Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk

International Journal of Health Geographics

Research

Xiao-Jian Chen¹  Keli Wang¹  Lei Dong¹  Yu Liu¹  Gezhi Xiu¹  Mei-po Kwan²  Xiaoyi Han³ 

[1] Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China;Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, 100091, Beijing, China;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China;Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China;The Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, 361005, Xiamen, China;School of Economics, Xiamen University, 361005, Xiamen, China;

关键词: COVID-19;    Non-pharmaceutical interventions;    Spatial spillover effects;    SEIR;    Human mobility;   

DOI  :  10.1186/s12942-023-00335-6

 received in 2023-02-23, accepted in 2023-05-26,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundNon-pharmaceutical interventions (NPIs) implemented in one place can affect neighboring regions by influencing people’s behavior. However, existing epidemic models for NPIs evaluation rarely consider such spatial spillover effects, which may lead to a biased assessment of policy effects.MethodsUsing the US state-level mobility and policy data from January 6 to August 2, 2020, we develop a quantitative framework that includes both a panel spatial econometric model and an S-SEIR (Spillover-Susceptible-Exposed-Infected-Recovered) model to quantify the spatial spillover effects of NPIs on human mobility and COVID-19 transmission.ResultsThe spatial spillover effects of NPIs explain 61.2%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$61.2\%$$\end{document} [95%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$95\%$$\end{document} credible interval: 52.8-84.4%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$84.4\%$$\end{document}] of national cumulative confirmed cases, suggesting that the presence of the spillover effect significantly enhances the NPI influence. Simulations based on the S-SEIR model further show that increasing interventions in only a few states with larger intrastate human mobility intensity significantly reduce the cases nationwide. These region-based interventions also can carry over to interstate lockdowns.ConclusionsOur study provides a framework for evaluating and comparing the effectiveness of different intervention strategies conditional on NPI spillovers, and calls for collaboration from different regions.

【 授权许可】

CC BY   
© The Author(s) 2023

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