Assessing wildlife die-off investigations and zoonotic disease surveillance in Colorado
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This project examines wildlife die-off surveillance in El Paso County, Colorado, and its role in detecting zoonotic pathogens such as Yersinia pestis (plague) and Francisella tularensis (tularemia). Using a One Health approach, the project integrates data from wildlife, veterinary, and public health sources to assess timeliness, coordination, and gaps in current systems. Data sources include county environmental health reports, laboratory testing records, and surveillance summaries from 2014-2025. Descriptive and spatial analyses were used to identify trends in wildlife mortality and overlaps with human and domestic animal exposures. Findings show that wildlife surveillance remains largely reactive, relying on public reports and limited annual field monitoring. Laboratory testing capacity is minimal, and data management systems operate independently, reducing opportunities for cross-sector analysis. These gaps delay early recognition of potential zoonotic events and limit the ability to link wildlife, human, and environmental data in real time. Findings show that while El Paso County maintains a strong foundation for wildlife surveillance, the system functions largely reactively, relying on public reports and limited seasonal field monitoring. Prairie dog colonies in undisturbed grassland and riparian areas remained stable, whereas those near roads or construction sites declined more frequently, indicating that habitat quality strongly influences colony persistence and potential disease activity. Data quality has improved in recent years, but spatial accuracy, laboratory linkage, and digital integration remain ongoing challenges. The evaluation identifies several opportunities to strengthen local surveillance, including developing standardized electronic reporting tools, improving data interoperability, and expanding limited vector monitoring to complement existing efforts. Increasing coordination among Environmental Health, Communicable Disease, and laboratory teams, as well as fostering stronger community engagement, would further enhance early detection and response. By applying a One Health lens, this project demonstrates how integrating wildlife, environmental, and human health data can improve preparedness for zoonotic disease threats and support long-term ecosystem and public health resilience.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.