Coinfection interactions systematically influence parasite diversity estimates in simulated host populations

Parasite diversity is a central component of epidemiological dynamics. Parasite diversity is commonly studied across animal populations and species using metrics like parasite species richness; although these metrics generally assume no interactions among parasite species within a community, such interactions are common and important, and could affect parasite diversity estimates in ways that are currently difficult to account for. Nevertheless, the strength of these effects are currently unclear due to a relative rarity of community-level parasite interaction data. To address this gap, we use theoretical models to explore how interactions among pathogen strains might influence estimates of pathogen diversity, using parasite species richness as an example. We simulate interactions among co-infecting pathogens and assess their impact on strain detectability, informing population-level pathogen richness estimates. We find that such interactions introduce bias and uncertainty into richness measurements which is as yet unaccounted for, possibly impacting a wide range of studies. The magnitude of this bias is dependent on the frequency and the nature (competitive or facilitative) of interactions among coinfecting pathogens. Until more is known about the structure of these pathogen communities, we cannot fully gauge the extent of this bias. Coinfection studies may benefit from approaches developed in microbial ecology to quantify networked interactions among pathogens within hosts.