Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
PLoS Negl Trop Dis. 2023 Jul 26;17(7):e0011437. doi: 10.1371/journal.pntd.0011437. eCollection 2023 Jul.
Cysticercosis is a neglected tropical disease caused by the larval stage of the zoonotic tapeworm (Taenia solium). While there is a clear spatial component in the occurrence of the parasite, no geostatistical analysis of active human cysticercosis has been conducted yet, nor has such an analysis been conducted for Sub-Saharan Africa, albeit relevant for guiding prevention and control strategies. The goal of this study was to conduct a geostatistical analysis of active human cysticercosis, using data from the baseline cross-sectional component of a large-scale study in 60 villages in Burkina Faso. The outcome was the prevalence of active human cysticercosis (hCC), determined using the B158/B60 Ag-ELISA, while various environmental variables linked with the transmission and spread of the disease were explored as potential explanatory variables for the spatial distribution of T. solium. A generalized linear geostatistical model (GLGM) was run, and prediction maps were generated. Analyses were conducted using data generated at two levels: individual participant data and grouped village data. The best model was selected using a backward variable selection procedure and models were compared using likelihood ratio testing. The best individual-level GLGM included precipitation (increasing values were associated with an increased odds of positive test result), distance to the nearest river (decreased odds) and night land temperature (decreased odds) as predictors for active hCC, whereas the village-level GLGM only retained precipitation and distance to the nearest river. The range of spatial correlation was estimated at 45.0 [95%CI: 34.3; 57.8] meters and 28.2 [95%CI: 14.0; 56.2] km for the individual- and village-level datasets, respectively. Individual- and village-level GLGM unravelled large areas with active hCC predicted prevalence estimates of at least 4% in the south-east, the extreme south, and north-west of the study area, while patches of prevalence estimates below 2% were seen in the north and west. More research designed to analyse the spatial characteristics of hCC is needed with sampling strategies ensuring appropriate characterisation of spatial variability, and incorporating the uncertainty linked to the measurement of outcome and environmental variables in the geostatistical analysis. Trial registration: ClinicalTrials.gov; NCT0309339.
囊尾蚴病是一种由动物源性带绦虫(猪带绦虫)幼虫引起的被忽视的热带病。虽然寄生虫的发生有明显的空间成分,但尚未对活动性人类囊尾蚴病进行任何地统计学分析,也没有对撒哈拉以南非洲进行这种分析,尽管这对于指导预防和控制策略很重要。本研究的目的是使用布基纳法索 60 个村庄的大型研究基线横断面部分的数据,对活动性人类囊尾蚴病进行地统计学分析。结果是使用 B158/B60 Ag-ELISA 确定的活动性人类囊尾蚴病(hCC)的患病率,同时还探索了与疾病传播和扩散相关的各种环境变量,作为 T. solium 空间分布的潜在解释变量。运行了广义线性地统计学模型(GLGM),并生成了预测图。分析是在个体参与者数据和分组村庄数据两个层面上进行的。使用向后变量选择程序选择最佳模型,并使用似然比检验比较模型。最佳个体水平 GLGM 包括降水(降水增加与阳性检测结果的几率增加相关)、到最近河流的距离(几率降低)和夜间土地温度(几率降低)作为活动性 hCC 的预测因子,而村庄水平 GLGM 仅保留降水和到最近河流的距离。估计个体水平和村庄水平数据集的空间相关范围分别为 45.0 [95%CI:34.3;57.8] 米和 28.2 [95%CI:14.0;56.2] 公里。个体水平和村庄水平 GLGM 揭示了东南、最南部和西北部地区存在活动性 hCC 预测患病率至少为 4%的大面积地区,而北部和西部地区则存在患病率估计低于 2%的斑块。需要进行更多旨在分析 hCC 空间特征的研究,采样策略确保适当描述空间变异性,并在地统计学分析中纳入与结局和环境变量测量相关的不确定性。试验注册:ClinicalTrials.gov;NCT0309339。