ABSTRACT
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.
