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Spatial disease dynamics of free-living pathogens under pathogen predation
Tommi Mononen1, Lasse Ruokolainen2
1University of Helsinki, Department of Biosciences, Helsinki, FI-00014, Finland. tommi.mononen@helsinki.fi.
Scientific Reports
|August 12, 2017
Summary
Metacommunity interactions, including pathogen-consuming species, can significantly alter disease spread. Introducing consumers can lead to disease-free patches and unexpected decreases in host morbidity, even with pathogen immigration.
Area of Science:
- Ecology
- Epidemiology
- Theoretical Biology
Background:
- Traditional disease dynamics studies focus on host-pathogen interactions.
- The role of broader community interactions in spatial disease spread is often overlooked.
- Free-living pathogens and their consumers add complexity to ecological disease models.
Purpose of the Study:
- To investigate how metacommunity interactions influence spatial epidemiological dynamics.
- To model the effects of a pathogen-consuming species on host-pathogen systems in multiple habitat patches.
- To analyze the impact of consumer and host dispersal on disease prevalence and asymmetry.
Main Methods:
- Development of a deterministic epidemiological model.
- Simulation of two interconnected habitat patches containing hosts, pathogens, and pathogen consumers.
- Analysis of scenarios with isolated patches, consumer dispersal, and host dispersal.
Main Results:
- Isolated patches exhibit periodic disease outbreaks driven by consumer-pathogen cycles.
- Consumer dispersal between patches creates asymmetric disease prevalence, with one patch remaining disease-free.
- Host dispersal leads to indirect pathogen movement, causing a counter-intuitive decrease in morbidity with increased pathogen immigration.
Conclusions:
- Community-level interactions, particularly involving consumers, are critical drivers of spatial disease dynamics.
- Metacommunity processes can generate significant spatial asymmetry in disease prevalence, even in homogeneous environments.
- Understanding these complex interactions is essential for predicting and managing infectious diseases in ecological systems.
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