Optimal control of COVID-19 infection rate considering social costs

TL;DR

This paper analyzes optimal COVID-19 control strategies balancing health and economic costs, identifying suppression, mitigation, and a new delay-mitigation approach through mathematical modeling.

Contribution

It introduces a mathematical framework for optimal control of COVID-19, including vaccination effects and new delay-mitigation strategies.

Findings

Suppression and mitigation strategies are characterized mathematically.

Incorporating vaccination leads to a new delay-mitigation strategy.

Optimal policies depend on social and economic cost considerations.

Abstract

The COVID-19 pandemic has posed a policy making crisis where efforts to slow down or end the pandemic conflict with economic priorities. This paper provides mathematical analysis of optimal disease control policies with idealized compartmental models for disease propagation and simplistic models of social and economic costs. Two locally optimal control strategies are found and categorized as `suppression' and `mitigation' strategies. We analyze how these strategies change when we incorporate vaccination into the model and find a new optimal `delay-mitigation' strategy.