Managing disease containment measures during a pandemic

Throughout the current COVID-19 pandemic, governments have implemented a variety of containment measures, ranging from hoping for herd immunity (which is essentially no containment) to mandating complete lockdown. On one hand, measures reduce lives lost by limiting disease spread and controlling load on healthcare system. other, such drag down economic activity, leading jobs, stall, societal disturbances, as protests, civil disobedience, increases in domestic violence. Hence, determining right set key social, economic, political decision policymakers. In this paper, we provide model dynamically managing level over course pandemic. We determine timing minimize impact pandemic activity lost, subject capacity stochastic evolution dynamics. Based practical evidence, examine two common classes policies – dynamic static find that are particularly valuable when rate low, recovery takes longer tight. Our work reveals fundamental relationship between structure Pareto-efficient (in terms activity) parameters infection rate, capacity. also analyze virus mutation vaccination decisions. This article protected copyright. All rights reserved