Controlling Epidemic Spread: Reducing Economic Losses with Targeted Closures

64 Pages Posted: 6 May 2020 Last revised: 18 Nov 2021

See all articles by John R. Birge

John R. Birge

University of Chicago - Booth School of Business

Ozan Candogan

University of Chicago - Booth School of Business

Yiding Feng

Microsoft Corporation - Microsoft Research New England

Date Written: May 18, 2020

Abstract

Data on population movements can be helpful in designing targeted policy responses to curb epidemic spread. However, it is not clear how to exactly leverage such data and how valuable they might be for the control of epidemics. To explore these questions we study a spatial epidemic model that explicitly accounts for population movements, and propose an optimization framework for obtaining targeted policies that restrict economic activity in different neighborhoods of a city at different levels. We focus on COVID-19 and calibrate our model using the mobile phone data that capture individuals’ movements within New York City (NYC). We use these data to illustrate that targeting can allow for substantially higher employment levels than uniform (city-wide) policies when applied to reduce infections across a region of focus. In our NYC example (which focuses on the control of the disease in April 2020), our main model illustrates that appropriate targeting achieves a reduction in infections in all neighborhoods while resuming 23.1%–42.4% of the baseline non- teleworkable employment level. By contrast, uniform restriction policies that achieve the same policy goal permit 3.92 to 6.25 times less non-teleworkable employment. Our optimization framework demonstrates the potential of targeting to limit the economic costs of unemployment while curbing the spread of an epidemic.

Suggested Citation

Birge, John R. and Candogan, Ozan and Feng, Yiding, Controlling Epidemic Spread: Reducing Economic Losses with Targeted Closures (May 18, 2020). University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2020-57, Available at SSRN: https://ssrn.com/abstract=3590621 or http://dx.doi.org/10.2139/ssrn.3590621

John R. Birge

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Ozan Candogan (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

HOME PAGE: http://faculty.chicagobooth.edu/ozan.candogan/

Yiding Feng

Microsoft Corporation - Microsoft Research New England ( email )

One Memorial Drive, 14th Floor
Cambridge, MA 02142
United States

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