Li, Yiang; Zhou, Xingzuo; Lyu, Zejian; (2024) Regional contagion in health behaviors: evidence from COVID-19 vaccination modeling in England with social network theorem. Journal of Computational Social Science 10.1007/s42001-023-00232-9. (In press).

Text Zhou_Regional_Contagion_in_Health_Behaviors__Evidence_from_COVID_19_Vaccination_Modeling_in_England_with_Social_Network_Theorem_RR3.pdf - Accepted Version Access restricted to UCL open access staff until 26 January 2025. Download (1MB)

Abstract

Social contagion is a key mechanism that shapes health behaviors, but few studies have applied this approach at the regional level to examine how vaccination beliefs and rates vary and diffuse across geographic areas. Building upon the traditional SIR model, this paper addresses this gap by applying social network theory to a new compartmental model to simulate regional contagion in COVID-19 vaccination rates in England, using panel data of new and accumulated vaccination numbers from December 2020 to June 2022. This Social Network Vaccination Rate (SNVR) model estimates each region’s initial and changing vaccination beliefs and their mutual influence on each other. The results reveal that remote regions had higher initial vaccination beliefs and stronger spillover effects on other regions such as London with more population diversity. The paper suggests that policies to increase vaccination rates should consider the heterogeneity and peer effects among regions that collectively affect vaccination beliefs. The paper also discusses the limitations of the network model and directions for future research.

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