Killing the Elephant

As the economy slowly comes to a partial halt, the opinion of most politicians, virtually all of the media and many health-case professionals is that saving lives MUST be our #1 priority. In the abstract, that view is hard to argue, but it's critically important when adopting policies, legislation, and mass restrictions on people, businesses, and society as whole to base decisions on accurate data—not emotion, or anecdotes, or data that has been tainted in a variety of different ways.

John P.A. Ioannidis (Professor of medicine, of epidemiology and population health, of biomedical data science, and of statistics at Stanford University) has written a detailed paper on the importance of statistical analysis before potentially damaging economic and societal decisions are made by our current leadership at the local, state and federal levels. He writes:

The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.

At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.

Draconian countermeasures have been adopted in many countries. If the pandemic dissipates — either on its own or because of these measures — short-term extreme social distancing and lockdowns may be bearable. How long, though, should measures like these be continued if the pandemic churns across the globe unabated? How can policymakers tell if they are doing more good than harm?

Ioannidis' analysis is arcane and detailed. He argues that the current "evidence" we have on COVID-19 is insufficient for the kinds of profound decisions (e.g., keeping children out of school for months at a time). He doesn't minimize the potential threat but notes that our estimates of mortality and spread may be off by orders of magnitude and that current statistical data are based on very limited samples that are often skewed by age, time of reporting, and many other factors. He writes:

Some worry that the 68 deaths from Covid-19 in the U.S. as of March 16 will increase exponentially to 680, 6,800, 68,000, 680,000 … along with similar catastrophic patterns around the globe. Is that a realistic scenario, or bad science fiction? How can we tell at what point such a curve might stop?

The most valuable piece of information for answering those questions would be to know the current prevalence of the infection in a random sample of a population and to repeat this exercise at regular time intervals to estimate the incidence of new infections. Sadly, that’s information we don’t have.

In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns. Unfortunately, we do not know if these measures work. School closures, for example, may reduce transmission rates. But they may also backfire if children socialize anyhow, if school closure leads children to spend more time with susceptible elderly family members, if children at home disrupt their parents ability to work, and more. School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease ...

Flattening the curve to avoid overwhelming the health system is conceptually sound — in theory. A visual that has become viral in media and social media shows how flattening the curve reduces the volume of the epidemic that is above the threshold of what the health system can handle at any moment.

Yet if the health system does become overwhelmed, the majority of the extra deaths may not be due to coronavirus but to other common diseases and conditions such as heart attacks, strokes, trauma, bleeding, and the like that are not adequately treated. If the level of the epidemic does overwhelm the health system and extreme measures have only modest effectiveness, then flattening the curve may make things worse: Instead of being overwhelmed during a short, acute phase, the health system will remain overwhelmed for a more protracted period. That’s another reason we need data about the exact level of the epidemic activity.

To date, we do not have statistical evidence on the virus that is trustworthy and accurate across all age groups and populations. Lacking that, we don't know whether morbidity is 5% as some claim or 0.5 percent as some data suggest. Ioannidis uses an interesting metaphor:

That huge range markedly affects how severe the pandemic is and what should be done. A population-wide case fatality rate of 0.05% is lower than seasonal influenza. If that is the true rate, locking down the world with potentially tremendous social and financial consequences may be totally irrational. It’s like an elephant being attacked by a house cat. Frustrated and trying to avoid the cat, the elephant accidentally jumps off a cliff and dies.

We need statistically valid, time-sequenced random testing across the United States before still more draconian measures are put into place. Hard decisions may very well be necessary, but only after statistical evidence is compelling. If we choose to proceed driven by emotion rather than data, we may very well kill the elephant while the cat runs free.

UPDATE (3-19-2020):
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Daniel Henninger comments on the political actions that are on-going:

Again, it’s hard to be optimistic. Even as medical professionals in hazmat suits focus on mitigating infection, Washington addresses financial panic with its own panic. Treasury Secretary Steven Mnuchin, in concert with House Speaker Nancy Pelosi, wants to throw a trillion dollars into the country. Meanwhile local officials in New York, Los Angeles and San Francisco are talking about releasing prisoners. And this even as an estimated 200,000 mom-and-pop stores in New York have voluntarily closed. Who’s going to release them?

Here’s a recovery idea Bernie Sanders won’t like, but what Bernie represents is looking pretty yesterday by now. Before this crisis, the real economy and the people who do real work were strong. When it’s over, every level of government—federal, state and local—should declare a two-year holiday from regulatory costs, such as the minimum wage. Ask any big-city shopkeeper or business owner if that relief wouldn’t help them hire back staff and turn the curve up quickly. Ask the laid-off workers if they’d take that deal.

The heroes of 9/11 were cops and firemen. The heroes of the pandemic of 2020 will be hospital workers. Miracles aren’t much in fashion, but if politicians took real risks to free the economy after the crisis, someone might even call them heroes.