Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network

TL;DR

This paper introduces a genotype network-based disease model that captures pathogen mutation, immune transcendence, and complex epidemic dynamics, revealing diverse behaviors beyond traditional single-pathogen models.

Contribution

It develops a novel model incorporating genotype networks to study multistrain epidemic dynamics, mutation pathways, and immune interactions, advancing understanding of pathogen diversity effects.

Findings

Genotype networks influence epidemic phase transitions.

Pathogen mutation along network pathways causes cyclic and fluctuating epidemics.

Localization around specific strains impacts epidemic behavior.

Abstract

Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population. This paradigm has been useful in simplifying the biological reality of epidemics and has allowed the modelling community to focus on the complexity of other factors such as population structure and interventions. However, there is an increasing amount of evidence that the strain diversity of pathogens, and their interplay with the host immune system, can play a large role in shaping the dynamics of epidemics. Here, we introduce a disease model with an underlying genotype network to account for two important mechanisms. One, the disease can mutate along network pathways as it spreads in a host population. Two, the genotype network allows us to define a genetic distance across strains and therefore to model the transcendence of immunity often observed in real world pathogens. We study the emergence of epidemics in this model, through its epidemic phase transitions, and highlight the role of the genotype network in driving cyclicity of diseases, large scale fluctuations, sequential epidemic transitions, as well as localization around specific strains of the associated pathogen. More generally, our model illustrates the richness of behaviours that are possible even in well-mixed host populations once we consider strain diversity and go beyond the "one disease equals one pathogen" paradigm.