Epidemiological and economic impact of COVID-19 in the US

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作者
Jiangzhuo Chen
Anil Vullikanti
Joost Santos
Srinivasan Venkatramanan
Stefan Hoops
Henning Mortveit
Bryan Lewis
Wen You
Stephen Eubank
Madhav Marathe
Chris Barrett
Achla Marathe
机构
[1] University of Virginia,Network Systems Science and Advanced Computing Division, Biocomplexity Institute
[2] University of Virginia,Department of Computer Science
[3] George Washington University,Department of Engineering Management and Systems Engineering
[4] University of Virginia,Department of Engineering Systems and Environment
[5] University of Virginia,Department of Public Health Sciences
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This research measures the epidemiological and economic impact of COVID-19 spread in the US under different mitigation scenarios, comprising of non-pharmaceutical interventions. A detailed disease model of COVID-19 is combined with a model of the US economy to estimate the direct impact of labor supply shock to each sector arising from morbidity, mortality, and lockdown, as well as the indirect impact caused by the interdependencies between sectors. During a lockdown, estimates of jobs that are workable from home in each sector are used to modify the shock to labor supply. Results show trade-offs between economic losses, and lives saved and infections averted are non-linear in compliance to social distancing and the duration of the lockdown. Sectors that are worst hit are not the labor-intensive sectors such as the Agriculture sector and the Construction sector, but the ones with high valued jobs such as the Professional Services, even after the teleworkability of jobs is accounted for. Additionally, the findings show that a low compliance to interventions can be overcome by a longer shutdown period and vice versa to arrive at similar epidemiological impact but their net effect on economic loss depends on the interplay between the marginal gains from averting infections and deaths, versus the marginal loss from having healthy workers stay at home during the shutdown.
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