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利用贝叶斯地理统计模型对巴西土壤传播的蠕虫感染进行空间分析和风险绘图。

Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

作者信息

Scholte Ronaldo G C, Schur Nadine, Bavia Maria E, Carvalho Edgar M, Chammartin Frédérique, Utzinger Jürg, Vounatsou Penelope

出版信息

Geospat Health. 2013 Nov;8(1):97-110. doi: 10.4081/gh.2013.58.

Abstract

Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

摘要

土源性蠕虫(蛔虫、鞭虫和钩虫)对数亿人的健康和福祉产生负面影响,尤其是在包括巴西在内的热带和亚热带国家。为了控制并最终消除土源性蠕虫病,需要可靠的空间分布图以及对感染人数的估计。我们运用先进的贝叶斯地理统计模型,结合地理信息系统和遥感技术,来直观呈现巴西三种土源性蠕虫的分布情况。将遥感获取的气候和环境数据,以及来自现有数据库的社会经济变量用作预测因子。我们的模型分别给出了蛔虫、鞭虫和钩虫的平均感染率估计值,依次为15.6%、10.1%和2.5%。通过以市为单位考虑感染风险和人口数量,我们估计有2970万巴西人感染蛔虫,1920万人感染鞭虫,470万人感染钩虫。我们基于模型的地图识别出了与土源性蠕虫传播相关的重要风险因素,并证实环境变量与贫困指数密切相关。我们的平滑风险地图(包括不确定性)突出显示了最急需开展土源性蠕虫病控制干预措施的地区,即巴西北部以及大部分沿海地区。我们认为,我们的预测风险地图对疾病控制管理人员确定控制干预措施的优先级以及提供更有效的监测-应对机制工具很有用。

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