April is mathematics awareness month, and this essay is about math and probability. Actuarial tables are used by the insurance industry to calculate risk. Actuarial data suggests that for Covid-19 there are significant variations in risk. In all likelihood, the number of deaths from Covid-19 will be comparable to other causes of death in
Let's start by using
Bad Data Means Bad Decisions
Deciding when the cost of not letting people go back to work outweighs the risk of increased mortality requires estimating the likelihood of death. The dilemma here is that we do not know the actual number of infections, and respected researchers say that mortality estimates are off by an order of magnitude. One study in
This means we can dismiss predictions of a pandemic like the Black Death or the 1918 influenza epidemic as exaggerated. Some of this exaggeration is driven by discontent with an administration widely perceived as erratic. Unfortunately, some reporting on Covid-19 is equally erratic. Approaching the pandemic as an actuarial problem suggests that too much of the public discussion is irrational. Reports that
The problem with a maximalist "complete shutdown" is that it maximizes economic harm. We need to weigh the Covid-19 response against the social distress caused by increased unemployment. Some estimates predict massive unemployment and a loss of as much as 24 percent of GDP because of the shutdown. If the 2008-2009 global financial crisis is a precedent, suicide rates will increase dramatically as will addiction and homelessness. We know that recession and unemployment decrease life expectancy and are accompanied by and exacerbate a range of other social problems that can last for years. These social problems will harm a much larger percentage of the
Actuarial data shows that Covid-19 mortality rates vary widely by age, health conditions, and location. Testing data would let us assess whether there are intermediate measures that reduce risk of mortality without massive economic harm. The initial lack of testing data is a significant handicap for determining how to manage risk. Actuarial data suggests that tailored policies could be effective. Countries such as
Data and Democracy
The math behind the Covid-19 response points to several areas for further work. The first, judging from the experience of the countries that were more successful in managing the outbreak, is how
Covid-19 also highlights a larger problem for democratic policymaking. Elected officials are influenced by public opinion. In turn, public opinion is shaped by media reporting, some of which can be inaccurate or alarmist. The internet and social media increase a natural human proclivity to emphasize risk. The mechanisms of democratic policymaking need to adjust to this new era of rapid and pervasive access to information and opinion presented in ways that make it difficult to distinguish between the two. Technology can remedy this, but the need for better data in democratic governance comes at a time when traditional sources of expertise in academia and the media face skepticism and new competition in the online environment.
In the future, better technology might allow citizens to ask, "Siri, is this claim of 200,000 American Covid deaths accurate?" The response from an improved AI assistant would be, "No, it is wrong, and here's why." The algorithms currently used by digital assistants are not sophisticated enough to do more than scrape the web, guaranteeing inaccuracy. What the new mechanisms for public policy in the information age will look like, how they will be shaped by improvements in the automation of knowledge and data analytics, and, above all, what voters will accept as authoritative is far from clear. Technology has brought us a contaminated information space; now the task is to see if technology can clean it up.
We Have Made This Mistake Before
The public discussion of Covid-19 has overemphasized risk. This is important because self-inflicted damage from overreaction to risk does real harm. After the 9/11 attacks, the Intelligence Community held a wargame on the responses to nationwide terrorist attacks. The game found that draconian responses (which included shutdowns) did more harm than terrorists by snarling the economy. We are approaching a similar situation in the response to Covid-19. The best policy would balance the risk of additional deaths against the certainty of economic damage, but much of the discussion has underestimated social and economic harm.
Actuarial data helps us make decisions about risk, and in this case, it is the risk of ending the draconian shutdowns. Shutdowns cost