Dissemin is shutting down on January 1st, 2025

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Public Library of Science, PLoS Neglected Tropical Diseases, 12(8), p. e3407, 2014

DOI: 10.1371/journal.pntd.0003407

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Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Schistosoma haematobium and Schistosoma mansoni are blood flukes that cause urogenital and intestinal schistosomiasis, respectively. In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species.; We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d'Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium-S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines.; We estimated that 8.9% of school-aged children in Côte d'Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country.; We provide a comprehensive analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d'Ivoire and a strong empirical basis for a rational targeting of control interventions.