Integrating infection intensity and aggregation into the dynamics of pathogens with within-host replication
Ruijiao Sun1, Jason Cosens Walsman1, Mark Wilber2
1Marine Science Institute, University of California Santa Barbara, Santa Barbara, California, USA.
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.
Insights
Disease aggregation, common in macroparasites, also impacts microparasites like the amphibian chytrid fungus (Bd). Understanding infection intensity and aggregation is key to predicting disease dynamics and outcomes.
Area of Science:
- Ecology
- Epidemiology
- Mathematical Biology
Background:
- Disease outcomes are influenced by infection intensity, which varies greatly among hosts.
- This variation, known as aggregation, is well-studied in macroparasites but less so in microparasites.
- Incorporating aggregation into microparasite models is crucial for understanding disease dynamics.
Purpose of the Study:
- To investigate mechanisms of aggregation in microparasite systems.
- To determine how aggregation and load-dependent effects influence host suppression and virulence-transmission trade-offs.
- To apply these concepts to the amphibian chytrid fungus (Batrachochytrium dendrobatidis - Bd).
Main Methods:
- Developed differential equation models to dynamically simulate pathogen load distribution.
- Incorporated both within- and between-host processes.
- Applied the framework to the Bd-amphibian system.
Main Results:
- Stronger load-dependent mortality and faster within-host replication reduce aggregation.
- Aggregation weakens host suppression and flattens the virulence-transmission trade-off.
- Peak transmission shifts to higher replication rates when aggregation is present.
Conclusions:
- Mechanisms of infection intensity and aggregation similarly affect microparasite and macroparasite dynamics.
- Provides a framework for integrating within-host processes into population-level disease models.
- Advocates for a unified approach to disease modeling across parasite types.
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