How does a Rational Agent Act in an Epidemic?

TL;DR

This paper models how rational individuals with limited information make decisions during an epidemic, revealing that such behaviors can still lead to epidemic growth despite rationality.

Contribution

It introduces a mean-field optimal control model to analyze the impact of partial information on individual decision-making and epidemic spread.

Findings

Limited information can cause epidemic growth even with rational agents

Agent decisions significantly influence virus transmission dynamics

Model highlights importance of information in epidemic control

Abstract

Evolution of disease in a large population is a function of the top-down policy measures from a centralized planner, as well as the self-interested decisions (to be socially active) of individual agents in a large heterogeneous population. This paper is concerned with understanding the latter based on a mean-field type optimal control model. Specifically, the model is used to investigate the role of partial information on an agent's decision-making, and study the impact of such decisions by a large number of agents on the spread of the virus in the population. The motivation comes from the presymptomatic and asymptomatic spread of the COVID-19 virus where an agent unwittingly spreads the virus. We show that even in a setting with fully rational agents, limited information on the viral state can result in an epidemic growth.