, argued that there was little risk in allowing the virus to spread through the general population as long as officials focused on “protection of the vulnerable” in nursing homes.

[Read: The last days of loneliness]

Yet the country has never succeeded at protecting the vulnerable, our data show. In December alone, at least 20,455 people have died in long-term-care facilities and nursing homes, the greatest toll since the COVID Tracking Project began collecting long-term-care data in late May. And in every region of the country but the Northeast, more people died in long-term-care facilities in the summer and fall than in the spring.

the covid tracking project

These two debacles have preyed on the effectiveness of the American pandemic response from the start. At the end of the year, the U.S. has more diagnosed COVID-19 cases than any other country, and it ranks fourth worldwide in COVID-19 deaths per capita. And December has been the deadliest month of the pandemic so far, our data show. Its death toll has exceeded that of April by 29 percent.

These data were collected by the COVID Tracking Project at The Atlantic. For each of the past 299 days, a team of volunteers and project members has watched press conferences, tracked social-media posts, and combed through dozens of government websites to compile the COVID-19 data that each U.S. state and territory provides. The project now records nearly 800 individual statistics.

The resulting database is a patchwork, built from the individual components that each state’s data systems capture and from the numbers that local political leaders allow to be published. Fusing together 56 state and territorial data sets can be a fraught, complex process, and the project publishes exhaustive documentation of what the numbers mean, how they compare to one another, and what we still don’t know, because of the variability of state reporting.

One of the most obvious elisions is the toll that the pandemic has taken on Black, Latino, and Indigenous people. The pandemic has disproportionately killed people in these communities, our data show. At least one in every 800 Black Americans has died of COVID-19, and Black people have died of COVID-19 at 1.7 times the rate of white people. Nationwide, Indigenous people and Alaska Natives have died of COVID-19 at 1.4 times the rate of white people.

[Read: The virus is showing Black people what they knew all along]

Yet the full scale of this damage is not quantifiable, because many states still do not track enough data by race and ethnicity for us to identify the full, disparate impact. Texas, for instance, reports race and ethnicity data for only 4 percent of cases. New York has never reported race and ethnicity case data, which obscures our understanding of the first surge in particular, when New York’s numbers dominated every national statistic.

Only seven states report the racial breakdown of testing data, an important tool in detecting how large outbreaks are overall, because knowing the fraction of a population that has been tested can indicate the breadth of the virus’s spread.

Because of such inconsistencies and gaps, the COVID Tracking Project team has also communicated with state and federal officials hundreds of times over the past 10 months to clarify the meaning of specific numbers and to push for higher data quality and more public transparency.

This effort meant that, for months, the COVID Tracking Project published the only public database of testing and hospitalization data. Today, it is the only data set detailing each state’s and territory’s daily case, testing, hospitalization, and death numbers since the pandemic began. The federal government, including the White House Coronavirus Task Force, has used data from our investigation because it has had no alternative. The CDC Advisory Committee on Immunization Practices has repeatedly cited our data on long-term-care facilities in the course of deciding that residents of those places should get vaccinated first.

[Read: What the vaccine’s side effects feel like]

Today, the federal government publishes data on many of the same metrics we began tracking in March. But for many of these metrics, our data remain the only independent check on that federal data.

The COVID Tracking Project has repeatedly identified issues with the data shared at the state and federal level. For instance, in the spring the CDC made the state of the pandemic less clear by lumping together two different types of tests—antibody tests, which detect past infection, and diagnostic tests, which detect present illness. Test-positivity statistics, widely used to make decisions about pandemic restrictions, still show massive variability, we have found, which make them extremely difficult to use when setting interstate policy. Now the millions of inexpensive, rapid tests that the Trump administration purchased and directed to vulnerable populations are not being reported at either the state or federal level.

Over the past 10 months, we have seen the federal government struggle to acquire, present, and analyze the data necessary to understand the pandemic. This could change in the coming weeks: The incoming Biden administration has said that it plans to make a National Pandemic Dashboard. What will matter, then, is not only having the data, but using them to save lives.

One Day, 3,000 Deaths

2020-12-09T21:17:00-05:00

Today states reported 3,054 deaths from COVID-19—the highest single-day total yet, according to the COVID Tracking Project at The Atlantic.

The seven-day average of daily deaths was also at a record high, of 2,276 deaths. Since mid-October, the U.S. death toll from COVID-19 has been climbing relentlessly, with only a brief dip in the days after Thanksgiving, when states delayed reporting daily data. This past weekend the seven-day deaths average for the first time surpassed the record set in the spring surge.

Today, too, the seven-day averages for reported new daily COVID-19 cases and currently hospitalized patients were at record highs, at 204,356 and 102,580 respectively. But because testing was so limited early in the pandemic, creating undercounts of both COVID-19 cases and related hospitalizations, the deaths number marks the clearest comparison with the spring. There is no doubt now: This is the worst moment of the pandemic so far.

Just three weeks ago, as case numbers were rising, The Atlantic wrote that predicting the deaths that would follow “has become a matter of brutal arithmetic,” and that the U.S. could cross the threshold of averaging 2,000 daily deaths within a month. The country reached that moment even sooner than expected.

[Read: The U.S. has passed the hospital breaking point]

With cases rising still, the math stays the same: More deaths will follow these, as 2020 turns to 2021. The pandemic’s end may be in sight, but each day that passes before then will mark the deaths of thousands more Americans.

These fatality numbers do not reflect any increased spread from Thanksgiving. Statistical analyses have found that deaths tend to rise roughly three weeks after confirmed cases. Looking back to November 18, the seven-day average number of cases was substantially lower than it is now. Three weeks from today will be December 30, and if the trends that we’ve seen through the pandemic continue to hold, there’s no reason to expect that today’s death record will be the last.

The U.S. Has Passed the Hospital Breaking Point

2020-12-04T15:07:23-05:00

Since the beginning of the pandemic, public-health experts have warned of one particular nightmare. It is possible, they said, for the number of coronavirus patients to exceed the capacity of hospitals in a state or city to take care of them. Faced with a surge of severely ill people, doctors and nurses will have to put beds in hallways, spend less time with patients, and become more strict about whom they admit into the hospital at all. The quality of care will fall; Americans who need hospital beds for any other reason—a heart attack, a broken leg—will struggle to find space. Many people will unnecessarily suffer and die.

“If, in fact, there’s a scenario that’s very severe, it is conceivable that will happen,” Anthony Fauci, the nation’s top infectious-disease doctor, said in mid-March. “We’re doing everything we can to not allow that worst-case scenario to happen.”

Fear of this scenario drove many of the most stringent stay-at-home orders in the spring. “There will be no normally functioning economy if our hospitals are overwhelmed,” Liz Cheney, a leading House Republican, said a week and a half later.

Yet that worst-case scenario never came to pass at a national level. At the springtime peak, even as northeastern hospitals faced a deluge, 60,000 people were hospitalized nationwide. When the Sun Belt frothed with cases this summer, hospitalizations again reached the 60,000 mark before they started to fall.

A month ago, in early November, hospitalizations passed 60,000—and kept climbing, quickly. On Wednesday, the country tore past a nauseating virus record. For the first time since the pandemic began, more than 100,000 people were hospitalized with COVID-19 in the United States, nearly double the record highs seen during the spring and summer surges.

The pandemic nightmare scenario—the buckling of hospital and health-care systems nationwide—has arrived. Several lines of evidence are now sending us the same message: Hospitals are becoming overwhelmed, causing them to restrict whom they admit and leading more Americans to die needlessly.

The current rise in hospitalizations began in late September, and for weeks now hospitals have faced unprecedented demand for medical care. The number of hospitalized patients has increased nearly every day: Since November 1, the number of people hospitalized with COVID-19 has doubled; since October 1, it has tripled.

Throughout that time, health-care workers have worried that hospitals would soon be overwhelmed. “The health-care system in Iowa is going to collapse, no question,” an infectious-disease doctor told our colleague Ed Yong early last month. The following week, a critical-care doctor in Nebraska warned, “The assumption we will always have a hospital bed for [you] is a false one.”

These catastrophes seem to be coming to pass—not just in Iowa and Nebraska, but all across the country. A national breakdown in hospital care is now starkly apparent in the coronavirus data.

[Read: Hospitals know what’s coming]

It is clearest in a single simple statistic, recently observed by Ashish Jha, the dean of the Brown University School of Public Health. For weeks, the number of people hospitalized with COVID-19 had been about 3.5 percent of the number of cases reported a week earlier. But, he noticed, that relationship has broken down. A smaller and smaller proportion of cases is appearing in hospitalization totals.

“This is a real thing. It’s not an artifact. It’s not data problems,” Jha told us.

Why would this number change? As hospitals run out of beds, they could be forced to alter the standards for what kinds of patients are admitted with COVID-19. The average American admitted to the hospital with COVID-19 today is probably more acutely ill than someone admitted with COVID-19 in the late summer. This isn’t because doctors or nurses are acting out of cruelty or malice, but simply because they are running out of hospital beds and must tighten the criteria on who can be admitted.

Many states have reported that their hospitals are running out of room and restricting which patients can be admitted. In South Dakota, a network of 37 hospitals reported sending more than 150 people home with oxygen tanks to keep beds open for even sicker patients. A hospital in Amarillo, Texas, reported that COVID-19 patients are waiting in the emergency room for beds to become available. Some patients in Laredo, Texas, were sent to hospitals in San Antonio—until that city stopped accepting transfers. Elsewhere in Texas, patients were sent to Oklahoma, but hospitals there have also tightened their admission criteria.

[Read: Hospitals can’t go on like this]

The COVID Tracking Project has found the same phenomenon by looking at a different variable in the data produced by the Department of Health and Human Services: the number of people admitted to the hospital every week. (Jha was analyzing the number of people currently hospitalized.)

In August and September, about 9.5 percent of COVID-19 cases were admitted to hospitals nationwide, according to federal data. As October began, this case-hospitalization proportion held for about a week. But then cases began to explode, especially in the Midwest and Great Plains, and hospitals suffered strain. In the last week of October, the average number of new COVID-19 cases surged past its all-time high of 66,000 new cases a day. Less than 8 percent of those cases made it into the hospital, a 16 percent drop in the proportion of sick people admitted versus September.

As the pandemic intensified, the fall continued. On November 10, the U.S. recorded more virus hospitalizations than ever before, passing the previous high set during the spring and summer surges. More than 100,000 Americans were diagnosed with the virus every day last month, on average, and more than ever were hospitalized as well. But as facilities ran short on bed space, the fraction of admitted cases fell. Ultimately, only 7.4 percent of COVID-19 cases were hospitalized in November—the lowest percentage yet.

This change may not seem ominous at first. You might expect to see such a divergence, for instance, if testing rapidly increased, so that states were suddenly detecting many more mild cases of COVID-19. But the data don’t show any evidence of this kind of “casedemic”—if anything, they show the opposite. Last month, the number of total COVID-19 tests increased by about a third compared with October, but the number of total cases discovered more than doubled. More people are getting sick.

At the same time, the virus seems to be killing a slightly higher fraction of people diagnosed with it. Using a method that accounts for clinical- and data-reporting lags between cases and deaths, for most of October and November, about 1.7 percent of cases resulted in death. But in the middle of November, that number lurched to more than 1.8 percent. While this change may seem small, it represents hundreds of deaths, because many more people are getting sick every day.

In other words, we’re observing exactly the opposite of what you’d expect from a rash of mild cases in the data. The virus seems to be killing more people. And that makes sense: As Yong and our colleague Sarah Zhang have both written, many of our medical triumphs over the virus have come from more attentive and knowledgeable hospital care for COVID-19 patients. (Very few, if any, people outside of a clinical trial have received the cocktail of antibody drugs that President Donald Trump claims is a “cure” for the disease.) Yet a smaller fraction of people are now receiving that expert and conscientious care.

CTP / Ryan Tibshirani

Since March, most of our writing about the pandemic has focused on the near-term future. We’ve described data as worrying or ominous, words implying that the worst is soon to arrive. There’s a good reason for this forward-looking approach: It gives people a sense of what’s coming, and it helps people make decisions to protect themselves or their family.

But ominous no longer fits what we’re observing in the data, because calamity is no longer imminent; it is here. The bulk of evidence now suggests that one of the worst fears of the pandemic—that hospitals would become overwhelmed, leading to needless deaths—is happening now. Americans are dying of COVID-19 who, had they gotten sick a month earlier, would have lived. This is such a searingly ugly idea that it is worth repeating: Americans are likely dying of COVID-19 now who would have survived had they gotten September’s level of medical care.

The first doses of vaccine will almost certainly go out by Christmas. Tens of millions of Americans could have protective immunity within eight weeks. As the days lengthen and the weather warms, the vaccine will become easier to get; more than 100 million Americans may have immunity by the end of February. Many indicators suggest that next summer will be happy and prosperous, and we will gather indoors and outdoors and grin at one another like children in June. But the world will be reduced, and not as wise, because tens of thousands of Americans will be dead when they should be alive.

How Many Americans Are About to Die?

2020-11-19T13:01:00-05:00

The United States has made huge advances in fighting the coronavirus. The astonishingly high death rates the country saw during the spring have fallen, and Americans are much more likely now than they were then to survive a COVID-19 hospitalization. New treatments have, in some cases, helped speed recovery—President Donald Trump has trumpeted his own bout with the virus as proof that there is a “cure” for the illness. (There is not.) These developments have given Americans the impression that no matter how high cases surge, deaths might not reach the heights of the spring.

But the truth is grimmer. The story people want to believe about how much treatments have improved in recent months does not hold up to quantitative scrutiny.

The U.S. health-care system has not reduced the deadliness of the coronavirus since July, according to a new estimate by a prominent COVID-19 researcher, which accounts for the lags in public reporting of cases and deaths. Instead, the virus has, with ruthless regularity, killed at least 1.5 percent of all Americans diagnosed with COVID-19 over the past four months.

This rate is a major improvement, down more than tenfold from the earliest days of the pandemic, when deaths were high and the extreme limits on coronavirus testing held down the number of diagnosed cases. But in this new phase of the pandemic, when testing is more widely available and a much higher proportion of cases are diagnosed to begin with, it is also terrible, terrible news.

Because the case-fatality rate has stayed fixed for so long and there are now so many reported cases, predicting the virus’s death toll in the near term has become a matter of brutal arithmetic: 150,000 cases a day, times 1.5 percent, will lead to 2,250 daily deaths. In the spring, the seven-day average of daily deaths rose to its highest point ever on April 21, when it reached 2,116 deaths. With cases rising as fast as they are, the U.S. could cross the threshold of 2,000 daily deaths within a month. Without a miraculous improvement in care, the United States is about to face the darkest period of the pandemic so far.

The new estimates were prepared by Trevor Bedford, a genomic epidemiologist at the Fred Hutchinson Cancer Research Center, in Seattle, using data from the COVID Tracking Project at The Atlantic, which compiles the cases and deaths that states report. They were then independently analyzed by the forecasting expert Ryan Tibshirani at the Delphi Group at Carnegie Mellon, which works closely with the CDC on disease modeling. If we look back over the past several months, the method Bedford used has proved more accurate than other means of forecasting near-term deaths.

The problem described by these numbers is not abstract. Some officials in the Trump administration continue to fight reasonable attempts to slow the spread of the virus. Over the past two weeks, the increase in reported coronavirus cases has jumped to record highs. Now the country must face a simple but devastating question: How many people will die in the coming days, just weeks before the first vaccines begin to roll out?

The relationship between coronavirus cases and death might be the most important fact about COVID-19 outbreaks, but it has been one of the hardest to pin down. At the most basic level, it is impossible to say how many people in the U.S. have become infected. Most studies suggest that the infection fatality rate, or the number of people who die divided by the total number of infections (diagnosed or not), is now substantially less than 1 percent, with wide variation between the young and old. And we also know that we confirm only some fraction of the total number of infections.

A case of COVID-19 can be confirmed only by a polymerase chain reaction, or PCR, test—the type of test that laboratories have offered since the spring. But in the early months of the pandemic, the U.S. failed to ramp up testing as the virus spread, so only a small percentage of sick people were tested. In the spring, an enormous outbreak hit the New York metro area, infecting perhaps 20 percent of all New Yorkers, more than 1.6 million people. But up through mid-May, as the initial outbreak wound down, fewer than 200,000 cases were confirmed with PCR tests. (Almost 16,000 people had died in New York City alone by then.)

[Read: The fog of the pandemic is returning]

Those shortcomings meant that the denominator in the pandemic’s key equation—deaths divided by cases—was far too small at first, inflating the death rate. As more testing capacity became available through the year, the U.S. started to detect more infections. States now report 1.5 million tests a day instead of 150,000 tests a day, as they did for much of April. Even now, though, no one is quite sure how many people have been infected; Bedford’s ballpark figure is that three out of four infections still go unconfirmed. (Other estimates are even higher.)

The numerator has also changed during the pandemic. As testing improved, doctors and nurses found new ways of treating patients, aided by medications like dexamethasone and new treatments like monoclonal antibodies, which Trump received during his infection and has raved about since. Public-health interventions—such as lockdowns, social distancing, and masking—helped “flatten the curve,” reducing the strain on emergency rooms and intensive-care units. The upshot: According to public-health groups, such as Prevent Epidemics, that have reviewed published research that looks at data up to August, death rates fell.

A quick comparison of the spring and summer surges demonstrates the change. While the number of cases reported in the summer far exceeded totals from the spring, the death rate and peak of deaths were lower.

Some people in this country, including those in the highest echelons of our government, like Scott Atlas, the Stanford radiologist who now sits on the coronavirus task force, have done everything they can to play down the danger of the virus in the United States. However, in spite of improvements, COVID-19 remained deadly long after the spring: More people have died since June 15 than died before that date, even though the outcome of cases in general has improved. On average, more than 850 Americans have died on average since July 11, back when case numbers were a quarter of what they are now.

This month, Bedford saw case numbers rising quickly and began to ask the obvious question: How many people might die during the third surge? Using data from the COVID Tracking Project, he built a simple method to analyze the death rate. He knew that because COVID-19 kills people slowly, often after days or weeks in the hospital, reported deaths lag behind confirmed cases. State health departments make the lag even longer: They are buckling under the strain of the pandemic, and it takes days, at least, for a person who has died alone in a hospital to be counted among the official death statistics.

But the data are not available to make precise calculations of that lag. So Bedford looked at state-level data to find the best match between case numbers in the past and death numbers some days later. What he found was that plotting the seven-day average of deaths today and the seven-day average of cases 22 days ago maximized the correlation between cases and deaths. At the national scale, you can see how well these numbers parallel each other in the chart below.

Once Bedford settled on this lag period—which roughly squared with a CDC estimate from the summer—he wanted to know how many of the cases reported 22 days ago would translate into deaths. He called this simple calculation of deaths today divided by cases a few weeks ago the “lagged case-fatality rate.” Then he calculated it going back in time.

[Read: The simple rule that could keep COVID-19 deaths down]

The chart that he generated is as simple as it is disturbing. It shows that, as we should expect, far fewer people are dying, per reported cases, than in the early days of the pandemic. But on the chart below, look at August, where much of the published research on death rates ends. The improvement stops. The numbers in the first week of August are not much different from the numbers in the first week of November. By Bedford’s method, the lagged case-fatality rate has averaged 1.8 percent since August.

This should be an extremely urgent signal that the U.S. response to COVID-19 has put the country on a dangerous track.

Case numbers have nearly quadrupled since late September, when roughly 700 people a day were dying. If 1.8 percent of confirmed cases are translating into recorded deaths 22 days later, the U.S. is about to enter some extremely harrowing days. Every 100,000 cases would mean roughly 1,800 dead Americans a few weeks later.

“I expect the U.S. to be reporting over 2,000 deaths per day in three weeks’ time,” Bedford concluded. “Importantly, this doesn’t assume any further increases in circulation and is essentially ‘baked into’ currently reported cases and represents conditions that take time to resolve and to be reported.”

And this analysis does not factor in new dynamics that could make outcomes worse, such as the possibility that local hospital systems collapse, which many health-care workers and experts are warning about . Already, more than 20 percent of hospitals are anticipating a staff shortage this week—and the Mayo Clinic reported that 900 of its workers had tested positive in the past two weeks. Nor does the analysis incorporate the possibility of an overburdened testing system becoming unable to complete as many tests as necessary, which would depress case counts. Either of these factors could push or skew the expected death rate even higher.

This is an extraordinary estimate—and it cuts sharply against the consensus forecasts of how many deaths we should expect. The CDC has a forecasting program that takes in dozens of forecasts. These are then synthesized into an “ensemble model” that has proved to perform better than any individual model at forecasting COVID-19 deaths. When Bedford made his initial investigations, for the week ending on December 5, the ensemble model’s most likely prediction was 8,606 deaths, or 1,230 deaths a day. The absolute outer edge of its prediction cone was 13,416, or 1,917 deaths a day. Bedford’s method predicts more than 14,000 deaths that week, outside the range that’s supposed to capture 95 percent of future possibilities. This was such a dire prediction that we immediately began to try to poke holes in Bedford’s work.

The most obvious source of overprojection would be that Bedford’s average over the past few months could be too high for these coming weeks. When we analyzed the different lagged fatality rates for recent days, we found that 1.7 percent (or even 1.6 percent) seemed to fit current COVID Tracking Project data the best, rather than the 1.8 percent that Bedford calculated over the data since July.

But these three projection lines, along with a fourth depicting an even lower, 1.5 percent death rate, show deaths continuing to rise rapidly. At a 1.8 percent death rate, we might hit 2,000 deaths a day on December 1. At a 1.5 percent death rate, we’d cross that threshold on December 5. The core proposition held: No matter how we plotted these numbers, if there was anything like the recent consistent relationship between cases at some point in the past and deaths today, deaths would rise far more than the ensemble model thinks is likely.

But for an estimate this consequential, we wanted another group of experts to look at the numbers. Perhaps Bedford had made a statistical error. So Tibshirani of the Delphi Group, one of two research groups the CDC has named a forecasting “National Center of Excellence,” agreed to undertake a data-analysis project, checking Bedford’s prediction.

Tibshirani’s first finding was that the lag time between states was quite variable—and that the median lag time was 16 days, a lot shorter than the mean. Looking state by state, Tibshirani concluded, it seemed difficult to land on an exact number of days as the “right” lag “with any amount of confidence,” he told us. Because cases are rising quickly, a shorter lag time would mean a larger denominator of cases for recent days—and a lower current case-fatality rate, something like 1.4 percent. This could mean fewer overall people are dying.

But this approach does not change the most important prediction. The country will still cross the threshold of 2,000 deaths a day, and even more quickly than Bedford originally predicted. Cases were significantly higher 16 days ago than 22 days ago, so a shorter lag time means that those higher case numbers show up in the deaths data sooner. Even with a lower case-fatality rate, deaths climb quickly. Estimating this way, the country would hit an average of 2,000 deaths a day on November 30.

The other major finding in Tibshirani’s analysis is that the individual assumptions and parameters in a Bedford-style model don’t matter too much. You can swap in different CFRs and lag-time parameters, and the outputs are more consistent than you might expect. They are all bad news. And, looking retrospectively, Tibshirani found that a reasonable, Bedford-style lagged-CFR model would have generated more accurate national-death-count predictions than the CDC’s ensemble model since July.

This is not a total surprise. The ensemble model has tended to perform well at moments when the pandemic was proceeding along the path of previous weeks, but this synthesis of forecasts has missed major turning points. Making a forecasting model that can work over long periods is very difficult.

The Bedford model might not hold up long term. It certainly is not a real forecasting model like the ones at the CDC, as Bedford freely admits. But it captures a crucial and counterintuitive dynamic of reality right now: For all our talk of better treatments and more widespread testing, we do not yet see evidence that those factors have led to major declines in the death rate over the past three months. And Bedford’s model doesn’t have to hold up until next March. If the statistical relationships he’s identified hold for just a few weeks, the country will be seeing spring-level deaths.

That’s not even taking into account the idea that the standard of care is likely to fall in places experiencing major surges. Treatment of severe COVID-19 is an intricate and laborious process; understaffed and exhausted units are unlikely to sustain the level of care that has improved the case-fatality rate.

[Read: Hospitals can’t go on like this]

More than 1,000 hospitals were anticipating staffing shortages this week, according to new data from Health and Human Services released to The Atlantic. That squares with in-depth reporting by our colleague Ed Yong about the toll that the pandemic has taken on health-care workers, and the fears they expressed to him about the toll to come, for themselves and for their patients. One doctor told Yong that the entire state of Iowa is now out of staffed hospital beds, with more than 3,000 cases being diagnosed every day. Another, in Utah, told Yong of working 36-hour shifts in an ICU treating twice as many patients as usual, as the state records cases at a rate almost five times greater than its summer peak.

Unlike past surges, this one is not localized to a particular region. So many places are experiencing exploding outbreaks that fewer health-care workers can be brought in from other places. Many of these outbreaks are in rural areas where patients cannot easily be transferred to a nearby hospital.

In the most recent CDC ensemble forecast, released on Monday, the model has begun to predict far more deaths. And yesterday states reported 1,869 deaths, the most single-day fatalities in more than six months. This marked an increase of 330 deaths from last Wednesday—a significant and unusually large jump—but it was very close to what the 1.7 percent CFR Bedford model predicted.

These projections, while rough and packed with uncertainties about the precise numbers, lend more weight to the story that’s playing out across the county: The pandemic is out of control and many, many people are dying. The longer we continue along our current path, the higher the death toll will rise.

Hospitals Can’t Go On Like This

2020-11-17T13:41:00-05:00

The reports have come in from all across the country: Hospitals are filling up, especially in the Midwest, and they are running out of the staff they need to take care of patients.

Last week, the United States broke its record from April for the number of hospitalized COVID-19 patients, blowing past 60,000 all the way to 73,000, according to data compiled by the COVID Tracking Project at The Atlantic.

Now new data released by the Department of Health and Human Services quantify the crisis in America’s hospitals in closer detail. At The Atlantic’s request, HHS provided data on the number of hospitals experiencing staffing shortages. From November 4 to November 11, 958 hospitals—19 percent of American hospitals—faced a staffing shortage. This week, 1,109 hospitals reported that they expect to face a staffing shortage. That’s 22 percent of all American hospitals.

In eight states, the situation is even more dire. More than 35 percent of hospitals in Arkansas, Missouri, North Dakota, New Mexico, Oklahoma, South Carolina, Virginia, and Wisconsin are anticipating a staffing shortage this week. COVID-19 puts pressure on hospitals in two ways. One, staff members get sick or are exposed to the coronavirus and have to stay home, reducing the labor supply. Two, more patients arrive at the hospital, increasing demand. A surge of cases makes both factors worse.

[Read: ‘No one is listening to us’]

As a rule of thumb, the COVID Tracking Project has found that an increase in cases shows up as an increase in hospitalizations about 12 days later. Over the past 12 days, the seven-day average for new cases has jumped from fewer than 90,000 a day to 150,000 a day. While we’ve been able to track the number of people hospitalized with COVID-19 since March, we have not known how many new people were being admitted to hospitals each day, perhaps the best indicator of surging infections. But yesterday, HHS released this data going back to mid-July. At the peak of the summer surge, the seven-day average of daily admissions topped 5,000. Yesterday, the same measure topped 10,000. We should expect many more hospitalizations, and even worse staffing shortages, to come.

Even if a state has open hospital beds, it may not have the workers to put patients in them. “We are short of staff all times, either because they have COVID or they have some other illness, and we need to rule out COVID before we bring them back to work,” University of Wisconsin Health CEO Alan Kaplan told CNBC last week. The desperate times have led to some desperate measures. Last week, North Dakota Governor Doug Burgum ordered that health-care workers who have COVID-19 but are asymptomatic can be sent back to work. Many nurses have objected to the practice.

Even without government mandates, the shortage of workers has meant that only 36 percent of hospital nurses are “always … able to stay home when they have influenza or COVID-like symptoms,” according to a survey by National Nurses United conducted from mid-October to November 9.

[Read: The worst day of the pandemic since May]

And that was before the current surge reached its recent heights. While we don’t have data for the spring, this week’s staffing shortages have already exceeded those of the summer, according to HHS. Nearly every state in every region is showing major increases in hospital admissions. But the Midwest is up roughly seven times from its September low. That’s a lot of pressure to exert on a region’s health-care systems, especially the staff. Beds can be built, floors can be repurposed, but you can’t simply train a new legion of nurses and doctors. During past surges, which were more localized, workers could be brought in from other places, but given that the current onslaught is national, that’s going to be much more difficult.

The core issue is the same one that doctors laid out in the spring: If infections are not brought under control, too many people will end up in beleaguered hospitals, and the standard of care will fall. We largely prevented that over the summer. And measured from the spring into the summer, death rates fell. While it is not clear that this drop continued into the fall, what does seem likely is that if a region’s health-care system begins to collapse under a staffing shortage, the case-fatality rate will rise again. That is to say, unless hospitalization trends change, more people will die, and die within sight of a vaccine.

“If we can get patients into staffed beds, I feel like they’re doing better,” Eli Perencevich, an infectious-disease doctor at the University of Iowa, told my colleague Ed Yong. “But that requires a functional health-care system, and we’re at the point where we aren’t going to have that.”

The Worst Day of the Pandemic Since May

2020-11-10T19:34:00-05:00

The United States is experiencing an unprecedented surge of hospitalizations across the country. Today, states reported that 61,964 people were hospitalized with COVID-19, more than at any other time in the pandemic. For context, there are now 40 percent more people hospitalized with COVID-19 than there were two weeks ago.

Seventeen states are at their current peaks for hospitalizations today. According to local news reports, hospitals are already on the brink of being overwhelmed in I owa, Kansas, Minnesota, Missouri, Montana, North Dakota, Texas, Utah, and Wisconsin, and officials in many other states warn that their health-care systems will be dangerously stressed if cases continue to rise.

[Read: A dreadful new peak for the American pandemic]

The new hospitalization record underscores that we’ve entered the worst period for the pandemic since the original outbreak in the Northeast. Although the number of detected cases was much lower back then because of test shortages, the large number of hospitalizations (and deaths) indicates that there were many more times the number of infections than our then-embryonic and broken testing system could confirm.

In the following months, some commentators, including government advisers, have played down the large case counts by saying tests were detecting people who weren’t actually sick—or if they were sick, only mildly sick. These hospitalization numbers prove that the current surge of COVID-19 cases is not merely the result of increased screening of asymptomatic people. Rather, the cases we’re detecting are a leading indicator that many people are seriously ill. Although case numbers are heavily influenced by the number of tests accessible in a particular area, hospitalizations are not.

The burst of hospitalizations is primarily located in the Midwest, where cases began to rise weeks ago. We have seen no indication that there is an end in sight to the outbreaks in the region. The outbreaks in Illinois, Michigan, and Ohio began spiking more than three weeks after early outlier Wisconsin—and cases and hospitalizations in Wisconsin are still rising.

[Read: Wisconsin is on the brink of a major outbreak]

What we’re seeing in the Midwest could foreshadow what is in store for the rest of the nation. The current wave of COVID-19 infections stretches across the whole country, and hospitalizations are rising in every region. Per capita, hospitalizations in the Midwest have now outpaced the South’s peak over the summer.

Even the Midwest remains far short of the per-capita hospitalizations in the Northeast’s spring outbreaks, but some low-population Midwest states are posting alarming per-capita numbers. And as noted above, we may have a long way to go before we see these outbreaks peak.

In both North and South Dakota, more than 1 in 2,000 state residents are hospitalized with COVID-19 right now. Only New York and New Jersey have seen higher rates of hospitalizations per capita.

Treatments for COVID-19 have improved since the Northeast outbreak. The ratio of hospitalizations to deaths has fallen tremendously since the spring. But it is also true that wherever we see hospitalizations go up, deaths rise two to three weeks later. We’ve seen it happen in state after state, in region after region, and nationally as well.

Improved outcomes depend on maintaining the highest standard of care. With hospitalization numbers like these, it is not clear that health-care systems in all hard-hit areas will be able to maintain this standard. In North Dakota, so many health-care workers have contracted COVID-19 that the state is now putting asymptomatic—but still infectious—workers back into hospitals to care for patients. Another crucial difference from the spring: When the surge hit New York and New Jersey, thousands of medical workers flew in from all over the country to help treat patients. With so many states experiencing severe outbreaks at the same time, it could be harder to mobilize surges of frontline workers to areas where health-care systems are at risk of failure.

The COVID-19 fatality rate is not a constant that can be permanently improved by better knowledge of the disease and the availability of treatments alone. To recover, patients require attentive, informed, round-the-clock care. Although hospital systems have made emergency calls for federal staffing support, discharged seriously ill patients to die at home, and been forced to send patients to other regional hospitals, the United States has never experienced the kind of widespread health-care collapse and care rationing seen in other parts of the world in the spring.

Throughout the year, hospitals and health-care workers have issued warnings that if we do see hospitals overwhelmed, fatality rates will soar. As cases and hospitalizations continue to rise nationwide, we are poised to enter a new and possibly bleaker phase of the pandemic. We can only hope that if more state officials act quickly to establish effective mitigation measures, their effects will come in time to avoid the worst.

This post appears courtesy of The COVID Tracking Project.

A Dreadful New Peak for the American Pandemic

2020-11-04T19:36:00-05:00

The United States reported 103,087 cases of COVID-19 on Wednesday, the highest single-day total on record, according to the COVID Tracking Project at The Atlantic. It marks the first time that the country—or any country in the world, for that matter—has documented more than 100,000 new cases in one day.

At the same time, states reported that more than 52,000 people are hospitalized with the coronavirus, the highest level since early August. The number of people hospitalized nationwide is increasing faster in November than it did in October, and—over the past 10 days—their ranks have risen by about 1,000 people a day.

The record officially marks what was already clear: As winter nears, the country’s third surge of infection is dangerously accelerating in almost every region of the country. This is the reality that the United States is facing, regardless of who will become its next chief executive: A deadly respiratory pandemic is spiraling out of control, and the number of hospitalized people—and deaths—is certain to rise over the next several months.

The unhappy milestone has been months in the making. On the final day of June, as states in the South and Southwest brimmed with infection, Anthony Fauci, the nation’s top infectious-disease expert, warned that the U.S. could soon see a 100,000-case day. His prediction came several months early. Three weeks later, the country’s summertime surge peaked at about 75,000 cases in one day. But that count likely fell far short of actual infections: In the hardest-hit states, such as Arizona, tests were so scarce that symptomatic doctors could not even test themselves.

By early September, the pandemic faded to its lowest level since June, with the country reporting only about 34,000 cases a day. Experts warned that the winter months could prove catastrophic, but President Trump took a victory lap. The country was “rounding the final turn” on the pandemic, he announced at a Pennsylvania rally on September 3, a line he echoed at the White House a week later.

In fact, the country was already riding a third wave of infection. By then, cases and hospitalizations were rising in the upper Midwest and Great Plains; North Dakota and Wisconsin busted through their all-time records. Then the Mountain West exploded, and Utah, Montana, and Idaho set new records. Then finally the Northeast, which had been lacerated in the spring, saw cases tick up.

Now the country has reached the 100,000 mark that Fauci predicted. On Wednesday, 34 states reported more than 1,000 new cases apiece, forming a single belt of infection from Massachusetts to Nevada. Sixteen states saw a record number of their residents hospitalized with the virus. More than 47,000 Americans have died since Trump’s Pennsylvania rally two months ago.

Wednesday’s six-figure record reflects high levels of infection across the country, including in some of the most populous states. Texas reported 9,600 new cases, with nearly a third coming from El Paso, where hospitals are above capacity. Indiana set a single-day record with 3,698 new cases. Illinois recorded 7,500 new cases, and its number of hospitalizations increased.

In addition, South Dakota reported—and North Dakota will likely soon report—more hospitalizations per capita than Arizona saw in its summertime surge.

No matter who wins the presidential election, it is virtually guaranteed that the next several months will be among the darkest of the pandemic. Hospitalizations are virtually certain to rise, and cases could spread further if Americans travel for Thanksgiving. And even if a vaccine were to be approved this month, it would likely not be deployed widely enough to bestow protective immunity for most at-risk Americans until well into the new year, Scott Gottlieb, who led the Food and Drug Administration from 2017 to 2019, has said.

The next president will take power in a country where 100,000 cases form a new baseline. It is November 4, 2020, and the United States is not a healthy country.

Why Trump’s Rapid-Testing Plan Worries Scientists

2020-10-09T10:16:57-04:00

The sun was beaming, the air was clear, and it seemed as if President Donald Trump was finally taking coronavirus testing seriously. Standing in the White House Rose Garden early last week, Trump announced to buoyant officials that a “massive and groundbreaking expansion” in testing was under way: The federal government had purchased 150 million new coronavirus tests from the company Abbott Laboratories.

These new rapid tests were “from a different planet,” Trump boasted. He was right. Each Abbott test cost only $5, one-20th the price of the most widely used test type. Instead of taking hours to deliver a result, the Abbott tests—which detect viral proteins—could provide an answer within 15 minutes. The government planned to send them to states, colleges, and nursing homes, a policy that would “more than double the number of tests already performed,” Trump said.

Every state could, “on a very regular basis, test every teacher who needs it,” he promised.

As Trump spoke, the coronavirus was already teeming through his body, information from his doctor now suggests. By the end of the week, the president, the first lady, and at least 23 of his advisers and staff were infected with the coronavirus. They had acted as if testing alone would protect them, but many of them seem to have been infected at a White House event where Abbott tests were used to screen visitors.

This series of events could have ended another way, with tests such as Abbott’s allowing Americans to recapture a shred of normal life. But it has instead opened to public view an already-ferocious debate among experts about the best way to defeat the pandemic—a fight with consequences that will outlast Trump’s symptoms.

[Read: The president is not well]

Since the spring, a group of experts led by Michael Mina, an epidemiology professor at Harvard, has called for the government to freely distribute tens of millions of 15-minute coronavirus tests a day. Never mind testing every teacher every day: Mina wants to test nearly every American every day, whether or not any given person shows symptoms of COVID-19. That’s impossible to do with the gold-standard reverse-transcription polymerase chain reaction, or PCR, tests—they are too expensive and take too long to return results. Frequent, cheaper testing, Mina claims, could defeat the pandemic within weeks, as infectious people are identified and quarantined. (We wrote about his plan in August.)

Other experts are doubtful and have warned that cheap, rapid tests will not work as promised. If distributed en masse and used to screen asymptomatic people, these antigen tests will deliver hundreds of thousands—if not millions—of false results, they say. False negatives could lead to reckless behavior by people who don't know they're sick. False positives can also put people at risk: If a virus-free nursing-home resident with a false positive is placed in a COVID-19 ward, that person could become infected.

“The point I'm trying to make here, and I'll be blunt, is that antigen testing will not and cannot work for asymptomatic screening, and [it] will probably kill a lot of people,” Geoffrey Baird, the acting laboratory-medicine chair at the University of Washington, told us. His lab at UW developed one of the earliest accurate COVID-19 tests in the U.S., and is widely respected within the diagnostic-testing field. Alexander McAdam, the director of the infectious-diseases diagnostic laboratory at Boston Children’s Hospital, told The New York Times that deploying the current antigen tests to screen populations “is a bad idea, and I’ll die on that hill.”

The stakes of this dispute are not only how Abbott tests are used, but whether they should be used at all. It could shape federal policy next year and determine whether more money is spent on fixes to address the virus aside from a vaccine. Already, this conflict is playing out on the state level. In Nevada, public-health authorities have told nursing homes to stop using two models of antigen-test machines, which the federal government has sent to more than 14,000 facilities, after only 16 of 39 positive tests were confirmed by subsequent PCR testing.

[Read: This overlooked variable is the key to the pandemic]

What everyone agrees on is that the tests were not deployed responsibly at the White House. The president hosted dozens of guests at a ceremony honoring Supreme Court nominee Amy Coney Barrett, without masks, amid a raging pandemic, and rejected some of the most basic safety protocols. As that event has demonstrated, testing must be an and strategy, not an or one. Rapid testing and masking. Rapid testing and social distancing. Rapid testing and vaccines.

“Testing is a belt-and-suspenders approach that adds incremental safety,” Baird said. “Belts and suspenders only work, though, when you are wearing pants.”

The president also seems to have personally rejected testing for himself. Trump’s doctor has persistently dodged questions about when the president last tested negative. The New York Times reported that Trump—who officials once claimed was tested “multiple times a day”—was not swabbed even once a day.

The debacle has accelerated preexisting concerns about the rollout of the Abbott tests. Late last month, even the proponents of rapid testing worried about the plans to distribute and use the Abbott tests. Mina, generally an advocate of rapid testing, warned that if the Abbott tests were not deployed the right way, with the proper safeguards and solid public education, they could further erode trust in the nation’s public-health systems. The White House's cavalier actions have now realized that fear.

These tests have the potential to create two problems. One is commonly cited by critics and very easy to understand: False negatives will give people too much confidence that they are virus-free, just like the White House attendees who drank and celebrated together without masks, even hugging one another. Given a negative test result, many people chose to eschew the simple precautions that have helped slow the spread of the virus.

The other problem is that these tests will generate many false positives, especially if deployed in asymptomatic populations where relatively few people are sick. It could very well be that, as in Nevada, the majority of positive test results are false. Besides the risks of grouping healthy people with those who are actually sick, false positives will keep well people home from work unnecessarily and prompt people to seek “confirmatory” PCR tests, potentially overwhelming an already fragile system.

Mina and other proponents argue that rapid antigen tests could still be useful with their current performance, but that distribution and communication must be improved. “If these tests are not messaged appropriately, we run the risk of the whole program coming crashing down pretty much immediately,” Mina told us.

[Read: How we survive the winter]

The early signs are not encouraging. The new Abbott test, the Binax NOW, received an emergency use authorization (EUA) based on results from just 102 samples. The next day, the government spent $760 million to buy the entire supply of tests. Notably, the FDA did not support the use of the test for screening asymptomatic people—which the most ambitious version of Mina's plan depends on. The emergency use authorization only covered testing for people within the first seven days of developing symptoms, when viral loads remain high.

In asymptomatic people, the tests will likely perform worse. The levels of virus are likely to be lower in any individual infected person, which would increase the false-negative rate. And in the general, symptom-free population, the expected levels of infection are actually quite low, so the false-positive rate could be very high.

Yet Admiral Brett Giroir, the administration’s “testing czar” and an assistant secretary at the U.S. Department of Health and Human Services, has explicitly said that the tests could be used for asymptomatic screening, at schools perhaps.

That contradiction worries Baird. “One branch of the government is saying, ‘Use this test for asymptomatic people,’ and then on the other side, they are saying, ‘Use this test for symptomatic people,’” he said.

Baird is particularly anxious that the performance of tests will deteriorate in the field and when applied to asymptomatic people. That always happens with lab tests, he told us. “They haven’t published clinical-trials data,” he said. “You foist that test on the public after collecting evidence that it would work.”

False positives worry Mina, too. Among people tested within the first seven days of showing symptoms, the Abbott test will, according to its EUA, generate a false positive from roughly one in 50 tests. Because relatively few people test positive out of the whole population, those false positives could represent a large percentage of the positive results that a batch of the tests would generate. For now, the solution is supposed to be for people who test positive to get a confirmatory PCR test. But “saying that these tests need to be confirmed with a PCR test isn’t a good answer,” Mina told us. If a “quick” positive result then forces people to wait four days for a PCR positive, the first result stops meaning much.

Mina suggests that a cornucopia approach could provide the answer: If you take an Abbott test and get a positive result, then you would take another quick test, made by a different company, that detects a different viral protein, for confirmation. He said that such procedures were common in screening for relatively rare diseases, such as HIV, where the Centers for Disease Control and Prevention issues an “algorithm” for sequencing tests.

“People are just thinking about COVID testing differently for some reason, but imperfect screens are pretty common, so I am scratching my head,” says Dan Larremore, a computer scientist and an infectious-disease modeler at the University of Colorado, who has collaborated with Mina. “The perfect has really been the enemy of the good here, in many ways—except that we also know how to embed the good within follow-up systems to make it nearly perfect.”

Mina is running a trial comparing PCR and antigen tests in both symptomatic and asymptomatic people, in order to generate real-world data about false positives and negatives. “My hope is that six weeks from now, we’ll have a pretty good set of data to reflect the performance,” he said.

He still thinks these quick, cheap tests could help America overcome the pandemic. “The point people are really missing is: What is the alternative? The alternative is no testing. Most K–12 students are not getting tested,” Mina said. “Every time we can pull a positive person out of the population, we stop tens, hundreds, or thousands of cases.”

The alternative for Baird is obvious: keep going with the behavioral interventions that have helped at least slow the spread in the U.S. “I think the quintessential problem in the country is an imbalance of supply and demand of testing,” Baird said. “Mina’s solution is increasing supply. And I have a strong belief that decreasing demand will be the way to get there—masking, physical distancing, not having large events. And, unfortunately, absorbing the societal toll that all of those things take.”

While the surface of the debate is about the technological characteristics of these tests, the substance of it is about human behavior. As restrictions on daily life enter their seventh full month and winter draws near, will the countermeasures that have limited, but never contained, the virus’s spread remain in force? And if we add tests that generate imperfect information, will that embolden people to abandon commonsense safety precautions? No test—and no testing strategy—is perfect; we are living through a pandemic, and people will get sick. To believe that antigen testing can improve life in this country is to believe that people will understand the limits of a test result and act accordingly. With the right public messaging, perhaps they could.

Now What?

2020-10-02T04:10:22-04:00

The gravest of what-ifs has become a “what now?”: This morning, while many Americans were sleeping, President Donald Trump announced that he and the first lady have tested positive for the coronavirus. He disclosed his diagnosis in a tweet, sent at nearly 1 a.m. eastern time: “We will begin our quarantine and recovery process immediately. We will get through this TOGETHER!”

The White House did not immediately point to contingency plans should the president become too ill to continue working, nor did it offer an explanation of how Trump was infected—edging an already tense nation toward ever more confusion.

The president’s health is a national-security issue. This is why he is surrounded by a massive security apparatus, including the Secret Service and the White House doctor; it is why people began speculating that nuclear command planes may have been dispatched shortly before the announcement of the positive test. Even during ordinary times, threats to the president’s safety can move markets and awaken armaments.

But these are not normal times, and the president’s diagnosis will intensify a wide-reaching and dangerous global crisis. As the coronavirus pandemic has killed more than 206,000 Americans, Trump has spent months undermining faith in the democratic process and vacillating on proven public-health policies.

[Read: All the president’s lies about the coronavirus]

The president’s reported illness also raises a chain-reaction question: When, exactly, was the president infected? And how many other people in the White House—or across the federal government—might be sick? The first hint that something might have gone amiss came last night, when Bloomberg reported that Hope Hicks, a close Trump adviser, had tested positive for the virus. Hicks was apparently at the president’s side on Wednesday as he traveled to Minnesota for a campaign rally. The night before, Trump had debated former Vice President Joe Biden, standing about a dozen feet from the Democratic nominee for more than 90 minutes.

Hicks came down with symptoms on Wednesday night and “quarantined” on Air Force One on the flight back to the capital, according to The Washington Post. She received a positive test yesterday morning. Yet the White House did not release the results of that test, or hint that anyone near the president might be ill, until Bloomberg’s report hours later.

Trump’s entourage has operated with a casual disregard for coronavirus protocol throughout the pandemic. In August, the president added Scott Atlas, a neuroradiologist with no background in infectious disease, to the Coronavirus Task Force. Atlas proceeded to downplay the virus and meddle with federal testing policy. Upon visiting the White House that month, our colleague Peter Nicholas reported that few West Wing staffers wore masks, and that visitors were not effectively screened for illness. The nation’s most famous address felt “like a coronavirus breeding ground,” he said, because of the lack of safety protocols.

[Read: White House, petri dish]

But the president’s illness still raises more questions than it answers. Although Hicks spent considerable time with the president this week, the timing of her illness and of the president’s positive test result may not match up. COVID-19 has a regular course of disease, with a predictable number of days separating infection, early symptoms, and the worst illness. Even the best PCR tests, which detect the virus’s genetic material, are not likely to catch infections that began within the previous two days. In other words, it typically takes four or more days for the virus to multiply and reach detectable levels inside the body.

Someone can test positive for the virus without experiencing symptoms. The Centers for Disease Control and Prevention says that symptoms of COVID-19 are most likely to begin four to five days after exposure, but they have been observed to start anywhere from two to 14 days after exposure. At the same time, current evidence suggests that people who have COVID-19 are most infectious at the very moment their symptoms begin.

It’s possible, in other words, that Hicks infected the president and the first lady on Tuesday, and he tested positive yesterday. But other possibilities seem just as likely: Perhaps Hicks was sick for longer than she knew, and she infected the president earlier this week. (If so, was she infectious when she attended the presidential debate on Tuesday?) Or perhaps some other person infected the president, the first lady, and Hicks—a scenario that would indicate a very serious outbreak in the White House. It would not be surprising if, in coming days, we learn that more members of Trump’s retinue and Cabinet have contracted the virus. Nor would it be shocking to learn that the president was contagious when he shared a debate stage with Biden.

[Read: Trump’s cordon un-sanitaire]

It’s also possible that the Trump White House has not been or will not be forthcoming about the president’s condition. Many presidential physicians have covered for their boss, and in a memo sent out to reporters, Sean Conley, the White House doctor, gave cheery reassurances that seemed unmatched to the weight of the moment. “Rest assured I expect the President to continue carrying out his duties without disruption while recovering,” Conley wrote.

But as millions of people around the world have discovered, the path that COVID-19 takes through the body is not predictable or kind, especially for older people. Trump is the third major world leader to contract the virus. In April, Prime Minister Boris Johnson of the United Kingdom was infected with COVID-19 during his country’s first wave of infection. Johnson, who is 56, was hospitalized in an intensive-care unit 10 days after he tested positive. He later thanked hospital workers for saving his life, saying his illness “could have gone either way.”

In July, President Jair Bolsonaro of Brazil contracted the virus. The 65-year-old spent nearly 20 days in partial isolation after experiencing fatigue, muscle pain, and fever.

[Read: The coronavirus-denial movement now has a leader]

Donald Trump is 74 years old, which puts him right on the cusp of the CDC’s riskiest age brackets for COVID-19 outcomes. According to the agency, adults who are 65 to 74 years old are at a higher risk of serious illness, hospitalization, and death than younger people. But adults who are 75 to 84 years old are at much higher risk. The fatality rate for people in Trump’s age cohort, based on the CDC’s most recent age-stratified data, is roughly 8 percent. But for people who are 75 to 84 years old, that rate soars to nearly 18 percent. The president, in other words, is unlikely to die from COVID-19. But the possibility must be acknowledged.

Trump’s mishandling of the coronavirus defines his presidency. He downplayed the severity of the disease, misled the country repeatedly about it, tried to pin the blame on local governments, did not “take responsibility at all” for the anemic American response, held massive rallies against scientific advice, hammered on states to reopen before it was safe, rejected easy safety measures, and undermined trust in our public-health institutions. Trump was never going to protect the country from the virus. But ultimately he could not even protect himself.

Fauci to a Meddling HHS Official: ‘Take a Hike’

2020-09-23T12:03:00-04:00

Editor’s Note: This article is part of our coverage of The Atlantic Festival. Learn more and watch festival sessions here.

Yesterday, after weeks of reports about political interference in the efforts of government scientists and public-health experts to inform Americans about the pandemic, Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases, directly addressed the two Trump-administration officials at the center of the recent controversy: Michael Caputo, a spokesperson for the Department of Health and Human Services, and Caputo’s former science adviser, Paul Alexander, who attempted to censor what scientists, including Fauci, said about the coronavirus.

“Caputo enabled Alexander,” Fauci told me over email. “Alexander is the one who directly tried to influence the CDC (he may have succeeded, I cannot really say) and even me (I told him to go take a hike).”

Fauci’s comments came after his appearance at The Atlantic Festival yesterday evening.

As first reported by Politico, Alexander tried to directly intervene in the publication of the Centers for Disease Control and Prevention’s well-known publication Morbidity and Mortality Weekly Report, and wrote scorching emails about CDC officials. He also tried to prevent Fauci from advocating for children to wear masks. Caputo ranted on Facebook Live about “deep state” operatives in the public-health infrastructure.

The interference from Caputo’s team had drawn sharp rebukes from the public-health community, especially as it does indeed appear to have been at least partly successful at influencing the CDC’s messaging. Caputo is now on medical leave, and Alexander was dismissed from HHS last week. (Alexander and HHS did not immediately return requests for comment.)

Watch: Atlantic staff writer Alexis Madrigal in conversation with Anthony Fauci

At the festival, Fauci urged Americans to maintain faith in the nation’s public-health institutions, despite the battles between political appointees at HHS and CDC researchers. “I think we could put that behind us right now,” he said. “I would trust the CDC, and I would trust the FDA.”

The agencies’ troubles haven’t disappeared with Alexander’s departure: This week, the CDC again ran into controversy when it posted, then retracted new guidance on how the coronavirus spreads. But the most serious problems of the American response to the pandemic, Fauci asserted, were much broader and deeper. With at least 200,000 Americans now dead from COVID-19, he said, “obviously the numbers speak for themselves.”

After the virus hit the Northeast, exacting a fearsome toll, Fauci said, states across the Sun Belt allowed case numbers to grow over the summer, which meant the U.S. was never able to get the baseline of cases low enough to mitigate the risks of reopening. “We’re looking at 40,000 new cases per day,” he said. “That’s unacceptable, and that’s what we’ve got to get down before we go into the more problematic winter.”

[Read: How we survive the winter]

Fauci’s message conveyed a new level of urgency about the challenges ahead. Two weeks ago, he told The Atlantic that the country had to get new daily cases down to 10,000 over “the next few weeks” to guard against surges in the winter, when containment will be even harder in many parts of the country as the weather grows colder. Cases, however, have remained near that 40,000-a-day plateau. There are signs that some states, such as Wisconsin, may be on the verge of bigger outbreaks. Time is running out to bring down viral spread.

How might the U.S. get those cases down? The path is well known, and Fauci ticked off the public-health mantras: ubiquitous masking, physical distancing, avoiding crowds, doing things outdoors when possible, and washing your hands. What’s less clear is how anything might change in the U.S. over the next few months, because public-health officials have long been saying that these things were necessary to constrain the virus. Fauci pointed out that their advice continues to be met with furious resistance and violent rhetoric from America’s right-wing fringe. “People have been threatening me as a public-health person, literally threatening me and my family,” Fauci said, “because I’m saying we should be doing public-health things like wearing a mask and physical distancing, as if I’m doing something that is harmful to them … not that the virus is hurting us.”

[Read: Anthony Fauci, lightning rod]

Fauci is much more optimistic about the development of a vaccine, which has progressed at an unprecedented speed. He cited the large-scale, Phase 3 clinical trials currently under way in the U.S. “The results that we have actually do look good,” he said. (One trial, AstraZeneca’s, remains partly on hold after two participants developed serious neurological illnesses.)

The federal government’s investments in vaccine development and production are a bright spot in the American response, which otherwise has been uncoordinated, chaotic from the top down, and predicated on pinning blame on individual states. By contrast, Operation Warp Speed, a name Fauci often decries because it sounds reckless, has been well funded, organized, and effective. In normal circumstances, vaccine makers would wait until after clinical trials conclude to begin manufacturing, but government funds have allowed them to begin over the past several months. “If we get an answer, let’s say, November, December—it’s possible it could be earlier, but I think it’s going to be likely November, December,” Fauci said, “we can then start vaccinating people, starting with the health-care workers, … the elderly, and those with underlying conditions.”

The Trump administration’s political rhetoric about vaccine development has raised alarm among other public-health experts. In the lead-up to the election, Trump has begun teasing that a vaccine could be available in weeks. Some have wondered whether the design of the current trials, released after substantial public pressure, will actually reveal the information that’s needed about these new vaccines. “The trials need to focus on the right clinical outcome—whether the vaccines protect against moderate and severe forms of COVID-19—and be fully completed,” wrote Eric Topol, a molecular-medicine professor at Scripps Research, and Peter Doshi, a professor at the University of Maryland School of Pharmacy, in a New York Times op-ed yesterday.

People across the political spectrum also are expressing uncertainty about taking the vaccine, which could blunt the positive effects of its availability.

So, as we approach winter, there are two wildly different stories to tell about what might happen. In the storybook ending, a vaccine becomes available, more testing reduces the number of contagious people, and the country brings the virus under control. In the darker scenario, vaccines are delayed, or even if one arrives, few people accept it as safe. Testing is ineffective, and collapsing social cohesion leads to less adherence to simple, effective public-health measures.

[Read: A vaccine reality check]

Throw in a presidential election, flu season, climate chaos, rampant misinformation online, and the path the country may end up on is not at all clear. “What the general public needs is a message that’s consistent, and that they can believe,” Fauci said. “And what’s happened, unfortunately—and I think you’d have to be asleep not to realize this—is that we are living in a very divisive society right now; there’s no doubt about that … It’s politically charged, and what’s happened is that public-health issues and public-health recommendations have taken on a we-versus-them approach.”

Can America’s science-and-technology infrastructure save us from a crumbling politics of grievance and anger? Not even a public servant with a record like Fauci’s can predict that.

The Fog of the Pandemic Is Returning

2020-09-10T08:00:00-04:00

President Donald Trump has never hidden his ambivalence about testing for the coronavirus. In June, when he told an arena of supporters in Tulsa, Oklahoma, that he had instructed “his people” to “‘slow the testing down, please,’” the disclosure prompted one of the more dire news cycles of the pandemic. The president said repeatedly that he wanted the United States to reduce its testing. But in the weeks that followed, testing increased.

Not so now. In the past month, the number of tests conducted in the United States has actually drifted down—and that may be partly because of Trump-administration policy.

The United States now reports about 100,000 fewer daily tests than it did in late July, according to the COVID Tracking Project at The Atlantic. Some of this decline is due to reduced demand: The surge of infections across the South and West has subsided, and when fewer people are sick, fewer people seek out tests. Yet this cannot explain all of it. In the Midwest, the number of confirmed cases is growing faster than the number of tests, which has been a sign of a growing outbreak throughout the pandemic.

[Read: A devastating new stage of the pandemic]

The decline in reported tests has come just as other changes have hit the testing system. In recent weeks, the Trump administration has taken unprecedented steps to interfere with guidance from the Centers for Disease Control and Prevention. As a result of White House meddling, the CDC now recommends against testing asymptomatic people, the group that may spread the virus the most. At the same time, new antigen-testing technology is rolling out nationwide. While quicker tests in greater numbers should help curb the virus, they are also decentralizing data collection.

So far, the U.S. has reported only about 200,000 antigen-test results. But some evidence suggests that these tests are being used on a much wider scale than is understood: Thousands, if not tens of thousands, of antigen tests may already be happening every day without their results appearing in any public data. Just as dark matter can’t be observed directly, even though it makes up much of the universe, this “dark testing” does not show up in the data but may already account for a substantial chunk of the coronavirus testing done in the U.S.

[Read: The plan that could give us our lives back]

The result of these changes is that some once-trustworthy numbers and measurements—such as the number of tests conducted in each state, and the percentage of tests that come back positive—now seem less reliable. Over the past months, as states have developed their testing systems, the picture of the pandemic clarified, but now it is blurring again.

In the immediate future, antigen tests could roll out nationwide, allowing health-care workers to catch outbreaks before they erupt. Or the national testing system could deteriorate further under White House pressure, meaning that states and cities might realize that an outbreak is growing only when hospitalizations bloom. As we stand at this crossroads, still confirming tens of thousands of cases a day, the shape of the pandemic is going to change again, and we may not have the tools we need to see how.

The first major change to beset the testing system is entirely because of Trump. Two weeks ago, the CDC changed its official guidance about when Americans should get a coronavirus test. The agency had once maintained that everyone who was exposed to the virus should get tested for it. Now it altered this advice: If someone was exposed to the virus but did not yet have symptoms of COVID-19, they did not necessarily need a test, the guidance said.

The edit was small but significant. It also made no sense. Scientists have known for months that people can spread the coronavirus before they develop symptoms of COVID-19, and some evidence suggests that truly asymptomatic people—that is, those who are infected but never develop symptoms—may be more efficient spreaders than anyone else. The only way to distinguish between a healthy person and an asymptomatic person who has COVID-19 is to test them. But this is exactly what the CDC now recommends against.

“To say you don’t have to test asymptomatic people—while knowing at least half of infections are driven by asymptomatic people—is idiotic,” Kristian Andersen, an immunology professor at Scripps Research, told us.

[Read: America is trapped in a pandemic spiral]

This change in guidance did not originate inside the CDC, according to CNN and The New York Times. Instead, the change was imposed on the agency by the White House, acting on the advice of Scott Atlas, a neuroradiologist and conservative policy wonk who has started to advise Trump on the pandemic. Atlas fought with Robert Redfield, the CDC’s director, over the new policy, according to the Times.

Atlas, who has no background in infectious disease, has advocated for a so-called herd-immunity approach, asserting that the federal government should protect only the elderly and the most vulnerable from COVID-19. This would lead to many more American deaths—Sweden, which pursued a similar policy, has a higher case-fatality rate than the United States, the European Union average, Iran, and more than 100 other countries, according to data from Johns Hopkins University—and it may not even work. But more important, herd immunity has nothing to do with testing. There is no reason that advocates of the herd-immunity approach should oppose testing, unless their goal is to let an outbreak spiral beyond control before anyone notices, Andersen said. “If you don’t test [asymptomatic people], you have a lower reported number of cases, but you end up with more cases overall. And you end up with more deaths and more hospitalizations, which you can’t hide, because you lose control of the virus.”

The change to the CDC guidance is not the only disruption of the testing landscape. In the past month, doctors and hospitals have started to use faster but less sensitive tests to look for the coronavirus. Unlike the gold-standard PCR tests, which detect genetic material from the virus, these tests look for the presence of chemicals, called antigens, that make up the virus. As we’ve written, these antigen tests will be a crucial tool in defeating the pandemic, because they will let offices, nursing homes, and other semipublic places identify contagious but asymptomatic people before they spread the virus.

We believe that dark testing is happening, because we see a hole where data about antigen testing should be. Millions of antigen tests are now being manufactured every month. Quidel, a $6 billion company that makes one of the most widely used antigen tests, says that it began producing at least 1 million tests a week earlier in the summer. In recent days it has upped that rate to nearly 2 million. “We don’t have any inventory,” Doug Bryant, its chief executive, told us. “We ship every day with what we have.” Becton Dickinson, which makes a competing antigen test, has predicted that it would be manufacturing 2 million tests a week by the end of September.

Some federal agencies have made these tests central to their national strategy. In August, the Centers for Medicare and Medicaid Services announced that it would buy antigen tests from Quidel and Becton Dickinson, for nursing homes nationwide. Estimates calculated from agency data suggest that it will distribute 2 million to 4 million tests to more than 13,000 nursing homes by September 30.

[Read: The most American COVID-19 failure yet]

Yet these millions of tests are missing from the public data. Only six states, representing 50 million people, make separate antigen-test data readily available. Those data show that a mere 215,000 antigen tests have been reported since early August, when they first appeared on state dashboards. Even if the data are taken as representative of the U.S. as a whole, and scaled accordingly, they imply that only 1.4 million antigen tests have ever been conducted—far fewer than the number of tests that companies have shipped since June, which is on the order of tens of millions.

Even though the Department of Health and Human Services has spent tens of millions of dollars distributing tests, it could not tell us how many of the tests have been used. The agency has said that it is aware of the reporting issue, and in late August, it threatened to fine nursing homes that do not report test results accurately. (The department did not respond to multiple requests for comment.)

In some ways, a small data gap is not surprising: Data about antigen tests are virtually guaranteed to be spottier than data about PCR tests. Antigen tests are conducted and analyzed in the same places where they’re used: nursing homes, doctors’ offices, and schools. PCR tests, meanwhile, must be analyzed at a central lab or hospital. Because labs and hospitals regularly report large amounts of data to public-health agencies, but schools and nursing homes do not, PCR data will almost always be more complete.

But this dark testing is missing from other places you might expect it to show up. For instance, under CDC rules that define who has a “case” of COVID-19, a person who tests positive on an antigen test is said to have a “probable case.” If antigen tests were flooding the market, states would report hundreds of thousands of probable cases. Yet again, there’s a gap: Most states do not report probable cases as a separate category. Of the more than 6.3 million COVID-19 cases reported in the United States, only 80,000 are “probable.” The antigen tests are missing here, too.

The dark-testing problem is certain to get worse. Quidel and Becton Dickinson say they will produce about 4 million tests a week, combined, by the end of September. Quidel is “building towards 5 million tests a week next year,” Bryant said. A third company, Abbott Laboratories, claims that in October, it will begin producing 50 million of its cheaper coronavirus tests a month. Abbott’s prospective volume alone is more than double the number of PCR tests ever conducted in a month nationwide; it means that dark testing would encompass as many as two in every three American coronavirus tests conducted by the end of the year.

All of this is to say: Antigen tests are being produced by the millions and showing up in our testing data in small numbers that require major and unreliable extrapolation.

[Read: How I mastered the art of ventilating my home]

What’s actually happening? There are multiple possibilities: First, perhaps only tens of thousands of antigen tests have actually been conducted, even though millions exist. For now, most antigen tests require a desktop machine, so the throughput for any individual location is limited. “You can run eight Quidel tests in the same amount of time you can run a full PCR plate of 384” tests, Andersen, the immunologist, said. “I would assume these tests would be dwarfed by PCR capacity—I would hope.”

Second, perhaps most test locations are simply not reporting test data back to state authorities; few point-of-care locations are set up to report these data electronically, so the hassle factor is high. Third, some states may be lumping antigen tests in with their PCR testing or case numbers. Researchers at the COVID Tracking Project at The Atlantic think at least 10—and perhaps as many as 30—states are lumping antigen tests in with PCR tests, which would hide them from our analyses. Finally, probable cases might not show up in the data, because nearly everyone who gets a positive antigen test is quickly retested by PCR. That’s what happened to Ohio Governor Mike DeWine, who tested positive for the virus on a rapid antigen test last month, then tested negative for it when retested by PCR later in the day.

Of course, some combination of factors could be at play simultaneously.

This is the current state of pandemic tracking: It is difficult to know whether millions of tests have been conducted at all. And if the data system is missing so many tests now, when maybe hundreds of thousands of antigen tests are being done each week, imagine what this will look like in a few months, when 1 million antigen tests might be completed each day. There is little doubt that we will lose the ability to track the large majority of tests completed in the country.

That could ultimately be a good thing, because it would signify that tests are so ubiquitous—and such a regular feature of everyday life—that they no longer need to be tracked as systematically. But because that change has come now, just as officials within the Trump administration are acting to suppress testing as never before, it has introduced uncertainty and disorder. If the number of tests completed each day continues to fall in the data, what will that reveal? It could mean that every American who wants a test can get one. Or it could mean that the president has finally succeeded in reducing testing.

A New Era of Coronavirus Testing Is About to Begin

2020-08-27T20:18:00-04:00

In 24 hours, the testing landscape of the United States has transformed.

Yesterday morning, all of the tests for COVID-19—traditional or rapid—that had received emergency authorization from the Food and Drug Administration required an expensive machine and cost around $40 or more. In the afternoon, the health-care company Abbott announced that it had received FDA authorization to distribute a new type of test. This test requires only a coated-paper card and a small swab, and the scale of its production is stunning: Abbott says it will begin manufacturing 50 million of these tests a month in October. The tests will cost just $5 apiece.

That wasn’t the only news. This morning, the Trump administration announced that it would be purchasing 150 million of these tests from the company. For comparison, states have reported fewer than 75 million tests total over the past six months, according to the COVID Tracking Project at The Atlantic.

Many experts have hailed Abbott’s new test as a huge milestone, and a rapid acceleration toward a plan that could give Americans back some sense of normalcy. Deployed widely and often enough, tests like Abbott’s might allow for kids to return to school, office workers to head back to cubicles, and essential employees who have been working throughout the pandemic to have a greater degree of safety. At a time when so many people are desperate to escape the pandemic, this kind of testing holds the tantalizing promise of a pre-vaccine way out of the quagmire.

[Read: The plan that could give us our lives back]

Abbott’s test itself is not quite the fulfillment of that grand vision, though—at least not yet. Michael Mina, a Harvard epidemiologist who has pushed for the deployment of this kind of rapid test, was not ready to declare that the new era had begun. “This is the type of test that we’ve been waiting for, but may not be the test,” Mina told me.

The fine details of the FDA’s emergency use authorization, the regulatory sign-off that allows a test to be sold, are significant. Antigen tests such as this one detect viral protein and are less sensitive than the gold-standard PCR tests, which detect viral RNA. So, to gain acceptance, Abbott showed data confirming that its test was able to classify a pool of samples in nearly the same way as PCR tests of the same samples. Although its performance was impressive, the number of samples was far smaller than would be tested under normal circumstances—just 102.

Also, the FDA’s authorization allows Abbott’s test to be used only on people with symptoms of COVID-19 within seven days of the onset of their symptoms. It cannot be used to test people at any time, an approach that is often called screening. Mina said that limits the test’s potential, because it can’t be used to detect people who carry the virus but don’t show symptoms, and asymptomatic and presymptomatic people are thought to transmit a substantial percentage of infections.

Kristian Andersen, an infectious-disease researcher at Scripps Research, noted that Abbott developed an app to go along with the test that would provide proof that a person had recently tested negative. To Andersen, this is clear evidence that “Abott didn’t just have symptomatic diagnostics in mind here, but also screening of asymptomatic people.” Symptomatic people are much more likely to have the virus, decreasing the chance of a false positive. For asymptomatic people, even in an area with lots of infections, Andersen worried that Abbott’s test isn’t accurate enough, and would generate a substantial number of false positives. (In May, Abbott was embroiled in a controversy over the sensitivity of another one of its rapid tests, Abbott ID Now.)

Andersen and Mina both offered up prospective solutions to increase the test’s specificity. For example, a future version of the test could look for two viral targets. Or two tests could be packaged together, one of which would be a slightly more expensive test that you’d take if you got a positive on the first. That is to say, many questions remain about the test, about Abbott’s strategy, about the Trump administration’s distribution of the tests, and more.

To process the potentially big news, I reached out to Abbott’s lead scientist on the project, John Hackett, to address some of the questions about how the new test might be deployed, improved, and criticized. I’ve condensed and lightly edited our conversation for clarity. Abbott’s FDA authorization might be limited right now, but the company’s vision is clearly bigger than its current regulatory status.

Alexis C. Madrigal: How do you see these tests being used?

John Hackett: This project was built around the concept: What do we need to start to move our society back to normal? How do we get people back to work? How do we ensure these workforces will be as safe as possible? How do we get people back to school? That was the goal.

So we really did want to have tests that could be as broadly distributed as possible.

Madrigal: Fifty million tests a month is a huge number. That’s more than twice the number of tests the U.S. completes in a month. How did you ramp up production so massively?

Hackett: This was the challenge of this program. We needed some sort of reliable testing that could be affordable and that doesn’t require instrumentation. You need scale. The more frequently you could test people, frankly, even tests with lower sensitivity would be very effective at identifying people quickly and slowing the spread. As we were developing the test, there were people working in parallel looking at supply chain and logistics. Abbott took a lot of risk—hundreds of millions of dollars were spent building two new manufacturing facilities focused solely on those tests. We hoped we could come to a solution that would be where we needed it from an overall accuracy perspective, but if you weren’t building capability simultaneously, there was no way it could be the answer.

[Read: A dire warning from COVID-19 test providers]

Madrigal: With the current sensitivity of the test, there are some questions about it as a screening test. The [emergency use authorization] doesn’t allow that yet. What would you have to do to roll this out as an FDA-authorized screening test?

Hackett: The FDA is starting to create templates for over-the-counter-type testing. We’re looking at that. And trying to explore the challenges. When you think about going to home testing, there are a lot of factors involved. This test is very easy to use; there’s no question. But you’d have to worry about how people store them. Are they sitting in their hot car? This test will be a major step, but we do have to continue to explore others.

Madrigal: So right now this test still needs to be done in some kind of a facility. But when I look at the number of tests you’re able to produce, it makes me think that at-home testing is where you’re ultimately driving, even if you aren’t allowed to do screening in general yet. Is that true?

Hackett: This is really a critical first step. The first primary thought was being able to do tests where people gather: a workplace is a good example, or a school. There, you can have a health-care provider—it doesn’t have to be a doctor, could be a school nurse, an occupational health specialist—who would use [the test] with very limited training. Any facility that has a CLIA certificate [in this case, a kind of waiver] for testing in a new-patient setting would be capable of using this.

We recognize there could be value in home testing, and we’ll continue to look at this. There are concerns. When you go to home testing, how effective is the sampling a person does? That’s the importance of why we chose a nasal swab [which just goes in the nostril] instead of nasopharyngeal [which goes way up in the nose]. It’s night and day in terms of pain. And you do need a trained health expert to do nasopharyngeal. We’ll explore other pathways to getting more testing to the people who need it.

Madrigal: One complication with widespread antigen testing is that it’s blurring the national picture of the pandemic. These tests aren’t really being reported, so even though this type of test is valuable, they’re currently creating a hole in the data. Have you given some thought to the data-reporting side of this?

Hackett: People testing are supposed to report positives. For example, if you were an employer using a test like this, that is the responsibility of the health group. We have created the Navica app, a complementary mobile app that goes with the test. We weren’t using it for that purpose, but it is one that allows the person to get a digital health pass.

We were thinking about: How can you lock in testing a test result and be able to verify that you were, in fact, tested? If you were an employer, you could know the employees have done the testing at whatever interval you wanted to do the testing. The default setting for that is seven days, but that could be modified.

Madrigal: Take my kids’ school as an example. It wants to do rapid testing. How would the school go about getting your tests and doing this testing? How would it actually work?

[Read: Why can’t we just have class outside?]

Hackett: We at Abbott do testing of critical staff. This is the sort of thing that can be set up. You need some health-care providers and to figure out what is the interval of testing that would achieve what your goal is overall or what you think is appropriate. Then it is really just organization. Again, I think that’s where the Navica app would be a real plus. If you went into a school building, they could just check; it would be like a boarding pass. And if, unfortunately, you were positive, you’d get a message to quarantine and see your doctor.

Madrigal: But that sounds like broad screening to me, not diagnostic testing of someone with symptoms.

Hackett: Well, that comes back to the health-care provider. For this test, you still need, in essence, a prescription, saying that these individuals are suspected or they have symptoms. This test, the indication is for seven days or less after the onset of symptoms.

Madrigal: How do you improve a test like this? How do you take the basic components and say “This is how we’re going to get to this sensitivity and this specificity”?

Hackett: Well, this is a situation where, obviously in this outbreak, there has been very little time to react. We haven’t had the normal time frames that we would to develop tests like these. There was a tremendous amount of work that went into the process, every level of this.

What protein of the virus should we target? Then, looking at the reality in this format, during the extraction process off of the swab, you need to be able to separate the proteins that are part of that virus in order to be able to detect them. So would you choose spike or nuclear protein? What type of swab? Abbott’s got a long history of this in the infectious-disease area. You can go back to 1985; we had the first FDA-approved test for HIV. This is part of our history.

The Plan That Could Give Us Our Lives Back

2020-08-14T10:05:46-04:00

Michael Mina is a professor of epidemiology at Harvard, where he studies the diagnostic testing of infectious diseases. He has watched, with disgust and disbelief, as the United States has struggled for months to obtain enough tests to fight the coronavirus. In January, he assured a newspaper reporter that he had “absolute faith” in the ability of the Centers for Disease Control and Prevention to contain the virus. By early March, that conviction was in crisis. “The incompetence has really exceeded what anyone would expect,” he told The New York Times. His astonishment has only intensified since.

Many Americans may understand that testing has failed in this country—that it has been inadequate, in one form or another, since February. What they may not understand is that it is failing, now. In each of the past two weeks, and for the first time since the pandemic began, the country performed fewer COVID-19 tests than it did in the week prior. The system is deteriorating.

Testing is a non-optional problem. Tests permit us to do the most basic task in disease control: Identify the sick, and separate them from the well. When tests are abundant, they can dispel the fear of contagion that has quieted public life. “The only thing that makes a difference in the economy is public health, and the only thing that makes a difference in public health is testing,” Simon Johnson, the former chief economist of the International Monetary Fund, told us. Optimistic timelines suggest that vaccines won’t be widely available, in the hundreds of millions of doses, until May or June. There will be a transition period in which doctors and health-care workers are vaccinated, but teachers, letter carriers, and police officers are not. We will need better testing then. But we need it now, too.

[Read: How the pandemic defeated America]

Why has testing failed so completely? By the end of March, Mina had identified a culprit: “There’s little ability for a central command unit to pool all the resources from around the country,” he said at a Harvard event. “We have no way to centralize things in this country short of declaring martial law.” It took several more months for him to find a solution to this problem, which is to circumvent it altogether. In the past several weeks, he has become an evangelist for a total revolution in how the U.S. controls the pandemic. Instead of restructuring daily life around the American way of testing, he argues, the country should build testing into the American way of life.

The wand that will accomplish this feat is a thin paper strip, no longer than a finger. It is a coronavirus test. Mina says that the U.S. should mass-produce these inexpensive and relatively insensitive tests—unlike other methods, they require only a saliva sample—in quantities of tens of millions a day. These tests, which can deliver a result in 15 minutes or less, should then become a ubiquitous part of daily life. Before anyone enters a school or an office, a movie theater or a Walmart, they must take one of these tests. Test negative, and you may enter the public space. Test positive, and you are sent home. In other words: Mina wants to test nearly everyone, nearly every day.

The tests Mina describes already exist: They are sitting in the office of e25 Bio, a small start-up in Cambridge, Massachusetts; half a dozen other companies are working on similar products. But implementing his vision will require changing how we think about tests. These new tests are much less sensitive than the ones we run today, which means that regulations must be relaxed before they can be sold or used. Their closest analogue is rapid dengue-virus tests, used in India, which are manufactured in a quantity of 100 million a year. Mina envisions nearly as many rapid COVID-19 tests being manufactured a day. Only the federal government, acting as customer and controller, can accomplish such a feat.

If it is an audacious plan, it has an audacious payoff. Mina claims that his plan could bring the virus to heel in the U.S. within three weeks. (Other epidemiologists aren’t as sure it would work—at least without serious downsides.) His plan, while costly, is one of the few commensurate in scale to the pandemic: Even if it costs billions of dollars to realize, the U.S. is already losing billions of dollars to the virus every day. More Americans are dying of the coronavirus every month, on average, than died in the deadliest month of World War II. Donald Trump has said that the U.S. is fighting a “war” against an “invisible enemy”; Mina simply asks that the country adopt a wartime economy.

[George Packer: We are living in a failed state]

We have been covering coronavirus testing since March. For most of that time, the story has been one of failure after failure. But in the past few weeks, something has changed. After months without federal leadership, a loose confederation of scientists, economists, doctors, financiers, philanthropists, and public-health officials has assembled to fill in that gap. They have reexamined every piece of the testing system and developed a new set of tactics to address the months-long testing shortage. Mina’s plan is the most aggressive of these ideas; other groups—such as the new nonprofit Testing for America, founded by private-sector experts who helped the White House in the spring—have advanced their own plans. Taken together, they compose a box of tools that could allow the country to fix its ramshackle house.

The government has also done more in the past month to stimulate the creation of new kinds of tests than it has done in any period of the pandemic so far. The National Institutes of Health has awarded $248 million in grants to companies so that they can scale up alternate forms of COVID-19 testing as quickly as possible. The Centers for Medicare and Medicaid has begun to support the nascent testing market as well. This investment is belated and too meager—by comparison, the government has spent more than $8 billion on vaccine development—but it is significant.

If the new proposals make anything clear, it’s that it is in our power to have an abundance of tests within months—and to return life to normal, or something close to it, even before a vaccine is found. There is a way out of the pandemic.

Today, if you go to the doctor with a dry cough and fever, and get swabbed for COVID-19, you will probably receive a test that was not designed for an out-of-control pandemic. It’s called a “reverse-transcription polymerase chain reaction” test, or PCR, test, and it is one of the miracles of medicine. The PCR technique has allowed us to probe the genomes of the Earth: Its invention, in 1983, cleared the way for the Human Genome Project, the early diagnosis of certain cancers, and the study of ancient DNA. It works, in essence, like a zoom-and-enhance feature on a computer: Using a specific mix of chemicals, called “reagents,” and a special machine, called a “thermal cycler,” the PCR process duplicates a certain strand of genetic material hundreds of millions of times.

When used to test for COVID-19, the PCR technique looks for a specific sequence of nucleotides that is unique to the coronavirus, a snippet of RNA that exists nowhere else. Whenever the PCR machine—as designed and sold, for instance, by the multinational firm Roche—encounters that strand, it makes a copy of both that sequence and a fluorescent dye. If, after multiplying both the strand and the dye hundreds of millions of times, the Roche machine detects a certain amount of the dye, its software interprets the specimen as a positive. To have a “confirmed case of COVID-19” is to have a PCR machine detect the dye in a sample and report it to a technician. Tested time and time again, the PCR technique performs stunningly well: The best-in-class PCR tests can reliably detect, in just a few hours, as few as 100 copies of viral RNA in a milliliter of spit or snot.

The PCR test has anchored the American response to the pandemic. In CDC guidelines written by a council of state epidemiologists, a positive PCR result is the only way to confirm a case of COVID-19. And the Food and Drug Administration, which regulates all COVID-19 tests used in the U.S., judges every other type of test against PCR. Of the more than 62 million COVID-19 tests conducted in the U.S. since March, the overwhelming majority have been PCR.

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However, a small but growing pile of clinical evidence—and a sky-scraping stack of real-world accounts—has revealed glaring issues with PCR tests. From a public-health perspective, the most important questions that a test can answer are: Is this person infected and contagious now? and If he’s not contagious, might he be soon? But these are not questions that even a positive PCR result can address. And especially as they’re conducted in the U.S. today, PCR tests do not tell us what we need to know to stop the virus.

Imagine that, at this instant, you are exposed to and infected with the coronavirus. You now have COVID-19—it is day zero—but it is impossible for you or anyone else to know it. In the following days, the virus will silently propagate in your body, hijacking your cells and making millions of copies of itself. Around day three of your infection, there might be enough of the virus in your nasal passages and saliva that a sample of either would test positive via PCR. Soon, your respiratory system will be so crowded with the virus that you will become contagious, spraying the virus into the air whenever you talk or yell. But you likely will not think yourself sick until around day five, when you start to develop symptoms, such as a fever, dry cough, or lost sense of smell. For the next few days, you will be at your most infectious.

And here is the first problem with PCR. To cut off a chain of transmission, public-health workers have to move faster than the virus. If they can test you early—around day three of your infection, for instance—and get a result back in a day or two, they may be able to isolate you before you infect too many people.

But right now, the U.S. is not delivering PCR results anywhere close to that fast. Brett Giroir, the federal coronavirus-testing czar, admitted to Congress last month that even a three-day turnaround time is “not a benchmark we can achieve today.” As an outbreak raged in Arizona this summer, some PCR results took 14 days or more to come back. That’s worse than useless—“I would not call that a test,” Johnson, the economist, told us—because most bouts of COVID-19 last 14 days or fewer. “The majority of all U.S. tests are completely garbage, wasted,” Bill Gates, who has helped fund COVID-19 testing, recently said.

After your symptoms start around day five, you might remain symptomatic for several days to several months. But some recent studies suggest that by day 14 or so—nine days after your symptoms began—you are no longer infectious, even if you are still symptomatic. By then, there is no longer live virus in your upper respiratory system. But because millions of dead virus particles line your mouth and nasal cavity, and because they contain strands of intact RNA, and because the PCR technique is very sensitive, you will still test positive on a PCR test. For weeks, in fact, you may test positive via PCR, even after your symptoms abate.

And here is PCR’s second problem: By this point in your illness, a positive PCR test does not mean what you might expect. It does not mean that you are infectious, nor does it necessarily mean that there is live SARS-CoV-2 virus in your body. It does not make sense to trace any contacts you’ve had in the past five days, because you did not infect them. Nor does it make sense for you to stay home from work. But our country’s public-health infrastructure cannot easily distinguish between a day-two positive and a day-35 positive.

The final issue with PCR tests is simple: There aren’t enough of them. The U.S. now runs more than 700,000 COVID-19 tests a day. On its own terms, this is a stupendous leap, a nearly 800-fold increase since early March. But we may be maxing out the world’s PCR capacity; supply chains are straining and snapping. For months, it has been difficult for labs to get the expensive chemical reagents that allow for RNA duplication. Earlier this summer, there was a global run on the tips of pipettes—the disposable plastic basters used to move liquid between vials. Sometimes the bottleneck is PCR machines themselves: As infections surged in Arizona last month, and people lined up to be tested, the number of tests far exceeded the machines’ capacity to run them.

The COVID Tracking Project at The Atlantic

When tests dwindle, the entire medical system suffers. In Arizona, many doctors’ offices were short-staffed at the peak of the outbreak, because any doctor exposed to the virus needed to test negative before returning to work, and the system simply couldn’t handle the volume of tests. “We’ve had people out seven to 10 days” waiting for a negative result, Catherine Gioannetti, the medical director of health and safety for Arizona Community Physicians, told us. “It’s essentially a broken system, because we don’t have results in a timely fashion.”

If labs don’t have the capacity to turn around doctors’ tests, which are often fast-tracked, they definitely do not have the capacity to test contagious people who are wholly asymptomatic. These silent spreaders may remain infectious for weeks but never develop any symptoms. They are the virus’s “secret power,” one testing executive told us, and they account for 20 to 40 percent of all infections. Some evidence suggests that they may be more infectious than symptomatic people, carrying higher viral loads for longer.

The challenge is clear: We need an enormous number of tests. As some have argued since the spring, the American population at large—and not just feverish, coughing people—has to be screened. Let’s say, for instance, that you wanted to test everyone in the U.S. once a week. That’s 45 million tests a day. How can we get there?

In the immediate future, the only way to increase testing is to squeeze more tests out of the existing PCR system. Our best bet to do so fast is through a technique called “pooling,” which could get a few hundred thousand more tests out of the system every day.

Pooling is straightforward: Instead of testing each sample individually, laboratories combine some samples, then test that “pooled” sample as one. The technique was invented by Robert Dorfman, a Harvard statistician, to test American soldiers for syphilis during World War II. Today it is commonly used by public-health labs to test for HIV. It works as follows: A lab technician mixes 50 HIV samples together, then tests this pool. If the result is negative, then none of the patients has HIV—and the researcher has evaluated 50 samples with the same materials it takes to run one test.

But if the pooled sample is positive, a new phase starts. The technician pools the same specimens again, this time into smaller groups of 10, and retests them. When one of these smaller pools is positive, she tests each individual sample in it. By the end of the process, she has tested 50 people for HIV, but used only a dozen or so tests. This approach saves her hundreds of tests over the course of a day.

Pooling is a great first step to maximizing our test supply, Jon Kolstad, an economist at UC Berkeley, told us. This is in part because regulators and public-health officials are already familiar with it. The FDA has told Quest Diagnostics, LabCorp, and BioReference, three major commercial laboratories, that they can start pooling a handful of coronavirus samples at a time. In some parts of New England that haven’t seen much of the virus, pooling could triple or even quadruple the number of tests available, a team at the University of Nebraska has found.

But pooling is only a stopgap. It works best for diseases that are relatively rare, such as HIV and syphilis. If a disease is too common, then the work of pooling—the laborious mixing and remixing of samples—is more work than it’s worth. (About twice as many Americans have been infected with the coronavirus as have contracted HIV since 1981.) In Arizona and some southern states burning with COVID-19, traditional pooling would not be worth the effort, the same Nebraska team found.

Kolstad and Johnson, the MIT economist, are experimenting with ways to increase the efficiency of pooling. By grouping samples more deliberately, they can create larger pools of people with similar risks. A group of office workers might be at lower risk than a group of meatpackers who work close together, and even within a meatpacking plant, workers on one side of the plant might be at greater risk than those on the other. And because pooling saves money, companies and colleges and schools could run more tests. This would create a virtuous cycle. Each day, a person has a certain chance of being infected that varies with the prevalence of the disease in a community. Test every day, and there is simply less time between tests in which a person could have been infected. This makes it possible to build larger pools of people who are likely negative.

Starting up these systems would require clearing logistical and regulatory hurdles—a positive coronavirus sample is a low-level biohazard, and the FDA regulates it as such. Dina Greene, who directs lab testing for Kaiser Permanente in Washington State, says that contamination problems are already difficult for labs to manage, and would be more so if labs have to manually mix together samples.

Kolstad has been thinking through this problem. His team is experimenting with a different technique, which one might call “intermediate pooling.” Instead of having labs make pools on the back end, Kolstad proposes deploying trained nurses in mobile pooling labs in retrofitted vans. It would work well for nursing homes, he says: The nurses might arrive at a certain time every day, test every employee, pool the samples in the van, and then drop them off at a nearby clinical lab. (Because the FDA regulates pooling in clinical labs more strictly than in this type of “surveillance testing,” it may also be easier to obtain FDA approval for this plan.) Kolstad and his team are trying out this technique with a network of nursing homes in the Boston area, and delivering the pooled tests to a nearly complete, fully automated COVID-19 testing facility run by Gingko Bioworks, a $4 billion start-up in Massachusetts that is pitching another method to scale up U.S. testing, one that could vastly increase the pace of processing.

Since its founding in 2009, Ginkgo Bioworks has specialized in synthesizing new kinds of bacteria for use in industrial processes. Its engineers spin new forms of DNA in part with genetic-sequencing machines made by Illumina, a large and publicly traded biotechnology company. But in the spring, as viral testing buckled, Ginkgo’s engineers realized that their Illumina machines could be put to another use: Instead of helping to create genes, they could identify existing ones—and do so much faster than a PCR machine can.

Unlike PCR machines, which can analyze at most hundreds of individual samples per run, sequencing machines can read thousands of samples simultaneously. A high-end PCR machine, operated by a round-the-clock staff, can run up to 1,000 samples a day; a single Illumina machine can read more than 3,000 samples in half that time. Ginkgo has sharpened that advantage by building its fully automated factory in Boston, centered on Illumina machines, which it says could test about 250,000 samples a day. It aims to open the facility by mid-October; in two months more, another three could go up and Ginkgo could be testing 1 million samples each day.

The company has designed its supply chain to withstand high demand. It has rejected some reagents, for instance, because it doesn’t trust that there will be enough of them; it uses saliva samples, not swabbed nose or throat samples, because it does not think there are enough swabs in the world to meet demand. The genetic-sequencing supply chain is already built for such scale because other automated factories—doing noninvasive neonatal testing, for example—already use Illumina machines.

Both Ginkgo and an Illumina-backed start-up, Helix, have received NIH grants to rapidly scale up their testing. If the technique receives FDA approval, as many expect, the two companies could as much as triple the country’s testing capacity. “In three months, I think we could be at between 1 and 3 million additional tests per day in this country, without any problem at all,” John Stuelpnagel, a bioscience entrepreneur and one of the founders of Illumina, told us.

The approach has its challenges. Any samples must be shipped to one of Ginkgo’s or Helix’s centralized testing locations, which imposes a huge logistical obstacle to scaling up. The incumbent testing companies—Quest and LabCorp—have achieved dominance because of their ability to collect samples from places where they’re tested. But in Ginkgo’s full vision, 1 million tests will cover far more than 1 million people.

The key to this approach is “front-end pooling.” Imagine that every day, when kids arrive in their classroom, they briefly remove their mask and spit into a bag. (It is a perfect plan for second graders.) The bag would then be shipped to the nearest Ginkgo factory, which could test the pooled sample and deliver a single result for the classroom by the next morning. “If you pool together one classroom, and test that classroom together, then if you get a positive, you can send the whole classroom home,” Blythe Adamson, an economist and epidemiologist at the nonprofit Testing for America, told us. “For children, it protects their privacy—we don’t know which student” tested positive.

Front-end pooling could also drive costs down, partly by saving on materials. “Do 10 people spit in one bag? That’s one-tenth the cost,” Jason Kelly, Ginkgo’s chief executive, told us. “It’s logistically simpler, because one bag shows up, not 10, so there’s 10 times less unboxing, 10 times less robotic movement.” The challenge, he said, is chiefly one of industrial design, not molecular biology: There is no FDA-approved device, at present, that will let 10 kids safely spit into one vial. We should have federally backed development and fast regulatory approval for that kind of device, Kelly said.

The Ginkgo sequencing approach and front-end pooling have never been tried before, because they make sense only in a pandemic. Only at the scale of tens of thousands of tests do Ginkgo tests start to cost less than PCR, Adamson said. But at that scale, their cost drops quickly in comparison—possibly down to $20, Stuelpnagel said, if not $10, compared with more than $100 for a PCR test.

“You’d never do [any of this] for HIV,” Kelly said. “It’s only in a pandemic you go, ‘Oh my God, we’re undertesting by a factor of 10.’”

(Adam Maida)

But what if testing needs to scale up not 10 times, but 20, or 50, or 100 times? That’s where another type of test—an antigen test—comes in.

At the same time that Ginkgo and other next-gen sequencing tests should come online, antigen tests will be scaling up. Unlike a PCR or a Ginkgo-style test, an antigen test does not identify any of the virus’s genetic material. Instead, it looks for an antigen, a slightly redundant name for any chemical that’s recognized by the test. Antigen tests aren’t as sensitive as genetic tests, but what they sacrifice in accuracy, they make up in speed, cost, and convenience. Most important, an antigen test can be conducted quickly at a “point of care” location, such as a doctor’s office, nursing home, or hospital.

Two of the most anticipated such tests are already on the market. Manufactured by two companies, Quidel and Becton, Dickinson, they look for an antigen called “nucleocapsid,” which is plentiful in the SARS-CoV-2 virus. The companies say they will be making a combined 14 million tests a month by the end of September; for comparison, the U.S. completed 23 million total tests in July. This scale alone will make this type of test an important factor in fall testing. Hospitals and doctors told us they are eager to get their hands on antigen tests, in part because they’re worried about dealing with COVID-19 during the coming flu season. In years past, if a patient had a cough and a runny nose in December, she would likely be diagnosed with the flu, even if she tested negative on a rapid flu test. “But now we can’t presume [patients] have the flu,” because they might have COVID-19, says Natasha Bhuyan, the West Coast medical director for One Medical, a chain of primary-care clinics. An antigen test seems to offer a way out of this dilemma.

The tests cost less than half as much as standard PCR tests, and they don’t need to be sent away to a lab. They can deliver a result in 15 minutes. But this approach has downsides. While the tests work well enough, successfully identifying most people with high viral loads, they have sometimes delivered false positives. Last week, Ohio Governor Mike DeWine tested positive on the Quidel test, leading him to cancel a meeting with President Trump. But later that day, he tested negative, three times, when analyzed by PCR.

And while these tests will be useful, they have their own supply-chain drawbacks. Both companies’ tests can be interpreted only with a proprietary reader, and while many clinics and offices already have these readers on hand, neither company is prepared to mass-produce them at the same scale as the tests. (Quidel now makes 2,000 of its readers a month, but is aiming to scale to 7,000 a month by September, a spokesperson told us.) Because both tests look for nucleocapsid, which exists only inside the coronavirus, they need a way to sever the virus’s outer membrane. This requires more reagents. For many technicians, these drawbacks aren’t worth the benefits. “Most people who are real lab experts are steering away from all that stuff because they can’t justify it,” Greene, the Kaiser lab director, said.

The readers are a particular sticking point for Michael Mina, the Harvard epidemiologist. He calls the BD and Quidel systems “Nespresso tests,” because, just as a Nespresso pod can transform into coffee only through a Nespresso brewer, they can deliver results only when their readers are at hand. “What I want is the instant coffee of tests,” he told us. What if there was an antigen test that could be made in huge numbers and didn’t require a specialized reader? What if it worked more like a pregnancy test—a procedure you can do at home, and not only at a doctor’s office?

Such tests exist—and have existed since April—and they are made by e25 Bio, a 12-person company in Cambridge. An e25 test is a paper strip, a few inches long and less than an inch wide. It needs only some spit, a saline solution, and a small cup—and it can deliver a result in 15 minutes. Like a pregnancy test, the strip has a faint line across its lower third. If you expose the strip to a sample and it fills in with color, then the test is positive. It does not require a machine, a reagent, or a doctor to work.

Its unusual quality is that it does not look for the same antigen as other tests. Instead of identifying nucleocapsid, the e25 test is keyed to something on the outside of the virus. It reacts to the presence of the coronavirus’s distinctive spike protein, the structure on the virus’s “skin” that allows it to hook onto and enter human cells. “I think we’re the only company in North America that has developed a spike antigen test,” Bobby Brooke Herrera, e25’s co-founder and chief executive, told us.

This has several advantages. It means, first, that the e25 test does not have to rupture the virus, which is why it doesn’t need reagents. And it means, second, that the e25 test is actually looking for something more relevant than the virus’s genetic material. The spike protein is the coronavirus’s most important structure—it plays a large part in determining the virus’s infectiousness, and it’s what both antibodies and many vaccine prototypes target—and its presence is a good proxy for the health of the virus generally. “We’ve developed our test to detect live viruses, or, in other words, spike protein,” Herrera said.

Working with two manufacturers, e25 thinks that it could make 4 million tests a month as soon as it receives FDA approval. Within six weeks of approval, it could make 20 million to 40 million tests a month. In short, e25 could single-handedly add as many as 1.2 million tests a day to the national total.

But FDA approval has not yet arrived, because the FDA compares every test to PCR, and no antigen test, however advanced, can stand up to the accuracy and sensitivity of the PCR technique. “The FDA, early on in the outbreak, said we had to follow a rubric of 80 percent sensitivity compared to PCR. How they got that number, I’m uncertain, but my best guess is it came from influenza epidemics in the past,” Herrera said.

This requirement has made antigen tests worse, Herrera argues, because it causes manufacturers to prioritize sensitivity at the cost of speed or convenience. It’s why other antigen tests use readers, or centrifuges, or look for nucleocapsid, he contends. By slightly weakening those guidelines, to 60 or 70 percent sensitivity, the FDA could let cheaper at-home tests come to market. The models that e25 uses show that even an at-home test that caught 50 percent of positives and 90 percent of negatives could detect outbreaks and reduce COVID-19 transmission.

Recall the coronavirus’s infection clock—how, from day zero of an infection to day five, the amount of the virus in your system exponentially increases; how it begins to ebb with the onset of symptoms; how, by day 14 or so, the PCR test is likely detecting only the refuse RNA of dead virus. While antigen tests need the equivalent of 100,000 viral strands per milliliter, a typical PCR test can detect a positive from as little as 1,000 strands per milliliter. There is only about a day at the beginning of an infection when the two tests would give different results—when there are more than 1,000 viral strands per milliliter of your saliva or snot but fewer than 100,000, according to Dan Larremore, a mathematician at the University of Colorado at Boulder. During that period—approximately day two or day three of an infection—antigen tests are truly inferior to PCR tests.

Yet the opposite is true as COVID-19 fades: There are potentially weeks at the end of an infection when there is enough viral RNA to clear the threshold for a positive PCR test but not enough to set off an antigen test. During that period, antigen tests, such as e25’s, outperform PCR tests, Mina argues, because they identify only people who are still contagious. So why, he asks, are they judged against PCR tests—and kept off the market—for failing to find the virus when there is no intact virus to find?

Antigen tests are not better than PCR tests in every instance. When someone at a hospital presents with severe COVID-19-like symptoms, for example, health-care workers cannot risk a false negative: They will need a PCR test. Some experts worry that at-home tests will have a much lower accuracy rate than advertised. Laboratory tests are conducted by professionals on machines they are familiar with, but amateurs will conduct at-home tests, which risks introducing errors not captured by official ratings or even imagined by regulators. At a national scale, this could mean that someone might have COVID-19, fail to realize it, and infect other people. “What’s concerning is the salami slicing of sensitivity. A percent here, a percent there, and pretty soon you’re talking real people,” Alex Greninger, a laboratory-medicine professor at the University of Washington, told us. Jennifer Nuzzo, an epidemiologist at the Johns Hopkins Center for Health Security, told us that it’s not yet clear whether people who receive a positive result on an at-home test will report that information to health authorities and choose to self-isolate.

But given that they are cheaper than PCR tests, have a faster turnaround time, and can be conducted at home, these paper tests do seem different, in a useful way. In some cases, they answer a more helpful question than PCR tests. There is good evidence to infer that a high viral load, which is what antigen tests detect, is correlated with infectiousness. The more virus in your body, the more contagious you are.

In that light, paper antigen tests aren’t SARS-CoV-2 tests at all, not like PCR tests are. They are rapid, cheap COVID-19 contagiousness tests. That shift in thinking, Mina argues, should undergird a shift in our national strategy.

Mina wants to coat the country in COVID-19 contagiousness tests. To understand the scale of his vision, start with the closest American analogue, the ubiquitous, paper-based, inexpensive at-home pregnancy test. Americans use 20 million of those each year. This is not sufficient for Mina’s plan. “Ideally, we’re making way more than 20 million [paper tests] a day,” Mina said. Entering a grocery store? Take a test first. Getting on a flight? There’s a test station at the gate. Going to work? Free coffee is provided with your mandatory test. He began pitching the idea as a moonshot in July, but it quickly took hold. By the end of the month, Howard Bauchner, the editor in chief of The Journal of the American Medical Association, gushed on a podcast that ubiquitous tests were “the best way we can get back to a semblance of working society.”

The idea has gained other advocates. Last month, a panel of experts convened by the Rockefeller Foundation called for the U.S. to do 3.5 million rapid antigen tests a day, or 25 million a week—five times more than the number of PCR tests they recommended. The researchers compiled a list of 12 rapid tests in development, including e25’s, and called for an aggressive government-led effort to support them. (The Rockefeller Foundation has also provided funding to the COVID Tracking Project at The Atlantic.) “These sort of tests are on the horizon, but getting them into the hands of everyone who needs them—schools, employers, health providers, public essential workers, vulnerable communities—will require the muscle that only the federal government can provide,” the experts wrote.

The muscle, specifically, of a wartime economy. The experts called for the White House to invoke the Defense Production Act, a Truman-era law that allows the federal government to compel companies to mass-produce goods in moments of national crisis. (Manufacturers are compensated for their effort at a fair price.) Only naked federal authority could push production fast enough to make enough tests in time to curb the virus, they wrote.

Herrera, the e25 executive, has been waiting for months for the government to invoke such power. There is essentially no resource constraint on the raw materials that make up antigen tests, but there is a profound limit to available productive capacity. “Being able to manufacture these products,” Herrera said, “is where the bottleneck lies.” And after it has the tests, Herrera believes, the company will need help sending them where they’re most needed. If testing companies are to save the world, they need federal support to do it.

And here is the tragedy—and the promise—of Mina’s moonshot: To fix testing, the federal government must do exactly what it has declined to do so far. Why is testing still a problem? Partly because the CDC and the FDA bickered in February and delayed by weeks the initial rollout of COVID-19 tests. Partly because infections continued to grow in the spring and summer, further boosting the number of tests needed to track the virus. But those reasons alone still do not explain the fundamental issue: Why has the U.S. never, not since the pandemic began, had enough tests?

The answer is because the Trump administration has addressed the lack of testing as if it is a nuisance, not a national-security threat. In March and April, the White House encouraged as many different PCR companies to sell COVID-19 tests as possible, declining to endorse any one option. While this idea allowed for competition in theory, it was a nightmare in practice. It effectively forced major labs to invest in several different types of PCR machines at the same time, and to be ready to switch among them as needed, lest a reagent run short. Today, the government cannot use the Defense Production Act to remedy the shortage of PCR machines or reagents—because the private labs running the tests are too invested in too many different machines.

Because of its trust in PCR, and its assumption that the pandemic would quickly abate, the administration also failed to encourage companies with alternative testing technologies to develop their products. Many companies that could have started work in April waited on the sidelines, because it wasn’t clear whether investing in COVID-19 testing would make sense, Sri Kosaraju, a member of the Testing for America governing council and a former director at JP Morgan, told us.

The Trump administration hoped that the free market would right this imbalance. But firms had no incentive to invest in testing, or assurance that their investments would pay off. Consider the high costs of building an automated testing factory, as Ginkgo is doing, said Stuelpnagel, the Illumina co-founder. A company would typically amortize the costs of that investment over three to five years. But that calculation breaks down in the pandemic. “There’s no way that we’re doing high-throughput COVID testing five years from now. And I hope there’s not COVID testing being done three years from now that would require this scale of lab,” he said. Companies aren’t built to deal with that level of uncertainty, or to serve a market that would dramatically shrink, or disappear altogether, if their product did its job. Even if the experimentation would benefit the public, it doesn’t make sense for individual businesses to take on those risks.

So nothing happened—for months. Only in the past few weeks has the federal government begun to address these concerns. The NIH grants awarded to Ginkgo, Helix, Quidel, and others were aimed, in part, at providing capital that would let businesses scale up quickly. And the Centers for Medicare and Medicaid has started to ensure that demand will exist for an experimental test: It has promised to buy Quidel or BD tests for every nursing home in the country.

But even if those companies succeed in delivering what they’ve promised, life will not go back to normal. An extra 1 million tests a day will allow us to ramp up contact-tracing operations and slow down the virus, but they will not change the texture of daily life in the pandemic, especially if there is another resurgence of the virus in the winter. For that, Mina’s moonshot is required. It will require much more than the $200 million the federal government has invested in testing technology so far, and it will require the full might of the federal government, with its unique ability to coerce manufacturing capacity. But its costs are not astronomical. If every paper test costs $1, as Mina hopes, and every American takes a test once a week, then his plan will cost about $1.5 billion a month. Congress has already authorized at least $7 billion to fix testing that the Trump administration had declined, for months, to spend. And even if Mina’s plan cost $300 million each day, the annual expense would amount to a fraction—about 3 percent—of the more than $3 trillion Congress has already spent dealing with the economic fallout of the pandemic. Yet the plan wouldn’t merely mitigate the harm of the pandemic. It could end it. To escape the pandemic in this way, the U.S. must make hundreds of millions of contagiousness tests—tests that are not perfect, but just good enough.

Mass-producing a cheap thing fast is, as it happens, something the United States is very good at, and something this country has done before. During the Second World War, the U.S. realized that the most effective way of shipping goods to Europe was not to use the fastest ship, but to use cheap “Liberty ships,” which were easy to mass-produce. The Allies “created this model of a ship that was kind of cheap, not as fast as they could make it, and not as good as they could make it,” Mark Wilson, a historian at the University of North Carolina at Charlotte, told us. “They were building cheap—one might say disposable—ships. They weren’t very good. But they just wanted to out-volume their opponents.”

We must out-volume the virus, and what will matter is not the strength of any one individual ship, but the strength of the system it is part of. When the FDA regulates tests, though, it looks at the sensitivity and specificity of a single test—how well the test identifies illness in an individual—not at how the test is part of a testing regimen meant to protect society. For this reason, Mina proposes that the FDA make room for the CDC or the NIH to oversee the use of contagiousness tests. “I think the CDC could potentially create a certification process really simply. They are the public-health agency, and could say, ‘We will evaluate different manufacturers. None of these will be fully regulated by law, but here are the ones you should or should not choose.’”

Paper tests do have downsides. Testing tens of millions of people each day would be an unprecedented biotechnical intervention in the country, and it might have unpredictable, nasty side effects. Mina’s plan is “being pushed without really thinking through the operational consequences,” Nuzzo said on a recent press call. Brett Giroir, the federal testing czar, has worried that a deluge of positive paper tests could lead asymptomatic people to swamp the rest of the medical system. “You do not beat the virus by shotgun testing everybody, all the time,” he said on the same call. Paper tests are based on an inference about human behavior. For example, if people knew that every paper test would catch only seven or eight infections out of every 10 (compared with PCR, which would catch all 10), would they keep taking them? Would the country’s testing system split in two, delivering PCR tests for the rich and cheap paper tests for the poor? Each way of testing for the virus is not only a technology or a medical device. Each is its own hypothesis about public health, human behavior, and market forces.

So here is what May 2021 could look like: Vaccines are rolling out. You haven’t gotten your dose yet, but you are no longer social distancing. When your daughter walks into her classroom, she briefly removes her mask and spits into a plastic bag; so do all the other children and the teacher. The bag is then driven across three states and delivered to the nearest Ginkgo processing facility. When you arrive at work, you spit into a plastic cup, then step outside to drink coffee. In 15 minutes, you get a text: You passed your daily screen and may proceed into the office. You still wear your mask at your desk, and you try to avoid common areas, but local infection levels are down in the single digits. That night, you and your family meet your parents at a restaurant, and before you proceed inside, you all take another contagiousness test. It’s normal, now, to see the little cups of saliva and saline solution, each holding a strip of color-changing paper, sitting on tables near the entrance of every public place. And before you fall asleep, you get a text message from the school district. Nobody in your daughter’s class tested positive this morning—instruction can happen in person tomorrow.

There is no technical obstacle to that vision. There is only a dearth of political will. “The lack of testing is a motivation problem,” Stuelpnagel said. “It’s going to take a lot of effort, but it should take a lot of effort, and we should be willing to take that effort.” Mina is frustrated that the answer is so close, and so doable, but not yet something the government is considering. “Let’s make the all-star team of people in this field, pay them whatever they need to be paid, put billions of dollars in, and get a working test in a month that could be truly scalable. Take it out of the free-market, capitalistic world and say: ‘This is a national emergency’—which,” he said, “it is.”

A Second Coronavirus Death Surge Is Coming

2020-07-15T19:31:22-04:00

There is no mystery in the number of Americans dying from COVID-19.

Despite political leaders trivializing the pandemic, deaths are rising again: The seven-day average for deaths per day has now jumped by more than 200 since July 6, according to data compiled by the COVID Tracking Project at The Atlantic. By our count, states reported 855 deaths today, in line with the recent elevated numbers in mid-July.

The deaths are not happening in unpredictable places. Rather, people are dying at higher rates where there are lots of COVID-19 cases and hospitalizations: in Florida, Arizona, Texas, and California, as well as a host of smaller southern states that all rushed to open up.

The deaths are also not happening in an unpredictable amount of time after the new outbreaks emerged. Simply look at the curves yourself. Cases began to rise on June 16; a week later, hospitalizations began to rise. Two weeks after that—21 days after cases rose—states began to report more deaths. That’s the exact number of days that the Centers for Disease Control and Prevention has estimated from the onset of symptoms to the reporting of a death.

Many people who don’t want COVID-19 to be the terrible crisis that it is have clung to the idea that more cases won’t mean more deaths. Some Americans have been perplexed by a downward trend of national deaths, even as cases exploded in the Sun Belt region. But given the policy choices that state and federal officials have made, the virus has done exactly what public-health experts expected. When states reopened in late April and May with plenty of infected people within their borders, cases began to grow. COVID-19 is highly transmissible, makes a large subset of people who catch it seriously ill, and kills many more people than the flu or any other infectious disease circulating in the country.

The likelihood that more cases of COVID-19 would mean that more people would die from the disease has always been very high. Even at the low point for deaths in the U.S., roughly 500 people died each day, on average. Now, with the national death numbers rising once again, there’s simply no argument that America can sustain coronavirus outbreaks while somehow escaping fatalities. America’s deadly summer coronavirus surge is undeniable. And it was predictable this whole time by looking honestly at the data.

In the United States, the rising severity of the current moment was obscured for several weeks by the downward drift of cases, hospitalizations, and deaths resulting from the spring outbreak in northeastern states. Even though deaths have been rising in the hardest-hit states of the Sun Belt surge, falling deaths in the Northeast disguised the trend.

It is true that the proportion of infections in younger people increased in June and July compared with March and April. And young people have a much lower risk of dying than people in their 60s and older. But, at least in Florida, where the best age data are available, early evidence suggests that the virus is already spreading to older people. Additionally, analysis of CDC data by The New York Times has found that younger Black and Latino people have a much higher risk of dying from COVID-19 than white people the same age. According to the racial data compiled by the COVID Tracking Project in concert with the Boston University Center for Antiracist Research, Latinos in Arizona, California, Florida, and Texas are 1.3 to 1.6 times more likely to be infected than their proportion of the population would suggest. It is telling that despite outbreaks all over Texas in recent weeks, the border region has been leading the state in deaths per capita.

Even with cases surging, if hospitalizations were not rising, that might suggest that this outbreak might be less deadly than the spring’s. But hospitalization data maintained by the COVID Tracking Project suggested otherwise as early as June 23. On that date, hospitalizations began to tick up across the South and West, and they have not stopped. It’s possible we’ll match the national peak number of hospitalizations from the spring outbreak over the next week.

Even if better knowledge of the disease and new treatments have improved outcomes by 25 or even 50 percent, so many people are now in the hospital that some of them will almost certainly die.

There was always a logical, simple explanation for why cases and hospitalizations rose through the end of June while deaths did not: It takes a while for people to die of COVID-19 and for those deaths to be reported to authorities.

So why has there been so much confusion about the COVID-19 death toll? The second surge is inconvenient for the Trump administration and the Republican governors who followed its lead, as well as for Mike Pence, the head of the coronavirus task force, who declared victory in a spectacularly incorrect Wall Street Journal op-ed titled, “There Isn’t a Coronavirus ‘Second Wave.’”

“Cases have stabilized over the past two weeks, with the daily average case rate across the U.S. dropping to 20,000—down from 30,000 in April and 25,000 in May,” Pence wrote. In the month since Pence made this assertion, the seven-day average of cases has tripled. Several individual states have reported more than 10,000 cases in a day, and Florida alone reported 15,000 cases, more than any state had before, on an absolute or per capita basis.

But there’s another reason for some of the confusion about the severity of the outbreak right now. And that’s the perceived speed at which the outbreak initially landed on American shores and started killing people. The lack of testing let the virus run free in February and much of March. As my colleague Robinson Meyer and I put it at the time, “Without testing, there was only one way to know the severity of the outbreak: counting the dead.” And that is how we figured out how bad the outbreak was. Thousands began dying in the greater New York City area and a few other cities around the country in early April. The seven-day average for new cases peaked on April 10, followed by the peak of the seven-day average for daily deaths just 11 days later.

Everything seemed to happen at once: lots of cases, lots of hospitalizations, lots of deaths. But some of this is also the compression of memory. Most of us remember the deaths in March beginning as quickly as the cases, especially given the testing debacle. That’s not exactly what happened, however. The nation did, in fact, see cases rise weeks before the death toll shot up. There was a time in March when we had detected more than 100 cases for each death we recorded. This is a crucial metric because it gets at the perceived gap between cases and deaths. And it tells us that we did see a lag between rising cases and deaths back in the spring.

During the slow-decline phase in May, the case-to-deaths ratio fell to about 20. Then, this summer, the case-to-death ratio began to rise in early June. On July 6, the ratio hit 100 again, just like in the spring. But as in spring, this was not a good sign, but rather the leading indicator that a new round of outbreaks was taking hold in the country. And, indeed, a week ago, this ratio began to fall as deaths ramped up.

The U.S. came most of the way down the curve from the dark days of April, and now we’re watching the surge happen again. The testing delays, the emergency-room-nurse stories, the refrigerated morgue trucks—the first time as a tragedy, the second time as an even greater tragedy. One must ask, without really wanting to know the answer, How bad could this round get?

By the absolute or per capita numbers, the U.S. stands out as nearly the only country besides Iran that had a large spring outbreak, began to suppress the virus, and then simply let the virus come back.

No other country in the world has attempted what the U.S. appears to be stumbling into. Right now, many, many communities have huge numbers of infections. When other countries reached this kind of takeoff point for viral spread, they took drastic measures. Although a few states like California are rolling back reopening, most American states are adamant about opening into the teeth of the outbreak. And this level of outbreak will not stay neatly within a governor’s political boundaries. There’s no way to win this state by state, and yet that’s exactly what we’re attempting. From the look of the map, the South and West—regions with a combined 200 million people—are in trouble.

The regional variation of the American outbreak is crucial to understanding both what happened and what’s going to happen next. Nationwide, the U.S. deaths per million tally—a hair under 400—is in the top ten globally. But look just at the Northeast’s 56 million people, and the death rate is more than double the national average: 1,100 deaths per million.

By contrast, the South and West—where SARS-CoV-2 is burning through the population—are much more populous than the Northeast. If those areas continue to see cases grow, they could see as many deaths per million as the Northeast did but multiplied by a larger number of people. At 1,100 deaths per million, the South and West would see 180,000 more deaths. Even at half the Northeast’s number, that’s another 69,000 Americans.

In truth, the fan of possibilities is probably wider. Looking at individual states, there was tremendous variation from low-death states like New Hampshire (288 deaths per million), to extremely high-death states like New Jersey (1,750 deaths per million), and a bunch in between, like Massachusetts (1,208); Washington, D.C. (805); and Pennsylvania (539).

It’s possible that the summer-outbreak states could follow the lower death trajectory traced by Pennsylvania or Washington, D.C. Right now, only Arizona, at 307 deaths per million, has crossed even the lowest line above, New Hampshire; there is a lot of room for things to get worse, even if they do not come close to equaling the horrors of the spring.

New York City is and probably will remain the worst-case scenario. New York City has lost 23,353 lives. That’s 0.28 percent of the city’s population. If, as some antibody-prevalence surveys suggest, 20 percent of New Yorkers were infected, that’s an infection-fatality rate of more than 1.3 percent, which exceeds what the CDC or anyone else is planning for. To put it in the same terms discussed here, New York City saw 2,780 deaths per million people. A similar scenario across the South and West would kill over 550,000 more Americans in just a few months, moving the country to 680,000 dead. It is unthinkable, and yet, 130,000 deaths—the current national death toll—was once unthinkable, too.

That’s still not the worst-case scenario for a truly uncontained outbreak, in which serious measures are not taken. For months, most public-health officials have argued that the infection-fatality rate—the number of people who die from all infections, detected and undetected, symptomatic and asymptomatic—was somewhere between 0.5 and 1 percent. The CDC’s latest estimates in its planning scenarios range from 0.5 to 0.8 percent. Take that lower number and imagine that roughly 40 percent of the country becomes infected. That’s 800,000 lives lost.

The point in laying out these scenarios is not that we’ll reach 300,000 or 800,000 American COVID-19 deaths. That still seems unlikely. But anyone who thinks we can just ride out the storm has perhaps not engaged with the reality of the problem. As the former CDC director Tom Frieden has said, “COVID is not going to stop on its own. The virus will continue to spread until we stop it.”

The lack of containment by American authorities has resulted in not only lost lives, but also lost businesses, savings accounts, school years, dreams, public trust, friendships. The country cannot get back to normal with a highly transmissible, deadly virus spreading in our communities. There will be no way to just “live with it.” There will only be dying from it for the unlucky, and barely surviving it for the rest of us.

A Dire Warning From COVID-19 Test Providers

2020-06-30T15:10:35-04:00

The United States is once again at risk of outstripping its COVID-19 testing capacity, an ominous development that would deny the country a crucial tool to understand its pandemic in real time.

The American testing supply chain is stretched to the limit, and the ongoing outbreak in the South and West could overwhelm it, according to epidemiologists and testing-company executives. While the country’s laboratories have added tremendous capacity in the past few months—the U.S. now tests about 550,000 people each day, a fivefold increase from early April—demand for viral tests is again outpacing supply.

If demand continues to accelerate and shortages are not resolved, then turnaround times for test results will rise, tests will effectively be rationed, and the number of infections that are never counted in official statistics will grow. Any plan to contain the virus will depend on fast and accurate testing, which can identify newly infectious people before they set off new outbreaks. Without it, the U.S. is in the dark.

[Read: A devastating new stage of the pandemic]

The delays have already started. Yesterday, Quest Diagnostics, one of the country’s largest medical-testing companies, said that its systems were overwhelmed and that it would now be able to deliver COVID-19 test results in one day only for hospitalized patients, patients facing emergency surgery, and symptomatic health-care workers. Everyone else now must wait three to five days for a test result.

“Despite the rapid expansion of our testing capacity, demand for testing has been growing faster,” Quest said in a statement last week warning of such a possibility. The company then said that orders for COVID-19 testing had grown by 50 percent in three weeks.

“This is very bad,” Michael Mina, an epidemiology professor at Harvard, told us. Rapid test-turnaround times are the only way to control the coronavirus without forcing every potentially contagious person—everyone who’s had contact with someone diagnosed with COVID-19—into quarantine, he said: “Our modeling efforts more or less show that if you don’t get results back in a day or so, outbreaks really can’t be stopped without isolating and quarantining all contacts preemptively.”

Quest is not the only firm to report growing problems. “We hit the wall three weeks ago,” Jon Cohen, the executive chairman of BioReference Laboratories, a lab-services company that is testing patients for the virus in New York, New Jersey, and Florida, told us. “At that point, most laboratories were already running at capacity, as far as I can tell.”

In mid-June, four changes hit all at once, Cohen said. Large companies began to test their employees en masse, hospitals started to test every patient who needed an elective procedure, and nursing homes started regularly testing their employees and some residents. The American public also seemed to seek out voluntary tests in greater numbers this month. The surge in testing overwhelmed both his testing company’s capacity and its equipment suppliers, he said.

“We not only hit capacity, but any ability to increase our capacity became limited by the supply side,” he said. “The vendors, the suppliers can’t keep up.”

[Read: America is giving up on the pandemic]

LabCorp, another major testing company, also recognized the surging demand for tests in a statement this weekend. “We are doing everything we can to continue delivering results in a timely manner while continually increasing testing capacity,” it said.

Unlike in the first days of the pandemic, when COVID-19 testing kits themselves were in short supply, now the problem lies with the equipment needed to get test results. The hardest-hit new areas do not have enough machines to process samples, leading to a growing backlog of tests, lab directors told us. Some are also running out of the chemical reagent that must react with a testing specimen.

Labs in the U.S. use several different types of viral-testing machines to diagnose COVID-19, and each type has its own supply-chain issues and processing challenges, Lauren Sauer, an emergency-medicine professor at Johns Hopkins, told us by text message. With “so many platforms” in use, she said, resolving bottlenecks and shortages nationwide is especially hard.

“What is currently happening [on testing] is so pocketed and disconnected,” she said.

The American Clinical Laboratory Association, a trade group that represents testing labs, has also warned of shortages. “While our members are collectively performing hundreds of thousands of tests each day, the anticipated demand for COVID-19 testing over the coming weeks will likely exceed members’ testing capacities,” said Julie Khani, its president, in a statement. The group’s members conduct about half of the country’s daily coronavirus tests, according to information in her statement.

The COVID Tracking Project

The problems have not been felt everywhere. Dina Greene, the director of laboratory services for the health-care group Kaiser Permanente in Washington State, told us that supply-chain problems have not yet disrupted the group’s ability to work. But demand for tests was increasing, she confirmed, and she “wouldn’t be surprised” if shortages hit her team soon.

[Read: ‘How could the CDC make that mistake?’]

Testing has hobbled the American response since the earliest days of the pandemic. As our reporting revealed, the U.S. had tested fewer than 3,000 people for the coronavirus by March 5, even though community spread of the virus had been detected more than a week earlier. In the following weeks, states and hospitals rationed access to tests, granting them only to health-care workers and the sickest patients. This meant that many people who may have had the virus, especially in the Northeast, were never tested for it.

Even after the initial crunch in March, the country’s testing apparatus continued to be beset by problems. For much of April, as the virus killed tens of thousands of Americans, testing plateaued at roughly 150,000 tests a day. Since then, the number of daily tests has increased, but not as fast as experts once hoped. Only in the past two weeks has the U.S. succeeded in testing more than 500,000 people a day, which the Harvard Global Health Institute once said would be a good goal for mid-May. The institute said today that the U.S. must test at least 1.2 million people a day to control the outbreak and at least 4.3 million people a day to eliminate it.

In all that time, the federal government never solved the testing problem. In early April, for instance, researchers at Duke University and the American Enterprise Institute, a conservative think tank, called for the government to take charge of the crisis by establishing a task force that would consolidate information about testing and help states and companies understand what was possible. Such a task force could manage emerging shortages, and it could help the country understand how much testing capacity might be attainable by July, August, or September.

But such an effort never took shape. “If this work has been done, I have not seen it, and I fear that neither have the governors and other state and local leaders who are having to make decisions about how and when to reopen,” Caitlin Rivers, an author of the report and a professor at Johns Hopkins University, told Congress last month.

Since then, the Trump administration’s grip on testing has slackened. Brett Giroir, the White House’s testing czar, returned to his day job at the Department of Health and Human Services this month. And at a rally on June 20, President Donald Trump said he told members of his staff to “slow down the testing, please,” because he did not like the growing number of confirmed coronavirus infections. (The president’s staff said afterward that he was joking. After denying for several days that he meant the comment in jest, Trump said last week that he’d been speaking “sarcastically.” Deborah Birx, who is coordinating the White House response to the coronavirus, has said that Trump never asked her to slow down testing.)

“We basically need a Manhattan Project for testing,” Sauer said. “A nationwide, systematic strategy with a clear agency lead is desperately needed. But it’s not happening and I think we all fear significant access issues and supply-chain disruptions in the near future.”

The U.S. is seeing a new surge of cases in the South and West that threatens to overwhelm its health system anew. The country reported more new confirmed COVID-19 cases last week than in any other week of the pandemic so far. While the administration’s focus has drifted elsewhere, demand for tests is only growing. Alex Greninger, a laboratory-medicine professor at the University of Washington, told us that it was little wonder the testing companies were overwhelmed.

“The testing supply chain wasn’t meant for this kind of onslaught of volume across the world at the same time,” he said.

A Devastating New Stage of the Pandemic

2020-06-25T14:02:12-04:00

Updated at 9:30 a.m. ET on June 26, 2020.

For the past few weeks in the United States, the awful logic of the coronavirus seemed to have lifted. Stores and restaurants reopened. Protesters flocked to the streets. Some people resumed going about their daily lives, and while many wore face masks, many others did not.

Yet cases continued to ebb. Even though the U.S. had adopted neither the stringent lockdowns nor the trace-and-isolate strategies seen in other countries, its number of confirmed COVID-19 cases settled into a slow decline. Last week, Vice President Mike Pence bragged that the country had made “great progress” against the disease, highlighting that the average number of new cases each day had dropped to 25,000 in May, and 20,000 so far in June.

[Read: The Sun Belt spikes could be a disaster for Trump]

That holiday has now ended. Yesterday, the U.S. reported 38,672 new cases of the coronavirus, the highest daily total so far. Ignore any attempt to explain away what is happening: The American coronavirus pandemic is once again at risk of spinning out of control. A new and brutal stage now menaces the Sun Belt states, whose residents face a nearly unbroken chain of outbreaks stretching from South Carolina to California. Across the South and large parts of the West, cases are soaring, hospitalizations are spiking, and a greater portion of tests is coming back positive.

The country’s second surge has arrived—and it is hammering states, such as Texas and Arizona, that escaped the first surge mostly unscathed.

[Read: America is giving up on the pandemic]

This new surge is large enough to shift the entire country’s top-line statistics. In terms of new confirmed cases, three of the 10 worst days of the U.S. pandemic so far have come since Friday, according to data collected by the COVID Tracking Project at The Atlantic. The seven-day average of new cases has now risen to levels last seen 11 weeks ago, during the worst of the outbreak in New York. The U.S. has seen more cases in the past week than in any week since the pandemic began.

Since June 15, most of these new cases have come in the South. The ongoing outbreak there is the second-worst regional outbreak that the U.S. has seen so far. Only the springtime calamity that befell the Northeast—which was one of the worst coronavirus outbreaks anywhere in the world, if not the worst—exceeds what is now happening across the Sun Belt.

Ominously, sparks from the Sun Belt outbreak may be landing in other parts of the country and igniting new blazes of infection. Since June 15, Ohio and Missouri have seen their average daily case counts increase by the hundreds. Virginia, which battled the virus in May but has so far escaped this month’s surge, has also seen cases rise in the past few days.

[Read: A hidden COVID-19 risk factor: your boss]

The national surge is driven primarily by potentially disastrous situations in Arizona, South Carolina, Texas, Florida, and Georgia. Many virus statistics in these states now look like straight lines pointing upward. In Arizona, where President Donald Trump held a large indoor rally this week, the situation is particularly bleak. Over the past month, the number of confirmed cases there has grown nearly fourfold; the number of people hospitalized has more than doubled. On Tuesday, the state reported more than 3,500 new cases in one day. That’s equal to 494 new cases for every 1 million residents, a figure that rivals New York State’s numbers in March and April.

Were it not for Arizona’s terrifying surge, spikes in other states would register as major events. Texas has seen an explosion: On June 1, it reported about 600 new cases of COVID-19; yesterday, it reported more than 5,000. Its hospitalizations have more than doubled in the same period. Florida, for its part, has reported an average of 3,756 new COVID-19 cases each day for the past week, a fourfold surge in daily cases compared with a month ago. And in South Carolina, new cases have grown sevenfold since mid-May. The Palmetto State now records nearly 950 new COVID-19 cases every day, or about 184 new daily cases for every 1 million residents.

Across the country, 10 states have set new records for case counts in the past three days.

Why are these spikes happening? The answer is not completely clear, but what unites some of the most troublesome states is the all-or-nothing approach they took to pandemic suppression. The stay-at-home order in Texas, for instance, lifted on April 30. A day later, the state allowed nearly all of its businesses and public spaces—stores, malls, churches, restaurants, and movie theaters—to open with limited capacity. It has since further loosened those restrictions. Arizona allowed some stores and businesses to reopen in early May; it lifted its stay-at-home order on May 15 and allowed bars, gyms, churches, malls, and movie theaters to reopen around the same time. And while the state mandated some form of capacity restrictions, those rules were regularly breached: For weeks, photos and videos have shown scenes of crowded Arizona bars and nightclubs.

[Read: COVID-19 can last for several months]

A form of wishful thinking seemed to drive these decisions: If the virus could be ignored, then it might go away altogether. Even though polls show that most Republicans wear masks, the Republican leaders of Texas and Arizona catered to the party’s anti-mask fringe and waffled on their importance. When the government of Harris County, Texas—which includes Houston, the country’s fourth-largest city—mandated that residents wear masks in public or risk a $1,000 fine, the state government blocked the rule. Texas Lieutenant Governor Dan Patrick called a face-mask mandate “the ultimate government overreach,” and Representative Dan Crenshaw said it could lead to “unjust tyranny.”

Eventually, Governor Greg Abbott of Texas and Governor Doug Ducey of Arizona went even further, blocking cities and counties from implementing any pandemic-related restriction more stringent than that required by the state.* This meant that when a video emerged of packed nightclubs in Phoenix, full of people who were not wearing masks, the mayor was unable to close or sanction the clubs—or even require them to force patrons to wear masks. Both governors finally reversed those policies last week. (“To state the obvious, COVID-19 is now spreading at an unacceptable rate in Texas, and it must be corralled,” Abbot said at a press conference on Monday. This had not been obvious to the governor less than a week earlier, when he told Texans that the state’s record-breaking number of new infections was “no reason today to be alarmed.”)

Yet these decisions do not fully explain the surge. Governor Ron DeSantis of Florida, also a Republican, allowed some cities and counties to wait to reopen on May 18, weeks after the rest of the state; though he criticized face-mask rules, he has not blocked cities from imposing their own. Governor Gavin Newsom of California, a Democrat, imposed the country’s first stay-at-home order, on March 19, and didn’t begin lifting restrictions until May 8. But counties have had wide leeway to enforce their own rules, and Newsom kept some high-risk businesses, such as gyms and movie theaters, closed until June 12. Yet in both states, infections are increasing.

[Read: A common snake oil reemerges for the coronavirus]

No matter their cause, these outbreaks are now too significant to explain away with statistics. In the past few weeks, President Donald Trump and other officials have claimed that the rise in cases is illusory and due solely to an increase in testing. “Cases are going up in the U.S. because we are testing far more than any other country, and ever expanding,” Trump said on Twitter earlier this week. “With smaller testing we would show fewer cases!”

This effect—if you test more people, you have more cases—is obvious enough, but it fails to explain the surge that we’re seeing now. Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases, disputed the idea that testing alone is responsible for the spiking case count.

[Read: We don’t even have a COVID-19 vaccine, and yet the conspiracies are here]

“Clearly, if you do more tests, you will pick up more cases that you would not have picked up if you don’t do the tests,” he told The Atlantic. “But—and this is a big but—what you look at is what percentage of the tests are positive. If the percentage of any given amount of tests in one week—take an arbitrary number, [if] 3 percent [are positive]—and the following week it’s 4 percent, and the week after that, it’s 5 percent: That can’t be explained by doing more tests. That can only be explained by more infections.

“When you see hospitalizations, that’s a clear indication that you’re getting more infections,” he said.

The South and West meet all of Fauci’s criteria: Cases, hospitalizations, and the test-positivity rate are spiking in both regions. A month ago, health-care workers in Arizona had to test about 11 people to find a new COVID-19 case; today, one in five people they test has the virus. In Florida, the number of tests per day has actually fallen in the past week while the number of new cases has spiked. The Sun Belt surge, in other words, is not a by-product of increased testing. In the South and West, finding people sick with COVID-19 is simply getting easier.

Felicia Goodrum, a professor of immunobiology at the University of Arizona and the president-elect of the American Society for Virology, has found it painful to watch her state accept its rapidly surging infections with defeat. State leaders “look at the numbers, at the rise in cases, which are staggering, and they say, ‘There’s nothing we can do about this.’ And that’s just not true,” she told us. Face masks and social distancing could still slow the virus’s spread, she said last week, but the state was running out of time.

“We’re reaching this critical point where the only way we’re going to reverse what’s happening is to do a complete shutdown again,” she said. “We’re playing with fire, and we will get burned.”

So much for the fears of a resurgence in the fall. As the first official days of summer unfurl, American coronavirus infections are threatening to bubble over. The virus has not gone away with warm weather, as President Trump once mused that it might. It has gotten worse.

Yet last week, as cases ticked up in the Southwest, Vice President Pence declared in The Wall Street Journal that “there isn’t a coronavirus ‘second wave.’” He pointed out that “more than half of states are actually seeing cases decline or remain stable.” This was the same op-ed in which he boasted that new cases have “stabilized” in the U.S., falling to 20,000 a day.

[Read: So, what can we do now?]

These numbers are not comforting. The vice president was still implicitly saying that nearly half of states are seeing an increase in new cases. He was also framing 20,000 new cases a day as an accomplishment, even though countries in Europe and East Asia have seen much lower daily case counts on a per capita basis.

What Pence’s op-ed suggests but does not say is that the U.S. never brought its pandemic under control—the “first wave” never ended. And his timing turned out to be dreadful. That key number—20,000 new cases a day—quickly became outdated: The U.S. is now seeing an average of about 30,000 new cases a day. Because more people live in the South than the Northeast, the country could soon record more than 40,000 cases a day, if not more.

[Read: The pandemic broke end-of-life care]

A “second wave” was never a good yardstick, because the “first wave” that struck the greater New York area this spring was a disaster beyond reckoning. Consider that New York City, population 8.4 million, saw more than 22,300 confirmed and probable deaths from COVID-19; one of Europe’s worst outbreaks, in the Lombardy region of Italy, population 10 million, saw about 16,500. In three and a half months, in other words, a new virus killed one in every 400 New Yorkers. Among the elderly, the toll was even worse: One in every eight New Jersey nursing-home residents died this spring.

The virus remains the virus. It can take up to 14 days for someone to show symptoms; it can take another two weeks for that person to appear in the data as a confirmed case. This means that, as the Northeast learned in the spring, virus statistics tell you what was happening in a community two to three weeks ago. The South, in other words, may have tens of thousands of COVID-19 infections that it cannot yet see. In the months to come, 20,000 new cases a day will look like a low point of new daily cases—a reprieve in the long horror of the American pandemic.

[Read: Why the coronavirus is so confusing]

The outlook is not entirely dismal. Last week, the U.S. met a long-sought milestone: It can now test half a million people each day for the virus. This is more than four times the number of people that could be tested in early April. This means that it may be possible to contain some outbreaks in the South. In addition, the U.S. death toll has been in a slow decline for weeks: About 600 Americans are dying of the coronavirus every day, the lowest daily total since March. This data point may mean that American hospitals are getting better at treating people sick with COVID-19—or it may simply mean that the Sun Belt surge has not yet shown its full lethal potential. For now, the data are impossible to interpret. Because COVID-19 itself can take weeks to kill its victims—and even then the data do not reflect them immediately—we should not expect to see victims of the Sun Belt surge appear in death data for as many as 28 days after it began.

We still have time to save lives. After the outbreak in the Northeast, experts and officials identified several countermeasures that did not require sheltering in place. One of the most important was protecting long-term-care facilities. Because the virus is deadliest for older people, killing about one in every 20 infected adults ages 65 and up, keeping the virus out of nursing homes could considerably reduce the death toll from the surge.

[Read: We’ll be wearing things on our faces for a long time]

Yet in Arizona, for instance, we have little idea what is happening inside such facilities. Preliminary data from the COVID Tracking Project show that the number of long-term-care facilities and assisted-living facilities with outbreaks has grown from 192 to 268. The virus is still clearly getting in. The state governments in Arizona, Florida, and Texas must do everything they can to stop it—in part by regularly testing residents in these facilities and by building a centralized quarantine site for older adults who have COVID-19 but do not require hospitalization.

[Read: ‘We’re literally killing elders now’]

A month ago, our colleague Ed Yong wrote that the United States was facing a “patchwork pandemic,” an awful months-long period when the virus would afflict states, cities, and neighborhoods differently. The U.S. now must prove that it can contain one of these flare-ups. New York, New Jersey, and Connecticut—the site of the first major U.S. COVID-19 outbreak—yesterday imposed restrictions on travelers arriving from Texas, Arizona, and other states in the South and West with dangerously high caseloads. The three states will require people arriving from these places to quarantine for two weeks, but their ability to enforce that policy is questionable. The spring surge trained us to think that regional outbreaks could stay contained to a region. But the northeastern surge happened when the whole country was sheltering in place. This moment is different: Can the rest of the country continue to reopen their economies while the South boils over with cases?

On Tuesday, Governor Abbott said that Texans have no reason to leave their homes—essentially asking them to voluntarily quarantine. He has since canceled elective surgeries in some of the state’s hospitals, but said that reimposing a formal shelter-in-place order in Texas is a measure of last resort. Such measures may seem unimaginable now. But if a coronavirus outbreak rips through the state, infecting a large portion of its 29 million residents, then more than just Texas’s health and economy will be on the line.

[George Packer: We are living in a failed state]

The spring surge resulted from a widespread failure of American governance. Yet a first coronavirus outbreak in the U.S. may have been unavoidable, and Americans eased its agony by choosing to act together: Our collective decision to stay at home averted an estimated 4.8 million additional COVID-19 cases.

A second surge will allow for no such succor. It will reveal that our leaders, instead of wrestling the virus into submission, gave up on it halfway. That choice will have an unaccountable cost. If several large states plunge into full-scale coronavirus outbreaks, then Americans may need to again act as one—or we will see so much misery that we will yearn for the spring.

*This article previously misstated the Arizona governor's first name. He is Doug Ducey, not Dan.

America Is Giving Up on the Pandemic

2020-06-07T14:19:00-04:00

After months of deserted public spaces and empty roads, Americans have returned to the streets. But they have come not for a joyous reopening to celebrate the country’s victory over the coronavirus. Instead, tens of thousands of people have ventured out to protest the killing of George Floyd by police.

Demonstrators have closely gathered all over the country, and in blocks-long crowds in large cities, singing and chanting and demanding justice. Police officers have dealt with them roughly, crowding protesters together, blasting them with lung and eye irritants, and cramming them into paddy wagons and jails.

There’s no point in denying the obvious: Standing in a crowd for long periods raises the risk of increased transmission of SARS-CoV-2, the virus that causes COVID-19. This particular form of mass, in-person protest—and the corresponding police response—is a “perfect set-up” for transmission of the virus, Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases, said in a radio interview on Friday. Some police-brutality activists (such as Black Lives Matter Seattle) have issued statements about the risk involved in the protests. Others have organized less risky forms of protests, such as Oakland’s Anti Police-Terror Project’s massive “caravan for justice.”

The risk of transmission is complicated by, and intertwined with, the urgent moral stakes: Systemic racism suffuses the United States. The mortality gap between black and white people persists. People born in zip codes mere miles from one another might have life-expectancy gaps of 10 or even 20 years. Two racial inequities meet in this week’s protests: one, a pandemic in which black people are dying at nearly twice their proportion of the population, according to racial data compiled by the COVID Tracking Project at The Atlantic; and two, antiblack police brutality, with its long American history and intensifying militarization. Floyd, 46, survived COVID-19 in April, but was killed under the knee of a police officer in May.

[Read: Defund the police]

Americans may wish the virus to be gone, but it is not. While the outbreak has eased in the Northeast, driving down the overall national numbers, cases have only plateaued in the rest of the country, and they appear to be on the rise in recent days in COVID Tracking Project data. Twenty-two states reported 400 or more new cases Friday, and 14 other states and Puerto Rico reported cases in the triple digits. Several states—including Arizona, North Carolina, and California—are now seeing their highest numbers of known cases.

These numbers all reflect infections that likely began before this week of protest. An even larger spike now seems likely. Put another way: If the country doesn’t see a substantial increase in new COVID-19 cases after this week, it should prompt a rethinking of what epidemiologists believe about how the virus spreads.

But as the pandemic persists, more and more states are pulling back on the measures they’d instituted to slow the virus. The Trump administration’s Coronavirus Task Force is winding down its activities. Its testing czar is returning to his day job at the Department of Health and Human Services. As the long, hot summer of 2020 begins, the facts suggest that the U.S. is not going to beat the coronavirus. Collectively, we slowly seem to be giving up. It is a bitter and unmistakably American cruelty that the people who might suffer most are also fighting for justice in a way that almost certainly increases their risk of being infected.

The protests have led to unusually agonized public-health communication. They have not been met with the stern admonition to stay home that has greeted earlier mass gatherings. Given the long-standing health inequities that black Americans have experienced, hundreds of public-health professionals signed a letter this week declining to oppose the protests “as risky for COVID-19 transmission”: “We support them as vital to the national public health and to the threatened health specifically of Black people in the United States,” they wrote. Yet the protests are indisputably risky, and officials at the Centers for Disease Control and Prevention have warned that the gatherings might “seed” new outbreaks.

Protesters themselves are not necessarily ignoring the pandemic. In videos of marches taken this week, many if not most of the demonstrators appeared to be wearing masks. Photos and videos of protests show both large, tightly packed crowds and some demonstrators attempting to adhere to some form of social distancing. Protesters carrying hand sanitizer and water pass through the crowd in many cities.

But the evidence does not reveal universal compliance with public-health guidelines. Protesters lay close together on the ground in many cities for nearly nine-minute-long “die-ins,” evoking the length of time that Derek Chauvin, a Minneapolis police officer, knelt on Floyd’s neck. Many protests have involved some form of shouting, chanting, or singing, which research suggests can be especially effective modes of transmission for the virus. Earlier this week, near the White House, a mostly masked crowd loudly sang “Lean on Me.”

[Adam Serwer: Trump gave police permission to be brutal]

Protesters and public-health officials alike may be taking into account what The New York Times called “a growing consensus” that being outdoors mitigates some risk of transmission. The virus appears to perish quickly in a sunny, humid environment, even at room temperature, according to research conducted in April by the Department of Homeland Security. (Viral particles may survive for hours longer in drier conditions, and epidemiologists do not believe that these climatic effects alone will dampen the outbreak.) The virus also seems to be more difficult to transmit outside, especially during the day, though scientists still do not know enough about the virus to say confidently that large outdoor gatherings are completely safe. The number of protests over the past week means that researchers will soon have a much better understanding of the risks of outdoor transmission.

Many of the potential drivers of coronavirus transmission this week do not involve protester tactics: Dozens of police forces have used security measures that could allow the virus to spread more easily. In Washington, D.C., for instance, federal officers used tear gas or another chemical irritant on hundreds of peaceful protesters gathered in front of the White House on Monday so that President Donald Trump could pose for a photograph. Tear gas and chemicals like it force people to cough and gag, a fertile mode of transmission for the virus. Later that night, city police crowded protesters together before arresting them one by one, an aggressive crowd-control technique known as “kettling.” Hundreds of protesters who were arrested this week were sent—even if briefly—to the city’s jails, which have so many coronavirus cases that the District government has separated that number out from the citywide total.

In Philadelphia, city police tear-gassed hundreds of peaceful protesters marching on a freeway, prompting them to cough and gag. (There is no evidence that the demonstrators posed a threat to the safety of officers or bystanders, or were becoming violent, according to the local NPR affiliate.) In New York City, officers crammed hundreds of peaceful demonstrators together, then struck them with batons. From Iowa to Texas, officers used tear gas on large, largely peaceful gatherings; in at least five states, police deployed pepper spray or tear gas on children or teenagers, some of whom just happened to be nearby and were not attending the protests.

[Read: I can’t breathe: braving teargas in a pandemic]

Journalists from across the country have reported that police officers are wearing masks less often than protesters. “The state is the one with the duty to protect public health,” Alexandra Phelan, a professor of global-health law at Georgetown University, told us earlier this week. Regardless of what the police think of the protests, she said, it is their obligation under international and domestic law to keep the protesters safe, including minimizing the health risk from viral spread.

There are too many variables to know exactly what the summer has in store for the outbreak in America, including what effect the protests will have. There are some signs of hope. Masks are in use around the country. Outdoor transmission seems to be fairly unlikely in most settings. And testing availability has improved. According to data from the COVID Tracking Project, the United States can now conduct 3 million tests a week. The public-health system is discovering and diagnosing a much greater percentage of cases than it did in the early days of the outbreak. Morgan Stanley estimated that the transmission rate in the U.S. was just above 1; this suggests that there has not been explosive growth in the number of active cases in recent weeks.

But that estimated rate also implies that cases are not rapidly declining. And the slow growth reflects the time before the full data from states’ recent moves to reopen their economy became available—before large swaths of the public returned to work, and before the mass protests and jailings began.

Few people believe that the U.S. is doing all it can to contain the virus. A brief glance at Covid Exit Strategy, a site that tracks state-by-state progress, reveals that most states are not actually hitting the reopening marks suggested by public-health experts. Yet state leaders have not stuck with the kinds of lockdowns that suppressed the virus in other countries; nobody has suggested that cases must be brought to negligible levels before normal activity can resume. No federal official has shared a plan for preventing transmission among states that have outbreaks of varying intensity. The Trump administration did not use the eight weeks of intense social distancing to significantly expand our suppression capacity.

What our colleague Ed Yong called “the patchwork pandemic” appears to have confused the American public about what is going on. The virus is not following one single course through the nation, but, like a tornado, is taking a meandering and at times incomprehensible path through cities and counties. Why this workplace but not another? Why this city or state but not others?

Chart tool by Peter Walker; data from the COVID Tracking Project at The Atlantic

The virus has not mapped neatly onto American political narratives, either. While some questions remain about their accounting, Georgia and Florida—where leaders opened up early and residents seemed relatively defiant of public-health advice—have seen relatively flat numbers, while California, which took a more conservative approach, has seen cases grow. The state most poised for major trouble seems to be Arizona, where the outbreak is spreading very quickly. Not only is the state (which lifted its stay-at-home order on May 16) setting new records for positive tests and people in the hospital, but the percentage of tests that are coming back positive is also growing. So much for warm weather and sunshine alone stamping out viral transmission, as some had hoped: Phoenix saw only a single day’s high under 90 degrees during May. The state’s age demographics also haven’t played an obvious role: The state is slightly younger than the U.S. as a whole.

Chart tool by Peter Walker; data from the COVID Tracking Project at The Atlantic

Americans have not fully grasped that we are not doing what countries that have returned to normal have done. Some countries have almost completely suppressed the virus. Others had large outbreaks, took intense measures, and have seen life return to normal. Americans, meanwhile, never stayed at home to the degree that most Europeans have, according to mobility data from Apple and Google. Our version of the spring lockdown looked more like Sweden’s looser approach than like the more substantial measures in Italy, or even the United Kingdom and France. Swedish public-health officials have acknowledged that this approach may not have been the best path forward.

[Read: Why America resists learning from other countries]

For several weeks at the beginning of the outbreak in the U.S., the need to control the virus took precedence over other concerns. Now, for many people, the pandemic is no longer the most pressing national issue. As protesters and some public-health officials have said they are weighing the harms of police violence against the risk of increased viral spread and choosing to gather in the streets, state governments have made similar risk-reward arguments about balancing public-health and economic concerns. The virus does not care about these trade-offs. Retail reopenings and racial-justice protests may exist on different moral planes, but to the virus they both present new environments for spreading.

Maybe the U.S. will somehow avoid another New York–style outbreak. Maybe the number of new infections will not grow exponentially. Maybe treatments have sufficiently improved that we will see huge outbreaks, but fewer people will die than we’ve come to expect. If so, it won’t be because the United States made concerted, coordinated decisions about how to balance the horrors of the pandemic and the frustration of pausing everyday life. Instead, the United States has moved from attempting to beat the virus to managing the harm of losing.

This is America. The problems with our response to the pandemic reflect the problems of the country itself. Our health-care system is almost uniquely ill-suited to dealing with a national health crisis; preexisting health disparities, entrenched and deepened by decades of racism, cannot be erased overnight; state and local health departments desperately needed federal leadership they did not receive; the Senate has not entertained a longer-lasting economic-rescue package that would allow a more prolonged period of sheltering in place; states are facing a fiscal cliff.

And yet, even though this health crisis reflects our nation’s political, social, and civic infrastructure, this plague has no consideration for morality. People partying in a pool may live while those protesting police brutality may die. People who assiduously followed the rules of social distancing may get sick, while those who flouted them happily toast their friends in a crowded bar. There is no righteous logic here. There is no justice in who can breathe easy and who can’t breathe at all.

Related Podcast

Listen to Alexis Madrigal discuss this story on an episode of Social Distance, The Atlantic’s podcast about life in a pandemic:

Subscribe to Social Distance on Apple Podcasts or Spotify (How to Listen)

‘How Could the CDC Make That Mistake?’

2020-05-21T00:35:22-04:00

The Centers for Disease Control and Prevention is conflating the results of two different types of coronavirus tests, distorting several important metrics and providing the country with an inaccurate picture of the state of the pandemic. We’ve learned that the CDC is making, at best, a debilitating mistake: combining test results that diagnose current coronavirus infections with test results that measure whether someone has ever had the virus. The upshot is that the government’s disease-fighting agency is overstating the country’s ability to test people who are sick with COVID-19. The agency confirmed to The Atlantic on Wednesday that it is mixing the results of viral and antibody tests, even though the two tests reveal different information and are used for different reasons.

This is not merely a technical error. States have set quantitative guidelines for reopening their economies based on these flawed data points.

Several states—including Pennsylvania, the site of one of the country’s largest outbreaks, as well as Texas, Georgia, and Vermont—are blending the data in the same way. Virginia likewise mixed viral and antibody test results until last week, but it reversed course and the governor apologized for the practice after it was covered by the Richmond Times-Dispatch and The Atlantic. Maine similarly separated its data on Wednesday; Vermont authorities claimed they didn’t even know they were doing this.

The widespread use of the practice means that it remains difficult to know exactly how much the country’s ability to test people who are actively sick with COVID-19 has improved.

[Read: There’s one big reason the U.S. economy can’t reopen]

“You’ve got to be kidding me,” Ashish Jha, the K. T. Li Professor of Global Health at Harvard and the director of the Harvard Global Health Institute, told us when we described what the CDC was doing. “How could the CDC make that mistake? This is a mess.”

Viral tests, taken by nose swab or saliva sample, look for direct evidence of a coronavirus infection. They are considered the gold standard for diagnosing someone with COVID-19, the disease caused by the virus: State governments consider a positive viral test to be the only way to confirm a case of COVID-19. Antibody tests, by contrast, use blood samples to look for biological signals that a person has been exposed to the virus in the past.

A negative test result means something different for each test. If somebody tests negative on a viral test, a doctor can be relatively confident that they are not sick right now; if somebody tests negative on an antibody test, they have probably never been infected with or exposed to the coronavirus. (Or they may have been given a false result—antibody tests are notoriously less accurate on an individual level than viral tests.) The problem is that the CDC is clumping negative results from both tests together in its public reporting.

[Read: Pools will test the limits of social distancing]

Mixing the two tests makes it much harder to understand the meaning of positive tests, and it clouds important information about the U.S. response to the pandemic, Jha said. “The viral testing is to understand how many people are getting infected, while antibody testing is like looking in the rearview mirror. The two tests are totally different signals,” he told us. By combining the two types of results, the CDC has made them both “uninterpretable,” he said.

The public-radio station WLRN, in Miami, first reported that the CDC was mixing viral and antibody test results. Pennsylvania’s and Maine’s decisions to mix the two tests have not been previously reported.

Kristen Nordlund, a spokesperson for the CDC, told us that the inclusion of antibody data in Florida is one reason the CDC has reported hundreds of thousands more tests in Florida than the state government has. The agency hopes to separate the viral and antibody test results in the next few weeks, she said in an email.

But until the agency does so, its results will be suspect and difficult to interpret, says William Hanage, an epidemiology professor at Harvard. In addition to misleading the public about the state of affairs, the intermingling “makes the lives of actual epidemiologists tremendously more difficult.”

“Combining a test that is designed to detect current infection with a test that detects infection at some point in the past is just really confusing and muddies the water,” Hanage told us.

[Read: Why the coronavirus is so confusing]

The CDC stopped publishing anything resembling a complete database of daily test results on February 29. When it resumed publishing test data last week, a page of its website explaining its new COVID Data Tracker said that only viral tests were included in its figures. “These data represent only viral tests. Antibody tests are not currently captured in these data,” the page said as recently as May 18.

Yesterday, that language was changed. All reference to disaggregating the two different types of tests disappeared. “These data are compiled from a number of sources,” the new version read. The text strongly implied that both types of tests were included in the count, but did not explicitly say so.

The CDC’s data have also become more favorable over the past several days. On Monday, a page on the agency’s website reported that 10.2 million viral tests had been conducted nationwide since the pandemic began, with 15 percent of them—or about 1.5 million—coming back positive. But yesterday, after the CDC changed its terms, it said on the same page that 10.8 million tests of any type had been conducted nationwide. Yet its positive rate had dropped by a percent. On the same day it expanded its terms, the CDC added 630,205 new tests, but it added only 52,429 positive results.

This is what concerns Jha. Because antibody tests are meant to be used on the general population, not just symptomatic people, they will, in most cases, have a lower percent-positive rate than viral tests. So blending viral and antibody tests “will drive down your positive rate in a very dramatic way,” he said.

The absence of clear national guidelines has led to widespread confusion about how testing data should be reported. Pennsylvania reports negative viral and antibody tests in the same metric, a state spokesperson confirmed to us on Wednesday. The state has one of the country’s worst outbreaks, with more than 67,000 positive cases. But it has also slowly improved its testing performance, testing about 8,000 people in a day. Yet right now it is impossible to know how to interpret any of its accumulated results.

[Read: Should you get an antibody test?]

Texas, where the rate of new COVID-19 infections has stubbornly refused to fall, is one of the most worrying states (along with Georgia). The Texas Observer first reported last week that the state was lumping its viral and antibody results together. On Tuesday, Governor Greg Abbott denied that the state was blending the results, but the Dallas Observer reports that it is still doing so.

While the number of tests per day has increased in Texas, climbing to more than 20,000, the combined results mean that the testing data are essentially uninterpretable. It is impossible to know the true percentage of positive viral tests in Texas. It is impossible to know how many of the 718,000 negative results were not meant to diagnose a sick person. The state did not return a request for comment, nor has it produced data describing its antibody or viral results separately. (Some states, following guidelines from the Council of State and Territorial Epidemiologists, report antibody-test positives as “probable” COVID-19 cases without including them in their confirmed totals.)

Georgia is in a similar situation. It has also seen its COVID-19 infections plateau amid a surge in testing. Like Texas, it reported more than 20,000 new results on Wednesday, the majority of them negative. But because, according to The Macon Telegraph, it is also blending its viral and antibody results together, its true percent-positive rate is impossible to know. (The governor’s office did not return a request for comment.)

These results damage the public’s ability to understand what is happening in any one state. On a national scale, they call the strength of America’s response to the coronavirus into question. The number of tests conducted nationwide each day has more than doubled in the past month, rising from about 147,000 a month ago to more than 413,000 on Wednesday, according to the COVID Tracking Project at The Atlantic, which compiles data reported by state and territorial governments. In the past week, the daily number of tests has grown by about 90,000.

At the same time, the portion of tests coming back positive has plummeted, from a seven-day average of 10 percent at the month’s start to 6 percent on Wednesday.

“The numbers have outstripped what I was expecting,” Jha said. “My sense is people are really surprised that we’ve moved as much as we have in such a short time period. I think we all expected a move and we all expected improvement, but the pace and size of that improvement has been a big surprise.”

The intermingling of viral and antibody tests suggests that some of those gains might be illusory. If even a third of the country’s gain in testing has come by expanding antibody tests, not viral tests, then its ability to detect an outbreak is much smaller than it seems. There is no way to ascertain how much of the recent increase in testing is from antibody tests until the most populous states in the country—among them Texas, Georgia, and Pennsylvania—show their residents everything in the data.