Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda

Colón-González, Felipe J., Tompkins, Adrian M., Biondi, Riccardo, Bizimana, Jean Pierre and Namanya, Didacus Bambaiha (2016) Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda. Geospatial Health, 11 (S1). pp. 18-37. ISSN 1827-1987

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We investigate the short-term effects of air temperature, rainfall, and socioeconomic indicators on malaria incidence across Rwanda and Uganda from 2002 to 2011. Delayed and nonlinear effects of temperature and rainfall data are estimated using generalised additive mixed models with a distributed lag nonlinear specification. A time series cross-validation algorithm is implemented to select the best subset of socioeconomic predictors and to define the degree of smoothing of the weather variables. Our findings show that trends in malaria incidence agree well with variations in both temperature and rainfall in both countries, although factors other than climate seem to play an important role too. The estimated short-term effects of air temperature and precipitation are nonlinear, in agreement with previous research and the ecology of the disease. These effects are robust to the effects of temporal correlation. The effects of socioeconomic data are difficult to ascertain and require further evaluation with longer time series. Climate-informed models had lower error estimates compared to models with no climatic information in 77 and 60% of the districts in Rwanda and Uganda, respectively. Our results highlight the importance of using climatic information in the analysis of malaria surveillance data, and show potential for the development of climateinformed malaria early warning systems.

Item Type: Article
Additional Information: Date of Acceptance: 11/11/2015 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Uncontrolled Keywords: malaria,weather effects,statistical modelling,health,sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School: Faculty of Science > School of Environmental Sciences
UEA Research Groups: University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research
Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research
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Depositing User: Pure Connector
Date Deposited: 14 Nov 2016 17:00
Last Modified: 14 Jun 2023 12:46
DOI: 10.4081/gh.2016.379

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