Don’t Stay Home

- AMERICA INSTITUTE FOR ECONOMIC RESEARCH - AUG 18, 2021 - Gerald P. O’Driscoll, Jr. -

With the new Delta variant, Covid-19 cases are increasing rapidly across the country (Johns Hopkins University CSSE). These developments have led to calls for reimposing various mandates, with veiled threats of renewed nationwide lockdowns. My previous post (“Covid Policy and Outcomes,” August 2, 2021) demonstrated that policies like lockdowns (shelter-in-place policies) and social distancing guidelines were not only futile, but even counterproductive. For now, the emphasis is on mask mandates. But it is worthwhile to further reexamine lockdown policies, lest there be more calls to reimpose them.

Casey B. Mulligan examined the relationship between group size and private efforts to avoid infections (“The Backward Art of Slowing the Spread? Congregation Efficiencies during COVID-19.” Working Paper No. 20021-51, April 2021 [Becker-Friedman institute]). In response to the pandemic, authorities shut down most businesses, many schools, and other places where crowds congregated. It was done on the “compelling theory” that the disease would spread more quickly in such venues (1). The population was urged, in some cases, compelled, to stay at home (SIP).

Mulligan developed a model in which private, rational efforts to prevent disease in organizations can make them safer than in one’s home. He noted that “disease prevention is an industry whose organization is a topic especially suitable to economic analysis” (1). Prevention has a cost, but also yields potential benefits in disease reduction (5).

Organizations, like firms, monitor activities of their workers. Among other things, this monitoring manages local externalities and public goods. Individual efforts to reduce the spread of disease fall into these categories. There are economies of scale in monitoring (6-7).

“Businesses, schools and other organizations implemented protocols to slow the spread of COVID-19 that were rarely, if ever, implemented in households.” These included physical barriers, positive assortative matching (e.g., screening and quarantining in hospitals, and limiting contacts), and social distancing. Masking was universal in all organizations studied. Some measures were specialized to certain industries, such as airflow control and filtering (for airlines and hospitals). Hospitals and schools put workers and students in pods. The University of Illinois developed and administered its own rapid Covid-19 test. Many of these protocols involve scale economies not available to households (14).

Mulligan presented some case studies. Duke Health system is a complex of hospitals and clinics in 10 counties of North Carolina, employing more than 21,000 workers. Six weeks after the implementation of disease-prevention protocols, work-acquired infection rates “almost stopped,” while cases continued in the outside community. “An hour worked in the Duke Health system went from being more dangerous than an hour outside work to being more than three times safer” (16).


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