疫苗犹豫情形下基于社区的针对性资源配置设计：一种数据驱动的仓室随机优化模型
Design of Targeted Community-Based Resource Allocation in the Presence of Vaccine Hesitancy via a Data-Driven Compartmental Stochastic Optimization Model
AI总结：
提出融合流行病学仓室模型与多阶段随机规划的数据驱动框架，在疫苗犹豫下动态配置医疗资源，并基于阿肯色州COVID-19数据量化部署时机、呼吸机供给与公平代价。
摘要：
疫苗已被证明可有效降低传染病暴发期间重症感染和死亡的威胁。然而，疫苗犹豫（VH）使跨地区和人群的疾病传播预测及医疗资源评估变得复杂。我们提出一个建模框架，将用于刻画传染病传播的流行病学仓室模型整合到多阶段随机规划（MSP）中，由后者在不确定性下确定关键资源的配置。所提出的仓室MSP模型能够自适应地管理资源配置，以应对人群疫苗接种行为的变化（即VH的波动性）、独特的疾病传播模式，以及医疗资源在时间和空间上的可获得性。该仓室MSP模型使我们能够分析资源配置中的公平代价。利用美国阿肯色州2021年1月至5月的真实COVID-19疫苗接种和医疗资源数据，我们的发现包括：（i）将额外呼吸机的初次部署推迟一个月，可能导致预期死亡人数平均每月增加285.41人，凸显了迅速行动的重要性；（ii）初始储备和供应中每增加一台呼吸机，分别使预期死亡人数每月减少1.09人和0.962人，强调了维持大规模储备和可扩展生产响应的重要性；（iii）确保公平资源配置的成本随时间和地点而变化，并在疾病暴发高峰期及人口稠密地区达到峰值。本研究强调了灵活、知情的公共卫生决策和准备工作的重要性，为突发公共卫生事件中的有效资源配置提供了模型。
英文摘要：
Vaccines have proven effective in mitigating the threat of severe infections and deaths during outbreaks of infectious diseases. However, vaccine hesitancy (VH) complicates disease spread prediction and healthcare resource assessment across regions and populations. We propose a modeling framework that integrates an epidemiological compartmental model that captures the spread of an infectious disease within a multi-stage stochastic program (MSP) that determines the allocation of critical resources under uncertainty. The proposed compartmental MSP model adaptively manages the allocation of resources to account for changes in population behavior toward vaccines (i.e., variability in VH), the unique patterns of disease spread, and the availability of healthcare resources over time and space. The compartmental MSP model allowed us to analyze the price of fairness in resource allocation. Using real COVID-19 vaccination and healthcare resource data from Arkansas, U.S. (January-May 2021), our findings include: (i) delaying the initial deployment of additional ventilators by one month could lead to an average increase in the expected number of deaths by 285.41/month, highlighting the importance of prompt action; (ii) each additional ventilator in the initial stockpile and in supply leads to a decrease in the expected number of deaths by 1.09/month and 0.962/month, respectively, emphasizing the importance of maintaining a large stockpile and scalable production response; (iii) the cost of ensuring equitable resource allocation varies over time and location, peaking during the peak of a disease outbreak and in densely populated areas. This study emphasizes the importance of flexible, informed public health decision-making and preparedness, providing a model for effective resource allocation in public health emergencies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
