Simple control for complex pandemics

TL;DR

This paper offers a practical analytical model to guide organizations in designing effective, resource-aware mitigation strategies for COVID-19, balancing measures like masks, vaccinations, testing, and contact tracing.

Contribution

It introduces a comprehensive analytical model that combines multiple mitigation strategies and provides simulation-based guidance for controlling disease spread in various settings.

Findings

Effective mitigation strategies depend on resource availability.

Simulation results demonstrate optimal combinations of interventions.

Guidance tailored for settings like college campuses.

Abstract

The COVID-19 pandemic began over two years ago, yet schools, businesses, and other organizations are still struggling to keep the risk of disease outbreak low while returning to (near) normal functionality. Observations from these past years suggest that this goal can be achieved through the right balance of mitigation strategies, which may include some combination of mask use, vaccinations, viral testing, and contact tracing. The choice of mitigation measures will be uniquely based on the needs and available resources of each organization. This article presents practical guidance for creating these policies based on an analytical model of disease spread that captures the combined effects of each of these interventions. The resulting guidance is tested through simulation across a wide range of parameters and used to discuss the spread of disease on college campuses.