Environment Change and Diarrheal Disease: A Natural Experiment

描述（由研究者提供）：腹泻病是世界范围内发病率和死亡率的主要原因，其基本的个人水平的危险因素是众所周知的。但是，我们对环境变化（如道路开发）和相关的社会和环境过程如何影响人类社区健康的理解仍然有限。厄瓜多尔沿海地区新公路的建设继续提供宝贵的自然实验，通过它可以研究长期以来环境和社会变化对健康的影响。在我们的第一个R01下，经过四年的数据收集，我们已经证明腹泻病病原体对人类和自然环境的变化很敏感，包括社会接触和凝聚力的变化。正如我们最近发表在《美国国家科学院院刊》（PNAS）上的文献所述，我们观察到，偏远村庄的感染和疾病水平低于靠近柏油路的村庄。在这个应用程序中，我们的目标是通过检查导致感染率区域差异的因果过程来扩展我们在第一个R01下完成的工作。两个假设将探讨，使用纵向数据在多个层次的分析。首先，偏远村庄拥有更密集的社会网络和更多的社会资本，这已被证明可以改善环境卫生和个人卫生，直接影响腹泻病的发病率。第二，更偏远的村庄的迁移率更低，因此接触新病原体菌株的比率也更低。为了解决这些假设，我们建议以两种方式修改我们的研究设计：一是采用纵向设计，建立在我们过去四年的数据基础上，这将有助于建立社会因素与腹泻疾病之间的因果关系；另一个是收集社会和分子数据，这将使我们能够在更精细的尺度上检查传播过程，提高我们对病原体运动、人类旅行和迁徙以及社会结构变化的理解。为了更好地了解病原体在整个地区的流动，我们计划将重点放在三种类型的分析上：1)时间序列分析，将区域层面的腹泻疾病和肠道感染模式随着时间的推移与行为、社会结构和偏远程度的变化联系起来（具体目标1）；2)大肠杆菌分离株的分子分析，以检查大肠杆菌菌株随时间和整个研究区域的区域水平传播模式（具体目标2）；3)系统分析，模拟社会资本和移民在肠道病原体传播中的作用，并探讨不同的社会结构如何影响最佳干预决策（具体目标3）。完成本应用程序中概述的具体目标将使我们能够检查腹泻疾病传播的社会和环境决定因素。最终，这将为制定更适当的长期干预计划提供必要的基础，这些计划可以考虑到将在其中执行这些计划的社会和环境结构。这是一个独特的机会，可以利用在初始R01项目期间开发的基础设施和收集的横断面数据。腹泻病病原体是全世界发病率和死亡率的主要来源，它似乎对人类和自然环境的变化很敏感，特别是与新道路建设有关的变化。厄瓜多尔沿海地区的这些新道路继续提供宝贵的自然实验，通过这些实验来研究环境和社会变化对腹泻病发病率的影响。本项目设计利用先前收集的横断面数据，在21个不同社区中进行多层次分析的疾病传播纵向研究。

DESCRIPTION (provided by investigator): Diarrheal disease is a leading cause of morbidity and mortality worldwide, and its basic individual-level risk factors are well known. But our understanding is still limited about how environmental changes (such as road development) and associated social and environmental processes impact the health of human communities. The construction of new roads in coastal Ecuador continues to provide a valuable natural experiment through which to examine the impacts of environmental and social changes on health over time. After four years of data collection under our first R01 we have demonstrated that diarrheal disease pathogens are sensitive to changes in human and natural environments, including changes in social contact and cohesion. As documented in our recent PNAS publication, we observed lower levels of infection and disease in remote villages than in villages closer to a paved road. In this application we aim to extend the work accomplished under our first R01 by examining the causal processes leading to this regional variability in rates of infection. Two hypotheses will be explored, using longitudinal data at multiple levels of analysis. The first is that remote villages have denser social networks and more social capital, which has been shown to lead to improved sanitation and hygiene, directly affecting diarrheal disease incidence. The second is that more remote villages have lower in-migration rates, and therefore have lower rates of exposure to new pathogen strains. To address these hypotheses we propose to modify our study design in two ways: One is to incorporate a longitudinal design, building on our previous four years of data, which will help to establish causality between social factors and diarrheal illness; and the other is to collect social and molecular data that will allow us to examine transmission processes at a much finer scale, improving our understanding of pathogen movement, human travel and migration, and changes in social structure. To better understand flows of pathogens throughout the region, we plan to focus on three types of analyses: 1) Time series analysis to correlate regional level diarrheal disease and enteric infection patterns over time with changes in behavior, social structure, and remoteness (Specific Aim 1); 2) Molecular analysis of E. coli isolates, to examine regional level transmission patterns of E. coli strains over time and across our study region (Specific Aim 2); and 3) Systems analysis to model the role that social capital and migration play in the transmission of enteric pathogens, and to explore how differing social structures might affect optimal intervention decisions (Specific Aim 3). Accomplishing the specific aims outlined in this application will enable us to examine the social and environ- mental determinants of diarrheal disease transmission over time. Ultimately, this will provide the foundation required to develop more appropriate long-term intervention plans that can take into account the social and environmental structures in which they will be implemented. This is a unique opportunity to take advantage of both the infrastructure developed and the cross-sectional data collected during our initial R01 project. PUBLIC HEALTH RELEVANCE Diarrheal disease pathogens, leading sources of morbidity and mortality worldwide -- appear sensitive to changes in both human and natural environments, particularly those related to the construction of new roads. These new roads in coastal Ecuador continue to provide a valuable natural experiment through which to examine the impacts of environmental and social changes on the incidence of diarrheal disease. This project design takes advantage of previously collected cross-sectional data to mount a longitudinal study of disease transmission at multiple levels of analysis among 21 different communities.