Measuring human behavior and ecological dimensions of pathogen transmission for outbreak control and prevention

This project proposes interdisciplinary research across biology and geography to examine links between human-environment interactions, spatiotemporal patterns of human mobility and health geographies, and endemic and emerging infectious diseases. This work focuses on measles and Ebola prevention and management in the Équateur province in the Democratic Republic of Congo (DRC), where both pathogens cause significant morbidity and mortality. Recurring outbreaks emphasize an urgent need for significant public health improvements. This research investigates the mechanisms underlying pathogen transmission and identifies epidemiological units, across which transmission occurs, and measure their vulnerability to outbreaks. Outputs will be developed with and for mobile health teams in the DRC and will provide a generalizable blueprint for the broader application of this approach across a range of contexts. The proposed research targets the intersection of theoretical frameworks to examine four interlinked topics. First, following Cutter in 2003, this project will develop formal spatial methods to identify and delineate epidemiological units of pathogen transmission and measure their epidemiological vulnerability. Vulnerability is determined by the mechanisms underlying locally specific transmission processes, which differ across diseases. This work includes health data quality as a problem that allow public health problems to persist where they most need improvement. Second, building on Kwan’s 2013 work, this research will start with R1’s epidemiological units and vulnerability indices and integrate the dynamics of seasonal and long-term population mobility, connectivity, and distribution. Population dynamics drive contacts, transmission, and spread for communicable pathogens and must be included in vaccinations and outbreak response. Third, extending Shuurman’s 2011 work, this research will visually represent these dynamic epidemiological units and vulnerability indices cartographically to advance methods in geovisualizations and provide usable spatial decision support systems (SDSS) for mobile health efforts. To maximize clarity and usability, these visualizations will be rigorously developed and tested with our collaborating humanitarian organization’s field teams and graduate students in infectious diseases and geography. Fourth, this work will develop dynamic quantitative models to produce formal comparisons of intervention strategies and iteratively improve them. Models will compare A) strategies using the proposed SDSS, which highlight acting on the vulnerability of epidemiological units of transmission before outbreaks occur for immunizations and outbreak responses and B) the current system, which is guided by administrative boundaries and case rate thresholds to trigger response. Linking spatial and temporal elements of human-environment interactions to support infectious disease prevention and outbreak management will significantly advance the current methods and theory in this field.