Coronavirus Crisis: Chaos, Counting, and Confronting Our Biases

Benjamin Radford

Credit: Celestia Ward

 

The numbers were grim, changed constantly, and told only part of the story. As of early June, there were nearly 6 million diagnosed cases of COVID-19 worldwide, with over 350,000 deaths and 2.3 million recovered. Of those, over 1.6 million patients and nearly 100,000 deaths were in the United States. With only a small percentage of Americans tested, it was likely that the true number of infected was far higher. Dozens of states were taking the first steps toward easing stay-at-home orders, at times spurred by “reopen” protests. Many nonessential businesses remained closed, and most Americans hadn’t sat down at a restaurant or gone to a movie theater in months. Conspiracy theories swirled, unemployment skyrocketed, economies sunk, and there were scattered reports of panic, shortages, and hoarding.

Getting Literate about Information

During times like this, there’s a natural—almost Pavlovian—tendency to follow the news closely. News and social media were awash with information about the covid-19 pandemic that had been spreading throughout the world since January. But much of what’s shared on social media about the coronavirus has been false, misleading, or speculative. It’s easy to become overwhelmed, and science-informed laypersons likely suffered this overload keenly, as we absorbed the firehose of information from a wide variety of sources: from the White House to the CDC, conspiracy cranks to Goop contributors.

It was a never-ending flood of information, and those charged with trying to sort it out were quickly inundated. We had a Goldilocks situation: too little, too much, and just the right amount of information about the covid-19 virus in the news and social media.

There’s information that’s true, including the most important, practical information—how to avoid coronavirus: wash your hands, avoid crowds, don’t touch your face, sanitize surfaces, and so on. This type of information has been proven accurate and consistent since the outbreak began. This is of course the smallest category of information: mundane but vital.

Then there was information that’s false, including a wide variety of rumors, miracle cures, misinformation, and so on. In March, the Center for Inquiry (CFI) set up an online Coronavirus Resource Center to help journalists and the public debunk false information and provide accurate resources. Drawing upon unique expertise from CFI’s Committee for Skeptical Inquiry, the site was at attempt to inoculate against misinformation. It provided original analytical articles, links examining the latest false medical claims and misinformation (one in April noted that Google saw more than 18 million daily malware and phishing emails related to covid-19 in just one week), and links to other general resources and knowledge centers, such as the CDC, FDA, and Johns Hopkins. (This report is an updated and revised blend of three original analyses written for and posted on that site. For more, see centerforinquiry.org/coronavirus.)

There was also a deluge of speculation, opinion, and conjecture. Dueling projections about the outbreak varied by orders of magnitude as experts and social media pundits alike shared their speculation. Of course, epidemiological models are only as good as the data that goes into them, and they are based on many premises, variables, and numerous unknowns.

Finally, there’s another, less-recognized category: information that is true but not helpful on an individual level, or what might be called “trivially true.” We usually think of false information being shared as harmful—and it certainly is—but trivially true information can also be harmful to public health. Even when it’s not directly harmful, it adds to the background of noise.

News media and social media are flooded with information and speculation that—even if accurate—is of little practical use to the average person. Much of the information is not helpful, useful, actionable, or applicable to daily life. One example might include photos of empty store shelves widely shared on social media, depicting the run on supplies such as sanitizer and toilet paper. The information was both true and accurate; it was not faked or staged. But it was not helpful, because it leads to panic buying, social contagion, and hoarding as people perceive a threat to their welfare and turn an artificial scarcity into a real one. Another example was President Trump’s reference on several occasions to the covid-19 virus as “the China virus.” It’s technically accurate that covid-19 was first detected in China—but it’s not a relevant nor useful detail. It doesn’t add to the discussion or help anyone’s understanding of what the disease is or how to deal with it. If anything, referring to it by other terms such as the China virus or Wuhan flu is likely to cause confusion and even foment racism.

Overreacting and Underreacting

There have been many pandemics throughout history, but none have taken place during such a connected time—both geographically and via social media. There’s a tendency to follow the news closely during times of emergency; especially when separated during isolation and quarantines, people are understandably desperate for information to keep their friends and family safe.

While scientists, doctors, nurses, epidemiologists, and others struggled to contain the disease, many other people were spending their self-isolating time on social media, sharing everything from useful information to dangerous misinformation to idle speculation. One thing most people could agree on was that other people and institutions weren’t handling the crisis correctly.

There was much debate about whether Americans and governments were underreacting or overreacting to the pandemic threat. This is of course a logical fallacy, because there are some 330 million Americans, and the answer is that some Americans were doing one or the other; most Americans, however, were doing neither.

On social media, the issue of how and whether the threat was being exaggerated often broke along political party lines, with conservatives seeing the danger as exaggerated or an outright hoax. There were countless examples of divisive rhetoric, and many framed the pandemic in terms of class warfare (for example, pitting the rich against the poor) or spinning the outbreak to suit other social and political agendas. This was understandable but not helpful. Pointing out that the wealthy universally have better access to health care than the poor is merely stating the obvious—like much pandemic information, it’s true but unhelpful. It’s not going to prevent someone’s family member from catching the virus and not going to open schools or businesses any faster. Liberals, conservatives, independents, and everyone else would benefit from putting aside the blame-casting, demonizing rhetoric and unite against the real enemy: the covid-19 virus that was sickening and killing people across races and social strata.

At the same time, it was important to recognize that the measures taken to slow the spread of the coronavirus in America and around the world—while necessary and effective—had taken a disproportionate toll on minorities. As Charles Blow wrote in The New York Times:

Social distancing is a privilege … this virus behaves like others, screeching like a heat-seeking missile toward the most vulnerable in society. And this happens not because it prefers them, but because they are more exposed, more fragile and more ill. … It is happening with poor people around the world, from New Delhi to Mexico City. If they go to work, they must often use crowded mass transportation, because low-wage workers can’t necessarily afford to own a car or call a cab.

While each side likes to paint the other in extreme terms as under- or overreacting, there’s plenty of common ground between these straw man positions. Most people were neither blithely and flagrantly ignoring medical advice nor spending their days in containment suits, terrified to go anywhere near others.

Idiots and Maniacs, Cassandras and Chicken Littles

People can take prudent precautions and still reasonably think or suspect that at least some of what’s going on in the world is an overreaction or underreaction. Policing other people’s opinions or shaming them because they’re taking the situation more (or less) seriously than we are is unhelpful. It’s like the classic George Carlin joke: “Anybody driving slower than you is an idiot, and anyone going faster than you is a maniac.”

Instead of seeing others as idiots and maniacs or panicky ninnies and oblivious fools, perhaps we can recognize that everyone is different. Some people are in poorer health than others; some people listen to misinformation more than others, and so on. Whether people were underreacting or overreacting is a matter of opinion, not fact. The truth, viewed from within the height of the pandemic, is that we simply don’t know what will happen or how bad it will get. Both positions argue from a false certainty, a smugness that they know better than others do, that the Cassandras and Chicken Littles will get their comeuppance. Humans crave certainty, but science can’t offer it. Certainty is why psychic predictions such as Sylvia Browne’s (supposedly foretelling the outbreak, as mentioned in the May/June 2020 issue of SI) have such popular appeal. The same is true for conspiracy theories and religion: All offer certainty—the idea that whatever happens is being directed by hidden powers and is all part of God’s plan (or the Illuminati’s schemes, take your pick).

Instead of bickering over how stupid or silly others are for however they’re reacting, it may be best to let them do their thing as long as it’s not hurting others. Polarization is a form of intolerance. Maybe this is a time to come together instead of mocking those who don’t share your opinions and fears. We all have different backgrounds and different tolerances for uncertainty.

Dueling Projections and Predictions

The record of wrong predictions about the coronavirus was long and growing by the hour. Around Valentine’s Day, the director of policy and emergency preparedness for the New Orleans Health Department, Sarah Babcock, said that Mardi Gras celebrations two weeks later should proceed, predicting, “The chance of us getting someone with coronavirus is low.” That projection was dead wrong: A month later, the city would have one of the worst outbreaks of covid-19 in the country, with correspondingly high death rates. Other projections overestimated the scale of infections, hospitalizations, and/or deaths.

It’s certainly true that many, if not most, news headlines about the virus were scary and alarmist; and that many, if not most, projections and predictions about covid-19 were wrong to a greater or lesser degree. There’s a plague of binary thinking, and it circulated in many forms. One claim involved a quasi-conspiracy that news media and public health officials were deliberately inflating covid-19 statistics. Some said it was being done to make Trump look incompetent at handling the pandemic; others said it was being done on Trump’s behalf to justify coming draconian measures, including Big Brother tracking.

Many suggested that media manipulation was to blame, claiming that numbers were being skewed by those with social or political agendas. There’s undoubtedly a grain of truth to that—after all, information has been weaponized for millennia—but there were more parsimonious (and less partisan) explanations for much of it, rooted in critical thinking and media literacy.

In many cases, it’s not experts and researchers who skew information but instead the news media who report on them. News media and social media, by their nature, highlight the aberrant extremes. Propelled by human nature and (for social media, algorithms), they selectively focus on the worst in society—the mass murders, the dangers, the cruelty, the outrages and disasters—and rarely profile the good.

When news media cover natural disasters, journalists photograph and film the dozens of homes that were flooded or wrenched apart by a tornado, not the tens or hundreds of thousands of neighboring homes that were unscathed. This isn’t some conspiracy by the news media to emphasize the bad, it’s just the nature of journalism—they report on what is new or different. But this often leads to the public overestimating the terrible state of the world—and those in it—as well as fear and panic. Another problem is news stories (whether about dire predictions or promising new drugs or trends) that are reported and shared without sufficient context. One notable example of an unvetted covid-19 news story that circulated widely concerned hydroxychloroquine, prematurely touted by Trump as a possible cure based on reports of a single French study of forty-two patients. Later studies failed to find evidence of the drug’s efficacy, and in April, a Brazilian study of the drug was stopped when some patients developed heart problems.

Uncertainties in Models and Testing

In addition to media biases toward worst-case views and simplicity, experts and researchers often have limited information to work with, especially in predictions. There were many potential sources of error in the epidemiological data about covid-19. Models are only as good as the information that goes into them; as they say: garbage in, garbage out. This is not to suggest that all the data is garbage, of course; it’s more a case of incomplete data in, incomplete data out.

One example of the uncertainty of data was the number of covid-19 deaths in New York City, one of the hardest-hit places. According to The New York Times:

The official death count numbers presented each day by the state are based on hospital data. Our most conservative understanding right now is that patients who have tested positive for the virus and die in hospitals are reflected in the state’s official death count … [however] The city has a different measure: Any patient who has had a positive coronavirus test and then later dies—whether at home or in a hospital—is being counted as a coronavirus death. … We also don’t really know how each of the city’s dozens of hospitals and medical facilities are counting their dead. For example, if a patient who is presumed to have coronavirus is admitted to the hospital, but dies there before they can be tested, it is unclear how they might factor into the formal death tally. There aren’t really any mechanisms in place for having an immediate, efficient method to calculate the death toll during a pandemic. Normal procedures are usually abandoned quickly in such a crisis.

Because of multiple co-morbidities and risk factors, pinpointing an exact cause of death can be difficult. If a person with pneumonia contracts covid-19 and soon dies, there’s no way to know for certain whether he or she would have died anyway; listing it as a COVID-19 death is not unreasonable. While it might seem inconceivably Dickensian (or suspicious) to some that in 2020 quantifying something as seemingly straightforward as death is complicated, this is not evidence of deception or anyone “fudging the numbers” but instead an ordinary and predictable lack of uniform criteria and reporting standards. The international situation is even more uncertain; different countries have different guidelines, making comparisons difficult. Not all countries have the same criteria for who should be tested, for example, or even had adequate numbers of tests available.

Incomplete Testing

Some people complained that everyone should be tested, suggesting that only the rich are being tested for the virus. There was a national shortage of tests, and in fact many in the public were being tested, but such complaints rather miss a larger point: Testing is of limited value to individuals. Screening the entire asymptomatic public is neither practical nor possible. Furthermore, though scientists were working on creating tests that yield faster and more accurate results, the ones so far have taken days. Because many people who carry the virus show no symptoms (or mild symptoms that mimic colds or even seasonal allergies), it’s entirely possible that a person could have been infected between the time they took the test and gotten a negative result back. So, it may have been true that a few days or a week earlier they hadn’t been infected, but they are now and don’t know it because they are asymptomatic. The point is not that the tests are flawed (though many were, and the British government wasted $20 million on faulty tests from Chinese companies), or that people should be afraid. Instead, it’s that testing, by itself, is of little value to the patient because of these uncertainties. If anything, it could provide a false sense of security and put others at risk.

If you’re ill, on a practical level—unless you’re very sick or at increased risk, as mentioned above—it doesn’t really matter whether you have covid-19 or not because (a) there’s nothing you can do about it except wait it out, like with any cold or flu; and (b) you should take steps to protect others anyway. People should assume that they are infected and act as they would for any communicable disease.

Certainty and the Unknown Knowns

Humans crave certainty and binary answers, but science can’t offer it. The truth is that we simply don’t know what will happen or how bad it will get. For many aspects of covid-19, we don’t have enough information to make accurate predictions. There are simply too many variables, too many factors involved. Even hindsight won’t be 20/20 but instead be seen by many through a partisan prism. We can never know alternative history or what would have happened; it’s like the concern over the “Y2K bug” two decades ago. Was it all over nothing? We don’t know because steps were taken to address the problem.

But uncertainty has been largely ignored by pundits and social media “experts” alike who routinely discuss and debate statistics while glossing over—or entirely ignoring—the fact that much of it is speculation and guesswork, unanchored by any hard data. Most people don’t know enough about epidemiology, statistics, or research design to have a good idea of how valid the disease data and projections are. It’s difficult for many people—and especially experts, skeptics, and scientists—to admit they don’t know the answer to a question. Even if it’s outside our expertise, we often feel as if not knowing (or even not having a defensible opinion) is a sign of ignorance or failure. Real experts freely admit uncertainty about the data.

One element of conspiracy thinking is that those who disagree are either stupid (that is, gullible “sheeple” who believe and parrot everything they see in the news—usually specifically the “mainstream media” or “MSM”) or simply lying (experts and journalists across various media platforms who know the truth but are intentionally misleading the public for political or economic gain). This “If You Disagree with Me, You Are Either Stupid or Dishonest” worldview has little room for uncertainty or charity, and it misunderstands the situation.

The appropriate position to take on most coronavirus predictions is one of agnosticism. It’s not that epidemiologists and other health officials have all the data they need to make good decisions and projections about public health and are instead carefully considering ways to fake data to deceive the public and journalists. It’s that they don’t have all the data they need to make better predictions, and as more information comes in, the projections do get more accurate. The solution is not to vilify or demonize doctors and epidemiologists but instead to understand the limitations of science and the biases of news and social media.

Social Media Hygiene

While self-isolating from the disease (and those who might carry it) is vital to public health, there’s a less-discussed aspect: Self-distancing from social media information on the virus, which is a form of social media hygiene. Six feet is enough distance in physical space, but it doesn’t apply to cyberspace where viral misinformation spreads unchecked.

The analogy between disease and misinformation is apt. Just as you can be a vector for a virus if you get it, you can be a vector for misinformation and fear. But you can stop it by removing yourself from it. You don’t need hourly updates on most aspects of the pandemic. Most of what you see and read isn’t relevant to you. The idea is not to ignore important and useful information about the coronavirus; in fact, it’s exactly the opposite: to better distinguish the news from the noise, the relevant from the irrelevant.

Doctors around the world were photographed sharing signs saying, “We’re at work for you. Please stay home for us.” That was excellent advice, but we can take it further. While at home not becoming a vector for disease—or even after restrictions are lifted—we can also take steps not to become a vector for misinformation. During a time when people are isolated, it’s cathartic to vent on social media. Humans are social creatures, and we find ways to connect even when we can’t physically. Especially during a time of international crisis, it’s easy to become outraged about one or another aspect of the pandemic. Everyone has opinions about what is (or isn’t) being done and what should (or shouldn’t) be done. Everyone’s entitled to those opinions, but they should be aware that those opinions expressed on social media have consequences and may well harm others, albeit unintentionally. Just as it feels good to physically hang out with other people (but may in fact be dangerous to them), it feels good to let off steam to others in your online social circles (but may be dangerous to them).

You don’t know who will end up seeing your posts and comments (such is the nature of “viral” posts and memes), and while you may think little of it, others may be more vulnerable. Just as people take steps to protect those with compromised immune systems, it may be wise to take similar steps to protect those with compromised psychological defenses on social media—those suffering from anxiety, depression, or other issues who are especially vulnerable at this time. There are many ways to reach out to others and share concerns and feelings in a careful and less public way—through email, direct messaging, video calls, and even good old-fashioned letters. Like anything else, people can express feelings and concerns in measured, productive ways, ways that are less likely to harm others.

Though the public loves to blame the news media for misinformation—and often deservedly so—we are less keen to see the culprit in the mirror. Many people, especially on social media, fail to recognize that they have become de facto news outlets through the stories and posts they share. We cannot control what news organizations (or anyone else) publishes or puts online. But we can—and indeed we have an obligation to—help stop the spread of misinformation in all its forms. You can’t do anything about how many deaths there are in China or Italy. You can’t do anything about whether or not medical masks are being manufactured and shipped quickly enough. But you can do something about bad information online.

Social media hygiene can be as simple as not forwarding, liking, or sharing that dubious news story before checking the facts, especially if that story seems crafted to encourage social outrage. Before believing or sharing information on social media, ask yourself questions. Is it true? Is it from a reliable source? But there are other questions to ask: Even if it may be factually true, is it helpful or useful? Does it promote unity or encourage divisiveness? Are you sharing it because it contains practical information important to people’s health? Or are you sharing it just to have something to talk about, some vehicle to share your opinions? The signal-to-noise ratio is already skewed against useful information, which is being drowned out by false information, speculation, opinion, and trivially true information. The best advice at the height of the pandemic and now: Be safe, practice social and cyber distancing, and wash your hands.

Benjamin Radford

Benjamin Radford, M.Ed., is a scientific paranormal investigator, a research fellow at the Committee for Skeptical Inquiry, deputy editor of the Skeptical Inquirer, and author, co-author, contributor, or editor of twenty books and over a thousand articles on skepticism, critical thinking, and science literacy. His newest book is Investigating Ghosts: The Scientific Search for Spirits (2018).