Houngbedji Clarisse A, Chammartin Frédérique, Yapi Richard B, Hürlimann Eveline, N'Dri Prisca B, Silué Kigbafori D, Soro Gotianwa, Koudou Benjamin G, Assi Serge-Brice, N'Goran Eliézer K, Fantodji Agathe, Utzinger Jürg, Vounatsou Penelope, Raso Giovanna
Unité de Formation et de Recherche Sciences de la Nature, Université Nangui Abrogoua, 02 BP 801, Abidjan 02, Côte d'Ivoire.
Département Environnement et Santé, Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, 01 BP 1303, Abidjan 01, Côte d'Ivoire.
Parasit Vectors. 2016 Sep 7;9(1):494. doi: 10.1186/s13071-016-1775-z.
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.
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.
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.
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.
在科特迪瓦，疟疾仍然是一个重大的公共卫生问题，因此是需要解决的优先事项。本研究的目的是确定学龄儿童中恶性疟原虫感染的空间明确指标，并使用环境预测因子对恶性疟原虫感染风险进行基于模型的空间预测。
进行了一项横断面调查，包括对科特迪瓦93所学校的5000多名儿童进行寄生虫学检查和访谈。从每个儿童采集指尖血样，使用吉姆萨染色的厚薄血膜确定疟原虫种类特异性感染和寄生虫血症。通过资产拥有情况和家庭特征评估家庭社会经济地位。就疟疾预防措施对儿童进行访谈。从卫星图像和数字化地图收集环境数据。采用贝叶斯地理统计随机搜索变量选择程序来识别与恶性疟原虫感染风险相关的因素。使用贝叶斯地理统计逻辑回归模型绘制恶性疟原虫感染的空间分布，并通过贝叶斯克里金法预测非采样地点的感染患病率。
科特迪瓦5322名5至16岁儿童的完整数据集可用。恶性疟原虫是主要种类（94.5%）。贝叶斯地理统计变量选择程序确定土地覆盖和社会经济地位是恶性疟原虫感染风险的重要预测因子。基于模型的预测确定科特迪瓦北部、中东部、东南部、西部和西南部存在高恶性疟原虫感染风险。在靠近阿比让的东南部地区以及该国中南部和中西部发现了低风险地区。
科特迪瓦学龄儿童的恶性疟原虫感染风险及相关不确定性估计代表了最新的疟疾风险地图。这些工具可用于疟疾控制干预措施的空间定位。
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