报告题目：Seeding efficient large-scale public health interventions in diverse spatial-social networks（在多元空间社会网络中播种高效的大规模公共卫生干预）

报告人：韩晓祎（厦门大学）

报告时间：2023年6月16日（星期五）下午1:00-2:00

报告地点：威斯尼斯人老品牌官网大楼318会议室

邀请部门：经济学系

报告人简介：

韩晓祎，2014年获美国俄亥俄州立大学经济学博士，现为厦门大学王亚南经济研究院与经济学经理聘副教授、博士生导师，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。

报告摘要：

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 (TSDPD) model with endogenized human-virus interactions. The model is used to study the initial COVID-19 vaccination rollout in the United States from February 5 to April 15, 2021. We find strong peer effects in state vaccination rates arising from the friendship network (coeff.=0.903, s.e.=0.024) and strong COVID-19 virus transmission through the mobility network (cross-state transmission coeff.=0.246, s.e.=0.088; diffusion coeff.=0.130, s.e.=0.089). Vaccination decreased infections mainly through reduced transmissibility upon passing a full vaccination rate threshold of 2.830% (s.e.=0.046%) for big states and 2.630% (s.e.=0.140%) for small states by population; whereas its impact on the mobility network slightly increased infections. Cumulative infections would have been 1.17 million or 24.85% higher if vaccines were not available. Targeting the six most populated US states or most spatially connected is the most clinically effective in reducing cumulative infections by more than 343,000, and targeting the six most socially influential states is the most clinically effective in increasing the national vaccination rate by 3.5 ppts to 18.54% (95% CI:18.90–19.00%). Targeting the six most socially influential states is more than 20 times as cost-effective as targeting the most populated or most spatially connected ones. Existing supply capacity will need to be temporally and spatially re-allocated to accommodate these seeding strategies.