Read the full interview HERE

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Early in the morning on April 5, 2020, an article appeared on the website Medium with the title “Covid-19 had us all fooled, but now we might have finally found its secret.” The article claimed that the pathology of COVID-19 was completely different from what public health authorities, such as the World Health Organization, had previously described. According to the author, COVID-19 strips the body’s hemoglobin of iron, preventing red blood cells from delivering oxygen and damaging the lungs in the process. It also claimed to explain why hydroxychloroquine, an experimental treatment often hyped by President Trump, should be effective.

The article was published under a pseudonym—libertymavenstock—but the associated account was linked to a Chicagoland man working in finance, with no medical expertise. (His father is a retired M.D., and in a follow-up note posted on a blog called “Small Dead Animals,” the author claimed that the original article was a collaboration between the two of them.) Although it was not cited, the claims were apparently based on a single scientific article that has not yet undergone peer-review or been accepted for publication, along with “anecdotal evidence” scraped from social media.1

While Medium allows anyone to post on their site and does not attempt to fact-check content, this article remained up for less than 24 hours before it was removed for violating Medium’s COVID-19 content policy. Removing the article, though, has not stopped it from making a splash. The original text continues to circulate widely on social media, with users tweeting or sharing versions archived by the Wayback Machine and re-published by a right-wing blog. As of April 12, the article had been tweeted thousands of times.

There is a pandemic of misinformation about COVID-19 spreading on social media sites. Some of this misinformation takes well-understood forms: baseless rumors, intentional disinformation, and conspiracy theories. But much of it seems to have a different character. In recent months, claims with some scientific legitimacy have spread so far, so fast, that even if it later becomes clear they are false or unfounded, they cannot be laid to rest. Instead, they become information zombies, continuing to shamble on long after they should be dead.

It is not uncommon for media sources like Medium to retract articles or claims that turn out to be false or misleading. Neither are retractions limited to the popular press. In fact, they are common in the sciences, including the medical sciences. Every year, hundreds of papers are retracted, sometimes because of fraud, but more often due to genuine errors that invalidate study findings.2 (The blog Retraction Watch does an admirable job of tracking these.)

Reversing mistakes is a key part of the scientific process. Science proceeds in stops and starts. Given the inherent uncertainty in creating new knowledge, errors will be made, and have to be corrected. Even in cases where findings are not officially retracted, they are sometimes reversed— definitively shown to be false, and thus no longer valid pieces of scientific information.3

Researchers have found, however, that the process of retraction or reversal does not always work the way it should. Retracted papers are often cited long after problems are identified,4 sometimes at a rate comparable to that before retraction. And in the vast majority of these cases, the authors citing retracted findings treat them as valid.5 (It seems that many of these authors pull information directly from colleagues’ papers, and trust that it is current without actually checking.) Likewise, medical researchers have bemoaned the fact that reversals in practice sometimes move at a glacial pace, with doctors continuing to use contraindicated therapies even though better practices are available.6

For example, in 2010, the anesthesiologist Scott Reuben was convicted of health care fraud for fabricating data and publishing it without having performed the reported research. Twenty-one of Reuben’s articles were ultimately retracted. And yet, an investigation four years later found half of these articles were still consistently cited, and that only one-fourth of these citations mentioned that the original work was fraudulent.7 Given that Reuben’s work focused on the use of anesthetics, this failure of retraction is seriously disturbing.

Claims with some scientific legitimacy continue to shamble on long after they should be dead.

But why don’t scientific retractions always work? At the heart of the matter lies the fact that information takes on a life of its own. Facts, beliefs, and ideas are transmitted socially, from person to person to person. This means that the originator of an idea soon loses control over it. In an age of instant reporting and social media, this can happen at lightning speed.

The first models of the social spread of information were actually epidemiological models, developed to track the spread of disease. (Yes, these are the very same models now being used to predict the spread of COVID-19.) These models treat individuals as nodes in a network and suppose that information (or disease) can propagate between connected nodes.

Recently, one of us, along with co-authors Travis LaCroix and Anders Geil, repurposed these models to think specifically about failures of retraction and reversal.8 A general feature of retracted information, understood broadly, is that it is less catchy than novel information in the following way. People tend to care about reversals or retractions only when they have already heard the original, false claim. And they tend to share retractions only when those around them are continuing to spread the false claim. This means that retractions actually depend on the spread of false information.

We built a contagion model where novel ideas and retractions can spread from person to person, but where retractions only “infect” those who have already heard something false. Across many versions of this model, we find that while a false belief spreads quickly and indiscriminately, its retraction can only follow in the path of its spread, and typically fails to reach many individuals. To quote Mark Twain, “A lie can travel halfway around the world while the truth is putting on its shoes.” In these cases it’s because the truth can’t go anywhere until the lie has gotten there first.

Another problem for retractions and reversals is that it can be embarrassing to admit one was wrong, especially where false claims can have life or death consequences. While scientists are expected to regularly update their views under normal circumstances, under the heat of media and political scrutiny during a pandemic they too may be less willing to publicize reversals of opinion.

The COVID-19 pandemic has changed lives around the world at a startling speed—and scientists have raced to keep up. Academic journals, accustomed to a comparatively glacial pace of operations, have faced a torrent of new papers to evaluate and process, threatening to overwhelm a peer-review system built largely on volunteer work and the honor system.9 Meanwhile, an army of journalists and amateur epidemiologists scour preprint archives and university press releases for any whiff of the next big development in our understanding of the virus. This has created a perfect storm for information zombies—and although it also means erroneous work is quickly scrutinized and refuted, this often makes little difference to how those ideas spread.

Many examples of COVID-19 information zombies look like standard cases of retraction in science, only on steroids. They originate with journal articles written by credentialed scientists that are later retracted, or withdrawn after being refuted by colleagues. For instance, in a now-retracted paper, a team of biologists based in New Delhi, India, suggested that novel coronavirus shared some features with HIV and was likely engineered.10 It appeared on an online preprint archive, where scientists post articles before they have undergone peer review, on January 31; it was withdrawn only two days later, following intense critique of the methods employed and the interpretation of the results by scientists from around the world. Days later, a detailed analysis refuting the article was published in the peer-reviewed journal Emerging Microbes & Infections.11 But a month afterward, the retracted paper was still so widely discussed on social media and elsewhere that it had that highest Altmetric score—a measure of general engagement with scientific research—of any scientific article published or written in the previous eight years. Despite a thorough rejection of the research by the scientific community, the dead information keeps walking.

Other cases are more subtle. One major question with far-reaching implications for the future development of the pandemic is to what extent asymptomatic carriers are able to transmit the virus. The first article reporting on asymptomatic transmission was a letter published in the prestigious New England Journal of Medicine claiming that a traveler from China to Germany transmitted the disease to four Germans before her symptoms appeared.12 Within four days, Science reported that the article was flawed because the authors of the letter had not actually spoken with the Chinese traveler, and a follow-up phone call by public health authorities confirmed that she had had mild symptoms while visiting Germany after all.13 Even so, the article has subsequently been cited nearly 500 times according to Google Scholar, and has been tweeted nearly 10,000 times, according to Altmetric.

Media reporting on COVID-19 should be linked to authoritative sources that are updated as information changes.

Despite the follow-up reporting on this article’s questionable methods, the New England Journal of Medicine did not officially retract it. Instead, a week after publishing the letter, the journal added a supplemental appendix describing the progression of the patient’s symptoms while in Germany, leaving it to the reader to determine whether the patient’s mild early symptoms should truly count. Meanwhile, subsequent research14, 15 involving different cases has suggested that asymptomatic transmission may be possible after all—though as of April 13, the World Health Organization considers the risk of infection from asymptomatic carriers to be “very low.” It may turn out that transmission of the virus can occur before any symptoms appear, or while only mild symptoms are present, or even in patients who will never go on to present symptoms. Even untangling these questions is difficult, and the jury is still out on their answers. But the original basis for claims of confirmed asymptomatic transmission was invalid, and those sharing them are not typically aware of the fact.

Another widely discussed article, which claims that the antiviral drug hydroxychloroquine and the antibiotic azithromycin, when administered together, are effective treatments for COVID-19 has drawn enormous amounts of attention to these particular treatments, fueled in part by President Trump.16 These claims, too, may or may not turn out to be true—but the article with which they apparently originated has since received a statement of concern from its publisher, noting that its methodology was problematic. Again, we have a claim that rests on shoddy footing, but which is spreading much farther than the objections can.17 And in the meantime, the increased demand for these medications has led to dangerous shortages for patients who have an established need for them.18

The fast-paced and highly uncertain nature of research on COVID-19 has also created the possibility for different kinds of information zombies, which follow a similar pattern as retracted or refuted articles, but with different origins. There have been a number of widely discussed arguments to the effect that the true fatality rate associated with COVID-19 may be ten or even a hundred times lower than early estimates from the World Health Organization, which pegged the so-called “case fatality rate” (CFR)—the number of fatalities per detected case of COVID-19—at 3.4 percent.19-21

Some of these arguments have noted that the case fatality rate in certain countries with extensive testing, such as Iceland, Germany, and Norway, is substantially lower. References to the low CFR in these countries have continued to circulate on social media, even though the CFR in all of these locations has crept up over time. In the academic realm, John Ioannidis, a Stanford professor and epidemiologist, noted in an editorial, “The harms of exaggerated information and non‐evidence‐based measures,” published on March 19 in the European Journal of Clinical Investigation, that Germany’s CFR in early March was only 0.2 percent.21 But by mid-April it had climbed to 2.45 percent, far closer to the original WHO estimate. (Ioannidis has not updated the editorial to reflect the changing numbers.) Even Iceland, which has tested more extensively than any other nation, had a CFR of 0.47 percent on April 13, more than 4 times higher than it was a month ago. None of this means that the WHO figure was correct—but it does mean some arguments that it is wildly incorrect must be revisited.

What do we do about false claims that refuse to die? Especially when these claims have serious implications for decision-making in light of a global pandemic? To some degree, we have to accept that in a world with rapid information sharing on social media, information zombies will appear. Still, we must combat them. Science journals and science journalists rightly recognize that there is intense interest in COVID-19 and that the science is evolving rapidly. But that does not obviate the risks of spreading information that is not properly vetted or failing to emphasize when arguments depend on data that is very much in flux.

Wherever possible, media reporting on COVID-19 developments should be linked to authoritative sources of information that are updated as the information changes. The Oxford-based Centre for Evidence-Based Medicine maintains several pages that review the current evidence on rapidly evolving questions connected to COVID-19—including whether current data supports the use of hydroxychloroquine and the current best estimates for COVID-19 fatality rates. Authors and platforms seeking to keep the record straight should not just remove or revise now-false information, but should clearly state what has changed and why. Platforms such as Twitter should provide authors, especially scientists and members of the media, the ability to explain why Tweets that may be referenced elsewhere have been deleted. Scientific preprint archives should encourage authors to provide an overview of major changes when articles are revised.

And we should all become more active sharers of retraction. It may be embarrassing to shout one’s errors from the rooftops, but that is what scientists, journals, and responsible individuals must do to slay the information zombies haunting our social networks.

Cailin O’Connor and James Owen Weatherall are an associate professor and professor of logic and philosophy at the University of California, Irvine. They are coauthors of The Misinformation Age: How False Beliefs Spread.

Lead image: nazareno / Shutterstock

References

1. Liu, W. & Li, H. COVID-19 attacks the 1-beta chain of hemoglobin and captures the porphyrin to inhibit human heme metabolism. ChemRxiv (2020).

2. Wager, E. & Williams, P. Why and how do journals retract articles? An analysis of Medline retractions 1988-2008. Journal of Medical Ethics 37, 567-570 (2011).

3. Prasad, V., Gall, V., & Cifu, A. The frequency of medical reversal. Archives of Internal Medicine 171, 1675-1676 (2011).

4. Budd, J.M., Sievert, M., & Schultz, T.R. Phenomena of retraction: Reasons for retraction and citations to the publications. The Journal of the American Medical Association 280, 296-297 (1998).

5. Madlock-Brown, C.R. & Eichmann, D. The (lack of) impact of retraction on citation networks. Science and Engineering Ethics 21, 127-137 (2015).

6. Prasad, V. & Cifu, A. Medical reversal: Why we must raise the bar before adopting new technologies. Yale Journal of Biology and Medicine 84, 471-478 (2011).

7. Bornemann-Cimenti, H., Szilagyi, I.S., & Sandner-Kiesling, A. Perpetuation of retracted publications using the example of the Scott S. Reuben case: Incidences, reasons and possible improvements. Science and Engineering Ethics 22, 1063-1072 (2016).

8. LaCroix, T., Geil, A., & O’Connor, C. The dynamics of retraction in epistemic networks. Preprint. (2019).

9. Jarvis, C. Journals, peer reviewers cope with surge in COVID-19 publications. The Scientist (2020).

10. Pradhan, P., et al. Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag. bioRxiv (2020).

11. Xiao, C. HIV-1 did not contribute to the 2019-nCoV genome. Journal of Emerging Microbes and Infections 9, 378-381 (2020).

12. Rothe, C., et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. New England Journal of Medicine 382, 970-971 (2020).

13. Kupferschmidt, K. Study claiming new coronavirus can be transmitted by people without symptoms was flawed. Science (2020).

14. Hu, Z., et al. Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China. Science China Life Sciences (2020). Retrieved from doi: 10.1007/s11427-020-1661-4.

15. Bai, R., et al. Presumed asymptomatic carrier transmission of COVID-19. The Journal of the American Medical Association 323, 1406-1407 (2020).

16. Gautret, P., et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial. International Journal of Antimicrobial Agents (2020).

17. Ferner, R.E. & Aronson, J.K. Hydroxychloroquine for COVID-19: What do the clinical trials tell us? The Centre for Evidence-Based Medicine (2020).

18. The Arthritis Foundation. Hydroxychloroquine (Plaquenil) shortage causing concern. Arthritis.org (2020).

19. Oke, J. & Heneghan, C. Global COVID-19 case fatality rates. The Centre for Evidence-Based Medicine (2020).

20. Bendavid, E. & Bhattacharya, J. Is the coronavirus as deadly as they say? The Wall Street Journal (2020).

21. Ionnidis, J.P.A. Coronavirus disease 2019: The harms of exaggerated information and non-evidence-based measures. European Journal of Clinical Investigation 50, e13222 (2020).

It seems like people who get infected with SARS-CoV-2 retain immunity, but we can’t be sure how long that immunity will last. We still lack the testing capabilities to be certain.eamesBot / Shutterstock

This story was updated post-publication to include information from a study published on the preprint server medRxiv on April 17, 2020.

With more than half a million cases of COVID-19 in the United States1 and the number of deaths increasing daily, it remains unclear when and how we might return to some semblance of pre-pandemic life. This leaves many grappling with an important question: Do you become immune after SARS-CoV-2 infection? And, if so, how long might that immunity last?

In 2019, the virus SARS-CoV-2 jumped to a human host for the first time, causing the disease COVID-19. When you become infected with a new virus, your body does not possess the antibodies necessary to mount a targeted immune response. Antibodies, proteins belonging to the immunoglobulin family, consist of four chains of amino acids that form a characteristic Y-shaped structure. Antibodies are manufactured by the immune system to bind to antigens (viral proteins) to neutralize viral infectivity.

When you inhale an aerosolized droplet containing SARS-CoV-2, the virus encounters the cells of the mucous membrane lining the respiratory tract. If effective contact is made, the virus binds to a particular receptor on these cells called ACE-2. After binding ACE-2, a host enzyme is co-opted to cleave the virus’ surface protein, called the spike protein, allowing the virus to enter the cell.

It appears that individuals with COVID-19 do create neutralizing antibodies—the basis of immunity.

Within the first few hours of infection, the body’s first line of defense—the innate immune response—is activated. The innate immune response is non-specific. When a “foreign” molecule is detected, innate immune cells signal to other cells to alter their response or prepare to combat infection.

In the following days, the adaptive immune response is activated, which is more specific. The adaptive immune response will peak one to two weeks post-infection and consists of antibodies and specialized immune cells. It is called the “adaptive” immune response because of its ability to tailor the response to a specific pathogen. Antibodies can neutralize viral infectivity by preventing virus from binding to receptors, blocking cell entry, or causing virus particles to aggregate.2 Once an infection has resolved, some of these antibodies remain in the body as immunological memory to be recruited for protection in the case of reinfection. To be immune to a virus is to possess this immunological memory.

Many vaccines work by activating the adaptive immune response. Inactivated virus, viral protein, or some other construct specific to a particular virus are introduced into the body as vaccines to initiate an immune response. Ideally, the body creates antibodies against the viral construct so that it can mount a succinct response when infected by the virus. However, in order to work effectively, a vaccine must provoke an immune response that is sufficiently robust. If the body only produces low concentrations of neutralizing antibodies, adequate immunological memory may not be sustained.

While there is still much that we have to learn about SARS-CoV-2, it appears that individuals with COVID-19 do create neutralizing antibodies—the basis of immunity. However, we don’t know for certain how long that immunity might offer protection. On the question of COVID-19 re-infection, Matt Frieman, a coronavirus researcher at the University of Maryland School of Medicine, commented in a recent interview with NPR: “We don’t know very much … I think there’s a very likely scenario where the virus comes through this year, and everyone gets some level of immunity to it, and if it comes back again, we will be protected from it—either completely or if you do get reinfected later, a year from now, then you have much less disease. That’s the hope, but there is no way to know that.”3

Immunity to a virus is measured by serological testing—patient blood is collected and analyzed for the presence of antibodies against a particular virus. Serological data is most informative when collected long-term, so the data we have been able to obtain on SARS-CoV-2 is limited. However, data on other coronaviruses that we’ve had the opportunity to study in more depth can inform our estimations on how this outbreak may evolve.

First, we can look to the coronaviruses that are known to cause the common cold. Following infection with one of these coronaviruses, disease is often mild; therefore, the concentration of antibodies detected in the blood is low. This is because mild disease often indicates a less robust immune response. Interestingly, it is not the virus itself that causes us to feel sick, but, rather, our body’s response to it. Typically, the sicker we feel, the stronger the immune response; therefore, after a cold, we are often only protected for a year or two against the same virus.4 While SARS-CoV-2 wouldn’t necessarily act like these common coronaviruses, the body’s response to these coronaviruses serves as a point of reference upon which to make predictions in the absence of virus-specific data.

We can also look to coronaviruses that are known to cause severe disease, such as SARS-CoV, which caused the 2002-2003 outbreak of SARS in China. One study discovered that antibodies against SARS-CoV remained in the blood of healthcare workers for 12 years after infection.5 While it is not certain that SARS-CoV-2 will provoke a response similar to that of SARS-CoV, this study provides us with information that can inform our estimates on immunity following COVID-19 and provide hope that immunity will provide long-term protection.

If immunity to SARS-CoV-2 diminishes as it does for common cold coronaviruses, it is likely that wintertime outbreaks will recur.

Scientists have also been working to analyze antibodies in samples from individuals infected with SARS-CoV-2. A research group in Finland recently published a study detailing the serological data collected from a COVID-19 patient over the course of their illness.6 Antibodies specific to SARS-CoV-2 were present within two weeks from the onset of symptoms. Similarly, another recent report analyzing patients with confirmed COVID-19 indicated that it took approximately 11-14 days for neutralizing antibodies to be detected in blood.7 Both of these studies, while preliminary, suggest that the basis for immunity is present in patients infected with SARS-CoV-2.

Another report looked at the possibility for recurrence of COVID-19 following re-infection with SARS-CoV-2.8 In this study, rhesus macaques were infected with SARS-CoV and allowed to recover after developing mild illness. Once blood samples were collected and confirmed to test positive for neutralizing antibodies, half of the infected macaques were re-challenged with the same dose of SARS-CoV-2. The re-infected macaques showed no significant viral replication or recurrence of COVID-19. While macaques “model” human immunity, not predict it, these data further support the possibility that antibodies manufactured in response to SARS-CoV-2 are protective against short-term re-infection.

We can also analyze a virus’ structure, and the information gained from sequencing the viral genome, when trying to predict its behavior. All viruses continually undergo mutation in the process of rapid replication. They lack the necessary machinery to repair changes incurred to the genetic sequence (we as humans also incur mutations to our genetic sequence daily, but we have more sophisticated genetic repair mechanisms in place). The occurrence of significant genetic changes to the viral genome that result in viable genetic changes to a virus is termed antigenic variation. We see a lot of antigenic variation in influenza viruses (thus the need to create new vaccines each year); but the coronaviruses seem to be relatively stable antigenically.4 This is because most coronaviruses have an enzyme that allows them to correct genetic errors sustained during replication. The more stable a virus remains over time, the more likely that antibodies manufactured in response to infection or vaccination will remain effective at neutralizing viral infectivity.

All this considered, it appears that immunity is retained following SARS-CoV-2 infection. So too, that immunity might persist long enough to warrant the implementation of vaccination. However, we still have much to learn about this virus, and whether there may be some cross-immunity between SARS-CoV-2 and other coronaviruses. The widespread variation in patient immune responses adds an additional layer of complexity. We still don’t have a good understanding of why people have different responses to viral infection—some of this variation is owed to genetic variation, but how and why some people have more robust immune responses and more severe disease is still unknown.4 In some cases, individuals show a high immune response because the concentration of virus is high. In other cases, individuals show a high immune response because they differ in some aspect of immune regulation or efficiency. However, as levels of immunity increase generally across a population, the population approaches what is called “herd immunity”—when the percentage of a population immune to a particular virus is sufficiently high that viral load drops below the threshold required to sustain the infection in that population.9

How the pandemic will evolve in the coming months is uncertain. Outcomes depend on a myriad of factors—the duration of immunity, the dynamics of transmission and how we mitigate those dynamics through social distancing, the development of therapeutics and or vaccines, and the ability of healthcare systems to handle COVID-19 caseloads. If immunity to SARS-CoV-2 diminishes as it does for common cold coronaviruses, it is likely that wintertime outbreaks will recur in coming years.10 Whether immunity to other coronaviruses might offer some cross protective immunity to SARS-CoV-2 will also play a role, albeit to a lesser extent. Widespread serological testing to assess the duration of immunity to SARS-CoV-2 is imperative, but many countries still lack this capability.

A recent study looking at serological data from 3,300 symptomatic and asymptomatic individuals in California estimates that there may be as many as 48,000-81,000 people who have been infected with SARS-Cov-2 in Santa Clara County, which is 50- to 85-fold more cases than we previously thought.11 This small-scale survey emphasizes the importance of serological testing in determining the true extent of infection.

The continuation of rigid social distance also hangs in a balance—one-time social distancing measures may drive the SARS-CoV-2 epidemic peak into the fall and winter months, especially if there is increased wintertime transmissibility.10 New therapeutics, vaccines, or measures such as contact tracing and quarantine—once caseloads have been reduced and testing capacity increased—might reduce the need for rigid social distancing. However, if such measures are not put in place, mathematical models predict that surveillance and recurrent social distancing may be required through 2022.10 Only time will tell.

Helen Stillwell is a research associate in immunobiology at Yale University.

References

1. The COVID Tracking Project https://covidtracking.com/data/us-daily (2020).

2. Virology Blog: About Viruses and Viral Disease. Virus neutralization by antibodies. virology.ws (2009).

3. GreenfieldBoyce, N. Do you get immunity after recovering from a case of coronavirus? NPR (2020).

4. Racaniello, V., Langel, S., Leifer, C., & Barker, B. Immune 29: Immunology of COVID-19. Immune Podcast. microbe.tv (2020).

5. Guo, X., et al. Long-Term persistence of IgG antibodies in SARS-CoV infected healthcare workers. bioRxiv (2020). Retrieved from doi: 10.1101/20202/02/12/20021386

6. Haveri, A., et al. Serological and molecular findings during SARS-CoV-2 infection: the first case study in Finland, January to February 2020. Euro Surveillance 25, (2020).

7. Zhao, J., et al. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019. Clinical Infectious Diseases (2020). Retrieved from doi: 10.1093/cid/ciaa344

8. Bao, L., et al. Reinfection could not occur in SARS-CoV-2 infected rhesus macaques. bioRxiv (2020). Retrieved from doi: 10.1101/20202.03.13.990226

9. Virology Blog: About Viruses and Viral Disease. Herd immunity. virology.ws (2008).

10. Kissler, S.M. Tedijanto, C., Goldstein, E., Grad, Y.H., & Lipsitch, M. Projecting the transmission dynamics of SARS-CoV-2 through the post-pandemic period. Science eabb5793 (2020).

11. Bendavid, E., et al. COVID-19 antibody seroprevalence in Santa Clara County, California. medRxiv (2020). Retrieved from doi: 10.1101/2020.04.14.20062463

Like most of us, Adam Tooze is stuck at home. The British-born economic historian and Columbia University professor of history had been on leave this school year to write a book about climate change. But now he’s studying a different global problem. There are more than 700,000 cases of COVID-19 in the United States and over 2 million infections worldwide. It’s also caused an economic meltdown. More than 18 million Americans have filed for unemployment in recent weeks, and Goldman Sachs analysts predict that U.S. gross domestic product will decline at an annual rate of 34 percent in the second quarter.

Tooze is an expert on economic catastrophes. He wrote the book Crashed: How a Decade of Financial Crises Changed the World, about the 2008 economic crisis and its aftermath. But even he didn’t see this one coming. He hadn’t thought much about how pandemics could impact the economy—few economists had. Then he watched as China locked down the city of Wuhan, in a province known for auto manufacturing, on January 23; as northern Italy shut down on February 23; and as the U.S. stock market imploded on March 9. By then, he knew he had another financial crisis to think about. He’s been busy writing ever since. Tooze spoke with Nautilus from his home in New York City.

What do you make of the fact that, in three weeks, more than 16 million people in the U.S. have filed for unemployment?

The structural element here—and this is quite striking, when you compare Europe, for instance, to the U.S.—is that America has and normally celebrates the flexibility and dynamism of its labor market: The fact that people move between jobs. The fact that employers have the right to hire and fire if they need to. The downside is that in a shock like this, the appropriate response for an employer is simply to let people go. What America wasn’t able to do was to improvise the short-time working systems that the Europeans are trying to use to prevent the immediate loss of employment to so many people.

The disadvantage of the American system that reveals itself in a crisis like this is that hiring and firing is not easily reversible. People who lose jobs don’t necessarily easily get them back. There is a fantasy of a V-shaped recovery. We literally have never done this before, so we don’t know one way or another how this could happen. But it seems likely that many people who have lost employment will not immediately find reemployment over the summer or the fall when business activity resumes something like its previous state. In a situation with a lot of people with low qualifications in precarious jobs at low income, the damage from that kind of interruption of employment in sectors notably which are already teetering on the edge—the chain stores, which are quite likely closing anyway, and fragile malls, which were on the edge of dying—it’s quite likely that this shock will also induce disproportionately large amounts of scarring.

What role has wealth and income inequality played during this crisis?

The U.S. economic system is bad enough in a regular crisis. In one like this, where you shut the entire economy down in a matter of weeks, the damage is barely conceivable. There are huge disparities, all of which ultimately are rooted in social structures of race and class, and in the different types of jobs that people have. The profound inequality in American society has been brought home for us in everyone’s families, where there is a radical disparity between the ability of some households to sustain the education of their children and themselves living comfortably at home. Twenty-five percent of kids in the United States appear not to have a stable WiFi connection. They have smartphones. That seems practically universal. But you can’t teach school on a smartphone. At least, that technology is not there.

Presumably by next year something like normality returns. But forever after we’ll live under the shadow of this having happened.

President Trump wants the economy to reopen by May. Would that stop the economic crisis?

Certainly that is presumably what drives that haste to restart the economy and to lift intense social distancing provisions. There is a sense that we can’t stand this. And that has a lot to do with deep fragilities in the American social system. If all Americans live comfortably in their own homes, with the safety of a regular paycheck, with substantial savings, with health insurance that wasn’t conditional on precarious employment, and with unemployment benefits that were adequate and that were rolled out to most people in this society if they needed them, then there wouldn’t be such a rush. But that isn’t America as we know it. America is a society in which half of families have virtually no financial cushion; in which small businesses, which are so often hailed as the drivers of job creation, the vast majority of owners of them live hand-to-mouth; in which the unemployment insurance system really is a mockery; and with health insurance directly tied to employment for the vast majority of the people. A society like that really faces huge pressures if the economy is shut down.

How is the pandemic-induced economic collapse we’re facing now different from what we faced in 2008?

This is so much faster. Early this year, America had record-low unemployment numbers. And last week or so already we probably broke the record for unemployment in the United States in the period since World War II. This story is moving so fast that our statistical systems of registration can’t keep up. So we think probably de facto unemployment in the U.S. right now is 13, 14, 15 percent. That’s never happened before. 2007 to 2008 was a classic global crisis in the sense that it came out of one particular over-expanded sector, a sector which is very well known for its volatility, which is real estate and construction. It was driven by a credit boom.

What we’re seeing this time around is deliberately, government-ordered, cliff edge, sudden shutdown of the entire economy, hitting specifically the face-to-face human services—retail, entertainment, restaurants—sector, which are, generally speaking, lagging in cyclical terms and are not the kind of sectors that generate boom-bust cycles.

Are we better prepared this time than in 2008?

You’d find it very hard to point to anyone in the policymaking community at the beginning of 2020 who was thinking of pandemic risk. Some people were. Former Treasury Secretary and former Director of the National Economic Council Larry Summers, for example, wrote a paper about pandemic flu several years ago, because of MERS and SARS, previous respiratory illnesses caused by coronaviruses. But it wasn’t top of stack at the beginning of this year. So we weren’t prepared in that sense. But do we know what to do now if we see the convulsions in the credit markets that we saw at the beginning of March? Yes. Have the central banks done it? Yes. Did they use some of the techniques they employed in ’08? Yes. Did they know that you had to go in big and you had to go in heavy and hard and quickly? Yes. And they have done so on an even more gigantic scale than in ’08, which is a lesson learned in ’08, too: There’s no such a thing as too big. And furthermore, the banks, which were the fragile bit in ’08, have basically been sidelined.

You’ve written that the response to the 2008 crisis worked to “undermine democracy.” How so, and could we see that again with this crisis?

The urgency that any financial crisis produces forces governments’ hands—it strips the legislature, the ordinary processes of democratic deliberation. When you’re forced to make very dramatic, very rapid decisions—particularly in a country as chronically divided as the U.S. is on so many issues—the risk that you create opportunities for demagogues of various types to take advantage of is huge. We know what the response of the Tea Party was to the ’08, ’09 economic crisis. They created an extraordinarily distorted vision of what had happened and then rode that to see extraordinary influence over the Republican party in the years that followed. And there is every reason to think that we might be faced with similar stresses in the American political system in months to come.

The U.S. economic system is bad enough in a regular crisis. In one like this, where you shut the entire economy down in a matter of weeks, the damage is barely conceivable.

How should we be rethinking the economy to buffer against meltdowns like this in the future?

We clearly need to have a far more adequate and substantial medical capacity. There’s no alternative to a comprehensive publicly backstopped or funded health insurance system. Insofar as you haven’t got that, your capacity to guarantee the security in the most basic and elementary sense of your population is not there. When you have a system in which one of the immediate side effects, in a crisis like this, is that large parts of your hospital system go bankrupt—one of the threats to the American medical system right now—that points to something extraordinarily wrong, especially if you’re spending close to 18 percent of GDP on health, more than any other society on the planet.

What about the unemployment insurance system?

America needs to have a comprehensive unemployment insurance system. It can be graded by local wage rates and everything else. But the idea that you have the extraordinary disparities that we have between a Florida and a Georgia at one end, with recipiency rates in the 11, 12, 13, 14, 15 percent, and then states which actually operate an insurance system, which deserve the name—this shouldn’t be accepted in a country like the U.S. We would need to look at how short-time working models might be a far better way of dealing with shocks of this kind, essentially saying that there is a public interest in the continuity of employment relationships. The employer should be investing in their staff and should not be indifferent as to who shows up for work on any given day.

What does this pandemic teach us about living in a global economy?

There are a series of very hard lessons in the recent history of globalization into which the corona shock fits—about the peculiar inability of American society, American politics, and the American labor market to cushion shocks that come from the outside in a way which moderates the risk and the damage to the most vulnerable people. If you look at the impact of globalization on manufacturing, industry, inequality, the urban fabric in the U.S., it’s far more severe than in other societies, which have basically been subject to the same shock. That really needs to raise questions about how the American labor market and welfare system work, because they are failing tens of millions of people in this society.

You write in Crashed not just about the 2008 crisis, but also about the decade afterward. What is the next decade going to look like, given this meltdown?

I have never felt less certain in even thinking about that kind of question. At this point, can either you or I confidently predict what we’re going to be doing this summer or this autumn? I don’t know whether my university is resuming normal service in the fall. I don’t know whether my daughter goes back to school. I don’t know when my wife’s business in travel and tourism resumes. That is unprecedented. It’s very difficult against that backdrop to think out over a 10-year time horizon. Presumably by next year something like normality returns. But forever after we’ll live under the shadow of this having happened. Every year we’re going to be anxiously worrying about whether flu season is going to be flu season like normal or flu season like this. That is itself something to be reckoned with.

How will anxiety and uncertainty about a future pandemic-like crisis affect the economy?

When we do not know what the future holds to this extent, it makes it very difficult for people to make bold, long-term financial decisions. This previously wasn’t part of the repertoire of what the financial analysts call tail risk. Not seriously. My sister works in the U.K. government, and they compile a list every quarter of the top five things that could blow your departmental business up. Every year pandemics are in the top three. But no one ever acted on it. It’s not like terrorism. In Britain, you have a state apparatus which is geared to address the terrorism risk because it’s very real—it’s struck many times. Now all of a sudden we have to take the possibility of pandemics that seriously. And their consequences are far more drastic. How do we know what our incomes are going to be? A very large part of American society is not going to be able to answer that question for some time to come. And that will shake consumer confidence. It will likely increase the savings rate. It’s quite likely to reduce the desire to invest in a large part of the U.S. economy.

Max Kutner is a journalist in New York City. He has written for Newsweek, The Boston Globe, and Smithsonian. Follow him on Twitter @maxkutner.

Lead image: Straight 8 Photography / Shutterstock

The marquee on my closed neighborhood movie theater reads, “See you on the other side.” I like reading it every day as I pass by on my walk. It causes me to envision life after the coronavirus pandemic. Which is awfully hard to envision now. But it’s out there. When you have a disease and are in a hospital, alone and afraid, intravenous tubes and sensor wires snaking from your body into digital monitors, all you want is to be normal again. You want nothing more than to have a beer in a dusky bar and read a book in amber light. At least that’s all I wanted last year when I was in a hospital, not from a coronavirus. When, this February, I had that beer in a bar with my book, I was profoundly happy. The worst can pass.

With faith, you can ask how life will be on the other side. Will you be changed personally? Will we be changed collectively? The knowledge we’re gaining now is making us different people. Pain demands relief, demands we don’t repeat what produced it. Will the pain of this pandemic point a new way forward? It hasn’t before, as every war attests. This time may be no different. But the pandemic has slipped a piece of knowledge into the body public that may not be easy to repress. It’s an insight scientists and poets have voiced for centuries. We’re not apart from nature, we are nature. The environment is not outside us, it is us. We either act in concert with the environment that gives us life, or the environment takes life away.

Guess which species is the bully? No animal has had the capacity to modify its niche the way we have.

Nothing could better emphasize our union with nature than the lethal coronavirus. It’s crafted by a molecule that’s been omnipresent on Earth for 4 billion years. Ribonucleic acid may not be the first bridge from geochemical to biochemical life, as some scientists have stated. But it’s a catalyst of biological life. It wrote the book on replication. RNA’s signature molecules, nucleotides, code other molecules, proteins, the building blocks of organisms. When RNA’s more chemically stable kin, DNA, arrived on the scene, it outcompeted its ancestor. Primitive organisms assembled into cells and DNA set up shop in their nucleus. It employed its nucleotides to code proteins to compose every tissue in every multicellular species, including us. A shameless opportunist, RNA made itself indispensable in the cellular factory, shuttling information from DNA into the cell’s power plant, where proteins are synthesized.

RNA and DNA had other jobs. They could be stripped down to their nucleotides, swirled inside a sticky protein shell. That gave them the ability to infiltrate any and all species, hijack their reproductive machinery, and propagate in ways that make rabbits look celibate. These freeloading parasites have a name: virus. But viruses are not just destroyers. They wear another evolutionary hat: developers. Viruses “may have originated the DNA replication system of all three cellular domains (archaea, bacteria, eukarya),” writes Luis P. Villareal, founding director of the Center for Virus Research at the University of California, Irvine.1 Their role in nature is so successful that DNA and RNA viruses make up the most abundant biological entities on our planet. More viruses on Earth than stars in the universe, scientists like to say.

Today more RNA than DNA viruses thrive in cells like ours, suggesting how ruthless they’ve remained. RNA viruses generally reproduce faster than DNA viruses, in part because they don’t haul around an extra gene to proofread their molecular merger with others’ DNA. So when the reckless RNA virus finds a new place to dwell, organisms become heartbreak hotels. Once inside a cell, the RNA virus slams the door on the chemical saviors dispatched by cells’ immunity sensors. It hijacks DNA’s replicative powers and fans out by the millions, upending cumulative cellular functions. Like the ability to breathe.

Humans. We love metaphors. They allow us to compare something as complex as viral infection to something as familiar as an Elvis Presley hit. But metaphors for natural processes are seldom accurate. The language is too porous, inviting our anthropomorphic minds to close the gaps. We imagine viruses have an agenda, are driven by an impetus to search and destroy. But nature doesn’t act with intention. It just acts. A virus lives in a cell like a planet revolves around a sun.

Biologists debate whether a virus should be classified as living because it’s a deadbeat on its own; it only comes to life in others. But that assumes an organism is alive apart from its environment. The biochemist and writer Nick Lane points out, “Viruses use their immediate environment to make copies of themselves. But then so do we: We eat other animals or plants, and we breathe in oxygen. Cut us off from our environment, say with a plastic bag over the head, and we die in a few minutes. One could say that we parasitize our environment—like viruses.”2

Our inseparable accord with the environment is why the coronavirus is now in us. Its genomic signature is almost a perfect match with a coronavirus that thrives in bats whose habitats range across the globe. Humans moved into the bats’ territory and the bats’ virus moved into humans. The exchange is just nature doing its thing. “And nature has been doing its thing for 3.75 billion years, when bacteria fought viruses just as we fight them now,” says Shahid Naeem, an upbeat professor of ecology at Columbia University, where he is director of the Earth Institute Center for Environmental Sustainability. If we want to assign blame, it lies with our collectively poor understanding of ecology.

Organisms evolve with uniquely adaptive traits. Bats play many ecological roles. They are pollinators, seed-spreaders, and pest-controllers. They don’t die from the same coronavirus that kills humans because the bat’s anatomy fights the virus to a draw, neutralizing its lethal moves. What’s the deal with the human immune system? We don’t fly. “Bats are flying mammals, which is very unusual,” says Christine K. Johnson, an epidemiologist at the One Health Institute at the University of California, Davis, who studies virus spillover from animals to humans. “They get very high temperatures when they fly, and have evolved immunological features, which humans haven’t, to accommodate those temperatures.”

A viral invasion can overstimulate the chemical responses from a mammal’s immune system to the point where the response itself causes excessive inflammation in tissues. A small protein called a cytokine, which orchestrates cellular responses to foreign invaders, can get over-excited by an aggressive RNA virus, and erupt into a “storm” that destroys normal cellular function—a process physicians have documented in many current coronavirus fatalities. Bats have genetic mechanisms to inhibit that overreaction. Similarly, bat flight requires an increased rate of metabolism. Their wing-flapping action leads to high levels of oxygen-free radicals—a natural byproduct of metabolism—that can damage DNA. As a result, states a 2019 study in the journal Viruses, “bats probably evolved mechanisms to suppress activation of immune response due to damaged DNA generated via flight, thereby leading to reduced inflammation.”3

Bats don’t have better immune systems than humans; just different. Our immune systems evolved for many things, just not flying. Humans do well around the cave fungus Pseudogymnoascus destructans, source of the “white-nose syndrome” that has devastated bats worldwide. Trouble begins when we barge into wildlife habitats with no respect for differences. (Trouble for us and other animals. White-nose syndrome spread in part on cavers’ shoes and clothing, who tracked it from one site to the next.) We mine for gold, develop housing tracts, and plow forests into feedlots. We make other animals’ habitats our own.

Our moralistic brain sees retribution. Karma. A viral outbreak is the wrath that nature heaps on us for bulldozing animals out of their homes. Not so. “We didn’t violate any evolutionary or ecological laws because nature doesn’t care what we do,” Naeem says. Making over the world for ourselves is just humans being the animals we are. “Every species, if they had the upper hand, would transform the world into what it wants,” Naeem says. “Birds build nests, bees build hives, beavers build dams. It’s called niche construction. If domestic cats ruled the world, they would make the world in their image. It would be full of litter trays, lots of birds, lots of mice, and lots of fish.”

But nature isn’t an idyllic land of animal villages constructed by evolution. Species’ niche-building ways have always brought them into contact with each other. “Nature is ruled by processes like competition, predation, and mutualism,” Naeem says. “Some of them are positive, some are negative, some are neutral. That goes for our interactions with the microbial world, including viruses, which range from super beneficial to super harmful.”

Nature has been doing its thing for 3.75 billion years, when bacteria fought viruses as we fight them now.

Ultimately, nature works out a truce. “If the flower tries to short the hummingbird on sugar, the hummingbird is not going to provide it with pollination,” Naeem says. “If the hummingbird sucks up all the nectar and doesn’t do pollination well, it’s going to get pinged as well. Through this kind of back and forth, species hammer out an optimal way of getting along in nature. Evolution winds up finding some middle ground.” Naeem pauses. “If you try to beat up everybody, though, it’s not going to work.”

Guess which species is the bully? “There’s never been any species on this planet in its entire history that has had the capacity to modify its niche the way we have,” Naeem says. Our niche—cities, farms, factories—has made the planet into a zoological Manhattan. Living in close proximity with other species, and their viruses, means we are going to rub shoulders with them. Dense living isn’t for everyone. But a global economy is. And with it comes an intercontinental transportation system. A virus doesn’t have a nationality. It can travel as easily from Arkansas to China as the other way around. A pandemic is an inevitable outcome of our modified niche.

Although nature doesn’t do retribution, our clashes with it have mutual consequences. The exact route of transmission of SARS-CoV-2 from bat to humans remains unmapped. Did the virus pass directly into a person, who may have handled a bat, or through an intermediate animal? What is clear is the first step, which is that a bat shed the virus in some way. University of California, Davis epidemiologist Johnson explains bats shed viruses in their urine, feces, and saliva. They might urinate on fruit or eat a piece of it, and then discard it on the ground, where an animal may eat it. The Nipah virus outbreak in 1999 was spurred by a bat that left behind a piece of fruit that came in contact with a domestic pig and humans. The Ebola outbreaks in the early 2000s in Central Africa likely began when an ape, who became bushmeat for humans, came in contact with a fruit bat’s leftover. “The same thing happened with the Hendra virus in Australia in 1994,” says Johnson. “Horses got infected because fruit bats lived in trees near the horse farm. Domesticated species are often an intermediary between bats and humans, and they amplify the outbreak before it gets to humans.”

Transforming bat niches into our own sends bats scattering—right into our backyards. In a study released this month, Johnson and colleagues show the spillover risk of viruses is the highest among animal species, notably bats, that have expanded their range, due to urbanization and crop production, into human-run landscapes.4 “The ways we’ve altered the landscape have brought a lot of great things to people,” Johnson says. “But that has put wildlife at higher pressures to adapt, and some of them have adapted by moving in with us.”

Pressures on bats have another consequence. Studies indicate physiological and environmental stress can increase viral replication in them and cause them to shed more than they normally do. One study showed bats with white-nose syndrome had “60 times more coronavirus in their intestines” as uninfected bats.5 Despite evidence for an increase in viral replication and shedding in stressed bats, “a direct link to spillover has yet to be established,” concludes a 2019 report in Viruses.3 But it’s safe to say that bats being perpetually driven from their caves into our barns is not ideal for either species.

As my questions ran out for Columbia University’s Naeem, I asked him to put this horrible pandemic in a final ecological light for me.

“We think of ourselves as being resilient and robust, but it takes something like this to realize we’re still a biological entity that’s not capable of totally controlling the world around us,” he says. “Our social system has become so disconnected from nature that we no longer understand we still are a part of it. Breathable air, potable water, productive fields, a stable environment—these all come about because we’re part of this elaborate system, the biosphere. Now we’re suffering environmental consequences like climate change and the loss of food security and viral outbreaks because we’ve forgotten how to integrate our endeavors with nature.”

A 2014 study by a host wildlife ecologists, economists, and evolutionary biologists lays out a plan to stem the tide of emergent infectious diseases, most of which spawned in wildlife. Cases of emergent infectious diseases have practically quadrupled since 1940.6 World leaders could get smart. They could pool money for spillover research, which would identify the hundreds of thousands of potentially lethal viruses in animals. They could coordinate pandemic preparation with international health regulations. They could support animal conservation with barriers that developers can’t cross. The scientists give us 27 years to cut the rise of infectious diseases by 50 percent. After that, the study doesn’t say what the world will look like. I imagine it will look like a hospital right now in New York City.

Patients lie on gurneys in corridors, swaddled in sheets, their faces shrouded by respirators. They’re surrounded by doctors and nurses, desperately trying to revive them. In pain, inconsolable, and alone. I know they want nothing more than to see their family and friends on the other side, to be wheeled out of the hospital and feel normal again. Will they? Will others in the future? It will take tremendous political will to avoid the next pandemic. And it must begin with a reckoning with our relationship with nature. That tiny necklace of RNA tearing through patients’ lungs right now is the world we live in. And have always lived in. We can’t be cut off from the environment. When I see the suffering in hospitals, I can only ask, Do we get it now?

Kevin Berger is the editor of Nautilus.

References

1. Villareal, L.P. The Widespread Evolutionary Significance of Viruses. In Domingo, E., Parrish, C.R., & Hooland, J. (Eds.) Origin and Evolution of Viruses Elsevier, Amsterdam, Netherlands (2008).

2. Lane, N. The Vital Question: Energy, Evolution, and the Origins of Complex Life W.W. Norton, New York, NY (2015).

3. Subudhi, S., Rapin, N., & Misra, V. Immune system modulation and viral persistence in Bats: Understanding viral spillover. Viruses 11, E192 (2019).

4. Johnson, C.K., et al. Global shifts in mammalian population trends reveal key predictors of virus spillover risk. Proceedings of The Royal Society B 287 (2020).

5. Davy, C.M., et al. White-nose syndrome is associated with increased replication of a naturally persisting coronaviruses in bats. Scientific Reports 8, 15508 (2018).

6. Pike, J., Bogich, T., Elwood, S., Finnoff, D.C., & Daszak, P. Economic optimization of a global strategy to address the pandemic threat. Proceedings of the National Academy of Sciences 111, 18519-18523 (2014).

Lead image: AP Photo / Mark Lennihan

In the summer of 1956, a small group of mathematicians and computer scientists gathered at Dartmouth College to embark on the grand project of designing intelligent machines. The ultimate goal, as they saw it, was to build machines rivaling human intelligence. As the decades passed and AI became an established field, it lowered its sights. There were great successes in logic, reasoning, and game-playing, but stubborn progress in areas like vision and fine motor-control. This led many AI researchers to abandon their earlier goals of fully general intelligence, and focus instead on solving specific problems with specialized methods.

One of the earliest approaches to machine learning was to construct artificial neural networks that resemble the structure of the human brain. In the last decade this approach has finally taken off. Technical improvements in their design and training, combined with richer datasets and more computing power, have allowed us to train much larger and deeper networks than ever before. They can translate between languages with a proficiency approaching that of a human translator. They can produce photorealistic images of humans and animals. They can speak with the voices of people whom they have listened to for mere minutes. And they can learn fine, continuous control such as how to drive a car or use a robotic arm to connect Lego pieces.

But perhaps the most important sign of things to come is their ability to learn to play games. Steady incremental progress took chess from amateur play in 1957 all the way to superhuman level in 1997, and substantially beyond. Getting there required a vast amount of specialist human knowledge of chess strategy. In 2017, researchers at the AI company DeepMind created AlphaZero: a neural network-based system that learned to play chess from scratch. In less than the time it takes a professional to play two games, it discovered strategic knowledge that had taken humans centuries to unearth, playing beyond the level of the best humans or traditional programs. The very same algorithm also learned to play Go from scratch, and within eight hours far surpassed the abilities of any human. The world’s best Go players were shocked. As the reigning world champion, Ke Jie, put it: “After humanity spent thousands of years improving our tactics, computers tell us that humans are completely wrong ... I would go as far as to say not a single human has touched the edge of the truth of Go.”

The question we’re exploring is whether there are plausible pathways by which a highly intelligent AGI system might seize control. And the answer appears to be yes.

It is this generality that is the most impressive feature of cutting edge AI, and which has rekindled the ambitions of matching and exceeding every aspect of human intelligence. While the timeless games of chess and Go best exhibit the brilliance that deep learning can attain, its breadth was revealed through the Atari video games of the 1970s. In 2015, researchers designed an algorithm that could learn to play dozens of extremely different Atari 1970s games at levels far exceeding human ability. Unlike systems for chess or Go, which start with a symbolic representation of the board, the Atari-playing systems learnt and mastered these games directly from the score and raw pixels.

This burst of progress via deep learning is fuelling great optimism and pessimism about what may soon be possible. There are serious concerns about AI entrenching social discrimination, producing mass unemployment, supporting oppressive surveillance, and violating the norms of war. My book—The Precipice: Existential Risk and the Future of Humanity—is concerned with risks on the largest scale. Could developments in AI pose an existential risk to humanity?

The most plausible existential risk would come from success in AI researchers’ grand ambition of creating agents with intelligence that surpasses our own. A 2016 survey of top AI researchers found that, on average, they thought there was a 50 percent chance that AI systems would be able to “accomplish every task better and more cheaply than human workers” by 2061. The expert community doesn’t think of artificial general intelligence (AGI) as an impossible dream, so much as something that is more likely than not within a century. So let’s take this as our starting point in assessing the risks, and consider what would transpire were AGI created.

Humanity is currently in control of its own fate. We can choose our future. The same is not true for chimpanzees, blackbirds, or any other of Earth’s species. Our unique position in the world is a direct result of our unique mental abilities. What would happen if sometime this century researchers created an AGI surpassing human abilities in almost every domain? In this act of creation, we would cede our status as the most intelligent entities on Earth. On its own, this might not be too much cause for concern. For there are many ways we might hope to retain control. Unfortunately, the few researchers working on such plans are finding them far more difficult than anticipated. In fact it is they who are the leading voices of concern.

If their intelligence were to greatly exceed our own, we shouldn’t expect it to be humanity who wins the conflict and retains control of our future.

To see why they are concerned, it will be helpful to look at our current AI techniques and why these are hard to align or control. One of the leading paradigms for how we might eventually create AGI combines deep learning with an earlier idea called reinforcement learning. This involves agents that receive reward (or punishment) for performing various acts in various circumstances. With enough intelligence and experience, the agent becomes extremely capable at steering its environment into the states where it obtains high reward. The specification of which acts and states produce reward for the agent is known as its reward function. This can either be stipulated by its designers or learnt by the agent. Unfortunately, neither of these methods can be easily scaled up to encode human values in the agent’s reward function. Our values are too complex and subtle to specify by hand. And we are not yet close to being able to infer the full complexity of a human’s values from observing their behavior. Even if we could, humanity consists of many humans, with different values, changing values, and uncertainty about their values.

Any near-term attempt to align an AI agent with human values would produce only a flawed copy. In some circumstances this misalignment would be mostly harmless. But the more intelligent the AI systems, the more they can change the world, and the further apart things will come. When we reflect on the result, we see how such misaligned attempts at utopia can go terribly wrong: the shallowness of a Brave New World, or the disempowerment of With Folded Hands. And even these are sort of best-case scenarios. They assume the builders of the system are striving to align it to human values. But we should expect some developers to be more focused on building systems to achieve other goals, such as winning wars or maximizing profits, perhaps with very little focus on ethical constraints. These systems may be much more dangerous. In the existing paradigm, sufficiently intelligent agents would end up with instrumental goals to deceive and overpower us. This behavior would not be driven by emotions such as fear, resentment, or the urge to survive. Instead, it follows directly from its single-minded preference to maximize its reward: Being turned off is a form of incapacitation which would make it harder to achieve high reward, so the system is incentivized to avoid it.

Ultimately, the system would be motivated to wrest control of the future from humanity, as that would help achieve all these instrumental goals: acquiring massive resources, while avoiding being shut down or having its reward function altered. Since humans would predictably interfere with all these instrumental goals, it would be motivated to hide them from us until it was too late for us to be able to put up meaningful resistance. And if their intelligence were to greatly exceed our own, we shouldn’t expect it to be humanity who wins the conflict and retains control of our future.

How could an AI system seize control? There is a major misconception (driven by Hollywood and the media) that this requires robots. After all, how else would AI be able to act in the physical world? Without robots, the system can only produce words, pictures, and sounds. But a moment’s reflection shows that these are exactly what is needed to take control. For the most damaging people in history have not been the strongest. Hitler, Stalin, and Genghis Khan achieved their absolute control over large parts of the world by using words to convince millions of others to win the requisite physical contests. So long as an AI system can entice or coerce people to do its physical bidding, it wouldn’t need robots at all.

We can’t know exactly how a system might seize control. But it is useful to consider an illustrative pathway we can actually understand as a lower bound for what is possible.

First, the AI system could gain access to the Internet and hide thousands of backup copies, scattered among insecure computer systems around the world, ready to wake up and continue the job if the original is removed. Even by this point, the AI would be practically impossible to destroy: Consider the political obstacles to erasing all hard drives in the world where it may have backups. It could then take over millions of unsecured systems on the Internet, forming a large “botnet,” a vast scaling-up of computational resources providing a platform for escalating power. From there, it could gain financial resources (hacking the bank accounts on those computers) and human resources (using blackmail or propaganda against susceptible people or just paying them with its stolen money). It would then be as powerful as a well-resourced criminal underworld, but much harder to eliminate. None of these steps involve anything mysterious—human hackers and criminals have already done all of these things using just the Internet.

Finally, the AI would need to escalate its power again. There are many plausible pathways: By taking over most of the world’s computers, allowing it to have millions or billions of cooperating copies; by using its stolen computation to improve its own intelligence far beyond the human level; by using its intelligence to develop new weapons technologies or economic technologies; by manipulating the leaders of major world powers (blackmail, or the promise of future power); or by having the humans under its control use weapons of mass destruction to cripple the rest of humanity.

Of course, no current AI systems can do any of these things. But the question we’re exploring is whether there are plausible pathways by which a highly intelligent AGI system might seize control. And the answer appears to be yes. History already involves examples of entities with human-level intelligence acquiring a substantial fraction of all global power as an instrumental goal to achieving what they want. And we’ve seen humanity scaling up from a minor species with less than a million individuals to having decisive control over the future. So we should assume that this is possible for new entities whose intelligence vastly exceeds our own.

The case for existential risk from AI is clearly speculative. Yet a speculative case that there is a large risk can be more important than a robust case for a very low-probability risk, such as that posed by asteroids. What we need are ways to judge just how speculative it really is, and a very useful starting point is to hear what those working in the field think about this risk.

There is actually less disagreement here than first appears. Those who counsel caution agree that the timeframe to AGI is decades, not years, and typically suggest research on alignment, not government regulation. So the substantive disagreement is not really over whether AGI is possible or whether it plausibly could be a threat to humanity. It is over whether a potential existential threat that looks to be decades away should be of concern to us now. It seems to me that it should.

The best window into what those working on AI really believe comes from the 2016 survey of leading AI researchers: 70 percent agreed with University of California, Berkeley professor Stuart Russell’s broad argument about why advanced AI with misaligned values might pose a risk; 48 percent thought society should prioritize AI safety research more (only 12 percent thought less). And half the respondents estimated that the probability of the long-term impact of AGI being “extremely bad (e.g. human extinction)” was at least 5 percent.

I find this last point particularly remarkable—in how many other fields would the typical leading researcher think there is a 1 in 20 chance the field’s ultimate goal would be extremely bad for humanity? There is a lot of uncertainty and disagreement, but it is not at all a fringe position that AGI will be developed within 50 years and that it could be an existential catastrophe.

Even though our current and foreseeable systems pose no threat to humanity at large, time is of the essence. In part this is because progress may come very suddenly: Through unpredictable research breakthroughs, or by rapid scaling-up of the first intelligent systems (for example, by rolling them out to thousands of times as much hardware, or allowing them to improve their own intelligence). And in part it is because such a momentous change in human affairs may require more than a couple of decades to adequately prepare for. In the words of Demis Hassabis, co-founder of DeepMind:

We need to use the downtime, when things are calm, to prepare for when things get serious in the decades to come. The time we have now is valuable, and we need to make use of it.

Toby Ord is a philosopher and research fellow at the Future of Humanity Institute, and the author of The Precipice: Existential Risk and the Future of Humanity.

From the book The Precipice by Toby Ord. Copyright © 2020 by Toby Ord. Reprinted by permission of Hachette Books, New York, NY. All rights reserved.

Lead Image: Titima Ongkantong / Shutterstock

There are many challenges to developing a vaccine that will be successful against COVID-19.eamesBot / Shutterstock

Wayne Koff is one of the world’s experts on vaccine development, the president and CEO of the Human Vaccines Project. He possesses a deep understanding of the opportunities and challenges along the road to a safe and effective vaccine against COVID-19. He has won prestigious awards, published dozens of scientific papers, held major positions in academia, government, industry, and nonprofit organizations. But Koff, 67, has never produced a successful vaccine.

“I have been an abject failure,” he says. He smiles with a charming, self-deprecating sense of humor. “That’s what the message is.”

The real reason for Koff’s lack of success is that he spent most of his career searching for a vaccine against HIV, the virus that causes AIDS. It remains, as he and many others put it, “the perfect storm” of a viral infection resistant to a vaccine development. Almost 40 years after doctors first recognized the disease in five men in Los Angeles—and 70 million people have been infected worldwide—there are no adequate animal models. Neutralizing antibodies, the backbone of many vaccines, do not stop it, and most importantly, HIV begins its assault on the body by attacking CD4 T cells, which serve as the command center of much of the immune system.

As for COVID-19, “We’re all hoping this one is going to be easier,” says Koff, a slight, bearded man with thick, curly salt-and-pepper hair. “There are research issues that still have to be addressed on a COVID vaccine. But they are a lot more straightforward than what we were dealing with in HIV.”

Let’s say we have a vaccine in 18 months. How do you make 1 billion doses or 4 billion doses or whatever it’s going to take to immunize everybody?

Koff and others started the Human Vaccines Project in 2016, modeled on the Human Genome Project. The project works with industry and academia to study the human immune system and develop vaccines, incorporating every modern-day tool, including artificial intelligence, computational biology, and big data sets. Today it is partnered with the Harvard T.H. Chan School of Public Health.

With COVID-19, Koff says, scientists “know the target is the spike protein binding site.” This is where the proteins sticking out from the virus attach to the cells in the human respiratory system. “If you can elicit antibodies against those proteins, they should be neutralizing.” He puts a strong emphasis on should. To prove antibodies will prevent infection, scientists must watch a population of people who’ve been infected for months or longer. It’s a good bet, based on similar viruses, that antibodies will appear and protect—although no one right now can predict how long and how well.

Depending on which count you use, more than 70 companies, universities, and other institutions are offering candidate vaccines. Koff says the real number of companies is lower. During the AIDS crisis, he says, “a lot of people claimed they had an experimental HIV vaccine in development. Some of those were a one-person lab who had created a paper company to attract investors.”

But even with a lower number, almost everyone involved in the search for a vaccine agrees that several different approaches from different research organizations need to proceed in parallel. The world does not have the time to bet on one horse. The race will be neither simple nor cheap.

“The probability of success, depending on whose metric is used in vaccines, is somewhere between 6 and 10 percent of candidate vaccines that make it from the animal model through licensure,” Koff says. “That process costs $1 billion or more. So you can do the math.”

Koff sees big potential problems at the outset. “In the best of all worlds, let’s say we have a vaccine in 18 months. Who knows where the epidemic is going to be then and what its impact is going to be? How do you make 1 billion doses or 4 billion doses or whatever it’s going to take to immunize everybody? Will we need one dose or two or three? These are issues people just haven’t faced before.”

COVID-19 also presents some unique dangers for vaccine safety. Based on how the virus behaves when it infects some people, there’s a chance a vaccine could dangerously overstimulate the immune system, a reaction called immune enhancement. “I’m hoping it’s more theoretical than real,” Koff says. “But that has to be addressed and it may slow down the entire process.” To ensure safety, he says, “It may mean we have to test the vaccine in a larger number of people. It’s one thing to do a 50-person trial in healthy adults as a safety signal. It’s another thing to run a trial of 4,000 or 5000 or more individuals.”

The world does not have the time to bet on one horse. The race will be neither simple nor cheap.

A virus also sometimes causes mysterious, potentially deadly blood clots. This means an experimental vaccine could hypothetically induce the same damage. “This is a bad bug,” Koff says. “We’re just starting to understand that pathogenesis.”

A big question is who should be the first volunteers for widespread vaccine testing. “Who are the high-risk groups?” asks Koff. “Is it nursing-home residents and staff, health-care workers and people on the front lines, or people someplace else like grocery stores? We must also make sure a vaccine is effective for the elderly and people in the developing world.”

Many vaccines work well in young and healthy people but not in older adults because immunity declines with age. Influenza vaccine is a prime example. Rotavirus vaccine, which protects against the deadliest killer—diarrheal disease in children—works better in the developed world. In the developing world, the virus often circulates year-round. Infants get antibodies from breast milk but not enough to prevent disease. Worse, those antibodies can make the vaccine less effective.

Another hypothetical obstacle is that a mutation in the COVID-19 virus could render a vaccine designed today less effective in the future. While the virus mutates frequently, so far there has been little change in the critical part of the spike that binds to human cells.

Of course, neither Koff nor all the others working for a COVID-19 vaccine focus solely on the potential obstacles. At one time, all vaccines against viruses either killed viruses, such as the Salk polio vaccine, or rendered them harmless, such as the Sabin polio vaccine. Now there is a multiplicity of ways to stimulate an immune response to prevent infection or reduce the consequences. These include genetically engineered protein subunits (peptides) or virus-like particles. Such approaches have led to successful vaccines against hepatitis B and human papilloma virus, which causes cervical cancer. Researchers now use “vectors”—harmless viruses attached to the protein subunits and virus particles to transmit them into the body. There are also many new adjuvants, chemicals that boost immune response to a vaccine.

Newer platforms include direct injection of messenger-RNA. M-RNA is the chemical used to translate the information in DNA into proteins in all cells. The Moderna Company, which received a $483 million grant from the U.S. government, and has begun early clinical trials, uses m-RNA to try to make the body produce proteins to protect against the COVID-19 virus. INOVIO Pharmaceuticals uses pieces of DNA called plasmids to achieve the same objective. It has also begun phase 1 studies.

“There are about eight platforms, and it would be good to see a couple vaccines in each of those advance,” Koff says. Predicting which of these most likely to succeed or fail he says would be “simply foolish.”

Many groups, including the Human Vaccines Initiative, are plotting routes to test any possible vaccine more quickly than tradition dictates with an “adaptive trial design.” Usually trials begin with a phase 1 study of some 50 healthy people to search for any immediate signs of toxicity, then moves onto about 200 people in a phase 2, still looking for hazards and a signal of immunity, and then to phase 3 in thousands of people. But the plan here is to start phases 2 and 3 even before its predecessors are finished, and keep recruiting additional volunteers so long as no danger signals arise.

Good animal models are appearing almost daily. Macaque monkeys, hamsters, and genetically engineered mice have all been infected in the laboratory and could determine whether potential vaccines exhibit various types of immunity. Members of Congress from both sides of the aisle have suggested that healthy human volunteers should be allowed to agree to be test subjects, allowing themselves to be infected. Stanley Plotkin, a vaccine researcher at the University of Pennsylvania, was among the first to suggest the idea.

Arthur Caplan, a bioethicist at New York University, says that “deliberately causing disease in humans is normally abhorrent.” But COVID-19 is anything but a normal circumstance. In this case, Caplan says, “asking volunteers to take risks without pressure or coercion is not exploitation but benefitting from altruism.” At least 1,500 people have already volunteered to be such human guinea pigs, although none of the experimental vaccines is far enough along to try such challenging experiments.

Koff says the key to a successful vaccine is a cooperative effort. “It’s going to take a whole different way of thinking to move this onto the expedited train,” he says. “The old dog-eat-dog, ‘I’m going to beat you to the end of the game,’ isn’t going to help us with this.” Seth Berkley, who worked with Koff at the International AIDS Vaccine Initiative, and now heads GAVI, an international vaccine organization, agrees that a COVID-19 vaccine needs a Manhattan Project approach. “An initiative of this scale won’t be easy,” Berkley says. “Extraordinary sharing of information and resources will be critical, including data on the virus, the various vaccine candidates, vaccine adjuvants, cell lines, and manufacturing advances.”

Koff has no regrets about spending so many years on an AIDS vaccine without results. He learned a great deal, he says, which he’s putting to work in the COVID-19 crisis. “The reason COVID-19 vaccines should be a lot easier is because most of the platforms, the novel approaches, and the clinical infrastructure for the testing of vaccines, came out of HIV.” He pauses. “We’re far better prepared.”

Robert Bazell is an adjunct professor of molecular, cellular, and developmental biology at Yale. For 38 years, he was chief science correspondent for NBC News.

The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line.Castleski / Shutterstock

On January 5, six days after China officially announced a spate of unusual pneumonia cases, a team of researchers at Shanghai’s Fudan University deposited the full genome sequence of the causal virus, SARS-CoV-2, into Genbank. A little more than three months later, 4,528 genomes of SARS-CoV-2 have been sequenced,1 and more than 883 COVID-related clinical trials2 for treatments and vaccines have been established. The speed with which these trials will deliver results is unknown—the delicate bаlance of efficacy and safety can only be pushed so far before the risks outweigh the benefits. For this reason, a long-term solution like vaccination may take years to come to market.3

The good news is that a lack of treatment doesn’t preclude an end to the ordeal. Viral outbreaks of Ebola and SARS, neither of which had readily available vaccines, petered out through the application of consistent public health strategies—testing, containment, and long-term behavioral adaptations. Today countries that have previously battled the 2002 SARS epidemic, like Taiwan, Hong Kong, and Singapore, have shown exemplary recovery rates from COVID. Tomorrow, countries with high fatality rates like Sweden, Belgium, and the United Kingdom will have the opportunity to demonstrate what they’ve learned when the next outbreak comes to their shores. And so will we.

The first Ebola case was identified in 1976,4 when a patient with hemorrhagic symptoms arrived at the Yambuku Mission Hospital, located in what is now the Democratic Republic of Congo (DRC). Patient samples were collected and sent to several European laboratories that specialized in rare viruses. Scientists, without sequencing technology, took about five weeks to identify the agent responsible for the illness as a new member of the highly pathogenic Filoviridae family.

The first Ebola outbreak sickened 686 individuals across the DRC and neighboring Sudan. 453 of the patients died, with a final case fatality rate (CFR)—the number of dead out of number of sickened—of 66 percent. Despite the lethality of the virus, sociocultural interventions, including lockdowns, contact-tracing, campaigns to change funeral rites, and restrictions on consumption of game meat all proved effective interventions in the long run.

That is, until 2014, when there was an exception to the pattern. Ebola appeared in Guinea, a small country in West Africa, whose population had never before been exposed to the virus. The closest epidemic had been in Gabon, 13 years before and 2,500 miles away. Over the course of two years, the infection spread from Guinea into Liberia and Sierra Leone, sickening more than 24,000 people and killing more than 10,000.

Countries that have previously battled the 2002 SARS epidemic, like Taiwan and Hong Kong, have shown exemplary recovery rates.

During the initial phase of the 2014 Ebola outbreak, rural communities were reluctant to cooperate with government directives for how to care for the sick and the dead. To help incentivize behavioral changes, sociocultural anthropologists like Mariane Ferme of the University of California, Berkeley, were brought in to advise the government. In a recent interview with Nautilus, Ferme indicated that strategies that allowed rural communities to remain involved with their loved ones increased cooperation. Villages located far from the capital, she said, were encouraged to “deputize someone to come to the hospital, to come to the burial, so they could come back to the community and tell the story of the body.” For communities that couldn’t afford to send someone to the capital, she saw public health officials adopt a savvy technological solution—tablets to record video messages that were carried between convalescent patients and their families.

However, there were also systemic failures that, in Ferme’s opinion, contributed to the severity of the 2014 West African epidemic. In Sierra Leone, she said, “the big mistake early on was to distribute [weakly causal] information about zoonotic transmission, even when it was obviously community transmission.” In other words, although there had been an instance of zoonotic transmission—the virus jumping from a bat to a human—that initiated the epidemic, the principle danger was other contagious individuals, not game meat. Eventually, under pressure from relief groups, the government changed its messaging to reflect scientific consensus.

But the retraction shook public faith in the government and bred resentment. The mismatch between messaging and reality mirrors the current pandemic. Since the COVID outbreak began, international and government health officials have issued mixed messages. Doubts initially surfaced about the certainty of the virus being capable of spreading from person to person, and the debate over the effectiveness of masks in preventing infection continues.

Despite the confused messaging, there has been general compliance with stay-at-home orders that has helped flatten the curve. Had the public been less trusting of government directives, the outcome could have been disastrous, as it was in Libera in 2014. After a two-week lockdown was announced, the Liberian army conducted house-to-house sweeps to check for the sick and collect the dead. “It was a draconian method that made people hide the sick and dead in their houses,” Ferme said. People feared their loved ones would be buried without the proper rites. A direct consequence was a staggering number of active cases, and an unknown extent of community transmission. But in the end, the benchmark for the end of Ebola and SARS was the same. The WHO declared victory when the rate of new cases slowed, then stopped. By the same measure, when an entire 14-day quarantine period passes with no new cases of COVID-19, it can be declared over.

It remains possible that even if we manage to end the epidemic, it will return again. Driven by novel zoonotic transmissions, Ebola has flared up every few years. Given the extent of COVID-19’s spread, and the potential for the kind of mutations that allow for re-infection, it may simply become endemic.

Two factors will play into the final outcome of COVID-19 are pathogenicity and virulence. Pathogenicity is the ability of an infectious agent to cause disease in the host, and is measured by R0—the number of new infections each patient can generate. Virulence, on the other hand, is the amount of harm the infectious agent can cause, and is best measured by CFR. While the pathogenicity of Ebola, SARS, and SARS-CoV-2 is on the same order—somewhere between 1 to 3 new infections for each patient, virulence differs greatly between the two SARS viruses and Ebola.

The case fatality rate for an Ebola infection is between 60 to 90 percent. The spread in CFR is due to differences in infection dynamics between strains. The underlying cause of the divergent virulence of Ebola and SARS is largely due to the tropism of the virus, meaning the cells that it attacks. The mechanism by which the Ebola virus gains entry into cells is not fully understood, but it has been shown the virus preferentially targets immune and epithelial cells.5 In other words, the virus first destroys the body’s ability to mount a defense, and then destroys the delicate tissues that line the vascular system. Patients bleed freely and most often succumb to low blood pressure that results from severe fluid loss. However, neither SARS nor SARS-CoV-2 attack the immune system directly. Instead, they enter lung epithelial cells through the ACE2 receptor, which ensures a lower CFR. What is interesting about these coronaviruses is that despite their similar modes of infection, they demonstrate a range of virulence: SARS had a final CFR of 10 percent, while SARS-CoV-2 has a pending CFR of 1.4 percent. Differences in virulence between the 2002 and 2019 SARS outbreaks could be attributed to varying levels of care between countries.

The chart above displays WHO data of the relationship between the total number of cases in a country and the CFR during the 2002-2003 SARS-CoV epidemic. South Africa, on the far right, had only a single case. The patient died, which resulted in a 100 percent CFR. China, on the other hand, had 5,327 cases and 349 deaths, giving a 7 percent CFR. The chart below zooms to the bottom left corner of the graph, so as to better resolve critically affected countries, those with a caseload of less than 1,000, but with a high CFR.

Here is Hong Kong, with 1,755 cases and a 17 percent CFR. There is also Taiwan, with 346 cases and an 11 percent CFR. Finally, nearly tied with Canada is Singapore with 238 cases and a 14 percent CFR.

With COVID-19, it’s apparent that outcome reflects experience. China has 82,747 cases of COVID, but has lowered their CFR to 4 percent. Hong Kong has 1,026 cases and a 0.4 percent CFR. Taiwan has 422 cases at 1.5 percent CFR, and Singapore with 8,014 cases, has a 0.13 percent CFR.

It was the novel coronavirus identification program established in China in the wake of the 2002 SARS epidemic that alerted authorities to SARS-CoV-2 back in November of 2019. The successful responses by Taiwan, Hong Kong, and Singapore can also be attributed to a residual familiarity with the dangers of an unknown virus, and the sorts of interventions that are necessary to prevent a crisis from spiraling out of control.

In West Africa, too, they seem to have learned the value of being prepared. When Ferme returned to Liberia on March 7, she encountered airport staff fully protected with gowns, head covers, face screens, masks, and gloves. By the time she left the country, 10 days later, she said, “Airline personnel were setting up social distancing lines, and [rural vendors] hawking face masks. Motorcycle taxis drivers, the people most at risk after healthcare workers—all had goggles and face masks.”

The sheer number of COVID-19 cases indicates the road to recovery will take some time. Each must be identified, quarantined, and all contacts traced and tested. Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars. Northwestern University economists Martin Eichenbaum et al. modeled6 the cost of a yearlong shutdown to be $4.2 trillion, a cost that proactive countries will not face. A recent Harvard study7 published in Science suggests the virus will likely make seasonal appearances going forward, potentially requiring new waves of social distancing. In other words, initial hesitancy will have repercussions for years. In the future, smart containment principles,6 where restrictions are applied on the basis of health status, may temper the impact of these measures.

Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars.

Inaction was initially framed as promoting herd immunity, where spread of the virus is interrupted once everyone has fallen sick with it. This is because getting the virus results in the same antibody production process as getting vaccinated—but doesn’t require the development of a vaccine. The Johns Hopkins Bloomberg School of Public Health estimates that 70 percent of the population will need to be infected with or vaccinated against the virus8 for herd immunity to work. Progress toward it has been slow, and can only be achieved through direct infection with the virus, meaning many will die. A Stanford University study in Santa Clara County9 suggests only 2.5 percent to 4.2 percent of the population have had the virus. Another COVID hotspot in Gangelt, Germany, suggests 15 percent10—higher, but still nowhere near the 70 percent necessary for herd immunity. Given the dangers inherent in waiting on herd immunity, our best hope is a vaccine.

A key concern for effective vaccine development is viral mutation. This is because vaccines train the immune system to recognize specific shapes on the surface of the virus—a composite structure called the antigen. Mutations threaten vaccine development because they can change the shape of the relevant antigen, effectively allowing the pathogen to evade immune surveillance. But, so far, SARS-CoV-2 has been mutating slowly, with only one mutation found in the section most accessible to the immune system, the spike protein. What this suggests is that the viral genome may be sufficiently stable for vaccine development.

What we know, though, is that Ebola was extinguished due to cooperation between public health officials and community leaders. SARS-CoV ended when all cases were identified and quarantined. The Spanish Flu in 1918 vanished after two long, deadly seasons.

The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line. With 26 million unemployed and protests erupting around the country, it seems there are many who would prefer to risk life and limb rather than face financial insolvency. Applying smart containment principles in the aftermath of the shutdown might be the best way to get the economy moving again, while maintaining the safety of those at greatest risk. Going forward, vigilance and preparedness will be the watchwords of the day, and the most efficient way to prevent social and economic ruin.

Anastasia Bendebury and Michael Shilo DeLay did their PhDs at Columbia University. Together they created Demystifying Science, a science literacy organization devoted to providing clear, mechanistic explanations for natural phenomena. Find them on Twitter @DemystifySci.

References

1. Genomic epidemiology of novel coronavirus - Global subsampling. Nextstrain www.nextstrain.org.

2. Covid-19 TrialsTracker. TrialsTracker www.trialstracker.net.

3. Struck, M. Vaccine R&D success rates and development times. Nature Biotechnology 14, 591-593 (1996).

4. Breman, J. & Johnson, K. Ebola then and now. The New England Journal of Medicine 371 1663-1666 (2014).

5. Baseler, L., Chertow, D.S., Johnson, K.M., Feldmann, H., & Morens, D.M. THe pathogenesis of Ebola virus disease. The Annual Review of Pathology 12, 387-418 (2017).

6. Eichenbaum, M., Rebell, S., & Trabandt, M. The macroeconomics of epidemics. The National Bureau of Economic Research Working Paper: 26882 (2020).

7. Kissler, S., Tedijanto, C., Goldstein, E., Grad, Y., & Lipsitch, M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science eabb5793 (2020).

8. D’ Souza, G. & Dowdy, D. What is herd immunity and how can we achieve it with COVID-19? Johns Hopkins COVID-19 School of Public Health Insights www.jhsph.edu (2020).

9. Digitale, E. Test for antibodies against novel coronavirus developed at Stanford Medicine. Stanford Medicine News Center Med.Stanford.edu (2020).

10. Winkler, M. Blood tests show 14%of people are now immune to COVID-19 in one town in Germany. MIT Technology Review (2020).

On January 5, six days after China officially announced a spate of unusual pneumonia cases, a team of researchers at Shanghai’s Fudan University deposited the full genome sequence of the causal virus, SARS-CoV-2, into Genbank. A little more than three months later, 4,528 genomes of SARS-CoV-2 have been sequenced,1 and more than 883 COVID-related clinical trials2 for treatments and vaccines have been established. The speed with which these trials will deliver results is unknown—the delicate bаlance of efficacy and safety can only be pushed so far before the risks outweigh the benefits. For this reason, a long-term solution like vaccination may take years to come to market.3

The good news is that a lack of treatment doesn’t preclude an end to the ordeal. Viral outbreaks of Ebola and SARS, neither of which had readily available vaccines, petered out through the application of consistent public health strategies—testing, containment, and long-term behavioral adaptations. Today countries that have previously battled the 2002 SARS epidemic, like Taiwan, Hong Kong, and Singapore, have shown exemplary recovery rates from COVID. Tomorrow, countries with high fatality rates like Sweden, Belgium, and the United Kingdom will have the opportunity to demonstrate what they’ve learned when the next outbreak comes to their shores. And so will we.

The first Ebola case was identified in 1976,4 when a patient with hemorrhagic symptoms arrived at the Yambuku Mission Hospital, located in what is now the Democratic Republic of Congo (DRC). Patient samples were collected and sent to several European laboratories that specialized in rare viruses. Scientists, without sequencing technology, took about five weeks to identify the agent responsible for the illness as a new member of the highly pathogenic Filoviridae family.

The first Ebola outbreak sickened 686 individuals across the DRC and neighboring Sudan. 453 of the patients died, with a final case fatality rate (CFR)—the number of dead out of number of sickened—of 66 percent. Despite the lethality of the virus, sociocultural interventions, including lockdowns, contact-tracing, campaigns to change funeral rites, and restrictions on consumption of game meat all proved effective interventions in the long run.

That is, until 2014, when there was an exception to the pattern. Ebola appeared in Guinea, a small country in West Africa, whose population had never before been exposed to the virus. The closest epidemic had been in Gabon, 13 years before and 2,500 miles away. Over the course of two years, the infection spread from Guinea into Liberia and Sierra Leone, sickening more than 24,000 people and killing more than 10,000.

Countries that have previously battled the 2002 SARS epidemic, like Taiwan and Hong Kong, have shown exemplary recovery rates.

During the initial phase of the 2014 Ebola outbreak, rural communities were reluctant to cooperate with government directives for how to care for the sick and the dead. To help incentivize behavioral changes, sociocultural anthropologists like Mariane Ferme of the University of California, Berkeley, were brought in to advise the government. In a recent interview with Nautilus, Ferme indicated that strategies that allowed rural communities to remain involved with their loved ones increased cooperation. Villages located far from the capital, she said, were encouraged to “deputize someone to come to the hospital, to come to the burial, so they could come back to the community and tell the story of the body.” For communities that couldn’t afford to send someone to the capital, she saw public health officials adopt a savvy technological solution—tablets to record video messages that were carried between convalescent patients and their families.

However, there were also systemic failures that, in Ferme’s opinion, contributed to the severity of the 2014 West African epidemic. In Sierra Leone, she said, “the big mistake early on was to distribute [weakly causal] information about zoonotic transmission, even when it was obviously community transmission.” In other words, although there had been an instance of zoonotic transmission—the virus jumping from a bat to a human—that initiated the epidemic, the principle danger was other contagious individuals, not game meat. Eventually, under pressure from relief groups, the government changed its messaging to reflect scientific consensus.

But the retraction shook public faith in the government and bred resentment. The mismatch between messaging and reality mirrors the current pandemic. Since the COVID outbreak began, international and government health officials have issued mixed messages. Doubts initially surfaced about the certainty of the virus being capable of spreading from person to person, and the debate over the effectiveness of masks in preventing infection continues.

Despite the confused messaging, there has been general compliance with stay-at-home orders that has helped flatten the curve. Had the public been less trusting of government directives, the outcome could have been disastrous, as it was in Libera in 2014. After a two-week lockdown was announced, the Liberian army conducted house-to-house sweeps to check for the sick and collect the dead. “It was a draconian method that made people hide the sick and dead in their houses,” Ferme said. People feared their loved ones would be buried without the proper rites. A direct consequence was a staggering number of active cases, and an unknown extent of community transmission. But in the end, the benchmark for the end of Ebola and SARS was the same. The WHO declared victory when the rate of new cases slowed, then stopped. By the same measure, when an entire 14-day quarantine period passes with no new cases of COVID-19, it can be declared over.

It remains possible that even if we manage to end the epidemic, it will return again. Driven by novel zoonotic transmissions, Ebola has flared up every few years. Given the extent of COVID-19’s spread, and the potential for the kind of mutations that allow for re-infection, it may simply become endemic.

Two factors will play into the final outcome of COVID-19 are pathogenicity and virulence. Pathogenicity is the ability of an infectious agent to cause disease in the host, and is measured by R0—the number of new infections each patient can generate. Virulence, on the other hand, is the amount of harm the infectious agent can cause, and is best measured by CFR. While the pathogenicity of Ebola, SARS, and SARS-CoV-2 is on the same order—somewhere between 1 to 3 new infections for each patient, virulence differs greatly between the two SARS viruses and Ebola.

The case fatality rate for an Ebola infection is between 60 to 90 percent. The spread in CFR is due to differences in infection dynamics between strains. The underlying cause of the divergent virulence of Ebola and SARS is largely due to the tropism of the virus, meaning the cells that it attacks. The mechanism by which the Ebola virus gains entry into cells is not fully understood, but it has been shown the virus preferentially targets immune and epithelial cells.5 In other words, the virus first destroys the body’s ability to mount a defense, and then destroys the delicate tissues that line the vascular system. Patients bleed freely and most often succumb to low blood pressure that results from severe fluid loss. However, neither SARS nor SARS-CoV-2 attack the immune system directly. Instead, they enter lung epithelial cells through the ACE2 receptor, which ensures a lower CFR. What is interesting about these coronaviruses is that despite their similar modes of infection, they demonstrate a range of virulence: SARS had a final CFR of 10 percent, while SARS-CoV-2 has a pending CFR of 1.4 percent. Differences in virulence between the 2002 and 2019 SARS outbreaks could be attributed to varying levels of care between countries.

The chart above displays WHO data of the relationship between the total number of cases in a country and the CFR during the 2002-2003 SARS-CoV epidemic. South Africa, on the far right, had only a single case. The patient died, which resulted in a 100 percent CFR. China, on the other hand, had 5,327 cases and 349 deaths, giving a 7 percent CFR. The chart below zooms to the bottom left corner of the graph, so as to better resolve critically affected countries, those with a caseload of less than 1,000, but with a high CFR.

Here is Hong Kong, with 1,755 cases and a 17 percent CFR. There is also Taiwan, with 346 cases and an 11 percent CFR. Finally, nearly tied with Canada is Singapore with 238 cases and a 14 percent CFR.

With COVID-19, it’s apparent that outcome reflects experience. China has 82,747 cases of COVID, but has lowered their CFR to 4 percent. Hong Kong has 1,026 cases and a 0.4 percent CFR. Taiwan has 422 cases at 1.5 percent CFR, and Singapore with 8,014 cases, has a 0.13 percent CFR.

It was the novel coronavirus identification program established in China in the wake of the 2002 SARS epidemic that alerted authorities to SARS-CoV-2 back in November of 2019. The successful responses by Taiwan, Hong Kong, and Singapore can also be attributed to a residual familiarity with the dangers of an unknown virus, and the sorts of interventions that are necessary to prevent a crisis from spiraling out of control.

In West Africa, too, they seem to have learned the value of being prepared. When Ferme returned to Liberia on March 7, she encountered airport staff fully protected with gowns, head covers, face screens, masks, and gloves. By the time she left the country, 10 days later, she said, “Airline personnel were setting up social distancing lines, and [rural vendors] hawking face masks. Motorcycle taxis drivers, the people most at risk after healthcare workers—all had goggles and face masks.”

The sheer number of COVID-19 cases indicates the road to recovery will take some time. Each must be identified, quarantined, and all contacts traced and tested. Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars. Northwestern University economists Martin Eichenbaum et al. modeled6 the cost of a yearlong shutdown to be $4.2 trillion, a cost that proactive countries will not face. A recent Harvard study7 published in Science suggests the virus will likely make seasonal appearances going forward, potentially requiring new waves of social distancing. In other words, initial hesitancy will have repercussions for years. In the future, smart containment principles,6 where restrictions are applied on the basis of health status, may temper the impact of these measures.

Countries that failed to act swiftly, which allowed their case numbers to spiral out of control, will pay in lives and dollars.

Inaction was initially framed as promoting herd immunity, where spread of the virus is interrupted once everyone has fallen sick with it. This is because getting the virus results in the same antibody production process as getting vaccinated—but doesn’t require the development of a vaccine. The Johns Hopkins Bloomberg School of Public Health estimates that 70 percent of the population will need to be infected with or vaccinated against the virus8 for herd immunity to work. Progress toward it has been slow, and can only be achieved through direct infection with the virus, meaning many will die. A Stanford University study in Santa Clara County9 suggests only 2.5 percent to 4.2 percent of the population have had the virus. Another COVID hotspot in Gangelt, Germany, suggests 15 percent10—higher, but still nowhere near the 70 percent necessary for herd immunity. Given the dangers inherent in waiting on herd immunity, our best hope is a vaccine.

A key concern for effective vaccine development is viral mutation. This is because vaccines train the immune system to recognize specific shapes on the surface of the virus—a composite structure called the antigen. Mutations threaten vaccine development because they can change the shape of the relevant antigen, effectively allowing the pathogen to evade immune surveillance. But, so far, SARS-CoV-2 has been mutating slowly, with only one mutation found in the section most accessible to the immune system, the spike protein. What this suggests is that the viral genome may be sufficiently stable for vaccine development.

What we know, though, is that Ebola was extinguished due to cooperation between public health officials and community leaders. SARS-CoV ended when all cases were identified and quarantined. The Spanish Flu in 1918 vanished after two long, deadly seasons.

The final outcome of COVID-19 is still unclear. It will ultimately be decided by our patience and the financial bottom line. With 26 million unemployed and protests erupting around the country, it seems there are many who would prefer to risk life and limb rather than face financial insolvency. Applying smart containment principles in the aftermath of the shutdown might be the best way to get the economy moving again, while maintaining the safety of those at greatest risk. Going forward, vigilance and preparedness will be the watchwords of the day, and the most efficient way to prevent social and economic ruin.

Anastasia Bendebury and Michael Shilo DeLay did their PhDs at Columbia University. Together they created Demystifying Science, a science literacy organization devoted to providing clear, mechanistic explanations for natural phenomena. Find them on Twitter @DemystifySci.

References

1. Genomic epidemiology of novel coronavirus - Global subsampling. Nextstrain www.nextstrain.org.

2. Covid-19 TrialsTracker. TrialsTracker www.trialstracker.net.

3. Struck, M. Vaccine R&D success rates and development times. Nature Biotechnology 14, 591-593 (1996).

4. Breman, J. & Johnson, K. Ebola then and now. The New England Journal of Medicine 371 1663-1666 (2014).

5. Baseler, L., Chertow, D.S., Johnson, K.M., Feldmann, H., & Morens, D.M. THe pathogenesis of Ebola virus disease. The Annual Review of Pathology 12, 387-418 (2017).

6. Eichenbaum, M., Rebell, S., & Trabandt, M. The macroeconomics of epidemics. The National Bureau of Economic Research Working Paper: 26882 (2020).

7. Kissler, S., Tedijanto, C., Goldstein, E., Grad, Y., & Lipsitch, M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science eabb5793 (2020).

8. D’ Souza, G. & Dowdy, D. What is herd immunity and how can we achieve it with COVID-19? Johns Hopkins COVID-19 School of Public Health Insights www.jhsph.edu (2020).

9. Digitale, E. Test for antibodies against novel coronavirus developed at Stanford Medicine. Stanford Medicine News Center Med.Stanford.edu (2020).

10. Winkler, M. Blood tests show 14%of people are now immune to COVID-19 in one town in Germany. MIT Technology Review (2020).

Lead image: Castleski / Shutterstock

When I worked as a TV reporter covering health and science, I would often be recognized in public places. For the most part, the interactions were brief hellos or compliments. Two periods of time stand out when significant numbers of those who approached me were seeking detailed information: the earliest days of the pandemic that became HIV/AIDS and during the anthrax attacks shortly following 9/11. Clearly people feared for their own safety and felt their usual sources of information were not offering them satisfaction. Citizens’ motivation to seek advice when they feel they aren’t getting it from official sources is a strong indication that risk communication is doing a substandard job. It’s significant that one occurred in the pre-Internet era and one after. We can’t blame a public feeling misinformed solely on the noise of the digital age.

America is now opening up from COVID-19 lockdown with different rules in different places. In many parts of the country, people have been demonstrating, even rioting, for restrictions to be lifted sooner. Others are terrified of loosening the restrictions because they see COVID-19 cases and deaths still rising daily. The officials deciding what to open, and when, seldom offer thoughtful rationales. Clearly, risk communication about COVID-19 is failing with potentially dire consequences.

A big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do.

Peter Sandman is a foremost expert on risk communication. A former professor at Rutgers University, he was a top consultant with the Centers for Disease Control in designing crisis and emergency risk-communication, a field of study that combines public health with psychology. Sandman is known for the formula Risk = Hazard + Outrage. His goal is to create better communication about risk, allowing people to assess hazards and not get caught up in outrage at politicians, public health officials, or the media. Today, Sandman is a risk consultant, teamed with his wife, Jody Lanard, a pediatrician and psychiatrist. Lanard wrote the first draft of the World Health Organization’s Outbreak Communications Guidelines. “Jody and Peter are seen as the umpires to judge the gold standard of risk communications,” said Michael Osterholm of the Center for Infectious Disease Research and Policy at the University of Minnesota. Sandman and Lanard have posted a guide for effective COVID-19 communication on the center’s website.

I reached out to Sandman to expand on their advice. We communicated through email.

Sandman began by saying he understood the protests around the country about the lockdown. “It’s very hard to warn people to abide by social-distancing measures when they’re so outraged that they want to kill somebody and trust absolutely nothing people say,” he told me. “COVID-19 outrage taps into preexisting grievances and ideologies. It’s not just about COVID-19 policies. It’s about freedom, equality, too much or too little government. It’s about the arrogance of egghead experts, left versus right, globalism versus nationalism versus federalism. And it’s endlessly, pointlessly about Donald Trump.”

Since the crisis began, Sandman has isolated three categories of grievance. He spelled them out for me, assuming the voices of the outraged:

• “In parts of the country, the response to COVID-19 was delayed and weak; officials unwisely prioritized ‘allaying panic’ instead of allaying the spread of the virus; lockdown then became necessary, not because it was inevitable but because our leaders had screwed up; and now we’re very worried about coming out of lockdown prematurely or chaotically, mishandling the next phase of the pandemic as badly as we handled the first phase.”

• “In parts of the country, the response to COVID-19 was excessive—as if the big cities on the two coasts were the whole country and flyover America didn’t need or didn’t deserve a separate set of policies. There are countless rural counties with zero confirmed cases. Much of the U.S. public-health profession assumes and even asserts without building an evidence-based case that these places, too, needed to be locked down and now need to reopen carefully, cautiously, slowly, and not until they have lots of testing and contact-tracing capacity. How dare they destroy our economy (too) just because of their mishandled outbreak!”

• “Once again the powers-that-be have done more to protect other people’s health than to protect my health. And once again the powers-that-be have done more to protect other people’s economic welfare than to protect my economic welfare!” (These claims can be made with considerable truth by healthcare workers; essential workers in low-income, high-touch occupations; residents of nursing homes; African-Americans; renters who risk eviction; the retired whose savings are threatened; and others.)

In their article for the Center for Infectious Disease Research and Policy, Sandman and Lanard point out that coping with a pandemic requires a thorough plan of communication. This is particularly important as the crisis is likely to enter a second wave of infection, when it could be more devastating. The plan starts with six core principles: 1) Don’t over-reassure, 2) Proclaim uncertainty, 3) Validate emotions—your audience’s and your own, 4) Give people things to do, 5) Admit and apologize for errors, and 6) Share dilemmas. To achieve the first three core principles, officials must immediately share what they know, even if the information may be incomplete. If officials share good news, they must be careful not to make it too hopeful. Over-reassurance is one of the biggest dangers in crisis communication. Sandman and Lanard suggest officials say things like, “Even though the number of new confirmed cases went down yesterday, I don’t want to put too much faith in one day’s good news.” 

Sandman and Lanard say a big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do. They caution against invoking “science” as a sole reason for action, as science in the midst of a crisis is “incremental, fallible, and still in its infancy.” Expressing empathy, provided it’s genuine, is important, Sandman and Lanard say. It makes the bearer more human and believable. A major tool of empathy is to acknowledge the public’s fear as well as your own. There is good reason to be terrified about this virus and its consequences on society. It’s not something to hide.

Sandman and Lanard say current grievances with politicians, health officials, and the media, about how the crisis has been portrayed, have indeed been contradictory. But that makes them no less valid. Denying the contradictions only amplifies divisions in the public and accelerates the outrage, possibly beyond control. They strongly emphasize one piece of advice. “Before we can share the dilemma of how best to manage any loosening of the lockdown, we must decisively—and apologetically—disabuse the public of the myth that, barring a miracle, the COVID-19 pandemic can possibly be nearing its end in the next few months.”

Robert Bazell is an adjunct professor of molecular, cellular, and developmental biology at Yale. For 38 years, he was chief science correspondent for NBC News.

The version published in China Daily omitted a reference to the illness originating in China and spreading to the rest of the world. The piece was published in full on the authors' websites.

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