Sub-optimal choices concerning COVID-19 and some common sense

Here is a link to a paper by Budish "Maximize Utility subject to R ≤ 1: A Simple Price-Theory Approach to Covid-19 Lockdown and Reopening Policy".

The paper illustrates the non-think to date exhibited by most Politicians, Talking Heads, and "Scientists" such as Fauci and Osterholm.

Here are some excerpts.

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When eradication of an infectious threat is not feasible,

the second-best from a public health perspective is to minimize its spread. For example Dr.

Michael Osterholm writes: “As epidemiologists, we have two goals. The first is to prevent.

When that is not possible, the second is to minimize ...” (Osterholm and Olshaker, 2020, pg.

26). As emphasized in the introduction, however, the minimize objective makes it difficult

to think about tradeoffs if the interventions themselves are very expensive. This latter point bears emphasis. In the HIV pandemic, the minimize strategy entailed widespread public

education about safe sex, condom distribution, needle exchange, etc. — but no public health

expert recommended literally trying to minimize the spread of the virus by banning sex (or

banning non-monogamous sex, etc.). In the Covid-19 pandemic, however, the minimize

strategy has included not just the kinds of interventions that are relatively cheap like virusrisk

education, masks, testing, etc., but also much more severe and expensive measures which

have included banning many forms of social and commercial contact.

[The “economic cost of reducing spread” curve grows very steeply as R gets lower than

lower than 1.0, even if simple interventions are utilized, because of the increasingly-valuable

activities that have to be dropped.]

The public-health instinct expressed by Dr. Osterholm to eradicate if feasible, and otherwise
minimize, is a useful heuristic in the scenarios depicted in Panels D, E, and F. Specifically, if we
understand “eradicate if feasible” to mean feasible at a fathomable fixed cost, and “minimize” to
mean doing all of the cheap interventions, on the relatively flat part of the mitigation curve, as
fully as possible, then this heuristic gets to the optimal policy response in each of Panels D, E,
and F.

However, if the costs of interventions being considered grow large enough — as they clearly
have done in the Covid-19 response — then this instinct may lead to sub-optimal policy. This is
the case depicted in Panels A and B and that has been emphasized throughout this paper.
It therefore seems that Covid-19 required a novel play in the epidemiological playbook: maximize
societal utility subject to R <= 1. That is, get to R <= 1 as efficiently as possible, using either
simple interventions or targeted bans of activities with particularly poor utility-to-risk.
I want to close by emphasizing that this paper, at most, puts economics language on a formulation
that many medical experts have converged on as well. There were also several other
economists who, early in the pandemic, seemed to have in mind that getting to R <= 1 at the
lowest harm to societal utility is the appropriate formulation of the policy problem.