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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
Relative importance of climatic, geographic and socio-economic determinants of malaria in Malawi
Malaria Journal, Volume 12, No. 1, Article 416, Year 2013
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Description
Background: Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the parasite and its vector, but also socio-economic conditions, such as levels of urbanization, poverty and education, which impact human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for the modelling of malaria risk in space and time. Methods. A statistical mixed model framework is proposed to model malaria risk at the district level in Malawi, using an age-stratified spatio-temporal dataset of malaria cases from July 2004 to June 2011. Several climatic, geographic and socio-economic factors thought to influence malaria incidence were tested in an exploratory model. In order to account for the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a generalized linear mixed model was adopted, which included structured and unstructured spatial and temporal random effects. A hierarchical Bayesian framework using Markov chain Monte Carlo simulation was used for model fitting and prediction. Results: Using a stepwise model selection procedure, several explanatory variables were identified to have significant associations with malaria including climatic, cartographic and socio-economic data. Once intervention variations, unobserved confounding factors and spatial correlation were considered in a Bayesian framework, a final model emerged with statistically significant predictor variables limited to average precipitation (quadratic relation) and average temperature during the three months previous to the month of interest. Conclusions: When modelling malaria risk in Malawi it is important to account for spatial and temporal heterogeneity and correlation between districts. Once observed and unobserved confounding factors are allowed for, precipitation and temperature in the months prior to the malaria season of interest are found to significantly determine spatial and temporal variations of malaria incidence. Climate information was found to improve the estimation of malaria relative risk in 41% of the districts in Malawi, particularly at higher altitudes where transmission is irregular. This highlights the potential value of climate-driven seasonal malaria forecasts. © 2013 Lowe et al.; licensee BioMed Central Ltd.
Authors & Co-Authors
Lowe, Rachel
Italy, Trieste
Abdus Salam International Centre for Theoretical Physics
Spain, Barcelona
Institut Català de Ciències Del Clima Ic3
Chirombo, James
Malawi, Lilongwe
Ministry of Health Malawai
Tompkins, Adrian Mark
Italy, Trieste
Abdus Salam International Centre for Theoretical Physics
Statistics
Citations: 10
Authors: 3
Affiliations: 3
Identifiers
Doi:
10.1186/1475-2875-12-416
e-ISSN:
14752875
Research Areas
Environmental
Genetics And Genomics
Infectious Diseases
Study Design
Randomised Control Trial
Cross Sectional Study
Cohort Study
Exploratory Study
Study Locations
Malawi