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Abstract We study the problem of synthesizinglockdown policies—schedules of maximum capacities for different types of activity sites—to minimize the number of deceased individuals due to a pandemic within a given metropolitan statistical area (MSA) while controlling the severity of the imposed lockdown. To synthesize and evaluate lockdown policies, we develop a multiscale susceptible, infected, recovered, and deceased model that partitions a given MSA into geographic subregions, and that incorporates data on the behaviors of the populations of these subregions. This modeling approach allows for the analysis of heterogeneous lockdown policies that vary across the different types of activity sites within each subregion of the MSA. We formulate the synthesis of optimal lockdown policies as a nonconvex optimization problem and we develop an iterative algorithm that addresses this nonconvexity through sequential convex programming. We empirically demonstrate the effectiveness of the developed approach by applying it to six of the largest MSAs in the United States. The developed heterogeneous lockdown policies not only reduce the number of deceased individuals by up to 45 percent over a 100 day period in comparison with three baseline lockdown policies that are less heterogeneous, but they also impose lockdowns that are less severe.
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Optimal lockdowns under constraints
Abstract We present a systematic examination of the impact of frictions on optimal pandemic response, bridging the significant gap between policy recommendations and implementation. We focus in particular on constraints in testing delivery and in lockdown efficacy in the context of a canonical pandemic model. The latter is modified for a more faithful representation of lockdowns. The paper sheds light on nuanced, and sometimes counter‐intuitive, relationships. It rationalizes key but divergent findings in the literature on the extent of substitution and complementarity between lockdowns and testing. It also demonstrates remarkable robustness in lockdown policy to changes in its efficiency.
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- Award ID(s):
- 1937229
- PAR ID:
- 10583604
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Economic Inquiry
- Volume:
- 63
- Issue:
- 2
- ISSN:
- 0095-2583
- Page Range / eLocation ID:
- 523 to 544
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1111/ecin.13265
