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Modeling vector-borne disease risk in migratory animals under climate change
Richard J Hall1, Leone M Brown2, Sonia Altizer2
1Odum School of Ecology and Department of Infectious Diseases, College of Veterinary Medicine (both University of Georgia, Athens, GA, 30602 USA). The Odum School of Ecology affiliation is correct for co-authors Brown and Altizer rjhall@uga.edu.
Integrative and Comparative Biology
|June 3, 2016
Summary
Climate change may disrupt migratory escape and culling, potentially increasing disease risk for migrating animals. Understanding these shifts is crucial for predicting pathogen prevalence and impacts.
Area of Science:
- Ecology
- Epidemiology
- Climate Change
Background:
- Migratory animals may escape pathogens at higher latitudes, a phenomenon known as migratory escape.
- Migration can also reduce infection prevalence through migratory culling, where infected individuals are removed.
- Climate change impacts arthropod vectors and migratory host phenology, potentially altering disease dynamics.
Purpose of the Study:
- To explore how climate change influences vector-borne disease dynamics in migratory hosts.
- To model the effects of climate change on migratory escape, culling, and disease transmission.
- To investigate scenarios of migratory mismatch and sedentary amplification.
Main Methods:
- Developed a simple modeling framework to simulate climate change impacts on migratory hosts and disease vectors.
- Examined two scenarios: migratory mismatch (divergent phenology) and sedentary amplification (reduced migration).
Main Results:
- Climate change can reduce migratory escape by altering vector and host phenology.
- Migratory mismatch can lead to reduced overlap between susceptible hosts and vectors.
- Sedentary amplification can increase nonbreeding survival of infected hosts, leading to larger epidemics.
Conclusions:
- Climate change can disrupt established mechanisms of disease regulation in migratory animals.
- Continued surveillance of climate-driven changes in migration and vector activity is essential.
- Predicting pathogen prevalence requires understanding the interplay between climate, migration, and vector-borne diseases.
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