论文标题
预期Covid-19疫苗接种的最佳安排：纽约州的案例研究
Optimal Scheduling of Anticipated COVID-19 Vaccination: A Case Study of New York State
论文作者
论文摘要
这项研究旨在通过将名为SEIR的广泛认可的传染病模型转化为最佳控制问题，以确定Covid-19-19大流行治疗中疫苗调度的最佳控制策略。通过添加药物和疫苗限制以匹配现实世界情况，可以增加问题。该问题的两个版本是为了最大程度地减少同一感染者的数量提供的最佳疫苗，可以将易感人群降低到相当低的状态。使用RBF-Galerkin方法解决了最佳控制问题。使用基准数据集对这些问题进行测试，以确定所需的参数。在此步骤之后，对美国纽约州的最新数据进行了测试。有关提议的最佳控制问题的结果提供了一组证据，可以从中选择疫苗调度的最佳策略，即当获得COVID-19的疫苗时。
This study aims to determine an optimal control strategy for vaccine scheduling in COVID-19 pandemic treatment by converting widely acknowledged infectious disease model named SEIR into an optimal control problem. The problem is augmented by adding medication and vaccine limitations to match real-world situations. Two version of the problem is formulated to minimize the number of infected individuals at the same provide the optimal vaccine possible to reduce the susceptible population to a considerably lower state. Optimal control problems are solved using RBF-Galerkin method. These problems are tested with a benchmarking dataset to determine required parameters. After this step, problems are tested with recent data for New York State, USA. The results regarding the proposed optimal control problem provides a set of evidences from which an optimal strategy for vaccine scheduling can be chosen, when the vaccine for COVID-19 will be available.
