Seeding efficient large-scale public health interventions in diverse spatial-social networks
报告人： 韩晓祎 (厦门大学)
时间：2023-11-02 15:10-17:00
地点：Room 217, Guanghua Building 2
Abstract:
The selection of target locations for large-scale public health interventions is complex when the take-up of such interventions has peer effects through social networks and health outcomes have spillover effects through spatial networks. To address this issue, we develop a threshold spatial dynamic panel data model to study target location selection for large-scale interventions in multilayer networks, accounting for regional differences and possible feedback effects. Results from the United States COVID-19 vaccination rollout at the early stage reveal peer effects of vaccination within a static friendship network, COVID-19 transmission via a dynamic mobility network, and the vaccination effect on reduced transmissibility. Counterfactual analysis shows that targeting the most populated or the most mobility connected states reduces the most infections, whereas targeting socially influential states proves to be the most cost-effective. Our modelling framework can address societal challenges with strong social and spatial spillover effects.
About the Speaker:
韩晓祎， 2014年获美国俄亥俄州立大学经济学博士，现为厦门大学经济学科长聘副教授、博士生导师，入选国家级青年高层次人才。主要研究领域为计量经济学、应用计量经济学、区域经济学和劳动经济学。多篇论文发表在PNAS、Journal of Business & Economic Statistics、Econometric Theory和Regional Science and Urban Economics、《数量经济技术经济研究》等国内外权威学术期刊上。主持国家自然科学基金面上项目2项、青年项目1项，以及福建省自然科学基金杰青项目。
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