# Another COVID Cost-Benefit Analysis

Yesterday I had a post that very briefly and informally tallied some costs and benefits of shutting down the economy to prevent the spread of COVID-19, concluding that the shutdowns were probably a good idea. (Big thanks to Noah Smith for spreading the word about my work before bothering to read it!) Today, The Incidental Economist, a prominent health-care-policy blog, has a post from Eline van den Broek-Altenburg and Adam Atherly that comes to a more dire conclusion than mine did.

Here are their key numbers:

In the United States, interventions that cost less than \$100,000 per [quality-adjusted life year] gained are often considered “cost effective,” although the precise number is somewhat controversial. . . . The Italian National Health Institute pegged the median age of death from COVID-19 in Italy at 80.5. This is consistent with early data from the United States. . . .

The average 80-year old in the United States has a life expectancy of about 9 years, suggesting that on average, a death averted will “buy” 9 extra years of life. In QALY-estimations, this number needs to be adjusted for the “quality of the years”. In Italy, 99% of deaths had an underlying pathology that needs to be incorporated in QALY adjustments. If we use diabetes as a reasonable proxy for the many chronic diseases, we would adjust the 9 years down to 7.8 years or QALYs. In other words: the average loss per person of quality-adjusted life years is 7.8.

. . . According to a CDC scenario analysis, the expected range of deaths is from 200,000 to 1.7 million people. This implies the pandemic, if unchecked, will lead to a loss of between 1.56 million and 13.26 million QALYs.

They then peg the costs of containment at \$1 trillion to \$4 trillion, leading to a conclusion that the cost per quality year of life gained ranges from \$75,000 to \$650,000: “somewhere between reasonably cost effective and clearly not a wise investment.” “Our calculations suggest that current strategies will be cost effective only if the predicted mortality rates are at the top of the predicted range and costs are at the bottom of the range — a combination of worst care / best case that is unlikely,” they add.

Most of the numbers here aren’t too far off from the ones I presented yesterday in my own bare-bones “quality-adjusted life years” math, but I think there’s a big thing they’re missing: The costs here aren’t just lives lost. If we let COVID get out of control we’ll also have many more cases where people do not die but do fall severely ill, which involves a lot of misery and a lot of health-care costs. (There’s more on the other side of the ledger, too, such as the long-term consequences of letting workers’ human capital stagnate as they stay home from work, but I would guess the former types of problems are generally more severe than the latter types.)

Further, we might not want to use “quality-adjusted life years,” which assume younger people’s lives are more valuable, at all. If you instead use the value of a “stastistical life,” you end up with far bigger benefits from controlling COVID, as I found yesterday and the economist Betsey Stevenson echoed in a tweet thread:

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