疫苗分发的外展策略：一个多阶段随机建模方法
Outreach Strategies for Vaccine Distribution: A Multi-Period Stochastic Modeling Approach
摘要：
接种疫苗已被证明是预防传染病的最有效方法。然而，在许多地理上分散和游牧人口的低收入和中等收入国家，最后一英里疫苗的运送可能极其复杂。由于偏远人口中心的新生儿往往无法直接前往诊所和医院，他们面临着疾病和感染的重大风险。在这些情况下，通常采用一种称为外联的方法来提高免疫接种率。选择一组这些偏远的地点，并在适当的规划期间，从一个仓库派出临床医生和支助人员小组，在这些地点建立流动诊所，为那里和周围地区的人们接种疫苗。在本文中，我们建模的问题，优化设计外展工作作为一个混合整数规划，是一个集合覆盖问题和车辆路径问题的组合。此外，由于与外展相关的因素（如人口和道路状况）往往不稳定和不可预测，我们应对不确定性并确定最坏情况的解决方案。这是使用多周期随机建模方法来完成的，该方法考虑更新的模型参数估计和后续规划周期的修订计划。我们还进行了数值实验，以提供有关人口特征如何影响外展规划以及外展规划人员在收集数据时应将注意力集中在何处的见解。
英文摘要：
Vaccination has been proven to be the most effective method to prevent infectious diseases. However, in many low and middle-income countries with geographically dispersed and nomadic populations, last-mile vaccine delivery can be extremely complex. Because newborns in remote population centers often do not have direct access to clinics and hospitals, they face significant risk from diseases and infections. An approach known as outreach is typically utilized to raise immunization rates in these situations. A set of these remote locations is chosen, and over an appropriate planning period, teams of clinicians and support personnel are sent from a depot to set up mobile clinics at these locations to vaccinate people there and in the immediate surrounding area. In this paper, we model the problem of optimally designing outreach efforts as a mixed integer program that is a combination of a set covering problem and a vehicle routing problem. In addition, because elements relevant to outreach (such as populations and road conditions) are often unstable and unpredictable, we address uncertainty and determine the worst-case solutions. This is done using a multi-period stochastic modeling approach that considers updated model parameter estimates and revised plans for subsequent planning periods. We also conduct numerical experiments to provide insights on how demographic characteristics affect outreach planning and where outreach planners should focus their attention when gathering data.
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