LW. Cong, K. Tang, B. Wang, J. Wang
Available at SSRN 3901449, 2021
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.
@article{cong2021ai,
title={An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States},
author={Cong, Lin William and Tang, Ke and Wang, Bing and Wang, Jingyuan},
journal={CoRR},
volume={abs/2109.10009},
year={2021}
}