Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses

TL;DR

This paper develops a spatial behavioral SIR model to analyze how geographic factors and local interactions influence infection spread and behavioral responses, challenging traditional invariance assumptions and informing policy evaluation.

Contribution

It introduces a spatial-SIR model incorporating local interactions and behavioral responses, revealing their impact on epidemic dynamics and policy implications.

Findings

Local interactions create matching frictions and herd immunity effects.

Geographical factors influence behavioral response effectiveness.

Traditional invariance properties of SIR models do not hold in spatial settings.

Abstract

We simulate a spatial behavioral model of the diffusion of an infection to understand the role of geographic characteristics: the number and distribution of outbreaks, population size, density, and agents' movements. We show that several invariance properties of the SIR model concerning these variables do not hold when agents interact with neighbors in a (two dimensional) geographical space. Indeed, the spatial model's local interactions generate matching frictions and local herd immunity effects, which play a fundamental role in the infection dynamics. We also show that geographical factors affect how behavioral responses affect the epidemics. We derive relevant implications for estimating the effects of the epidemics and policy interventions that use panel data from several geographical units.