Mapping malaria risk among children in Côte d’Ivoire using Bayesian geo-statistical models

Malaria Journal

Research

Jürg Utzinger¹  Marcel Tanner¹  Nadine Schur¹  Penelope Vounatsou¹  Giovanna Raso²  Emile S Tchicaya³  Kigbafori D Silué³  Eliézer K N’Goran³  Benjamin G Koudou⁴  Fabian Rohner⁵  Serge Assi⁶  Barbara Matthys⁷ 

[1] Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, P.O. Box, CH-4002, Basel, Switzerland;University of Basel, P.O. Box, CH-4003, Basel, Switzerland;Département Environnement et Santé, Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, BP 1303, Abidjan 01, Côte d’Ivoire;Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, P.O. Box, CH-4002, Basel, Switzerland;University of Basel, P.O. Box, CH-4003, Basel, Switzerland;Département Environnement et Santé, Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, BP 1303, Abidjan 01, Côte d’Ivoire;UFR Biosciences, Université de Cocody, 22 BP 522, Abidjan 22, Côte d’Ivoire;Département Environnement et Santé, Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, BP 1303, Abidjan 01, Côte d’Ivoire;UFR Sciences de Nature, Université d’Abobo-Adjamé, 02 BP 801, Abidjan 02, Côte d’Ivoire;Vector Group, Liverpool School of Tropical Medicine, Pembroke Place, L3 5QA, Liverpool, United Kingdom;Global Alliance for Improved Nutrition, P.O. Box 55, Rue de Vermont 37-39, CH-1211, Geneva 20, Switzerland;Programme National de Lutte Contre le Paludisme, BP V4, Abidjan, Côte d’Ivoire;Institut Pierre Richet, 01 BP 1500, Bouaké 01, Côte d’Ivoire;University of Basel, P.O. Box, CH-4003, Basel, Switzerland;Swiss Centre for International Health, Swiss Tropical and Public Health Institute, P.O. Box, CH-4002, Basel, Switzerland;

关键词: Malaria;    Normalize Difference Vegetation Index;    Plasmodium;    Indoor Residual Spray;    Deviance Information Criterion;   

DOI  :  10.1186/1475-2875-11-160

 received in 2011-10-28, accepted in 2012-04-23,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundIn Côte d’Ivoire, an estimated 767,000 disability-adjusted life years are due to malaria, placing the country at position number 14 with regard to the global burden of malaria. Risk maps are important to guide control interventions, and hence, the aim of this study was to predict the geographical distribution of malaria infection risk in children aged <16 years in Côte d’Ivoire at high spatial resolution.MethodsUsing different data sources, a systematic review was carried out to compile and geo-reference survey data on Plasmodium spp. infection prevalence in Côte d’Ivoire, focusing on children aged <16 years. The period from 1988 to 2007 was covered. A suite of Bayesian geo-statistical logistic regression models was fitted to analyse malaria risk. Non-spatial models with and without exchangeable random effect parameters were compared to stationary and non-stationary spatial models. Non-stationarity was modelled assuming that the underlying spatial process is a mixture of separate stationary processes in each ecological zone. The best fitting model based on the deviance information criterion was used to predict Plasmodium spp. infection risk for entire Côte d’Ivoire, including uncertainty.ResultsOverall, 235 data points at 170 unique survey locations with malaria prevalence data for individuals aged <16 years were extracted. Most data points (n = 182, 77.4%) were collected between 2000 and 2007. A Bayesian non-stationary regression model showed the best fit with annualized rainfall and maximum land surface temperature identified as significant environmental covariates. This model was used to predict malaria infection risk at non-sampled locations. High-risk areas were mainly found in the north-central and western area, while relatively low-risk areas were located in the north at the country border, in the north-east, in the south-east around Abidjan, and in the central-west between two high prevalence areas.ConclusionThe malaria risk map at high spatial resolution gives an important overview of the geographical distribution of the disease in Côte d’Ivoire. It is a useful tool for the national malaria control programme and can be utilized for spatial targeting of control interventions and rational resource allocation.

【 授权许可】

CC BY   
© Raso et al.; licensee BioMed Central Ltd. 2012