Abstract

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

Highlights

  • Interactions between strains of the same pathogen play a central role in how they spread in host populations. [1,2,3,4,5,6,7]

  • We analyzed the real-case example of Staphylococcus aureus spread in a hospital, leveraging on a combined dataset of carriage and close proximity interactions

  • We found that contact dynamics has a profound impact on a strain population

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Summary

Introduction

Interactions between strains of the same pathogen play a central role in how they spread in host populations. [1,2,3,4,5,6,7]. Since they impact the spread of single pathogens, the same characteristics could affect the dynamics in multi-strain populations It was shown, that network structure impacts transmission with two interacting strains [39,40,41,42,43,44,45,46], the evolution of epidemiological traits [47,48,49] and the effect of cross-immunity [50, 51]. Complex biological mechanisms—such as mutation, variations in transmissibility and infectious period, cross immunity—were used to differentiate between pathogens, thereby making the role of network characteristics difficult to assess in its own right

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