Human-induced ecological and social changes are transforming the landscape of infectious disease at a scale unprecedented in both speed and global reach. Anticipating and preventing disease expansions is a critical goal for humanity, which requires understanding fundamental ecological mechanisms that drive infectious disease transmission. Vector-borne diseases—those transmitted by biting arthropods like mosquitoes and ticks, including malaria, dengue, West Nile, Zika, and Lyme disease, are highly sensitive to environmental change because vectors live, breed, and bite hosts in the human-impacted environment. This research investigates the mechanisms by which ecological changes in land use, such as deforestation, agricultural intensification, and unplanned urbanization, affect vector-borne disease transmission. The project will build capacity in STEM research and education, focusing on promoting diversity and open access to science and including a geospatial data analysis tutorial. Results of the research will be incorporated into tools directly useful to policymakers, including informing the development of InVEST software, which describes how natural ecosystems support human health and welfare and is currently in use in over 180 countries.
This project addresses three questions: (1) How does land use change affect the vector, host, and pathogen distributions and traits that drive disease transmission? (2) How important is land use change for vector-borne disease incidence observed at large scales in the field? (3) By what socioeconomic, behavioral, and ecological mechanisms does land use affect vector-borne disease transmission in the field? The hypothesis is that a dynamic gradient of land use intensification leads to a turnover in ecological suitability for transmission of different vector-borne diseases, resulting in succession from forest-based yellow fever and some forms of leishmaniasis, to malaria during early land conversion, to arboviruses transmitted by suburban and urban mosquitoes. The research will codify this hypothesis by developing trait-based epidemiological models of transmission for each of these focal diseases. Next, the research will test proposed relationships between environment and disease transmission using large-scale geospatial data on human disease, environment, and population in an econometrics statistical regression framework. Finally, the research will drill down into local transmission dynamics by surveying vector abundance, pathogen presence, human behavior, and socioeconomic conditions, combined with local-scale disease incidence data in situ in a field setting where land use is rapidly changing. Together, these approaches will identify and predict impacts of land use change on human disease.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
