Session: Using NASA Satellite Data to Enhance Understanding of Vector Habitats and Disease Transmission Symposium
305 - VectorSurv: Toward Web-based Forecasting of West Nile Virus Disease Risk
Tuesday, March 5, 2024
2:15pm – 2:30pm
Location: D3
VectorSurv is dedicated to providing a cutting-edge web-based platform designed to streamline the management, visualization, and analysis of data pertaining to vector surveillance and control. Its primary objective is to enhance the usability of data for key stakeholders within the public health community, spanning various agencies at the local, state, and national levels. Currently, VectorSurv is actively utilized by vector control agencies and public health organizations in over 20 U.S. states and territories, underscoring its scalability for nationwide implementation.
The system’s core functionality centers on data management and decision-support tools, including “nowcasts” that translate surveillance data into real-time assessments of entomological or epidemiological risks for arboviral diseases. This significantly enhances assessment of arboviral disease threats by standardizing data collection and ensuring public accessibility. Alongside its hosting of vector surveillance data, the web-based VectorSurv platform constantly updates and hosts climate and other environmental data essential for modeling vector distributions and pathogen transmission.
VectorSurv is engaged in ongoing efforts to create short-term forecasting models. These models will seamlessly integrate real-time vector surveillance data with NASA’s Earth observations and other complementary environmental data sources. The transition to a web-based format for these models is aimed at democratizing access to predictive tools, catering to a wide range of users and needs, including vector control professionals, public health officials, and researchers.
VectorSurv is committed to establishing a direct connection between predictive models and the extensive underlying database. This integration is expected to catalyze collaborations between modelers and decision-makers. By bridging this long-standing divide, we aim to create a synergy where scientific evidence can swiftly inform strategic actions, ultimately resulting in more effective vector control measures and proactive public health responses.