Toward epidemic thresholds on temporal networks: a review and open questions

TL;DR

This paper reviews methods for predicting epidemic thresholds in temporal contact networks, emphasizing the importance of network dynamics in disease spread and highlighting open research questions in the field.

Contribution

It provides a comprehensive overview of existing approaches to estimate epidemic thresholds on temporal networks and identifies key gaps for future investigation.

Findings

Temporal network dynamics critically influence epidemic thresholds.

Current methods vary in accuracy and applicability.

Open questions remain in modeling complex contact patterns.

Abstract

Epidemiological contact network models have emerged as an important tool in understanding and predicting the spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become an epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.