Modeling COVID-19 Spread in Small Colleges

TL;DR

This paper presents an agent-based network model to analyze COVID-19 spread in small colleges, emphasizing the importance of combined policies and cautious student behavior for safe reopening.

Contribution

It introduces a tailored agent-based model for small college settings and identifies key policy and behavioral factors critical for controlling COVID-19 spread.

Findings

Comprehensive testing and facemasks are highly effective interventions.

Faster test result turnaround reduces total infections.

Campus closures can cause infection spikes elsewhere depending on behavior.

Abstract

We develop an agent-based model on a network meant to capture features unique to COVID-19 spread through a small residential college. We find that a safe reopening requires strong policy from administrators combined with cautious behavior from students. Strong policy includes weekly screening tests with quick turnaround and halving the campus population. Cautious behavior from students means wearing facemasks, socializing less, and showing up for COVID-19 testing. We also find that comprehensive testing and facemasks are the most effective single interventions, building closures can lead to infection spikes in other areas depending on student behavior, and faster return of test results significantly reduces total infections.