Abstract
Abstract. Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission driven by climatic time series. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear ecohydrological model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.
Highlights
The World Health Organization estimates that 250 million clinical episodes of malaria occur annually, resulting in at least one million disease-associated deaths (World HealthOrganization, 2008)
The ecohydrological model we derive makes a series of simplifying assumptions, our results show that variability in soil water content is significantly correlated with variability in malaria incidence, whereas neither rainfall nor temperature alone shows this correlation
We considered whether soil water content dynamics may be associated with malaria case anomalies
Summary
The World Health Organization estimates that 250 million clinical episodes of malaria occur annually, resulting in at least one million disease-associated deaths (World HealthOrganization, 2008). Since the pioneering work by Ross (1910) and MacDonald (1957), progress in understanding malaria dynamics has been made through the development of mathematical models and their statistical inference with incidence data A subset of these models has considered the role that external forcing plays in generating patterns of seasonal and interannual case variability. Despite these advances, early warning systems for malaria have still only limited ability (and thereby efficacy) to predict outbreaks, and the factors contributing to malaria case variability still require more thorough investigation (Pascual et al, 2008; Craig et al., 2004a,b). Two climatic variables that have long been known to influence malaria’s seasonal and interannual dynamics are temperature and rainfall. A moderate level of rainfall appears to have a positive effect on mosquito recruitment, intense rainfall events may destroy mosquito habitats and thereby reduce malaria incidence shortly following their occurrence (Briet et al, 2008)
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