Is Preventing Deaths From COVID-19 Worth a Severe Recession? The answer depends on controversial assumptions about the epidemic’s lethality.
In a paper Three economists on Monday published the tradeoff between COVID-19 inclusion and economic activity in the United States. They estimate that “the optimal containment policy will make the recession more severe, but will save about half a million lives in the United States.” According to their model, aggressive control measures are more than double the drop in total consumption. The lead author, Northwestern University economist Martin Eichenbaum, says the difference over the course of a year would mean an additional $ 1 trillion reduction. That works out to about $ 2 million for every life saved, which seems like a bargain compared to the $ 9.3 million per life value used in the model.
Eichenbaum and his co-authors – Sergio Rebelo, also at Northwestern, and Mathias Trabandt of the Free University in Berlin – struggle with a problem that politicians usually ignored when responding to COVID-19: at what point do the costs of their interventions weigh up against the expected benefits? But the answer to that question depends on assumptions that are controversial, impossible to verify based on existing data, or both.
The value that Eichenbaum et al. Assign to each saved life is similar to the number calculated by Vanderbilt University economist W. Kip Viscusi based on labor market data. But it is arguably too high, because it does not take into account the age distribution of deaths from COVID-19, which are concentrated in the elderly. “We found that our conclusions are robust against reasonable distortions of this value,” say the economists.
More consistently, Eichenbaum et al. Assume a 1 percent death rate (CFR) for COVID-19, which is the highest level of the range that federal public health officials deem reasonable. Currently, the raw CFR is in the United States about 1.3 percent. But that percentage is undoubtedly an overestimate, as the denominator includes only confirmed cases.
Current testing capacity in the United States is very limited, and symptoms of COVID-19 are typically mild to nonexistent, meaning that many infected people will not seek medical attention or tests. Therefore, the actual number of infections is probably several times the official number. The size of that gap is critical in estimating the actual CFR.
If the number of U.S. infections is six times the official number – as it was in the early stages of the Chinese epidemic, according to an estimate—The actual CFR would be about 0.2 percent at this point, a fifth of the rate used in this study. Eichenbaum acknowledges that “the savings depend on the death rate,” although he cautions that you can’t simply multiply the cost per life saved, since people would behave differently in response to a significantly lower CFR. The real CFR for the United States cannot be calculated without testing everyone, or at least a nationally representative sample.
Another important variable is the percentage of the population that would eventually become infected without drastic measures. Eichenbaum and his co-authors use a figure of 65 percent, based on a March 11 speech by German Chancellor Angela Merkel, who said“The consensus among experts is that 60 to 70 percent of the population will remain infected as long as this remains the situation.” The in the worst case outlined by the U.S. Centers for Disease Control and Prevention (CDC) also envisions that 65 percent of Americans are infected, with an estimated 214 million infections and 1.7 million deaths.
Because Eichenbaum et al. Assume a 1 percent CFR, as opposed to the 0.8 percent that the CDC assumes, they predict even more deaths: 2.2 million. Even under their “optimal containment policy,” the number of deaths is the same as in the CDC’s worst-case scenario.
Merkel’s estimate that 60 to 70 percent of Germans would eventually become infected is equivalent to one two-year projection by the Robert Koch Institute, “based on model calculations.” Those calculations can be misleading if they do not sufficiently take into account adaptive behavior (avoiding crowds, limiting social interaction, extra attention to hygiene, etc.) This would be done without broad coercive measures such as lockdowns.
In any case, fear of a widespread infection seems at odds with hopes of herd immunity. “In the absence of treatments or vaccines, the only way to gain immunity is to become infected and restore,” Eichenbaum and his co-authors note. “Unfortunately, this process is accompanied by the death of many people who never recover from an infection. The need to develop ‘herd immunity’ is a characteristic of epidemics [that] serves as an important backdrop for our discussion of optimal policy. They say “the optimal way to achieve this critical level of immunity is becoming gradual[ing] control measures as infections increase and they slowly relax as new infections decrease. “
In addition to assuming a relatively high death rate in combination with widespread infection, the calculation of Eichenbaum et al. Does not include the full economic costs of aggressive intervention. “Our model abstracts from various forces that can affect the long-term performance of the economy,” they write. “These forces include bankruptcy costs, hysteresis effects of unemployment and supply chain destruction. It is important to embody these forces in macroeconomic models of epidemics and to study their positive and normative implications.”
Last week The New York Times described the cost-effectiveness of COVID-19 controls as “a taboo question”. Yesterday the Times careful raised the issue again. “Can we put a price tag on a life? “The headline asked.” The closure enforces a new look. ‘Certainly.
“Economists should do this cost-benefit analysis,” said Walter Scheidel, Stanford economic historian Times. “Why doesn’t anyone give figures on the economic costs of a month-long or a year-long cessation of lives saved? The whole discipline is well equipped for it. But there is some reluctance for people to stick their necks out. “
Eichenbaum, Rebelo and Trabandt deserve praise for sticking their necks out. But their efforts underscore the shaky empirical basis for supporting (or opposing) shutdowns. When “best estimates” for the CFR of COVID-19 range from 0.1 percent to 1 percent, as Assistant Secretary to Health Brett Giroir told reporters earlier this month – or possibly from 0.05 percent to 1 percent, such as Stanford epidemiologist John Ioannidis suggests– It is difficult to say with any confidence whether these measures can be justified rationally or for how long.