Here's a recent largely empirical paper by many authors, looking at the actual and counterfactual impact of different pandemic responses in different cities, with the aim (among others) of mapping the employment/mortality frontier of different policies. They build on GPS and payment data for modeling movement and interpersonal contact, and electronic health records for hospitalization and deaths. Thus, for example, they find that in Chicago, different policies can make big moves along the employment/mortality frontier (allowing only essential workers to go to work reduces deaths and increases unemployment, both by a lot), while in a more sparsely inhabited city like Sacramento, it's hard to change the mortality rate (but only allowing essential workers still causes lots of unemployment).
Socioeconomic Network Heterogeneity and Pandemic Policy Response
Mohammad Akbarpour, Cody Cook, Aude Marzuoli, Simon Mongey, Abhishek Nagaraj, Matteo Saccarola, Pietro Tebaldi, Shoshana Vasserman, Hanbin Yang
NBER Working Paper No. 27374
Issued in June 2020
Abstract: "We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including data on individuals' mobility and encounters across metropolitan areas, health records, and measures of the possibility to be productively working from home. This combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions.
"We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses."
Socioeconomic Network Heterogeneity and Pandemic Policy Response
Mohammad Akbarpour, Cody Cook, Aude Marzuoli, Simon Mongey, Abhishek Nagaraj, Matteo Saccarola, Pietro Tebaldi, Shoshana Vasserman, Hanbin Yang
NBER Working Paper No. 27374
Issued in June 2020
Abstract: "We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including data on individuals' mobility and encounters across metropolitan areas, health records, and measures of the possibility to be productively working from home. This combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions.
"We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses."
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