Analysis of the competition among viral strains using a temporal interaction-driven contagion model

TL;DR

This paper models the competition among multiple viral strains on temporal networks, highlighting how temporal interaction dynamics and encounter durations influence pathogen spread and competition outcomes.

Contribution

It introduces a temporal interaction-driven contagion model to analyze viral competition, emphasizing the importance of encounter duration in disease dynamics.

Findings

Temporal dynamics critically affect viral competition outcomes.

Longer encounter durations can lead to second waves of infection.

Slower pathogens can persist and cause secondary outbreaks.

Abstract

The temporal dynamics of social interactions were shown to influence the spread of disease. Here, we model the conditions of progression and competition for several viral strains, exploring various levels of cross-immunity over temporal networks. We use our interaction-driven contagion model and characterize, using it, several viral variants. Our results, obtained on temporal random networks and on real-world interaction data, demonstrate that temporal dynamics are crucial to determining the competition results. We consider two and three competing pathogens and show the conditions under which a slower pathogen will remain active and create a second wave infecting most of the population. We then show that when the duration of the encounters is considered, the spreading dynamics change significantly. Our results indicate that when considering airborne diseases, it might be crucial to consider the duration of temporal meetings to model the spread of pathogens in a population.