Revisiting SIR in the age of COVID-19: Explicit Solutions and Control Problems

TL;DR

This paper introduces a non-population conserving SIR model with explicit solutions, compares it to the standard model, and explores control strategies for managing epidemic spread with multiple communities and intervention levels.

Contribution

It proposes the SIR-NC model that accounts for mortality and non-conservation, providing explicit solutions and control frameworks for epidemic management.

Findings

SIR-NC admits a closed-form solution.

Numerical comparisons show differences from standard SIR.

Control strategies effectively manage infection levels.

Abstract

The non-population conserving SIR (SIR-NC) model to describe the spread of infections in a community is proposed and studied. Unlike the standard SIR model, SIR-NC does not assume population conservation. Although similar in form to the standard SIR, SIR-NC admits a closed form solution while allowing us to model mortality, and also provides different, and arguably a more realistic, interpretation of the model parameters. Numerical comparisons of this SIR-NC model with the standard, population conserving, SIR model are provided. Extensions to include imported infections, interacting communities, and models that include births and deaths are presented and analyzed. Several numerical examples are also presented to illustrate these models. Two control problems for the SIR-NC epidemic model are presented. First we consider the continuous time model predictive control in which the cost function variables correspond to the levels of lockdown, the level of testing and quarantine, and the number of infections. We also include a switching cost for moving between lockdown levels. A discrete time version that is more amenable to computation is then presented along with numerical illustrations. We then consider a multi-objective and multi-community control where we can define multiple cost functions on the different communities and obtain the minimum cost control to keep the value function corresponding to these control objectives below a prescribed threshold.