Environment Change and Diarrheal Disease: A Natural Experiment

描述(由调查人员提供)：腹泻病是全世界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。但我们对环境变化(如道路发展)以及相关的社会和环境进程如何影响人类社区的健康的了解仍然有限。厄瓜多尔沿海地区的新公路建设继续提供宝贵的自然实验，通过它来研究环境和社会变化对健康的影响。在根据我们的第一个R01进行了四年的数据收集之后，我们已经证明了腹泻疾病病原体对人类和自然环境的变化，包括社会接触和凝聚力的变化非常敏感。正如我们在最近的PNAS出版物中所记录的那样，我们观察到偏远村庄的感染和疾病水平低于靠近铺设好的道路的村庄。在这项申请中，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在我们的第一个R01中完成的工作。两个假设将被探索，使用多层次分析的纵向数据。首先，偏远村庄拥有更密集的社会网络和更多的社会资本，这已被证明有助于改善卫生和个人卫生，直接影响腹泻病的发病率。第二，更偏远的村庄迁入率较低，因此接触新病原体菌株的比率较低。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：一是在我们之前四年数据的基础上纳入纵向设计，这将有助于建立社会因素和腹泻疾病之间的因果关系；另一种是收集社会和分子数据，使我们能够在更精细的范围内检查传播过程，提高我们对病原体移动、人类旅行和迁移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，我们计划集中进行三种类型的分析：1)时间序列分析，以将区域层面的腹泻疾病和肠道感染模式随时间与行为、社会结构和偏远地区的变化联系起来(特定目标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跨我们研究区域的区域层面的传播模式(特定目标2)；以及3)系统分析，以模拟社会资本和移民在肠道病原体传播中的作用，并探索不同的社会结构如何影响最佳干预决策(特定目标3)。完成本申请中概述的具体目标将使我们能够检查腹泻疾病随时间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所需的基础，这些计划能够考虑到将在其中实施这些计划的社会和环境结构。这是一个独特的机会，可以利用在我们最初的R01项目中开发的基础设施和收集的横断面数据。与公共卫生有关的腹泻病病原体是全世界发病率和死亡率的主要来源，似乎对人类和自然环境的变化很敏感，特别是与修建新道路有关的环境变化。厄瓜多尔沿海的这些新道路继续提供宝贵的自然实验，通过它来检查环境和社会变化对腹泻病发病率的影响。这一项目设计利用之前收集的横断面数据，在21个不同社区中进行了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.