Spatial mapping and prediction of Plasmodium falciparum infection risk among school-aged children in Cote dIvoire

Abstract

Background

In Cote 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 Cote 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 Cote 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 Cote 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 Cote d'Ivoire represent the most up-to-date malaria risk maps. These tools can be used for spatial targeting of malaria control interventions.