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Modeling Economic Drivers and Spatial Dependencies in COVID‐19 Transmission: A Locality‐Based Environmetric Approach

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  • Chich‐Ping Hu

Abstract

Cities are breeding grounds for viruses and bacteria. Socioeconomic as well as physical conditions that is needed for spread of COVID‐19 including intensive population, dense buildings, mass transportation system, narrow space, disadvantaged and marginalized groups, and frequent flow of people are almost all concentrated in cities. In this article, 358 townships in Taiwan are used as object to construct COVID‐19 spread model for the investigation of spatial effects from factors of built environment and human related variables. Overall, driving factors of COVID‐19 except for “Church”, “Temple”, “Community Care” significantly affect transmission at different directions and scales during the periods of Early Phase as well as Pandemic Phase by a Negative Binomial Spatial Durbin Model with Spatial Error. In addition, spatial spillover effects from COVID‐19 spread and its' influential factors need to be referred in public policy decision making. This article shows “Floor Area” and “Congestion” to be the two most significant factors to affect COVID‐19 spread.

Suggested Citation

  • Chich‐Ping Hu, 2025. "Modeling Economic Drivers and Spatial Dependencies in COVID‐19 Transmission: A Locality‐Based Environmetric Approach," Environmetrics, John Wiley & Sons, Ltd., vol. 36(8), December.
    • Handle: RePEc:wly:envmet:v:36:y:2025:i:8:n:e70048
    DOI: 10.1002/env.70048
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