背景:伤寒,或者肠热,是一种高度致命的传染病,每年影响全球900多万人,导致超过11万人死亡。减轻低收入国家的伤寒负担对公共卫生至关重要,需要实施可行的水,卫生,和卫生(WASH)干预措施,尤其是在人口稠密的城市贫民窟。
目的:在本研究中,在米尔普尔进行,孟加拉国,我们旨在评估大型前瞻性队列(n=98,087)的培训亚群中家庭WASH状态与伤寒风险之间的关联,并评估机器学习算法在创建复合WASH变量时的性能。Further,在2年的随访期内,我们调查了与生活在WASH设施改善的家庭和此类设施患病率增加的集群中相关的保护措施.
方法:我们使用机器学习算法基于3个WASH变量创建了一个二分复合变量(“更好”和“不更好”):私人厕所设施,安全饮用水源,和水过滤器的存在。使用来自训练亚群的数据训练该算法,然后在不同亚群(n=65,286)中验证以评估其灵敏度和特异性。Cox回归模型用于评估“更好”WASH家庭和“更好”WASH患病率增加的集群中生活的保护作用。
结果:我们发现,居住在WASH设施改善的家庭中,伤寒风险降低38%(调整后的风险比=0.62,95%CI0.49-0.78;P<.001)。在第一次人口普查时,这种减少在10岁以下的个人中尤为明显,调整后的风险比为0.49(95%CI0.36-0.66;P<.001)。此外,我们观察到集群中“更好”WASH设施的患病率与伤寒的发病率之间存在负相关关系,尽管这种关联在多变量模型中没有统计学意义.具体来说,对于集群中“更好”WASH的患病率每增加一个百分比,校正后的伤寒危害降低0.996(95%CI0.986-1.006)(P=.39).
结论:我们的研究结果表明,在人口稠密的城市贫民窟中,现有的家庭WASH变化与伤寒风险的差异有关。这表明WASH设施的可实现改进可以有助于增强伤寒控制,特别是在重大基础设施改进具有挑战性的环境中。这些发现强调了在低收入国家实施和促进全面的WASH干预措施的重要性,以此作为减轻伤寒负担和改善弱势群体公共卫生结果的手段。
Typhoid fever, or enteric fever, is a highly fatal infectious disease that affects over 9 million people worldwide each year, resulting in more than 110,000 deaths. Reduction in the burden of typhoid in low-income countries is crucial for public health and requires the implementation of feasible water, sanitation, and hygiene (WASH) interventions, especially in densely populated urban slums.
In this study, conducted in Mirpur, Bangladesh, we aimed to assess the association between household WASH status and typhoid risk in a training subpopulation of a large prospective cohort (n=98,087), and to evaluate the performance of a machine learning algorithm in creating a composite WASH variable. Further, we investigated the protection associated with living in households with improved WASH facilities and in clusters with increasing prevalence of such facilities during a 2-year follow-up period.
We used a machine learning algorithm to create a dichotomous composite variable (\"Better\" and \"Not Better\") based on 3 WASH variables: private toilet facility, safe drinking water source, and presence of water filter. The algorithm was trained using data from the training subpopulation and then validated in a distinct subpopulation (n=65,286) to assess its sensitivity and specificity. Cox regression models were used to evaluate the protective effect of living in \"Better\" WASH households and in clusters with increasing levels of \"Better\" WASH prevalence.
We found that residence in households with improved WASH facilities was associated with a 38% reduction in typhoid risk (adjusted hazard ratio=0.62, 95% CI 0.49-0.78; P<.001). This reduction was particularly pronounced in individuals younger than 10 years at the first census participation, with an adjusted hazard ratio of 0.49 (95% CI 0.36-0.66; P<.001). Furthermore, we observed an inverse relationship between the prevalence of \"Better\" WASH facilities in clusters and the incidence of typhoid, although this association was not statistically significant in the multivariable model. Specifically, the adjusted hazard of typhoid decreased by 0.996 (95% CI 0.986-1.006) for each percent increase in the prevalence of \"Better\" WASH in the cluster (P=.39).
Our findings demonstrate that existing variations in household WASH are associated with differences in the risk of typhoid in densely populated urban slums. This suggests that attainable improvements in WASH facilities can contribute to enhanced typhoid control, especially in settings where major infrastructural improvements are challenging. These findings underscore the importance of implementing and promoting comprehensive WASH interventions in low-income countries as a means to reduce the burden of typhoid and improve public health outcomes in vulnerable populations.