标题： 在随机SIR模型中优化实时疫苗分配 显示英文标题

标题： Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model

摘要： 实时接种疫苗在疫情爆发后可以有效减轻传染病造成的损害。 然而，在许多情况下，可用资源不足以对整个高风险人群进行接种，物流导致疫苗部署延迟，不同城市成员之间的相互作用促进了感染的广泛空间传播。 有限的疫苗、时间延迟以及城市之间的相互作用（或耦合）导致权衡，这些权衡会影响疫情的整体规模。 这些权衡要求研究最优策略，通过优先将疫苗分配给特定亚人群来最小化疫情的严重程度。 我们使用一个SIR模型来描述在一座城市爆发并传播到另一座城市的疫情疾病动力学。 我们求解一个主方程以确定最终疫情规模的概率分布。 然后，我们确定疫苗、时间延迟和耦合之间的权衡，并确定由此产生的最优接种方案。 显示英文摘要

摘要： Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.