The focus of public discussion has been on lowering mortality (and to a lesser extent morbidity) rates, and a lot less attention has been focused on the countervailing costs of drastic containment measures. A friend of mine sent me what I consider at least a decent framework for thinking about such questions, though of course the results one gets determines on assumptions for which we lack sufficient data to have any certainty about. I've posted, with permission, below what my friend sent me. I would add one more thing: when I've raised such issues with people, they raise the question of unlikely but at least remotely possible worst-case health scenarios. I counter that we also have to consider unlikely but at least remotely possible worst-case economic scenarios, such as the shutdowns plus government intervention causing a massive long-term contraction, or, alternatively, hyperinlation:

Someone needs to do a cost-benefit analysis for the containment measures being considered and in some states (like my own) implemented. The benefit, obviously, is saving lives that would otherwise be lost due to CV19. The cost is drastic reductions in economic activity, which will result in loss of life as well as reduced quality of life. For harsh enough and lengthy enough measures, the latter will eventually outweigh the former. I haven't seen anyone do this math yet, so I'm going to take a stab.

To do the math, I'll have to make a lot of assumptions, and you may disagree with some of them. That's fine. I'm just trying to wrap my head around the problem with some actual numbers. But if you want to challenge my assumptions, please suggest better assumptions so that you (or I) can redo the math and see what changes.

For this kind of analysis, government regulatory agencies typically put a value on human life. This will offend some people, but refusing to do so results in absurd conclusions, such as shutting down activities with levels of risk that normal people willingly accept on a daily basis in their everyday lives. So what's the value of a human life? Agencies are not consistent, but the range is usually somewhere between $5 million and $9 million.

Now, how many lives will be saved by the measures in question? I don't know. The answer depends on infection rates, fatality rates, and the efficacy of social distancing and other measures. It also depends on the capacity of the healthcare system—the whole "flattening the curve" argument. But it's definitely wrong to consider all deaths as the potential benefit of containment measures, because many deaths will happen regardless. We have to consider the reduction in deaths. According to one estimate I found, the overall number of deaths could be around 480,000 in the US. Let's assume that the containment measures will reduce this by half, meaning 240,000 lives. That's the potential benefit.

Now consider the costs. Let's focus on GDP (which means we're ignoring any human cost in terms of lost personal contact and so on). Let's suppose the containment measures will reduce GDP by 50% for one quarter of the year (or equivalently, by 25% for half of the year, or by 12.5% for a whole year). I don't really know if this is a reasonable assumption. Maybe a lot more of the economy can just operate on autopilot. But when everyone not in an "essential profession" is told to stay home, reductions of this magnitude don't seem out of the ballpark. The GDP of the US is about $21.5 trillion, so based on the above reduction, the cost of the containment measures would be about $2.7 trillion.

Dividing that $2.7 trillion cost by 240,000 lives saved, we get a cost per life of about $11.2 million per life—which is beyond the high-end estimate of the value of a human life used by regulatory agencies.

What happens if we change the assumptions? Depends on which ones we change, obviously. If we halve the GDP loss, then containment measures will pass the cost-benefit test after all. On the other hand, if these measures only save half as many people, or 125,000, then they will be even more unjustified. Feel free to sub in your own numbers to see what you get.

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