Long-term spatial and population-structured planning of non-pharmaceutical interventions to epidemic outbreaks
研究如何规划非药物干预措施（如封锁、社交距离）以长期控制传染病传播，建立考虑空间和人口结构异质性的优化模型，并用波兰新冠疫情数据验证，发现引入个体流动性显著提升决策质量。
In this paper, we consider the problem of planning non-pharmaceutical interventions to control the spread of infectious diseases. We propose a new model derived from classical compartmental models; however, we model spatial and population-structure heterogeneity of population mixing. The resulting model is a large-scale non-linear and non-convex optimisation problem. In order to solve it, we apply a special variant of covariance matrix adaptation evolution strategy. We show that results obtained for three different objectives are better than natural heuristics and, moreover, that the introduction of an individual's mobility to the model is significant for the quality of the decisions. We apply our approach to a six-compartmental model with detailed Poland and COVID-19 disease data. The obtained results are non-trivialand sometimes unexpected; therefore, we believe that our model could be applied to support policy-makers in fighting diseases at the long-term decision-making level.