埃塞俄比亚农村地区婴儿接触粪便污染的多途径定量评估

Yuke Wang, Yang Yang, Crystal M. Slanzi, Xiaolong Li, Amanda Ojeda, Fevi Paro, Löıc Deblais, Habib Yakubu, Bahar Mummed Hassen, Halengo Game, Kedir Teji Roba, Elizabeth Schieber, Abdulmuen Mohammed Ibrahim, Jeylan Wolyie, Jemal Yusuf Hassen, Gireesh Rajashekara, Sarah L. McKune, Arie H. Havelaar, Christine L. Moe, Song Liang
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引用次数: 0

摘要

在中低收入国家(LMICs),肠道感染对儿童健康构成了严重威胁。然而,人们对中低收入国家幼儿何时、何地、如何接触肠道病原体的具体情况,以及动物贮藏库、环境媒介和人类宿主在接触过程中所起的作用的了解仍然有限。本研究系统评估了埃塞俄比亚哈拉马亚农村地区婴儿通过各种途径接触大肠杆菌的情况。2021 年 6 月至 2022 年 6 月期间,我们对 79 名 4-8 个月(时间点 1)和 11-15 个月(时间点 2)的婴儿进行了超过 1300 小时的结构化行为观察。调查员使用 Countee © 应用程序记录婴儿与暴露相关的行为,包括何时何地发生的行为。与此同时,我们从婴儿、其他人和环境的主要接触界面收集了 1338 份环境样本,以检测大肠杆菌。对于持续时间长的行为,我们采用了竞争危险模型;对于频率高的行为,我们采用了不均匀泊松点过程模型;对于大肠杆菌污染水平,我们采用了左删失对数正态分布模型。然后将行为和环境信息整合到基于代理的暴露模型框架中,通过不同途径量化大肠杆菌的暴露量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative Multi-pathway Assessment of Exposure to Fecal Contamination for Infants in Rural Ethiopia
In low- and middle-income countries (LMICs), enteric infections pose a significant threat to children’s health. However, understanding the specifics of when, where, and how young children in LMICs are exposed to enteric pathogens and the roles of animal reservoirs, environmental media, and human hosts play during exposure remains limited. This study systematically evaluates infants’ exposure to E. coli through various pathways in the rural Haramaya woreda of Ethiopia. Between June 2021 and June 2022, we conducted over 1300 hours of structured behavioral observations on 79 infants when aged 4–8 months (Timepoint 1) and 11–15 months (Timepoint 2). Enumerators recorded the infant’s behavior related to exposure, including when and where it occurred, using the Countee © application. Concurrently, we collected 1338 environmental samples from key contact interfaces between infants, other people, and the environment to test for E. coli. We used a competing hazard model for duration-based behaviors, an inhomogeneous Poisson point process model for frequency-based behaviors, and a left-censored lognormal distribution model for E. coli contamination levels. The behavioral and environmental information was then integrated into an agent-based exposure model framework to quantify the exposure to E. coli through different pathways.
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