Spatial Interactions and the Spread of COVID-19: A Network Perspective

Cui Zhang () and Dandan Zhang
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Cui Zhang: Jinan University
Dandan Zhang: Jinan University

Computational Economics, 2023, vol. 62, issue 1, No 14, 383-405

Abstract: Abstract We use unique data on the travel history of confirmed patients at a daily frequency across 31 provinces in China to study how spatial interactions influence the geographic spread of pandemic COVID-19. We develop and simultaneously estimate a structural model of dynamic disease transmission network formation and spatial interaction. This allows us to understand what externalities the disease risk associated with a single place may create for the entire country. We find a positive and significant spatial interaction effect that strongly influences the duration and severity of pandemic COVID-19. And there exists heterogeneity in this interaction effect: the spatial spillover effect from the source province is significantly higher than from other provinces. Further counterfactual policy analysis shows that targeting the key province can improve the effectiveness of policy interventions for containing the geographic spread of pandemic COVID-19, and the effect of such targeted policy decreases with an increase in the time of delay.

Keywords: Spatial interactions; Spillovers; Social network; Externalities; Pandemic COVID-19 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10614-022-10278-y

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