How Trump Is Going to Get Away With a Pandemic

How Trump Is Going to Get Away With a Pandemic

How Trump Is Going to Get Away With a Pandemic

There are lots of ways for the Trump administration to cook the data to hide the extent of the coronavirus outbreak—in fact, it already is doing so.

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In the early days of the coronavirus outbreak in Wuhan, the Trump administration and right-wing commentators were only too keen to condemn the Chinese government’s secrecy about the epidemic and to proclaim themselves immune to such blatant coverups. “Citizens of democratic nations,” one observer wrote in a late February Atlantic story, “can reasonably expect a higher level of candor and accountability from their governments.”

If only.

By now, the administration’s failure to test Americans at scale and in a timely fashion—ensuring that the virus’s spread among us is virtually invisible—is well known. What is less known are all the other ways the administration has tried, and may continue to try, to massage the data to obscure the reality of the coronavirus pandemic in the United States.

Contagions are commonly understood as quantifiable biological phenomena that render certain brute facts. Either the test was conducted or not; either the result was positive or not; either the victim is alive or not. A consensus has formed that these material facts will be decisive in the post-epidemic political reckoning. Trump suggested as much in his recent announcement that a tally of 100,000 deaths would be proof of his success; Democratic candidate Joe Biden acknowledged the inescapable decisiveness of the facts of the epidemic, noting that “the proof, you know, is going to be in the pudding.” But the long history of secret contagions, and the opportunities to manipulate data to which the Trump administration is already availing itself, suggest otherwise.

Consider the testing fiasco. Not only did the administration bungle the rollout of testing for the virus, but, for a period, it also effectively expunged the data that might have tracked that failure from the official record.

The problem began earlier this month. As soon as it became clear that testing had gotten off to an embarrassingly slow and muddled start, the administration attempted to wash its hands of the business of collating the total number of Americans tested. On March 2, the Centers for Disease Control excised information about the number of people who had been tested from its website. “All of a sudden,” Wisconsin Representative Mark Pocan told CNN, “those stats vanished.” When Pocan complained to the CDC, he was told the agency would be “trying” to collate the state data and “might” share it publicly.

The administration justified this lack of transparency by pointing to its decision to decentralize coronavirus testing and allow private companies and labs to use their own test kits. That meant that collating the total number of people tested required collecting data from a wide range of untracked, disparate sources. It also meant that any comprehensive accounting of the number of Americans tested could become impossible. Strapped for resources, several states—including Maryland, New Jersey, Texas, and Louisiana, for examples—announced that they would no longer collect data on the number of people tested for the virus at all.

On March 10, the testing data finally re-materialized on the CDC website, but there was still a problem: The agency listed the number of “specimens” tested—an inflated and confusing figure, since at least two (and sometimes more) specimens are required for each person tested. In this breach, journalists launched a volunteer-driven effort called the Covid Tracking Project to attempt to piece together testing data, but they found the available data “incomplete” and “not useful to citizens or political leaders.” Still, their effort revealed that less than a quarter of the diagnostic tests promised by Trump’s FDA commissioner had been conducted, more than two weeks after they’d been promised—and that US testing has lagged far behind that of other countries.

Weeks after the virus took hold in this country, tracking remains compromised and incomplete. In the vacuum, officials have been free to disseminate exaggerated claims about the speed and scale of testing, obscuring both spread of the virus and the failure of their containment efforts. As a result, we may not know for months, if ever, the full extent of the virus’s spread among us.

The political incentive to manipulate data is baked into contagions. For many outbreaks, containment requires painful and certain short-term economic disruptions, in exchange for outcomes that are uncertain, long-term, and invisible. The most perfectly “contained” outbreak takes the form of an absence of excess deaths and illness. There is no triumphal victory. Nothing happens at all. Massaging the data alleviates political pressure for any unpalatable trade-offs.

And, as history shows, it’s surprisingly easy to do, because assessing the toll of any infectious pathogen is an exercise in estimation. Take one of our oldest known contagions, malaria. People who can’t access health care, or who don’t seek it out because they aren’t that ill or because they don’t think they’ll get any useful help, regularly go uncounted. Experts estimate that as much as 90 percent of the world’s malaria cases go unreported, as a result. But along with this vast amount of so-called “underreporting,” there’s also over-reporting. Clinicians aware of malaria’s ubiquity or eager for the ease of paperwork may simply presume their fever cases are caused by malaria, whether they take the trouble to spy malaria parasites in their patients’ blood or not. The sum total of malaria cases depends almost entirely on “assumption built on assumption built on assumption,” as one expert put it, providing ample opportunities to inflate or diminish statistics on the size of the contagion. Estimates on the number of malaria cases worldwide can vary by the hundreds of millions.

That’s why, far from being the sole province of authoritarian governments, conspiracies to conceal outbreaks in democratic societies go back centuries. In the face of an outbreak of cholera in New York City in 1832, for example, the Board of Health and the mayor refused to notify the public about the spread of the disease, instead issuing vague reports about “sudden deaths” from “unknown disease.” Hospital records where cholera patients were quarantined, which would have revealed the extent of the epidemic, mysteriously disappeared. Enraged local physicians who were coping with dying patients called it “criminal neglect,” and issued their own bulletins instead. The conspiracy helped protect the shipping industry, which continued to ferry cholera-infected passengers down canals and across oceans throughout the 19th century pandemics of cholera.

Italy hid its 1911 cholera outbreak, which killed 18,000 people, from the press, historians, and the international community for over 80 years. The disease had inconveniently erupted on the eve of the country’s 50th-anniversary celebrations. The prime minister sent a telegram to his public health authorities informing them to “obtain and maintain the greatest possible secrecy” about the outbreak. Officials stopped tallying cases diagnosed by physicians and coroners, as they’d done in the past, opting to report instead only those cases confirmed by lab tests, a shift that did nothing to change the course of the outbreak but slashed the official caseload in half nonetheless.

Government officials also secretly paid newspaper reporters to avoid mentioning the disease; censored telegrams that mentioned the scourge; and conducted nighttime raids on medical societies that dared to distribute cholera education materials, as the historian Frank Snowden described in his 1995 book, Naples in the Time of Cholera. Even as cholera spread and felled thousands of Italians, the Italian government manufactured the medical fiction that only a minor outbreak had occurred, which had been quickly contained. The German novelist Thomas Mann, who visited Italy during its secret contagion, called it a kind of “nameless horror.”

Today, more than a century later, another contagion manifests, its contours not fully known, as untold numbers of Americans across the country suffer through mysterious illnesses, chalked up to the flu, allergies, or “some bug.” Just how the administration might continue to cook the data as the Covid-19 outbreak progresses is a critical question.

One politically expedient way to manipulate the statistics is to tinker with the way cases are defined. Overly restrictive criteria for defining hurricane-related deaths, for example, allowed government officials in Puerto Rico to obscure the massive death toll from Hurricane Maria. For months, they counted only the 64 deaths directly caused by the storm, rather than the thousands of other deaths that independent analyses showed followed in its wake. The state updated its death toll a year later after being forced to by a court ruling, but by then national attention to the government’s mishandling of the disaster had long faded.

How might the Trump administration tinker with the criteria in the case of the new coronavirus? One possibility: by counting only those deaths that result directly from Covid-19 infection, as opposed to those deaths brought on by the cascading collapse of hospital systems, emergency response services, and the safety net more broadly.

Wide use of at-home Covid-19 self-testing kits could have a similar effect. Critics say users are unlikely to get an accurate result with such kits, since doing so requires an uncomfortable swab deep into the back of the nose or throat where the virus lurks. More likely, users will take a shallow swab, miss the virus, and obtain a happy but false negative result—contributing to a rosy and politically expedient underestimate of the epidemic. Along with hastily approving such self-testing kits, the administration’s top officials have touted the discomfort of more accurate lab tests. Vice President Pence called his “kind of invasive.” If hospitals were to muzzle their staff by, say, preventing them from sharing their work experiences—as anecdotal reports suggest some are—they might help conceal the extent of the outbreak, too, by obscuring the carnage unfolding in their wards.

For now, exaggerated claims abound. FEMA administrator Peter Gaynor, for example, said in an interview with ABC News on March 22 that the agency was “prepared to go to zero” in the national stockpile of masks and other protective medical gear, citing “hundreds of thousands of millions of things” being shipped to desperate hospitals. But when pressed, Gaynor admitted he couldn’t, in fact, provide even the “rough number” of masks shipped by the agency.

Meanwhile, Trump has been busing making inflated claims about data on the effectiveness of new treatments. A study on Covid-19 patients treated with hydroxychloroquine and azithromycin that Trump called “one of the biggest game changers in the history of medicine” in fact involved just 36 patients. STAT called the study “small and hastily designed even by the standard of Phase 1 studies.”

But the president tells us not to worry. He has said that ordinary car accidents are far worse than the untreatable, exponentially spreading pathogen. He has said that he doubts New York state needs 30,000 ventilators, because some major hospitals get along fine with just two. He has said he’d love to have the country “opened up by Easter.”

As the papers blared during Italy’s secret contagion, “There is no cholera, and never was!”

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