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Shifting patterns: malaria dynamics and rainfall variability in an African highland.
M Pascual1, B Cazelles, M J Bouma
1Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA. pascual@umich.edu
Proceedings. Biological Sciences
|November 15, 2007
Summary
Malaria outbreaks in East African highlands show increasing trends and epidemic sizes. Climate variability and disease dynamics interact, playing complementary roles at different scales, crucial for predictive models.
Area of Science:
- Epidemiology
- Climate Science
- Mathematical Biology
Background:
- Long-term malaria patterns in East African highlands show rising cases and epidemic sizes.
- The influence of climate variability on malaria epidemic cycles is debated, often contrasted with endogenous disease dynamics.
Purpose of the Study:
- To investigate the interplay between climate variability and malaria dynamics in western Kenya.
- To analyze long-term malaria case data and identify drivers of epidemic cycles.
Main Methods:
- Utilized a time-series epidemiological model (susceptible-infected-recovered) for monthly malaria cases (1970-2003).
- Employed a statistical approach for non-stationary patterns to analyze disease dynamics and climate forcing.
Main Results:
- Multiyear malaria outbreak cycles emerged in the 1980s, coinciding with a regime shift in case dynamics.
- Outbreaks intensified in the 1990s, with stronger coupling between malaria and rainfall, linked to increased rainfall variance.
- Disease dynamics and climate forcing act complementarily across different temporal scales.
Conclusions:
- Malaria epidemic cycles are driven by an interaction between disease dynamics and climate variability, not solely one or the other.
- Integrating these interacting mechanisms is essential for developing accurate future malaria predictive models.
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