An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States

Lin Cong, Ke Tang, Bing Wang and Jingyuan Wang

Papers from arXiv.org

Abstract: We build a deep-learning-based SEIR-AIM model integrating the classical Susceptible-Exposed-Infectious-Removed epidemiology model with forecast modules of infection, community mobility, and unemployment. Through linking Google's multi-dimensional mobility index to economic activities, public health status, and mitigation policies, our AI-assisted model captures the populace's endogenous response to economic incentives and health risks. In addition to being an effective predictive tool, our analyses reveal that the long-term effective reproduction number of COVID-19 equilibrates around one before mass vaccination using data from the United States. We identify a "policy frontier" and identify reopening schools and workplaces to be the most effective. We also quantify protestors' employment-value-equivalence of the Black Lives Matter movement and find that its public health impact to be negligible.

Date: 2021-09
New Economics Papers: this item is included in nep-big, nep-cmp, nep-hea, nep-isf and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2109.10009

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