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Spatiotemporal Transmission Model to Simulate an Interregional Epidemic Spreading

地理空间分析 人口 正确性 计算机科学 地理 数据科学 运筹学 地图学 工程类 社会学 人口学 程序设计语言
作者
Zitong Li,Haiping Zhang,Chen Ding,Canyu Chen,Renyu Chen,Nuozhou Shen,Huang Yi,Liyang Xiong,Guoan Tang
出处
期刊:Annals of the American Association of Geographers [Taylor & Francis]
卷期号:113 (9): 2084-2107 被引量:6
标识
DOI:10.1080/24694452.2023.2216296
摘要

Infectious disease spread is a spatiotemporal process with significant regional differences that can be affected by multiple factors, such as human mobility and manner of contact. From a geographical perspective, the simulation and analysis of an epidemic can promote an understanding of the contagion mechanism and lead to an accurate prediction of its future trends. The existing methods fail to consider the mutual feedback mechanism of heterogeneities between the interregional population interaction and the regional transmission conditions (e.g., contact probability and the effective reproduction number). This disadvantage oversimplifies the transmission process and reduces the accuracy of the simulation results. To fill this gap, a general model considering the spatiotemporal characteristics is proposed, which includes compartment modeling of population categories, flow interaction modeling of population movements, and spatial spread modeling of an infectious disease. Furthermore, the correctness of a theoretical hypothesis for modeling and prediction accuracy of this model was tested with a synthetic data set and a real-world COVID-19 data set in China, respectively. The theoretical contribution of this article was to verify that the interplay of multiple types of geospatial heterogeneities dramatically influences the spatial spread of infectious disease. This model provides an effective method for solving infectious disease simulation problems involving dynamic, complex spatiotemporal processes of geographical elements, such as optimization of lockdown strategies, analyses of the medical resource carrying capacity, and risk assessment of herd immunity from the perspective of geography. Key Words: geospatial heterogeneities, health geography, interregional population interaction, spatiotemporal analysis, transmission modeling.
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