SISS-Geo: Leveraging Citizen Science to Monitor Wildlife Health Risks in Brazil

Area of Science:

• Wildlife health surveillance
• Ecology and epidemiology
• Information systems and data science

Background:

• Human and wildlife health face challenges in pathogen monitoring, data integration, and risk prediction.
• Brazil's vast territory and fragmented policies hinder effective wildlife health surveillance systems.
• Existing systems struggle with integrating diverse data, species, and socio-environmental contexts.

Purpose of the Study:

• To introduce the Brazilian Wildlife Health Information System (SISS-Geo) as a collaborative platform for wildlife health monitoring.
• To overcome challenges in wildlife health surveillance across Brazil's diverse landscapes.
• To foster integration and participation across societal segments for improved wildlife health management.

Main Methods:

• Citizen scientists register animal occurrences, contributing to data collection.
• Expert networks and laboratories provide reliable pathogen diagnoses.
• Computational and mathematical approaches are used for analytical and predictive systems, data integration, and visualization.

Main Results:

• SISS-Geo facilitates collaborative monitoring of wildlife health events.
• The system integrates data from citizen science, expert diagnostics, and advanced analytics.
• Successfully applied to support decision-making during a Yellow Fever epizootic.

Conclusions:

• SISS-Geo is a valuable tool for georeferenced wildlife health information and collaborative monitoring.
• The platform enhances the capacity for early detection and response to wildlife health threats.
• Integration of diverse data sources and societal participation is key to effective wildlife health surveillance.