A New York City Fire Department Emergency Medical Technician wheels a patient into an emergency arrival area at Elmhurst Hospital in Queens, N.Y., April 6, 2020. (Eduardo Munoz/Reuters)

Standards for pessimists, standards for optimists

NRPLUS MEMBER ARTICLE I n A. A. Milne’s classic Winne-the-Pooh children’s tales, Eeyore, the old gray donkey, is perennially pessimistic and gloomy. He always expects the worst to happen.

Milne understood that Eeyore’s outbursts of depression could at first be salutatory but then become monotonous. The outlook of the pessimist (“if you think it’s bad now, just wait”) always enjoys advantages over both the realist (“so what, life goes on”) and the optimist (“oh, come on, it can’t be that bad”).


When the pessimist frequently errs in his gloomy prognostications, he can plead that they were intended to be didactic, if not therapeutic. Only by offering scarifying models can the glum epidemiologist and statesman sufficiently terrify the public and thereby allow policymakers to enact the necessary draconian shelter-in-place protocols. That strategy could apply to the recent near celebrity Neil Morris Ferguson, OBE FMedSci, the British epidemiologist and professor of mathematical biology at the Imperial College in London, whose “2 million” possible deaths terrified America into lockdown, just as his modeled “500,000” fatalities in Britain did the same in his own homeland.

If the Eeyores are proven right, then, they are seen as not only prescient but sanctified — the voices in the wilderness who spoke the inconvenient truths that saved lives.


The sunnier prognosticators suffer a lose-lose dilemma rather than the pessimist’s win-win chances. If one doubts these original nightmarish Imperial College worst-case predications of 2 million-plus deaths in the United States, and is proven correct, it matters little. The pessimist argues that it was only his bleak forecasts that changed behaviors and that, without such changes, the optimist’s obviously faulty data and poor reasoning would have led policymakers over a cliff.


If the optimist is wrong and the situation becomes far grimmer than he initially predicted, he is not just wrong but culpable, with, to quote the Boston Globe, “blood on his hands.”

So far no one is suggesting that some of the wild-eyed modeling of the Imperial College in the U.K. led to what will be seen in retrospect and hindsight as not just wrong but dangerously so — policies that destroyed a booming economy and that unnecessarily cost hundreds if not thousands of lives. Oddly, the pessimist does not suffer that reproof of causing widespread mayhem that the optimist does if the virus proves deadlier than he thinks.

Yet many of these gloomy models that have had clear policy complications do not include hypotheses that fully weigh possible herd immunity, radically different initial exposures of the infected to viral load, geometric increases in the efficacy of treatment and social policies, and the institutionalization of new habits of collective hygiene and prevention. The number of researchers who study COVID-19 worldwide increases daily, which increases the odds that they’ll hone efficacious treatments. Anyone who has studied the nearly unbelievable monthly leaps in Allied wartime production between 1942 and 1944 could appreciate the ability of Western free-market economies, the U.S. in particular, to achieve geometric rates of industrial-production ramp-ups.



Optimists and realists who do not downplay the particular lethality of the virus among the elderly, the compromised, and young health workers probably believe that the viral year may end up comparable to past influenza epidemics: similar to or less serious than the 1957 outbreak that killed 116,000 Americans, or the H1N1 virus of 2009, which eventually infected 60.8 million, hospitalized 274,304, and may have killed 12,469 — or perhaps a bad flu year like 2017, which likely killed more than 60,000 Americans, put nearly a million in the hospital, and may have infected more than 60 million.

Kindred realists add that, should the shutdown continue much longer, the increase in suicides, depression, anxieties, stress, and substance abuse may ultimately kill more Americans than COVID-19 — well aside from the multiyear ripples of damage from a multi-trillion-dollar hit to the economy and a staggering debt passed on to generations of Americans not yet born.


Added to the volatile mix and acrimony the fact that 2020 is an election year. The outcome may hinge on perceptions of how well, or poorly, President Trump handles the crisis. That report card will be adjudicated on all sorts of criteria from economic data and third-quarter reports to the numbers of infections, deaths, and infection and fatality percentages compared with those of other countries (if the existent global data is reliable) — in a climate in which over 90 percent of media coverage is negative to Trump, as the Shorenstein Center on Media, Politics and Public Policy at Harvard found long before the outbreak of COVID-19.

For now, there may be a great deal of fluidity across party lines in reaction to the outbreak. But, as a general, unscientific observation, Trump supporters seem more optimistic and more eager to return to semi-normal life. His critics prefer longer shelter-in-place policies. The former cite economic prognoses more; the latter, medical modeling. Human nature being what it is, most Americans know that politicos are gaming the shutdowns-versus-infection question in an effort to discover what America wants — and it’s a given that what the public wants now won’t necessarily be what later, with hindsight, it claims that it wanted at this time.

Salaried professionals seem less vulnerable to the economic ravages from the shutdown than the self-employed are, and those working in the public sector are less vulnerable than private-sector workers. Perhaps the poorer and middle classes, more vulnerable to recession than the coastal professionals, and more inured to the reality of economic hardship, favor risking a more rapid return to normality. The coastal professionals seem to want near absolute certainty about the danger of infections that they see as a greater threat than a temporary cut in pay. As the more health-conscious and financially blessed, they can better afford to play the odds of economic downturn than epidemic infection.

“Science” cuts both ways. Economists can match the bleak prognostications of epidemiologists and doctors, presenting models to show that more will die eventually from shelter-in-place economic slowdowns than from coronavirus infections. For now, we have a contest between disciplines of pessimists versus pessimists, in that few economists are offering rosy scenarios of recovery from extended shutdowns, and few epidemiologists are offering scenarios analogous to the 2009 H1N1 or the 2017 flu.


In our present predicament, much of the virus modeling is nearly worthless. We have no reliable data on the number of those who have been infected, or even those who are now carrying the active virus. We suspect only that the number of positives is far larger than the minority of those who seek testing because they are not feeling well or they believe they were exposed to virus carriers — even when the vast majority of people tested (over 90 percent?) turn our not to have COVID-19.

Even the death rate is not quite as reliable as we wish to believe, given that each country seems to have different standards in determining who dies with the virus (while having other underlying conditions such as diabetes and cardiovascular risks) and who dies directly because of it. Nonetheless, the number of deaths thought to be primarily caused by COVID-19 is a more reliable statistic than the number of known positive cases. So is the population number of a given state or nation.

If we calculate the known COVID-19 deaths in a known population, we find a more or less reliable statistic of deaths per million of population. And by that measure, the U.S. is doing “well,” if we dare use such an expression in times of plague. America’s current hourly fluctuating fatality rate per million fares well in comparison with that of other large European nations (only German usually has a somewhat lower percentage each day).

Whether the shutdown continues is not predicated only on the terrible arithmetic of how many Americans will additionally die of the virus when shelter-in-place and other restrictions are lifted versus how many will die if the economy goes into severe recession and Americans stay confined to close quarters.

Rather, the decision will ultimately be based on the mood of the American people, itself massaged by polls, the media, perceptions of self-interest, and politicians. At the point when Americans believe that the virus — however more terrifying, more contagious, and more novel than the flu in its methods of killing people — nevertheless ultimately is as bad, or even not as bad, as a bad flu, then they will risk a return to semi-normalcy, as they did in 1956, 2009 and 2017 when they dealt with a severe flu season without today’s draconian measures. If Americans are convinced that death by coronavirus probably hinges on whether the infected person of any age has preexisting coronary, pulmonary, or diabetes morbidities, or is a health-care, front-line worker exposed hourly to viral tsunamis, then they can make the necessary adjustments and take precautions.

More important, once reliable antibody testing spreads — predicated on representative criteria that include region, age, gender, race, occupation, current health status, etc. — it will provide some picture of how many have had the virus or currently have it. With this information, we will obtain far more accurate data about the number of cases and the fatality rate per positives, and we’ll refine treatment options and focus.


Current premature speculative modeling, based on incomplete or faulty data, then will return to more normal parameters, offer more legitimate predictions, and regain lost credibility. Prior reputations based on optimistic or pessimistic forecasts will be sustained or damaged by the advent of harder science.

A final note. The learn-nothing/forget-nothing Left, in the manner of Talleyrand’s purported appraisal of the Bourbons, could be setting itself up for another 25th-Amendment-Stormy-Mueller-Impeachment–Wiley E. Coyote moment. By charging that Trump alone is responsible for the purportedly culpable reaction to the virus (as in such quotes as the “Trump virus,” “blood on his hands,” and “as the president fiddled, people died”), and specifically the initial lapses of the CDC in green-lighting tests and the comments (perhaps also channeled from Anthony Fauci’s initial assessments) that the virus could be comparable to a severe flu, the Left has assured that Trump will be credited for being responsible for good news if the Eeyores are wrong. Have the latter really modeled the effects of a variety of efficacious off-label drug treatments already in use, the unknown number of people who already have antibodies, putting the country back to work with reasonable cautionary policies in a month, a vaccine in near trials, and a global Nobel Prize race to find antidotes and prophylactics to the virus?

Given the media’s horrific prognostications of mass death, and given the Left’s insistence that Donald Trump owns the nation’s reaction to the virus, if the U.S. dodges the viral bullet and ends up by midsummer with far less death, infection, hospitalizations, and economic damage than predicted, then we know what follows: a boomerang that paints Trump as also owning a miraculous recovery from what was once forecast as some sort of 1918-type wipeout.

So what is called for from our modelers and pessimists is a little humility. The Eeyores simply do not have enough information — yet — to issue the sort of dire warnings that have now become characteristic and determinative in setting policies of life and death for hundreds of millions.

Finally, because of the new role of the electric lynch mob of social media, the polarized red–blue divide, the murky continuing role of China, the 2020 election year, the novelty of the coronavirus and the reaction to it, and the sensationalism and institutional bias of an often reckless media, be prepared for an impending Armageddon of blame and hindsight.