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.
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.
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