P-21 - New insights from mosquito surveillance collaboration between University of Notre Dame and St. Joseph County Environmental Health Department, Indiana, 2021-2024

Abstract: In 2021, the University of Notre Dame piloted a collaborative program between the College of Science and the St. Joseph County Environmental Health Department to conduct mosquito abundance and species surveillance for medically important mosquito species at two nature preserves in eastern St. Joseph County. Here, we demonstrate the significant contributions of a program like this to the local community and broader public health efforts. The team set a combination of CDC light traps baited with CO₂ and light, gravid traps baited with putrid alfalfa water, and resting boxes throughout the sites. Traps were set overnight, collected the following afternoon, and identified by dichotomous guides. Species implicated in arboviral disease transmission, namely Equine Encephalitis Virus (EEEV), West Nile Virus (WNV), and Lacrosse Encephalitis (LE), were sent to the Indiana State Health Department for viral testing. Over four years, we collected and keyed a total of 171,922 females, including 126,835 Coquillettidia perturbans, the main bridging vector of EEEV to mammals in the region. We identified two WNV positive pools in gravid traps in 2024, and identified regional morphologic variation in Culiseta melanura, the vector responsible for enzootic maintenance of EEEV in bird populations. Additionally, across the project timeline, we trained local high school and undergraduate students on mosquito identification, conducted community engagement and education, and implemented a training and testing protocol to validate a new artificial intelligence (AI)-based platform for mosquito identification. Finally, we were able to make reliable forecasts on total mosquito abundance based on weather attributes. We have shown the application of a collaborative surveillance model like ours to local health department efforts. Future work is needed to continue optimizing collection procedures to maximize efficacy and minimize strain on personnel, formalize a training program for students, expand surveillance to ticks, and further evaluate incorporating AI into vector surveillance workflows.