A study protocol for an interrupted time series analysis and pre-post surveys to assess the effects a community-wide sanitation system on environmental contamination, infection risk, and well-being in Alabama's Black Belt

一项研究方案,采用中断时间序列分析和前后测调查,评估阿拉巴马州黑带地区社区卫生系统对环境污染、感染风险和居民福祉的影响。

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Abstract

INTRODUCTION: Rural sanitation deficits in the United States represent an important source of non-point source pollution and may present risks to public health. We propose an interrupted time series analysis to measure the effect of a town-wide sanitation expansion program on the release of pathogens to the environment. This work is expected to yield valuable insight into the potential for rural sanitation improvements to reduce pathogen releases and support public health and well-being. METHODS: We will conduct a longitudinal baseline study including quantitative measurement of key enteric pathogens and fecal indicator bacteria adjacent to households lacking adequate sanitation. As households connect to a new sewerage system serving the entire community, longitudinal household sampling will continue until crossover is complete. We will include concurrent comparison sites with existing appropriate sanitation as well as sites never receiving the intervention to monitor secular trends in pathogen releases during the study period. ANALYSIS: We will compare the concentration of culturable E. coli in the environment pre- and post-intervention using a time series regression analysis suitable for an interrupted time series. We will couple pathogen measurements with quantitative microbial risk assessment to estimate the potential effect of the intervention on infection risks via key exposure pathways. A linked pre-post survey will focus on self-reported quality of life measures among households connecting to the system. ETHICS AND DISSEMINATION: Informed consent will be obtained prior to data collection, with participants informed of study details and risks. Participation is completely voluntary, and identifiable data will be securely and separately stored from all other data. Each household will be offered a summary of their site-specific data. Deidentified results will be shared with the community in a public forum and published in peer-reviewed journals.

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