CAREER: The role of phenological mismatch and climate refugia in the ecology of infectious disease under global change

Global change, including climate and land use change, is shifting when and where species are active. For many infectious diseases, multiple species are involved in the amplification or dampening of disease risk and these species can be differentially affected by environmental conditions. For example, if the available suite of species upon which mosquito vectors of disease feed are not very effective at carrying the pathogen, disease risk may decrease even if mosquitoes are abundant. Alternatively, if the vector is active when effective hosts are abundant, disease risk likely increases more than otherwise expected. Thus, how disease risk will change will not only be determined by mosquito responses to environmental change, but how animal hosts of disease respond to these same processes. Using West Nile virus (WNV) in California's Central Valley as a case study, this project will investigate how seasonal activity of mosquito vectors and bird hosts will respond to environmental change, and whether and where activity of mosquitos and birds is likely to become more, or less synchronous as climate changes. More synchronous activity will likely increase disease transmission and human health risks. This project will also develop teaching materials and provide hands-on learning opportunities for underrepresented community college students in the Central Valley, develop outreach materials for communicating changing health risks to the public, and train undergraduates, graduate students and postdoctoral scholars in quantitative methods for predicting infectious disease dynamics. This project addresses three key questions at the interface of community ecology, global change ecology, and human health: 1) whether the degree of phenological synchrony between mosquito vectors and bird hosts predicts WNV activity, 2) how future scenarios of mosquito and bird host phenology might interact to change WNV prevalence and future transmission risk, and 3) how land use could modify phenological mismatch, creating climate refugia for vector-host interactions and pathogen transmission. This research will leverage a combination of machine learning-based species distribution modeling, causal inference statistical approaches, citizen science, and vector surveillance data. Together those approaches will be used to model mosquito and bird host phenology, its influence on West Nile virus infection rates in mosquitos, and potential future phenological mismatch. The project will also include field-based data collection for model validation, as well as associated public outreach and educational opportunities for underrepresented community college students in the Central Valley of California. 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.