Work

Integrating infection intensity and aggregation into the dynamics of pathogens with within‐host replication

Year: 2026

Type: article

Abstract: Disease outcomes depend heavily on infection intensity which is often heterogeneous across and within host populations. Most individuals carry low pathogen loads and a few carry high loads, a pattern known as aggregation. Although well characterized in macroparasite systems, aggregation and infection intensity are rarely incorporated into microparasite models. This raises key questions: Do similar mechanisms underlie aggregation in macro- and microparasite systems? Moreover, how do aggregation and load-dependent effects shape outcomes such as host suppression and virulence-transmission trade-offs? To address these questions, we developed a series of differential equation models that allow the pathogen load distribution across hosts to evolve dynamically, shaped by both within- and between-host processes. We applied this framework to the amphibian chytrid fungus system caused by Batrachochytrium dendrobatidis (Bd), a fungal pathogen threatening amphibian populations worldwide. Our results show that both stronger load-dependent mortality and faster within-host replication reduce aggregation. Aggregation, in turn, weakens host suppression and flattens virulence-transmission trade-off, shifting peak transmission to higher replication rates. Overall, our models show that similar mechanisms of infection intensity and aggregation influence host-pathogen dynamics in microparasites as in macroparasites. This work offers a framework for advancing theoretical and data-driven understanding of how within-host processes scale to population-level disease dynamics, advocating for a unified approach to disease modelling that bridges the macro- and microparasites.

Source: Journal of Animal Ecology

DOI: 10.1111/1365-2656.70272

Authors: Ruijiao Sun, Jason Cosens Walsman, Mark Wilber, Cheryl J. Briggs

Institutions: University of California, Santa Barbara, University of Tennessee System, University of Tennessee at Knoxville

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,610