Quantifying the benefits of customized vaccination strategies: A network‐based optimization approach
研究如何设计疫苗接种分配策略以最大程度减轻传染病爆发的影响，通过嵌入个体风险和接触信息的多周期优化框架，在德克萨斯州COVID-19案例中显示定制化策略可显著减少预期死亡人数。
Abstract We study the problem of designing vaccine distribution strategies that maximally mitigate the negative impact of an infectious disease outbreak. This is achieved through a multiperiod optimization‐based framework that embeds important subject‐specific risk and contact information into the decision‐making process. By analyzing the structure of the resulting optimization problem, we identify key structural properties which we use to construct a globally convergent solution scheme (suitable for smaller problem instances) and two, more scalable, heuristic schemes. We demonstrate the benefits of the considered framework through a case study on COVID‐19 in Texas. Our results highlight the importance of considering risk and contact information as doing so substantially reduces the total expected number of fatalities over conventional compartmental‐based approaches. These findings indicate that customization can have a significant benefit, particularly for community‐scale planning.