Anthropogenic land use alters ecological communities, leading to the question: How do these changes alter infectious disease transmission, including to humans? This question is especially important in low-income countries such as Madagascar, where zoonotic diseases remain major threats to public health. The proposed research aims to model the ecological and socioeconomic factors that influence disease spread and predict how infectious agents spread from small mammals and domesticated animals to people. This goal will be pursued through innovative and interdisciplinary field, laboratory, and analytical approaches. The team of ecologists, social scientists, and a mathematician will integrate and model ecological and socioeconomic data from the field site in rural Madagascar, which includes a protected area surrounded by native forest fragments, agricultural fields, and villages of subsistence agriculturalists. Around four villages and in the park, the team will investigate multiple hypotheses concerning how human land use activities shape zoonotic disease transmission. To extend the findings globally, the researchers will use the Global Mammal Parasite Database to investigate how human land use and network connectivity impact host-parasite relationships and prevalence. The interdisciplinary team is uniquely positioned to investigate infectious disease transmission in this system. By integrating multiple data sources into unified mathematical representations, the team will investigate specific hypotheses for how diseases spread using multilayer transmission potential networks (TPNs). Significantly, they will test how TPNs and disease transmission change with human activities and identify the socioeconomic factors that lead some people to be more connected into transmission networks. Specifically, the team will: (i) identify pathways of disease transmission using cutting-edge field and analytical methods, coupled with infectious disease data representing multiple transmission modes; (ii) investigate socioeconomic characteristics of individual humans that most strongly connect them into TPNs of wildlife and domesticated animals; (iii) characterize how human activities generate entry points of infectious disease. Comparative analyses will extend the findings beyond the Malagasy study system. TPNs will be based on trapping data for small mammals, GPS data for people and domesticated animals, and social network surveys for people. The team will test whether these networks predict infection with multiple pathogens, including Leptospira, Yersinia, Babesia, Rickettsia, and gastrointestinal helminths. The research team has all necessary permits, extensive on-the-ground logistical support, and substantial pilot data on human and animal populations at the site.


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