Epidemic spreading in group-structured populations

TL;DR

This paper investigates how the organization and correlation of group structures in populations influence epidemic spread, showing that correlated group arrangements can reduce epidemic severity and improve containment strategies.

Contribution

It introduces a novel analysis of how correlated group structures affect epidemic dynamics and demonstrates practical benefits through data-driven optimization of student assignments.

Findings

Correlated group structures lead to longer but milder outbreaks.

Higher correlation among groups enhances intervention effectiveness.

Optimized student assignment reduces epidemic severity by 2-5 times.

Abstract

Individuals involved in common group activities/settings -- e.g., college students that are enrolled in the same class and/or live in the same dorm -- are exposed to recurrent contacts of physical proximity. These contacts are known to mediate the spread of an infectious disease, however, it is not obvious how the properties of the spreading process are determined by the structure of and the interrelation among the group settings that are at the root of those recurrent interactions. Here, we show that reshaping the organization of groups within a population can be used as an effective strategy to decrease the severity of an epidemic. Specifically, we show that when group structures are sufficiently correlated -- e.g., the likelihood for two students living in the same dorm to attend the same class is sufficiently high -- outbreaks are longer but milder than for uncorrelated group structures. Also, we show that the effectiveness of interventions for disease containment increases as the correlation among group structures increases. We demonstrate the practical relevance of our findings by taking advantage of data about housing and attendance of students at the Indiana University campus in Bloomington. By appropriately optimizing the assignment of students to dorms based on their enrollment, we are able to observe a two- to five-fold reduction in the severity of simulated epidemic processes.