Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d'Ivoire

Houngbedji, Clarisse A. and Chammartin, Frédérique and Yapi, Richard B. and Hürlimann, Eveline and N'Dri, Prisca B. and Silué, Kigbafori D. and Soro, Gotianwa and Koudou, Benjamin G. and Assi, Serge-Brice and N'Goran, Eliézer K. and Fantodji, Agathe and Utzinger, Jürg and Vounatsou, Penelope and Raso, Giovanna. (2016) Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Côte d'Ivoire. Parasites and Vectors, 9. p. 494.

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BACKGROUND: In Côte d'Ivoire, malaria remains a major public health issue, and thus a priority to be tackled. The aim of this study was to identify spatially explicit indicators of Plasmodium falciparum infection among school-aged children and to undertake a model-based spatial prediction of P. falciparum infection risk using environmental predictors.
METHODS: A cross-sectional survey was conducted, including parasitological examinations and interviews with more than 5,000 children from 93 schools across Côte d'Ivoire. A finger-prick blood sample was obtained from each child to determine Plasmodium species-specific infection and parasitaemia using Giemsa-stained thick and thin blood films. Household socioeconomic status was assessed through asset ownership and household characteristics. Children were interviewed for preventive measures against malaria. Environmental data were gathered from satellite images and digitized maps. A Bayesian geostatistical stochastic search variable selection procedure was employed to identify factors related to P. falciparum infection risk. Bayesian geostatistical logistic regression models were used to map the spatial distribution of P. falciparum infection and to predict the infection prevalence at non-sampled locations via Bayesian kriging.
RESULTS: Complete data sets were available from 5,322 children aged 5-16 years across Côte d'Ivoire. P. falciparum was the predominant species (94.5 %). The Bayesian geostatistical variable selection procedure identified land cover and socioeconomic status as important predictors for infection risk with P. falciparum. Model-based prediction identified high P. falciparum infection risk in the north, central-east, south-east, west and south-west of Côte d'Ivoire. Low-risk areas were found in the south-eastern area close to Abidjan and the south-central and west-central part of the country.
CONCLUSIONS: The P. falciparum infection risk and related uncertainty estimates for school-aged children in Côte d'Ivoire represent the most up-to-date malaria risk maps. These tools can be used for spatial targeting of malaria control interventions.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Biostatistics > Bayesian Modelling and Analysis (Vounatsou)
UniBasel Contributors:Utzinger, Jürg and Vounatsou, Penelope and Raso, Giovanna
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:20 Oct 2016 13:22
Deposited On:20 Oct 2016 13:22

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