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贫困地区的卫生干预措施与疫情下的恢复力

Health Interventions in a Poor Region and Resilience in the Presence of a Pandemic.

作者信息

Batabyal Amitrajeet A, Beladi Hamid

机构信息

Department of Economics, Rochester Institute of Technology, 92 Lomb Memorial Drive, Rochester, NY 14623-5604 USA.

Department of Economics, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249-0631 USA.

出版信息

Appl Spat Anal Policy. 2022 Apr 14:1-17. doi: 10.1007/s12061-022-09440-8.

DOI:10.1007/s12061-022-09440-8
PMID:35440949
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9009977/
Abstract

We focus on a poor region and study the nexuses between health interventions undertaken by a regional authority (RA) and this region's Holling resilience in the presence of a pandemic such as Covid-19. First, we show how a health intervention by the RA probabilistically affects an appropriately defined health indicator. Second, we compute the chance that the health status of this region's population falls below a minimum acceptable level in the presence of the health intervention. Third, we solve an optimization problem in which the RA maximizes the likelihood that the health status of this region's population stays above a minimum acceptable level at a given economic cost. Our analysis demonstrates that there is a connection between a health intervention, a region's health status, and its Holling resilience by presenting two applications. Our analysis reveals that this paper's methodology can be used to compute a region's Holling resilience with a particular health intervention. The main policy implications of our analysis concern the need for a RA to pay attention to (i) a region's health infrastructure and financing, (ii) sufficient engagement with the region's population, (iii) regional heterogeneity, (iv) data collection, and (v) the likelihood that sicker regions are likely to require more health interventions at a higher cost.

摘要

我们聚焦于一个贫困地区,研究地区当局(RA)实施的卫生干预措施与该地区在新冠疫情等大流行情况下的霍林恢复力之间的联系。首先,我们展示RA的卫生干预措施如何概率性地影响一个适当定义的健康指标。其次,我们计算在实施卫生干预措施的情况下,该地区人口健康状况降至最低可接受水平以下的概率。第三,我们解决一个优化问题,即RA在给定经济成本的情况下,使该地区人口健康状况保持在最低可接受水平以上的可能性最大化。我们的分析通过两个应用案例表明,卫生干预、地区健康状况及其霍林恢复力之间存在联系。我们的分析揭示,本文的方法可用于计算特定卫生干预措施下一个地区的霍林恢复力。我们分析的主要政策含义涉及RA需要关注以下方面:(i)地区的卫生基础设施和融资;(ii)与该地区人口的充分互动;(iii)地区异质性;(iv)数据收集;以及(v)病情较重的地区可能需要更多且成本更高的卫生干预措施的可能性。