Location: Crop Bioprotection ResearchTitle: Predicting the direct and indirect impacts of climate change on malaria in coastal Kenya
|LE, PHONG - University Of Illinois|
|KUMAR, PRAVEEN - University Of Illinois|
|RUIZ, MARILYN - University Of Illinois|
|MBOGO, CHARLES - Kenya Medical Research Institute|
|Muturi, Ephantus (juma)|
Submitted to: PLoS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/10/2019
Publication Date: 2/6/2019
Citation: Le, P.V., Kumar, P., Ruiz, M.O., Mbogo, C., Muturi, E.J. 2019. Predicting the direct and indirect impacts of climate change on malaria in coastal Kenya. PLOS One. 14:e0211258. https://doi.org/10.1371/journal.pone.0211258.
Interpretive Summary: The impacts of climate change on malaria transmission remain a subject of intense debate. Few studies have examined the causal relationship among rainfall, humidity, soil moisture, and mosquito breeding sites. None has incorporated the indirect impacts of ecohydrological responses induced by vegetation acclimation under climate change on malaria. Understanding these impacts may shed light on the sophisticated linkage between climate change and the dynamics of malaria. We examine the indirect impacts of vegetation acclimation on mosquito's habitat distribution and make prediction of changes in malaria transmission under global warming. We demonstrate the important role of indirect impacts of climate change through ecohydrologic modifications (i.e. change in hydrologic fluxes) on malaria dynamics. The results indicate the opposing effects of elevated [CO2] and air temperature increase on the dynamics of malaria. The increases in the frequency or the severity of malaria outbreaks as a result of global warming will be less serious than we expect.
Technical Abstract: The transmission of malaria is highly variable and depends on a range of climatic and anthropogenic factors. This study investigates the combined, i.e. direct and indirect, impacts of climate change on the dynamics of malaria through modifications in: (i) the sporogonic cycle of Plasmodium induced by air temperature increase, and (ii) the life cycle of Anopheles vector triggered by changes in natural breeding habitat arising from the altered moisture dynamics resulting from acclimation responses of vegetation under climate change. The study is performed for a rural region in Kilifi county, Kenya. We use a stochastic lattice-based malaria (SLIM) model to make predictions of changes in Anopheles vector abundance, the life cycle of Plasmodium parasites, and thus malaria transmission under projected climate change in the study region. SLIM incorporates a nonlinear temperature-dependence of malaria parasite development to estimate the extrinsic incubation period of Plasmodium. It is also linked with a spatially distributed eco-hydrologic modeling framework to capture the impacts of climate change on soil moisture dynamics, which served as a key determinant for the formation and persistence of mosquito larval habitats on the land surface. Malaria incidence data collected from 2008 to 2013 is used for SLIM model validation. Projections of climate change and human population for the region are used to run the models for prediction scenarios. Under elevated atmospheric CO2 concentration ([CO2]) only, modeled results reveal wetter soil moisture in the root zone due to the suppression of transpiration from vegetation acclimation, which increases the abundance of Anopheles vectors and the risk of malaria. When air temperature increases are also considered along with elevated CO2, the life cycle of Anopheles vector and the extrinsic incubation period of Plasmodium parasites are shortened nonlinearly. However, the reduction of soil moisture resulting from higher evapotranspiration due to air temperature increase also reduces the larval habitats of the vector. Our findings show the complicated role of vegetation acclimation under elevated CO2 on malaria dynamics and indicate an indirect but ignored impact of air temperature increase on malaria transmission through reduction in larval habitats and vector density.