Implications of heterogeneous SIR models for analyses of COVID-19
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10058_2024_355_ReferencePDF.pdf
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1.19 MB
Format
Adobe PDF
Checksum (MD5)
f53ae11bc313dab8c6c10225317d8c7e
Author(s)
Ellison, Glenn
Date Issued
July 15, 2024
Journal
Review of Economic Design
Publisher
Springer Berlin Heidelberg
Citation
Ellison, G. Implications of heterogeneous SIR models for analyses of COVID-19. Rev Econ Design 28, 651–687 (2024).
Version
Author's final manuscript
Abstract
This paper provides a quick survey of results on the classic SIR model and variants allowing for heterogeneity in contact rates. It notes that calibrating the classic model to data generated by a heterogeneous model can lead to forecasts that are biased in several ways and to understatement of the forecast uncertainty. Among the biases are that we may underestimate how quickly herd immunity might be reached, underestimate differences across regions, and have biased estimates of the impact of endogenous and policy-driven social distancing.
MIT Department
Massachusetts Institute of Technology. Department of Economics
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Creative Commons Attribution-Noncommercial-ShareAlike
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DOI of Published Version
https://doi.org/10.1007/s10058-024-00355-z
