Scheduling Lockdowns Under Conditions of Pandemic Uncertainty

Abstract

The objective of our work was to develop a tool to support the process of making strategic decisions about the COVID-19 pandemic by optimizing suppression intervention schedules. We focus mainly on hard lockdowns that have the effect of containing the spread of the virus and, consequently, minimizing the number of infections and keeping the incidence of COVID-19 at low levels. Properly implemented restrictions can reduce the likelihood of infection and thus push the pandemic back. On the contrary, lifting restrictions results in a sharp increase in likelihood of infection and the development of a pandemic. The model proposed in this paper indicates the optimal moments to implement full lockdown, accounting for both the costs of lockdown and the costs of not applying lockdown.

Keywords

• COVID-19
• decision making
• lockdown scheduling
• mixed integer programming
• strategic management