Understanding the mechanisms of transmission of human leptospirosis in slums settlements in Salvador, Brazil

钩端螺旋体病是一种螺旋体人畜共患病，随着贫民窟在世界范围内迅速扩大并为老鼠传播创造了条件，钩端螺旋体病已成为一个重要的卫生问题。在巴西，每年有12,000人感染钩端螺旋体病，死亡率约为12%。在巴西萨尔瓦多市，该病的传播主要发生在家庭周围环境中，政府主导的封闭下水道网络的扩建使钩端螺旋体病的感染率显著下降。然而，由于政治上的忽视和贫民窟不受控制的扩张，传统的政府主导的封闭式下水道系统的建设日益成问题。为了解决这一问题，需要社区居民参与（COM-INT）的创新和更经济的方法已成为改善贫民窟住区卫生的合适替代方案。然而，评估卫生干预措施的实际影响，如政府综合干预和com综合干预，是有问题的，因为混淆因素和人口随机化难以获得足够大的样本量所导致的方法学问题。据我们所知，尚未开展任何研究来评估COM-INT对降低钩端螺旋体病风险的潜在积极作用。根据本项目直接促成的萨尔瓦多正在进行的一项研究的初步描述性统计数据，人们推测政府- int和COM-IN在减少钩端螺旋体病感染方面同样有效。在这种情况下，使用时空统计方法至关重要，以便通过考虑钩端螺旋体病感染的测量和未测量危险因素来推断COM-INT的实际影响。研究aims1。确定COM-INT和GOV-INT减少城市贫民窟污水直接接触和环境病原体负荷的机制。确定COM-INT和GOV-INT对大城市中心严重疾病发病率下降的贡献。研究设计/方法作为威康信托项目的一部分，本研究将分为以下两个部分（每个部分依次参考上述目标）1。钩端螺旋体感染的主要原因是接触受污染的污水和径流。因此，为了实现第一个研究目标，结合环境水库和居民运动信息的统计方法将适用于巴西萨尔瓦多Marechal Rodon社区正在进行的研究的数据。本研究点由9个区域组成，其中3个为政府干预区，3个为COM-INT区，3个为无干预区。在干预之前和之后，将收集总共2582个土壤样本，并对其进行钩端螺旋体DNA检测。这些数据将与使用多功能传感器节点收集的150个人的人类活动数据相结合，以定量暴露于污染源2。将利用1996年以来在医院开展的钩端螺旋体病监测所收集的数据，进行二次时空地统计分析，以评估联合调查和政府调查的有效性。为了考虑混杂效应，有关社会经济和环境因素的信息也将纳入时空模型。

Global health needLeptospirosis, a spirochetal zoonosis, has emerged as an important health problem as slum settlements have expanded rapidly worldwide and created conditions for rat-borne transmission. In Brazil, 12,000 individuals are annually infected with leptospirosis, with a death rate of about 12%. In the city of Salvador, Brazil, where transmission mostly occurs in peridomestic environments, the government-led expansion of closed sewer networks has resulted in a significant decrease of infection rates for leptospirosis. However, due to political neglect and the uncontrolled expansions of slums, construction of conventional governmentally led closed sewer systems (GOV-INT) is increasingly problematic. To address this issue, innovative and more economical methods that require of community residents involvement (COM-INT) have emerged as suitable alternatives to improve sanitation in slum settlements. However, assessing the real impact of sanitation intervention, such as GOV-INT and COM-INT, is problematic because of methodological issues due to confounding factors and difficulties with randomization of the population to obtain large enough large sample sizes.Current knowledge gapsTo the best of our knowledge, no study has been carried out to assess the potentially positive effects of COM-INT on the reduction of leptospirosis risk. Based on preliminary descriptive statistics from an ongoing study in Salvador, to which this project directly contributes, it has been conjectured that GOV-INT and COM-IN are equally effective in the reduction of Leptospirosis infections. In this context, the use of spatio-temporal statistical methods are crucial in order to infer the actual impact of COM-INT by taking account of both measured and unmeasured risk factors of Leptospirosis infection. Study aims1. Determine the mechanisms by which COM-INT and GOV-INT reduce direct human contact with sewage and environmental pathogen load in urban slums.2. Determine the contribution of COM-INT and GOV-INT on a decline in severe disease incidence in a large urban center.Study design/methodologyAs part of a Wellcome-Trust project, this study will be split into the following two parts (each referring to the above aims in turn)1. The main cause of Leptospira infection is exposure to contaminated sewage and run-off. Hence, to pursue the first study aim, statistical methods that combine information from environmental reservoirs and resident's movement will be fitted to data from an ongoing study in the community of Marechal Rodon in Salvador, Brazil. This study site consists of 9 areas, 3 with GOV-INT, 3 with COM-INT and 3 with no intervention. A total of 2,582 soils samples will be collected and tested for Leptospira DNA, before and after the interventions. These data will be integrated with human mobility data collected on 150 individuals using multifunctional sensor nodes to quantity the exposure to contamination sources2. A secondary spatio-temporal geostatistical analysis will be conducted to assess the effectiveness of COM-INT and GOV-INT, using data collected since 1996 from a hospital-based surveillance for leptospirosis that covers the population of Salvador since. To account for confounding effects, information on socio-economic and environmental factors will also be incorporated into the spatio-temporal model.