Scientists May Be Using the Wrong Cells to Study Covid-19

BY NOW THERE’S little doubt about hydroxychloroquine: It doesn’t work for treating Covid-19. But there’s a bigger, more important lesson hidden in the story of its failure—a rarely mentioned, but altogether crucial, error baked into the early research. The scientists who ran the first, promising laboratory experiments on the drug had used the wrong kind of cells. Instead of testing its effects on human lung cells, they relied on a supply of mass-produced, standardized cells made from a monkey’s kidney. In the end, that poor decision made their findings more or less irrelevant to human health. Worse, it’s possible that further research into novel Covid-19 cures will end up being compromised by the same mistake.SUBSCRIBE

The problem began in early February, when the scientific journal Cell Research published data from the Wuhan Institute of Virology suggesting that a pharmaceutical cousin of hydroxychloroquine was “highly effective” at controlling infections with SARS-CoV-2, the virus that causes Covid-19. (In 2005, lab tests of the same drug found it could inhibit the coronavirus that caused the original SARS outbreak.) A separate, full-fledged study from a different Chinese group, which appeared in the journal Clinical Infectious Diseases on March 9, found hydroxychloroquine to be more potent, and has since been cited hundreds of times. About a week after that, a third journal, Cell Discovery, put out the results from another study by the Wuhan group, which concluded that hydroxychloroquine, in particular, “has a good potential to combat the disease.”

The experiments described in those three papers—and also the one on SARS from 15 years ago—all suffered from the same problem: They started with a set of kidney cells that traces back to an African green monkey dissected in the spring of 1962.

It’s not at all uncommon for individual scientists—or even entire subfields of research—to waste their time in just this way, by choosing the most familiar animal or “model system” as the basis for their work, even when it’s not well suited to the question at hand. Rodent research findings, for example, have been notoriously misleading on a number of important topics, including potential treatments for amyotrophic lateral sclerosis (ALS) and tuberculosis. Cell lines, too, can be misapplied out of habit or convenience. The ones derived from an African green monkey kidney, known as Vero cells, are especially popular among virologists, in part because they contain fewer antiviral proteins known as interferons than other cells, and thus provide a fertile breeding ground for certain viruses that are otherwise quite fickle and difficult to grow in the lab. (Lab mice have long been used to study cancer for the same reason: They happen to be startlingly adept at getting tumors.)

The experiments all suffered from the same problem: They started with a set of kidney cells that traces back to an African green monkey dissected in the spring of 1962.

Vero cells have at times been indispensable to the study of coronaviruses. One of the earliest papers to identify the pathogen behind the 2003 SARS outbreak, for instance, used this kind of cell to grow the virus so that scientists could study it in detail. But the cells’ more recent use provides a cautionary tale. Whereas hydroxychloroquine does appear to stop SARS-CoV-2 from infecting Vero cells, it fails to do the same for human lung cells in a dish. According to research from Stefan Pöhlmann, head of the Infection Biology Unit at the German Primate Center in Göttingen, and his collaborators, the devil was in the details of how the cells interact with the SARS-CoV-2’s dreaded ‘spike’ protein. Human lung cells contain at least two different enzymes that can help the virus sneak through their membranes. With Vero cells, however, only one of those modes of entry is available—and it turns out to be the one that hydroxychloroquine will block. Pöhlmann and his team published the results in the journal Nature on July 22. For him, it’s a clear example of why using human lung cells is really important in studying this pandemic virus. Vero cells should be “handled with caution,” Pöhlmann says. “It’s true that the Vero cells are very popular. But unfortunately for this particular aspect of Covid-19 research, they are absolutely not useful. I think this is now clear to the field.”Get WIRED AccessSUBSCRIBEMost Popular

The notion that doctors might once more forge ahead with ad hoc treatments based on nothing more than Vero-cell results worries Vincent Racaniello, a microbiologist at Columbia University in New York and host of the popular TWiV virology podcast. Racaniello says that he received a message from someone who was excited about a study posted to a preprint server that suggested the antidepressant Prozac inhibits the SARS-CoV-2 virus—but this work, too, was done in Vero cells. He was unimpressed.

Both Racaniello and Pöhlmann note that Vero cells might be fine for investigating drugs that work by slowing or stopping the virus from making more copies once it’s already inside a cell. But they say that not all scientists are aware of those nuances. There are plenty who have abandoned their main areas of expertise to explore Covid-19, including virologists who have never worked with coronaviruses before. Madhu Pai, epidemiologist and director of the Global Health Program and TB Centre at McGill University in Montreal, has described this as the “Covidization of research,” where “well-intentioned scientists with real expertise in one field intrude into another, passing judgment where they lack expert-level training and insight.” The result, he says, is to “open the door to big mistakes with bad consequences.”

Concerns about the overreliance on Vero cells in this pandemic are not limited to the study of potential therapies. Experts have also cautioned against Vero-based research into how efficiently the new coronavirus infects its hosts, and whether patients with positive Covid test results are necessarily contagious after the first week or so of illness

Pöhlmann expects that academic journals will start paying more attention to the flaws of Vero cells—and demanding evidence from human lung cells—when reviewing studies of potential therapies for Covid-19. But this vetting is even less likely to occur for preprint papers, so journalists and the public should be vigilant as well.

All this hand-wringing over Vero cells isn’t just a minor scientific quibble. Sure, more than six months into this pandemic, scientists finally figured out why hydroxychloroquine was a bust, but that only happened after massive amounts of time and money were spent on clinical trials of a drug with potentially fatal side effects. The US scrambled to secure a stockpile of hydroxychloroquine pills; by mid-June it had distributed 31 million of them to state and local health departments. Meanwhile, at least one-third of lupus patients in the US who take hydroxychloroquine had trouble accessing the drug—which is known and approved to treat their condition—because of shortages resulting from the Covid-19 hype. We would have avoided all of this if scientists had double-checked their Vero findings in human lung cells before racing to publish their results. The cells that scientists select are tiny, but their repercussions are anything but small.

How to Think Like an Epidemiologist

Don’t worry, a little Bayesian analysis won’t hurt you.

There is a statistician’s rejoinder — sometimes offered as wry criticism, sometimes as honest advice — that could hardly be a better motto for our times: “Update your priors!”

In stats lingo, “priors” are your prior knowledge and beliefs, inevitably fuzzy and uncertain, before seeing evidence. Evidence prompts an updating; and then more evidence prompts further updating, so forth and so on. This iterative process hones greater certainty and generates a coherent accumulation of knowledge.

In the early pandemic era, for instance, airborne transmission of Covid-19 was not considered likely, but in early July the World Health Organization, with mounting scientific evidence, conceded that it is a factor, especially indoors. The W.H.O. updated its priors, and changed its advice.

This is the heart of Bayesian analysis, named after Thomas Bayes, an 18th-century Presbyterian minister who did math on the side. It captures uncertainty in terms of probability: Bayes’s theorem, or rule, is a device for rationally updating your prior beliefs and uncertainties based on observed evidence.

Reverend Bayes set out his ideas in “An Essay Toward Solving a Problem in the Doctrine of Chances,” published posthumously in 1763; it was refined by the preacher and mathematician Richard Price and included Bayes’s theorem. A couple of centuries later, Bayesian frameworks and methods, powered by computation, are at the heart of various models in epidemiology and other scientific fields

As Marc Lipsitch, an infectious disease epidemiologist at Harvard, noted on Twitter, Bayesian reasoning comes awfully close to his working definition of rationality. “As we learn more, our beliefs should change,” Dr. Lipsitch said in an interview. “One extreme is to decide what you think and be impervious to new information. Another extreme is to over-privilege the last thing you learned. In rough terms, Bayesian reasoning is a principled way to integrate what you previously thought with what you have learned and come to a conclusion that incorporates them both, giving them appropriate weights.”

With a new disease like Covid-19 and all the uncertainties it brings, there is intense interest in nailing down the parameters for models: What is the basic reproduction number, the rate at which new cases arise? How deadly is it? What is the infection fatality rate, the proportion of people with the virus that it kills?

But there is little point in trying to establish fixed numbers, said Natalie Dean, an assistant professor of biostatistics at the University of Florida.

“We should be less focused on finding the single ‘truth’ and more focused on establishing a reasonable range, recognizing that the true value may vary across populations,” Dr. Dean said. “Bayesian analyses allow us to include this variability in a clear way, and then propagate this uncertainty through the model.”

A textbook application of Bayes theorem is serology testing for Covid-19, which looks for the presence of antibodies to the virus. All tests are imperfect, and the accuracy of an antibody test turns on many factors including, critically, the rarity or prevalence of the disease.

The first SARS-CoV-2 antibody test approved by the F.D.A., in April, seemed to be wrong as often as it was right. With Bayes theorem, you can calculate what you really want to know: the probability that the test result is correct. As one commenter on Twitter put it: “Understanding Bayes’ theorem is a matter of life and death right now.”

Joseph Blitzstein, a statistician at Harvard, delves into the utility of Bayesian analysis in his popular course “Statistics 110: Probability.” For a primer, in lecture one, he says: “Math is the logic of certainty, and statistics is the logic of uncertainty. Everyone has uncertainty. If you have 100 percent certainty about everything, there is something wrong with you.”

By the end of lecture four, he arrives at Bayes’s theorem — his favorite theorem because it is mathematically simple yet conceptually powerful.

“Literally, the proof is just one line of algebra,” Dr. Blitzstein said. The theorem essentially reduces to a fraction; it expresses the probability P of some event A happening given the occurrence of another event B.

“Naïvely, you would think, How much could you get from that?” Dr. Blitzstein said. “It turns out to have incredibly deep consequences and to be applicable to just about every field of inquiry” — from finance and genetics to political science and historical studies. The Bayesian approach is applied in analyzing racial disparities in policing (in the assessment of officer decisions to search drivers during a traffic stop) and search-and-rescue operations (the search area narrows as new data is added). Cognitive scientists ask, ‘Is the brain Bayesian?’ Philosophers of science posit that science as a whole is a Bayesian process — as is common sense.

Take diagnostic testing. In this scenario, the setup of Bayes’s theorem might use events labeled “T” for a positive test result — and “C” for the presence of Covid-19 antibodies:

Now suppose the prevalence of cases is 10 percent (that was so in New York City in the spring), and you have a positive result from a test with accuracy of 87.5 percent sensitivity and 97.5 percent specificity. Running numbers through the Bayesian gears, the probability that the result is correct, and that you do indeed have antibodies is 79.5%. Decent odds, all things considered. If you want more certainty, get a second opinion. And continue to be cautious.

An international collaboration of researchers, doctors and developers created another Bayesian strategy, pairing the test result with a questionnaire to produce a better estimate of whether the result might be a false negative or a false positive. The tool, which has won two hackathons, collects contextual information: Did you go to work during lockdown? What did you do to avoid catching Covid-19? Has anyone in your household had Covid-19?

“It’s a little akin to having two ‘medical experts,’” said Claire Donnat, who recently finished her Ph.D. in statistics at Stanford and was part of the team. One expert has access to the patient’s symptoms and background, the other to the test; the two diagnoses are combined to produce a more precise score, and more reliable immunity estimates. The priors are updated with an aggregation of information.

“As new information comes in, we update our priors all the time,” said Susan Holmes, a Stanford statistician, via unstable internet from rural Portugal, where she unexpectedly pandemicked for 105 days, while visiting her mother.The Coronavirus Outbreak ›

Updated August 4, 2020

That was the base from which Dr. Holmes refined a preprint paper, co-authored with Dr. Donnat, that provides another example of Bayesian analysis, broadly speaking. Observing early research in March about how the pandemic might evolve, they noticed that classic epidemiological models tend to use fixed parameters, or constants, for the reproduction number — for instance, with an R0 of 2.0.

But in reality, the reproduction number depends on random, uncertain factors: viral loads and susceptibility, behavior and social networks, culture and socioeconomic class, weather, air conditioning and unknowns.

With a Bayesian perspective, the uncertainty is encoded into randomness. The researchers began by supposing that the reproductive number had various distributions (the priors). Then they modeled the uncertainty using a random variable that fluctuates, taking on a range of values as small as 0.6 and as large as 2.2 or 3.5. In something of a nesting process, the random variable itself has parameters that fluctuate randomly; and those parameters, too, have random parameters (hyper-parameters), etcetera. The effects accumulate into a “Bayesian hierarchy” — “turtles all the way down,” Dr. Holmes said.

The effects of all these up-and-down random fluctuations multiply, like compound interest. As a result, the study found that using random variables for reproductive numbers more realistically predicts the risky tail events, the rarer but more significant superspreader events.

Humans on their own, however, without a Bayesian model for a compass, are notoriously bad at fathoming individual risk.

“People, including very young children, can and do use Bayesian inference unconsciously,” said Alison Gopnik, a psychologist at the University of California, Berkeley. “But they need direct evidence about the frequency of events to do so.”

Much of the information that guides our behavior in the context of Covid-19 is probabilistic. For example, by some estimates, if you get infected with the coronavirus, there is a 1 percent chance you will die; but in reality an individual’s odds can vary by a thousandfold or more, depending on age and other factors. “For something like an illness, most of the evidence is usually indirect, and people are very bad at dealing with explicit probabilistic information,” Dr. Gopnik said.

Even with evidence, revising beliefs isn’t easy. The scientific community struggled to update its priors about the asymptomatic transmission of Covid-19, even when evidence emerged that it is a factor and that masks are a helpful preventive measure. This arguably contributed to the world’s sluggish response to the virus.

“The problems come when we don’t update,” said David Spiegelhalter, a statistician and chair of the Winton Centre for Risk and Evidence Communication at the University of Cambridge. “You can interpret confirmation bias, and so many of the ways in which we react badly, by being too slow to revise our beliefs.”

There are techniques that compensate for Bayesian shortcomings. Dr. Spiegelhalter is fond of an approach called Cromwell’s law. “It’s heaven,” he said. In 1650, Oliver Cromwell, Lord Protector of the Commonwealth of England, wrote in a letter to the Church of Scotland: “I beseech you, in the bowels of Christ, think it possible you may be mistaken.”

In the Bayesian world, Cromwell’s law means you should always “keep a bit back — with a little bit of probability, a little tiny bit — for the fact that you may be wrong, ”Dr. Spiegelhalter said. “Then if new evidence comes along that totally contradicts your main prior belief, you can quickly ditch what you thought before and lurch over to that new way of thinking.”

“In other words, keep an open mind,” said Dr. Spiegelhalter. “That’s a very powerful idea. And it doesn’t necessarily have to be done technically or formally; it can just be in the back of your mind as an idea. Call it ‘modeling humility.’ You may be wrong.”

I’d Need Evidence Before I Got a Covid-19 Vaccine. It Doesn’t Exist Yet.

Coronavirus vaccines are rapidly advancing through the development pipeline. The University of Oxford’s vaccine is in large trials in BritainBrazil and South Africa. In the United States, researchers just began enrolling around 30,000 volunteers to test Moderna’s vaccine, and more trials are starting every day. Operation Warp Speed has set an ambitious goal of delivering 300 million doses of a safe, effective vaccine by January.

But the concept of developing a vaccine at “warp speed” makes many people uncomfortable. In a May survey, 49 percent of the Americans polled said they plan to get a coronavirus vaccine when one is available, 20 percent do not, and 31 percent indicated that they were not sure. The World Health Organization considers “vaccine hesitancy” a major threat to global health, and poor uptake would jeopardize the impact of a coronavirus vaccine.RelatedScientists Worry About Political Influence Over Coronavirus Vaccine ProjectAug. 2, 2020

This hesitancy isn’t surprising. Why should we expect Americans to agree to a vaccine before one is even available? “I think it’s reasonable to be skeptical about a vaccine that doesn’t exist yet,” Dr. Paul Offit, the director of the Vaccine Education Center at Children’s Hospital of Philadelphia, told Today.

I’m a vaccine researcher, and even I would place myself in the “not sure” bucket. What we have right now is a collection of animal data, immune response data and safety data based on early trials and from similar vaccines for other diseases. The evidence that would convince me to get a Covid-19 vaccine, or to recommend that my loved ones get vaccinated, does not yet exist.

That data can be generated by the large trials that are just beginning, known as Phase III or efficacy trials. Some have argued that we already have enough safety and immune response data to start vaccinating people now. But this would be a big mistake.

This is how Phase III trials work: Thousands of healthy adult volunteers are randomized to receive either a new Covid-19 vaccine or a control — a placebo or an already licensed vaccine for another disease. Then they go about their normal lives. They do not know what they have received (known as “blinding”) so the two groups behave similarly in terms of risk taking.

Participants are monitored for side effects and contacted regularly to ask about symptoms and to be tested for infection. The goal is to compare the rates of disease or infection across the two groups to measure how well the vaccine prevents Covid-19 “in the field.”

It is possible that some Covid-19 vaccines may not prevent infection entirely, but they could still prepare a person’s immune system so that, if infected, they would experience milder symptoms, or even none at all. That’s similar to the flu vaccine: It’s not perfect, but we advise people to get it because it reduces intensive care admissions and deaths.

How many people need to be protected by a vaccine before it’s recommended for widespread use? Ideally, rates of disease will be 70 percent lower in vaccinated people than in unvaccinated people. The World Health Organization says a vaccine should be at minimum 50 percent effective, averaged across age groups. (We know from influenza that vaccines don’t always work as well on older adults whose immune systems have declined.)

This benchmark is crucial because a weak vaccine might be worse than no vaccine at all. We do not want people who are only slightly protected to behave as if they are invulnerable, which could exacerbate transmission. It is also costly to roll out a vaccine, diverting attention away from other efforts that we know work, like mask-wearing, and from testing better vaccines.

The last thing Phase III trials do is examine safety. Earlier trials do this, too, but larger trials allow us to detect rarer side effects. One of those rare effects researchers are paying attention to is a paradoxical phenomenon known as immune enhancement, in which a vaccinated person’s immune system overreacts to infection. Researchers can test for this by comparing the rates of disease severe enough to require hospitalization across the two groups. A clear signal that hospitalization is higher among vaccinated participants would mark the end of a vaccine.

The speed of the trials depends on how quickly we can detect a difference between the two groups. If two vaccinated people became sick versus 10 who got a placebo, it could be because of chance. But if it were 20 compared to 100, we would feel much more confident that the vaccine was working.

Key to getting a quick result is placing the trial in outbreak hot spots where people are most likely to be infected. We can even target the highest-risk people within those areas, using mobile teams to travel to neighborhoods, bringing the trial directly to the people. Some trials explicitly prioritize essential workers like health care workers or grocery employees. Others are simply focused on enrolling large numbers of participants as fast as possible.

Combining those efforts, it could take as little as three to six months to generate enough convincing safety and efficacy data for companies to apply for expedited review by the Food and Drug Administration.

There are ways for vaccines to be approved without definitive efficacy data, based on animal or immune response data instead, but the bar is extremely high, and for good reason. A precondition is that efficacy trials are not possible, typically because the disease is so rare or sporadic that it would require hundreds of thousands of participants to be followed for many years to tell if the vaccine is effective (rabies, for example). That is not the situation here.

While there is promising data from smaller trials that measured the antibody response in people who got a vaccine, it’s not enough to approve a vaccine. We don’t know the level of antibodies needed to prevent infection from this virus. There is a history of vaccines with promising immune response data that did not pan out in the field.

With this in mind, the F.D.A. has committed to the need for traditional efficacy trial data to approve Covid-19 vaccines. And it follows the W.H.O.’s recommendation, stating that vaccines must be at least 50 percent effective to be approved.

I worry nonetheless that public pressure may mount to approve a product that doesn’t meet our standards. Other countries may decide to approve vaccines based on weaker evidence. Russia, for example, claims to be on track to approve a vaccine in just a few weeks.

We must resist the desire to rush out a product. Creating vaccines is hard, and we should be prepared for the reality that some promising ones will not meet the F.D.A.’s criteria. Researchers and the government should also commit to transparency so that people can see the results for themselves to understand the regulatory decisions.

Waiting for a better vaccine to come along may feel like torture, but it is the right move. With so many potential shots on goal, scientists are optimistic that a safe and effective vaccine is out there. We can’t afford to jeopardize the public’s health and hard-earned trust by approving anything short of that.

Covid Tests and Quarantines: Colleges Brace for an Uncertain Fall

This month, many colleges around the country plan to welcome back thousands of students into something they hope will resemble normal campus life. But they face challenges unlike any other American institution — containing the coronavirus among a young, impulsive population that not only studies together, but lives together, parties together, and, if decades of history are any guide, sleeps together.

It will be a hugely complex and costly endeavor requiring far more than just the reconfiguring of dorm rooms and cafeterias and the construction of annexes and tent classrooms to increase social distancing. It also crucially involves the creation of testing programs capable of serving communities the size of small cities and the enforcement of codes of conduct among students not eager to be policed.

Who will be tested for the coronavirus and how quickly can they get results? Will mask wearing be mandated? And what will happen to tailgating, keg parties and sneaking into your partner’s dorm room? Colleges are mapping strategies as varied as the contrasting Covid regulations enacted by the states, reflecting the culture and leadership of their schools.

Syracuse is vowing to play the strict parent, requiring students to sign codes of conduct with penalties for violating Covid-19 rules more severe than the punishment for smoking marijuana. But the University of Kentucky is presenting a more lenient front, adopting existing honor codes that urge students to “promote personal responsibility and peer accountability.”

And the University of Texas-Austin has prohibited students from holding parties on or off campus, banned overnight guests in dorm rooms and warned students that they can be disciplined for “purposefully invading the personal space of others,” at least without a face mask on.

All of these efforts are coming at great cost, potentially adding more than $70 billion to the budgets of the nation’s 5,000 colleges. Yet college administrators say giving their constituents — students and their families — at least a taste of college life is worth it, if done in the safest possible way. Whether those constituents agree is an open question, and complaints about tuition have led a growing number of schools to offer rebates.

It is still possible that the frantic planning will come to naught. Almost daily, universities that had released detailed plans for in-person classes this semester have reversed themselves and said they will go almost entirely online. On Friday, the University of Pennsylvania became the latest, announcing that almost all undergraduate classes would be taught online and that undergraduates returning to Philadelphia, regardless of whether they were living on or off campus, would have to take a minimum of two Covid tests to participate in any Penn activities this fall.

“We have learned how to close safely,” Hiram Chodosh, president of Claremont McKenna College, a liberal arts school in Claremont, Calif., said. “But the big question now is, can we open safely?”

Testing capacity, a problem in communities throughout the country, varies widely among schools and could play a major role in whether they can remain open during an outbreak.

Big schools, from Syracuse University to the University of California, San Diego, that have connections to labs, health programs or medical schools say they are capable of processing large numbers of Covid tests in 24 to 48 hours.

In a typical big-school plan, the University of California, Berkeley, will test all residentialstudents within 24 hours of their arrival, for free, using either a standard nasal swab or a saliva test being developed by an internationally renowned genomics research lab on campus. Students will subsequently be sequestered for 7 to 10 days, leaving their single dorm rooms only to go (masked) to the bathroom or to pick up a meal from a central location in the building or outside, then retested. If they test positive, they’ll be isolated in a special dorm. (Some schools hope to create supportive communities, along the lines of an old-fashioned TB sanitarium, for students who test positive.) After that, everyone living on campus will be tested regularly, twice a month, if the spit test proves to be accurate enough.

But little Cornell College in Iowa, with only 1,000 students, is not doing universal testing on arrival, believing that it would give a false sense of security because of the incubation period. The school will be doing randomized rapid testing of 3 percent of its asymptomatic students per week through its health center, which will take just a few minutes to get results. It will reserve the more sophisticated testing, with the help of the county health department, for students who show symptoms. Other small schools in similar situations are finding themselves at the mercy of private labs that can take days to deliver results, making results almost meaningless.

But even some big schools are worried about testing backlogs. “If we have to wait days for a result,” said Michael Haynie, Syracuse’s vice chancellor of Strategic Initiatives and Innovation, “the quarantine requirements will overwhelm us before we even get started.”

Alison Byerly, president of Lafayette College, in Easton, Pa., cited worries about testing supplies as a reason to shift all classes online, and to ask most students to study from home.


Cost is an issue. Delaware State University, an historically black college, is among several that have enlisted the nonprofit Testing for America and the Thurgood Marshall College Fund, among others, to help finance its testing program.

So is personal freedom. Despite Florida’s high infection rate, the University of Florida has declined to force students to be tested, worrying some local officials and residents in Gainesville who fear that students could cause an outbreak in the city. Although Florida has among the highest per capita rates of infection in the country, the university is mandating testing only for athletes, those who report Covid-19 symptoms and a few other exceptions. “The Gator Nation will not be deterred,” says the school’s reopening plan.

“We’re a public institution, so constitutional considerations come into play in terms of what we require — and how we will be able to enforce that requirement,” said Ken Garcia, a campus spokesman, in an email. And testing backlogs are a major issue, university officials said in a university webcast.

Equally daunting is the task of regulating the behavior of an age group known for its risk-taking behavior.

Many schools have adopted social compacts and behavior codes. Masks are a key part of almost every code, to be worn except in situations like brushing teeth, walking alone outside, or being alone in a dorm room.

Most ban partying or socializing outside “social pods” — the small groups of students that some colleges are assigning students to, usually based on their dorms. Penalties for code violations range from being kicked out of class and counseled, to eviction from campus housing and expulsion.

The word “sex” is not mentioned in the typical behavior code. Some colleges may try to prohibit overnight visits in dorms, and many are stressing the obvious risks intimate contact poses of spreading the virus. But most administrators seem to believe that a rule banning sex is unrealistic, and are quietly hoping that students will use common sense and refrain from, say, having it with people outside their pod.The Coronavirus Outbreak ›

“I think at some point, if you treat young people like adults, they are going to act like adults,” Gordon Gee, the president of West Virginia University, said. “In the end, we’re not going to patrol every aspect of their lives.”

Or, as one official at another college, put it: “Could there be love in the pod? I guess so.”

The behavior codes generally apply both on and off campus, though they are clearly harder to enforce off-campus, and some students say that they immediately began looking for off-campus housing when they realized where rules would be strictly supervised.

The rules of local governments also apply.

“In Berkeley, indoor gatherings which would constitute a party or are outside of your social pod are forbidden,” Dan Mogulof, a spokesman for the university, said. “So we are and are going to remain consistent with what the city’s rules are, and we have to run everything through them.”

But students say social pods, especially when assigned by administrators, could quickly fracture if one or two students have a falling out.

West Virginia University has persuaded the governor to shut down bars serving students at its Morgantown campus after a Covid outbreak in the area, Mr. Gee said. It has been in effect for about two weeks, and he would like to renew it.

“Bars get people together in small places, and they cause these kids to really really, really get too damn close to each other,” Mr. Gee said.

Travel restrictions are also common. In an email to students at the University of Pennsylvania’s Wharton School two weeks ago, before the school went mainly online, Maryellen Reilly, deputy vice dean, said that students would be expected to limit all unnecessary travel.

“Does this mean that if your spouse or partner lives in D.C. or N.Y. that you can’t go visit for the weekend?,” her email said. “Unfortunately, yes. The risk of bringing germs back and forth is too great — this also means we ask that you don’t have visitors who could be traveling with the virus.”

Already some students are pushing back against codes of conduct and choosing either to skip the semester or live off-campus, where they can control their own environment.

Maria Gray, a junior at Bates College in Maine, was horrified when she paged through enrollment documents and found that she was being asked to sign a legal document with her digital PIN. “I acknowledge and agree that by committing to attend Bates College as an on-campus residential student, I am voluntarily assuming any and all risks,” the statement said, ending with a warning that the outcome of getting sick with Covid-19 could be “disability, or even death.”

That document was scary enough. But then on Friday, the school sent her an email saying that students could have to evacuate campus within 24-48 hours if there were an outbreak, and to bring only what they could easily pack. That made a closing seem inevitable.

“I have faith in people to be responsible and understand the stakes,” said Ms. Gray, who now plans to study online at her home in Portland, Ore. “But also, this shouldn’t be a life or death thing. The stakes just got really high really fast.”

Your Coronavirus Antibodies Are Disappearing. Should You Care?

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Your blood carries the memory of every pathogen you’ve ever encountered. If you’ve been infected with the coronavirus, your body most likely remembers that, too.

Antibodies are the legacy of that encounter. Why, then, have so many people stricken by the virus discovered that they don’t seem to have antibodies?

Blame the tests.

Most commercial antibody tests offer crude yes-no answers. The tests are notorious for delivering false positives — results indicating that someone has antibodies when he or she does not.

But the volume of coronavirus antibodies drops sharply once the acute illness ends. Now it is increasingly clear that these tests may also produce false-negative results, missing antibodies to the coronavirus that are present at low levels.

Moreover, some tests — including those made by Abbott and Roche and offered by Quest Diagnostics and LabCorp — are designed to detect a subtype of antibodies that doesn’t confer immunity and may wane even faster than the kind that can destroy the virus.

What that means is that declining antibodies, as shown by commercial tests, don’t necessarily mean declining immunity, several experts said. Long-term surveys of antibodies, intended to assess how widely the coronavirus has spread, may also underestimate the true prevalence.

“We’re learning a lot about how antibodies change over time,” said Dr. Fiona Havers, a medical epidemiologist who has led such surveys for the Centers for Disease Control and Prevention.

If the narrative on immunity to the coronavirus has seemed to shift constantly, it’s in part because the virus was a stranger to scientists. But it’s increasingly clear that this virus behaves much like any other.

This is how immunity to viruses generally works: The initial encounter with a pathogen — typically in childhood — surprises the body. The resulting illness can be mild or severe, depending on the dose of the virus and the child’s health, access to health care and genetics.

A mild illness may trigger production of only a few antibodies, and a severe one many more. The vast majority of people who become infected with the coronavirus have few to no symptoms, many experts believe, and those people may produce a milder immune response.

But even a minor infection is often enough to teach the body to recognize the intruder.

After the battle ends, balloon-like cells that live in the bone marrow steadily pump out a small number of specialized assassins. The next time — and every time after that — that the body comes across the virus, those cells can mass-produce antibodies within hours.

The mnemonic response grows stronger with every encounter. It’s one of the great miracles of the human body.

“Whatever your level is today, if you get infected, your antibody titers are going to go way up,” said Dr. Michael Mina, an immunologist at Harvard University, referring to the levels of antibodies in the blood. “The virus will never even have a chance the second time around.”

A single drop of blood contains billions of antibodies, all lying in wait for their specific targets. Sometimes, as may be the case for antibodies to the coronavirus, there are too few to get a positive signal on a test — but that does not mean the person tested has no immunity to the virus.

“Even if their antibodies wane below the limits of detection of our instruments, it doesn’t mean their ‘memory’ is gone,” Dr. Mina said.

A small number of people may not produce any antibodies to the coronavirus. But even in that unlikely event, they will have so-called cellular immunity, which includes T cells that learn to identify and destroy the virus. Virtually everyone infected with the coronavirus seems to develop T-cell responses, according to several recent studies.

“This means that even if the antibody titer is low, those people who are previously infected may have a good enough T-cell response that can provide protection,” said Akiko Iwasaki, an immunologist at Yale University.

T cells are harder to detect and to study, however, so when it comes to immunity, antibodies have received all of the attention. The coronavirus carries several antigens — proteins or pieces of a protein — that can provoke the body into producing antibodies.

The most powerful antibodies recognize a piece of the coronavirus’s spike protein, the receptor binding domain, or R.B.D. That is the part of the virus that docks onto human cells. Antibodies that recognize the R.B.D. can neutralize the virus and prevent infection.

But the Roche and Abbott tests that are now widely available — and several others authorized by the Food and Drug Administration — instead look for antibodies to a protein called the nucleocapsid, or N, that is bound up with the virus’s genetic material.

Some scientists were stunned to hear of this choice.

“God, I did not realize that — that’s crazy,” said Angela Rasmussen, a virologist at Columbia University in New York. “It’s kind of puzzling to design a test that’s not looking for what’s thought to be the major antigen.”

The N protein is plentiful in the blood, and testing for antibodies to it produces a swifter, brighter signal than testing for antibodies to the spike protein. Because antibody tests are used to detect past infection, however, manufacturers are not required to prove that the antibodies their tests seek are those that actually confer protection against the virus.

Officials at the Food and Drug Administration did not respond to requests for comment on whether the two tests target the appropriate antibodies.

There’s another wrinkle to the story. Some reports now suggest that antibodies to the viral nucleocapsid may decline faster than those to R.B.D. or to the entire spike — the really effective ones.

“The majority of people are getting tested for anti-N antibody, which does tend to wane more rapidly — and so, you know, it may be not the most suitable test for looking at neutralizing capacity,” Dr. Iwasaki said.The Coronavirus Outbreak ›

Frequently Asked Questions

Updated July 27, 2020

  • Should I refinance my mortgage?
    • It could be a good idea, because mortgage rates have never been lower. Refinancing requests have pushed mortgage applications to some of the highest levels since 2008, so be prepared to get in line. But defaults are also up, so if you’re thinking about buying a home, be aware that some lenders have tightened their standards.
  • What is school going to look like in September?
    • It is unlikely that many schools will return to a normal schedule this fall, requiring the grind of online learningmakeshift child care and stunted workdays to continue. California’s two largest public school districts — Los Angeles and San Diego — said on July 13, that instruction will be remote-only in the fall, citing concerns that surging coronavirus infections in their areas pose too dire a risk for students and teachers. Together, the two districts enroll some 825,000 students. They are the largest in the country so far to abandon plans for even a partial physical return to classrooms when they reopen in August. For other districts, the solution won’t be an all-or-nothing approach. Many systems, including the nation’s largest, New York City, are devising hybrid plans that involve spending some days in classrooms and other days online. There’s no national policy on this yet, so check with your municipal school system regularly to see what is happening in your community.
  • Is the coronavirus airborne?
  • What are the symptoms of coronavirus?
  • Does asymptomatic transmission of Covid-19 happen?
    • So far, the evidence seems to show it does. A widely cited paper published in April suggests that people are most infectious about two days before the onset of coronavirus symptoms and estimated that 44 percent of new infections were a result of transmission from people who were not yet showing symptoms. Recently, a top expert at the World Health Organization stated that transmission of the coronavirus by people who did not have symptoms was “very rare,” but she later walked back that statement.

In the United States, millions of people have taken the Roche and Abbott tests. LabCorp alone has performed more than two million antibody tests made by the two manufacturers.

Quest relies on tests made by Abbott, Ortho Clinical and Euroimmun. Quest declined to reveal what proportion of the 2.7 million tests it has deployed so far were made by Abbott.

Dr. Jonathan Berz, a physician in Boston, tested positive for the virus in early April but felt fine, apart from a sore throat. His wife was sicker, and despite several negative diagnostic tests, she remained ill for weeks.

“Initially, we felt as a family that, ‘Oh wow, we got sick, unfortunately,’” Dr. Berz said. “But the good side of that is that we’re going to have immunity.’”

In early June, the couple and their two children took Abbott antibody tests processed by Quest. All four turned up negative. Even though Dr. Berz knew that immunity is complex and that T cells also play a role, he was disappointed.

As a doctor in a Covid-19 clinic, he had always acted as though he was at risk for infection. But after seeing the antibody results, he said, “my level of anxiety just increased.”

A spokeswoman at Abbott said the test had 100 percent sensitivity 17 days after symptoms began but did not provide information about sensitivity beyond that time.

Dr. Beatus Ofenloch-Haehnle, who heads immunoassay research at Roche, defended the company’s antibody test. His team has tracked N antibodies in 130 people who had mild to no symptoms and has not yet seen a decline, he said.

“There is some fluctuation, but no waning at all,” he said. “We have a lot of data, and we do not rely anymore on theory.” The N antibody can be a decent proxy for immunity, Dr. Ofenloch-Haehnle added.

He also pointed to a study by Public Health England that suggested that the Abbott and Roche tests seemed to perform well up to 73 days after symptom onset. “I think we should be careful to jump to conclusions too soon,” he said.

Other experts also urged caution. Without more information about what antibody testing results mean, they said, people should do as Dr. Berz did: Act as though they do not have immunity.

There is no definitive information as yet on what levels of antibodies are needed for immunity or how long that protection might last. “I think we’re getting closer and closer to that knowledge,” Dr. Iwasaki said.

After Early Success, South Africa Buckles Under Coronavirus Surge

JOHANNESBURG—Lauded in the early stages of the pandemic for taking decisive steps to limit Covid-19 infections, South Africa is now battling one of the world’s fastest-growing coronavirus outbreaks that is overpowering hospitals and has caused a dramatic increase in deaths.

Public schools, which partially reopened in early June, will close for four weeks starting Monday, as the country enters a peak-infection period that models suggest could stretch into September. Africa’s most developed economy now has confirmed 434,200 cases of Covid-19, the fifth-highest toll in the world behind the more-populous U.S., Brazil, India and Russia.

“The coronavirus storm has indeed arrived,” President Cyril Ramaphosa said Thursday, in his 11th address to the nation since the first case of coronavirus was identified in early March. “As a country, we have never before faced such a severe crisis or such an abrupt disruption of our lives.”

South Africa’s sharp increase in hospitalizations and deaths in recent weeks followed the June reopening of large parts of the economy. It is a Catch-22 that spotlights how economic realities are restricting politicians’ ability to act against the pandemic in low- and middle-income countries that can’t afford the large stimulus packages adopted by richer nations. In April and May, the World Health Organization and other public-health officials praised Mr. Ramaphosa for successfully keeping transmissions at bay through one of the world’s strictest lockdowns.Weekly deaths in South AfricaSource: South African Medical Research Council(deaths, predictions); Johns Hopkins University CSSE(Covid-19 deaths).deathsWeekly deathsWeekly confirmed deaths by Covid-19Prediction bounds, upper and lowerFeb. 2020July02,5005,0007,50010,00012,50015,000

The real number of coronavirus infections is likely to be much higher than the official count. South Africa’s hardest-hit province, Gauteng, which is home to its economic and political capitals Johannesburg and Pretoria, said Friday that it has now moved to testing only patients in need of hospitalization and medical staff. Nationwide, nearly one-fourth of tests are coming back positive.

On Wednesday, the South African Medical Research Council said that between May 6 and July 14 it counted 17,090 extra deaths compared with previous years—an increase of 59%. That is far above the 6,655 people that the health ministry says had died of the disease.

Debbie Bradshaw, the council’s chief specialist scientist, said excess deaths were increasing much faster than during the HIV/AIDS epidemic that ravaged South Africa in the late 90s and early 2000s. “We’re reliving those years in weeks now,” she said.

Doctors working in public hospitals in Johannesburg and Cape Town, South Africa’s two largest cities, say they are running out of beds and have to split oxygen ports so that one tank can support two patients. In Eastern Cape, the country’s poorest province, nurses and cleaning staff have gone on strike over a lack of protective gear, leaving patients in one maternity hospital to give birth on squalid floors, according to a doctor there.

“Our hospitals can’t cope with this burden of disease,” said one doctor at Chris Hani Baragwanath Hospital in Johannesburg’s Soweto township, which now has the highest number of active infections in the country. “The system wasn’t designed to have this degree of stress.”

At Baragwanath, which with 3,200 beds is Africa’s largest hospital, psychiatrists have been drafted to help care for Covid-19 patients and doctors and nurses are given just five N-95 masks—which filter out small, virus-carrying particles—a month, the doctor said. Some staff buy their own protective gear, because they don’t trust that masks supplied by the hospital meet regulatory standards, the doctor said.

A spokesman at Baragwanath hospital referred a request for comment to the provincial health department. A spokeswoman for the department said tents have been set up for patients awaiting their test results and to isolate those with mild symptoms in an effort to decongest hospitals. She also said that the province had sufficient supplies of protective equipment and would contact Baragwanath management to ensure the hospital had what it needed.

Mr. Ramaphosa’s government now has to flatten the infection curve while trying to contain further damage to an economy that was in recession and battling a 30% unemployment rate before the pandemic reached its borders.

The lockdown—which banned outside exercise and the sale of nonessential goods, including alcohol and cigarettes—has taken a huge economic toll. Retail sales plunged by 50% in April, according to figures released this week. The central bank has said that gross domestic product collapsed by an annualized 33% between April and June. For the full year, the bank expects the economy to shrink by 7.3%, the largest contraction since the end of apartheid in 1994.

A recent survey by the Southern Africa Labour and Development Research Unit, a group of academics, found that more than a quarter of workers lost their income in April, while nearly half of households ran out of money to buy food.

In June, Mr. Ramaphosa opened up large parts of the economy even though infections were rising, especially in poor areas where living conditions make social distancing impossible. Hairdressers, beauty salons and restaurants were allowed to reopen—including indoor dining—as were cinemas and theaters, albeit with capacity limitations.

Since then, Mr. Ramaphosa has been forced to again tighten some regulations. Earlier this month, with alcohol-related trauma patients taking up hospital beds, he reimposed a ban on alcohol sales. The four-week school closure, was announced after several thousand students and teachers were found to have the virus. In Gauteng province alone, more than 3,000 students, teachers and support staff tested positive and 12 teachers have died of Covid-19.

Amid the human suffering, several high-profile cases of alleged theft of funds earmarked for medical supplies, food parcels and unemployment benefits have made headlines. South Africans, accustomed to stories of official corruption during the scandal-hit presidency of Mr. Ramaphosa’s predecessor Jacob Zuma, have been joking darkly about “Covidpreneurs.” Mr. Ramaphosa said at least 36 cases of alleged fraud linked to Covid-19 funds are being investigated.

Malcom Moyo, a 32-year-old father of three, said his family had no savings to fall back on when he lost his job as a waiter at the end of March. “I felt helpless because I needed food and winter clothes for my girls,” he said. He said he’s going back to work next week—at reduced hours.

Who Is Immune to the Coronavirus?

Among the many uncertainties that remain about Covid-19 is how the human immune system responds to infection and what that means for the spread of the disease. Immunity after any infection can range from lifelong and complete to nearly nonexistent. So far, however, only the first glimmers of data are available about immunity to SARS-CoV-2, the coronavirus that causes Covid-19.

What can scientists, and the decision makers who rely on science to inform policies, do in such a situation? The best approach is to construct a conceptual model — a set of assumptions about how immunity might work — based on current knowledge of the immune system and information about related viruses, and then identify how each aspect of that model might be wrong, how one would know and what the implications would be. Next, scientists should set out to work to improve this understanding with observation and experiment.

The ideal scenario — once infected, a person is completely immune for life — is correct for a number of infections. The Danish physician Peter Panum famously figured this out for measles when he visited the Faroe Islands (between Scotland and Iceland) during an outbreak in 1846 and found that residents over 65 who had been alive during a previous outbreak in 1781 were protected. This striking observation helped launch the fields of immunology and epidemiology — and ever since, as in many other disciplines, the scientific community has learned that often things are more complicated.

One example of “more complicated” is immunity to coronaviruses, a large group of viruses that sometimes jump from animal hosts to humans: SARS-CoV-2 is the third major coronavirus epidemic to affect humans in recent times, after the SARS outbreak of 2002-3 and the MERS outbreak that started in 2012.

Much of our understanding of coronavirus immunity comes not from SARS or MERS, which have infected comparatively small numbers of people, but from the coronaviruses that spread every year causing respiratory infections ranging from a common cold to pneumonia. In two separate studies, researchers infected human volunteers with a seasonal coronavirus and about a year later inoculated them with the same or a similar virus to observe whether they had acquired immunity.

In the first study, researchers selected 18 volunteers who developed colds after they were inoculated — or “challenged,” as the term goes — with one strain of coronavirus in 1977 or 1978. Six of the subjects were re-challenged a year later with the same strain, and none was infected, presumably thanks to protection acquired with their immune response to the first infection. The other 12 volunteers were exposed to a slightly different strain of coronavirus a year later, and their protection to that was only partial.

In another study published in 1990, 15 volunteers were inoculated with a coronavirus; 10 were infected. Fourteen returned for another inoculation with the same strain a year later: They displayed less severe symptoms and their bodies produced less of the virus than after the initial challenge, especially those who had shown a strong immune response the first time around.

No such human-challenge experiments have been conducted to study immunity to SARS and MERS. But measurements of antibodies in the blood of people who have survived those infections suggest that these defenses persist for some time: two years for SARS, according to one study, and almost three years for MERS, according to another one. However, the neutralizing ability of these antibodies — a measure of how well they inhibit virus replication — was already declining during the study periods.

These studies form the basis for an educated guess at what might happen with Covid-19 patients. After being infected with SARS-CoV-2, most individuals will have an immune response, some better than others. That response, it may be assumed, will offer some protection over the medium term — at least a year — and then its effectiveness might decline.

Other evidence supports this model. A recent peer-reviewed study led by a team from Erasmus University, in the Netherlands, published data from 12 patients showing that they had developedantibodies after infection with SARS-CoV-2. Several of my colleagues and students and I have statistically analyzedthousands of seasonal coronavirus cases in the United States and used a mathematical model to infer that immunity over a year or so is likely for the two seasonal coronaviruses most closely related to SARS-CoV-2 — an indication perhaps of how immunity to SARS-CoV-2 itself might also behave.

If it is true that infection creates immunity in most or all individuals and that the protection lasts a year or more, then the infection of increasing numbers of people in any given population will lead to the buildup of so-called herd immunity. As more and more people become immune to the virus, an infected individual has less and less chance of coming into contact with a person susceptible to infection. Eventually, herd immunity becomes pervasive enough that an infected person on average infects less than one other person; at that point, the number of cases starts to go down. If herd immunity is widespread enough, then even in the absence of measures designed to slow transmission, the virus will be contained — at least until immunity wanes or enough new people susceptible to infection are born.

At the moment, cases of Covid-19 have been undercounted because of limited testing — perhaps by a factor of 10 in some places, like Italy as of late last month. If the undercounting is around this level in other countries as well, then a majority of the population in much (if not all) of the world still is susceptible to infection, and herd immunity is a minor phenomenon right now. The long-term control of the virus depends on getting a majority of people to become immune, through infection and recovery or through vaccination — how large a majority depends on yet other parameters of the infection that remain unknown.

One concern has to do with the possibility of reinfection. South Korea’s Centers for Disease Control and Prevention recently reported that 91 patients who had been infected with SARS-CoV-2 and then tested negative for the virus later tested positive again. If some of these cases were indeed reinfections, they would cast doubt on the strength of the immunity the patients had developed.

An alternative possibility, which many scientists think is more likely, is that these patients had a false negative test in the middle of an ongoing infection, or that the infection had temporarily subsided and then re-emerged. South Korea’s C.D.C. is now working to assess the merit of all these explanations. As with other diseases for which it can be difficult to distinguish a new infection from a new flare-up of an old infection — like tuberculosis — the issue might be resolved by comparing the viral genome sequence from the first and the second periods of infection.

For now, it is reasonable to assume that only a minority of the world’s population is immune to SARS-CoV-2, even in hard-hit areas. How could this tentative picture evolve as better data come in? Early hints suggest that it could change in either direction.

It is possible that many more cases of Covid-19 have occurred than have been reported, even after accounting for limited testing. Onerecent study (not yet peer-reviewed) suggests that rather than, say, 10 times the number of detected cases, the United States may really have more like 100, or even 1,000, times the official number. This estimate is an indirect inference from statistical correlations. In emergencies, such indirect assessments can be early evidence of an important finding — or statistical flukes. But if this one is correct, then herd immunity to SARS-CoV-2 could be building faster than the commonly reported figures suggest.

Then again, another recent study (also not yet peer-reviewed) suggests that not every case of infection may be contributing to herd immunity. Of 175 Chinese patients with mild symptoms of Covid-19, 70 percent developed strong antibody responses, but about 25 percent developed a low response and about 5 percent developed no detectable response at all. Mild illness, in other words, might not always build up protection. Similarly, it will be important to study the immune responses of people with asymptomatic cases of SARS-CoV-2 infection to determine whether symptoms, and their severity, predict whether a person becomes immune.

The balance between these uncertainties will become clearer when more serologic surveys, or blood tests for antibodies, are conducted on large numbers of people. Such studies are beginningand should show results soon. Of course, much will depend on how sensitive and specific the various tests are: how well they spot SARS-CoV-2 antibodies when those are present and if they can avoid spurious signals from antibodies to related viruses.

Even more challenging will be understanding what an immune response means for an individual’s risk of getting reinfected and their contagiousness to others. Based on the volunteer experiments with seasonal coronaviruses and the antibody-persistence studies for SARS and MERS, one might expect a strong immune response to SARS-CoV-2 to protect completely against reinfection and a weaker one to protect against severe infection and so still slow the virus’s spread.

But designing valid epidemiologic studies to figure all of this out is not easy — many scientists, including several teams of which I’m a part — are working on the issue right now. One difficulty is that people with a prior infection might differ from people who haven’t yet been infected in many other ways that could alter their future risk of infection. Parsing the role of prior exposure from other risk factors is an example of the classic problem epidemiologists call “confounding” — and it is made maddeningly harder today by the fast-changing conditions of the still-spreading SARS-CoV-2 pandemic.

And yet getting a handle on this fast is extremely important: not only to estimate the extent of herd immunity, but also to figure out whether some people can re-enter society safely, without becoming infected again or serving as a vector, and spreading the virus to others. Central to this effort will be figuring out how long protection lasts.

With time, other aspects of immunity will become clearer as well.Experimental and statistical evidence suggests that infection with one coronavirus can offer some degree of immunity against distinct but related coronaviruses. Whether some people are at greater or lesser risk of infection with SARS-CoV-2 because of a prior history of exposure to coronaviruses is an open question.

And then there is the question of immune enhancement: Through a variety of mechanisms, immunity to a coronavirus can in some instances exacerbate an infection rather than prevent or mitigate it. This troublesome phenomenon is best known in another group of viruses, the flaviviruses, and may explain why administering a vaccine against dengue fever, a flavivirus infection, can sometimesmake the disease worse.

Such mechanisms are still being studied for coronaviruses, but concern that they might be at play is one of the obstacles that have slowed the development of experimental vaccines against SARSand MERS. Guarding against enhancement will also be one of the biggest challenges facing scientists trying to develop vaccines for Covid-19. The good news is that research on SARS and MERS hasbegun to clarify how enhancement works, suggesting ways around it, and an extraordinary range of efforts is underway to find a vaccine for Covid-19, using multiple approaches.

More science on almost every aspect of this new virus is needed, but in this pandemic, as with previous ones, decisions with great consequences must be made before definitive data are in. Given this urgency, the traditional scientific method — formulating informed hypotheses and testing them by experiments and careful epidemiology — is hyper-accelerated. Given the public’s attention, that work is unusually on display. In these difficult circumstances, I can only hope that this article will seem out of date very shortly — as much more is soon discovered about the coronavirus than is known right now.

Big Tobacco Joins Race for Coronavirus Vaccine

The race to find a vaccine for the novel coronavirus has an unlikely new entrant: tobacco companies.

Lucky Strike owner British American Tobacco PLC is developing a potential vaccine grown in tobacco plants, while Medicago Inc., a biotech firm partly owned by Marlboro maker Philip Morris International Inc., is pursuing a similar effort.

The initiatives join dozens already under way at drug companies, universities and other research institutions across the globe seeking a vaccine or treatment for Covid-19, the sometimes fatal disease caused by the new coronavirus.

BAT this week said its Kentucky BioProcessing subsidiary had identified an antigen—a protein it hopes will stimulate an immune response to the virus—and was reproducing it in tobacco plants. If early tests are successful, human trials could start by June, it said. The unit previously manufactured a drug for Ebola, which was only moderately successful, using a similar method.

“I appreciate that we aren’t a conventional vaccine player,” said David O’Reilly, BAT’s head of scientific research. “I’d ask people to try to look beyond that and look at our technology at face value.”

BAT and Medicago are playing in an increasingly crowded field.Johnson & Johnson on Monday said it had made progress on a vaccine that could be ready in early 2021. Moderna Inc. has begun human trials for a vaccine using a novel approach that relies on the virus’s messenger RNA, a type of genetic material. Sanofi SA of France has begun work on a similar approach.

While there is no indication that BAT’s effort has a greater chance of working than others, using tobacco plants to cultivate a vaccine could be cheaper and faster to scale up than traditional methods, which often use chicken eggs or other animal cells.

Tobacco is well-researched, cheap to grow and can yield large amounts of vaccine quickly. Tobacco-based vaccines also don’t need refrigeration, simplifying the supply chain. Scientists say these factors could reduce production time to weeks instead of months and make vaccines as much as 40% cheaper to produce than using animal cells.

The speed and scale at which a vaccine or treatment can be brought to market has become increasingly important as the virus spreads, claiming thousands more lives every day.

The success of BAT’s approach—like all vaccine research efforts—will depend on whether its product elicits the appropriate immune response to protect against future infection with the new coronavirus, said Beate Kampmann, director of the London School of Hygiene and Tropical Medicine’s Vaccine Centre. “What’s promising is the scalability,” she said.

Plant-based vaccines are generally made by infecting a plant—sometimes by dipping leaves in a liquid—with a bacteria that contains the genetic sequence of the desired protein. The bacteria hijacks the plant cells to make large quantities of the protein in the space of about a week, which is then harvested from the plant and purified into a raw material for the vaccine.

Advocates say plant-based vaccines can more quickly adapt to mutations in viruses and lack pathogens harmful to humans that might be present in animal methods.

However, while tobacco-based vaccines have previously been developedfor avian flu and Norwalk norovirus—also known as cruise-ship virus—none are commercially available.

That is partly because much of this work is conducted by small laboratories that struggle to attract the industry funding needed for large clinical trials and large-scale manufacture, said Ed Rybicki, director of the Biopharming Research Unit at the University of Cape Town in South Africa.

“Academia is trying these things on a small scale,” said Dr. Rybicki. “We have to get industry to join us.” He has received funding from Medicago.

Before coronavirus hit, BAT was working on a tobacco-based influenza vaccine, which is due to be tested on humans next month.

BAT said tests to check if its vaccine stimulates the production of antibodies against Covid-19 will take around four weeks. It then plans to test the vaccine in animals deliberately exposed to the virus but needs to find a partner first. BAT is using fast-growing, Australian dwarf tobacco plants that aren’t used in its cigarettes, and says it isn’t looking to turn a profit from its potential coronavirus vaccine.

When the vaccine will be available partly depends on whether regulators agree to accelerate clinical studies or grant emergency authorization, the company said. It is also seeking partners to help fund large-scale clinical trials and expand manufacturing capacity.

BAT plans to pre-emptively ramp up production at its site in Kentucky and thinks it could make between one million and three million doses a week by June. It is also exploring production in the U.K.

Medicago, which is one-third owned by Philip Morris, is using a virus-like particle grown in a close relative of the tobacco plant. It is aiming to begin human tests this summer and estimates it would take 12 to 18 months to release the vaccine, although this could be sooner if regulators accelerate the approval process, said Chief Executive Bruce Clark. Virus-like particles mimic viruses, enabling the body’s immune system to recognize them and create an immune response, while lacking the core genetic material that makes them harmful and infectious.

The Quebec City-based company has already submitted a plant-based flu vaccine for approval from Health Canada, which Mr. Clark hopes could make the process easier for its coronavirus offering. The provincial government of Quebec is providing $7 million toward the coronavirus vaccine, which Mr. Clark says will be priced to be widely accessible.

The lower prices for tobacco-based vaccines could be crucial for low- and middle-income countries, said Julian Ma, director of the Institute for Infection and Immunity at St. George’s Hospital Medical School in London. “This is important for a disease which is spreading to every country in the world,” he said.