Predicting the thermal dependencies of infectious disease with the metabolic theory of ecology
Abstract
Environmental conditions can impact the spread of disease, but there has been debate as to whether warming temperatures will increase the frequency of infectious disease epidemics. The metabolic theory of ecology (MTE) provides a general framework of thermal scaling that may be useful for predicting how climate change will affect disease dynamics. Using Daphnia magna and a microsporidian gut parasite, we conducted three experiments across a wide thermal range and fitted mechanistic models of within-host parasite population dynamics and between-host transmission models that utilize MTE submodels for parameters. We found that the MTE models effectively predict host survival, parasite growth, cost of infection, and disease transmission across temperature. We then used these models to parameterize a population-level epidemiological model to predict disease dynamics under both constant and warming environmental conditions. We tested our model predictions by driving experimental Daphnia - parasite populations through constant or slowly warming conditions and found that our MTE model is able to accurately forecast disease dynamics and whether or not an epidemic will occur. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at both the within-host and between-host levels.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMGH41B1205K
- Keywords:
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- 0230 Impacts of climate change: human health;
- GEOHEALTH;
- 0240 Public health;
- GEOHEALTH;
- 0245 Vector born diseases;
- GEOHEALTH;
- 1813 Eco-hydrology;
- HYDROLOGY