Data Collection and Management Tools for Wildlife Health Surveillance
3:30 a 3:45 pm, Centro de Estudios Científicos
Diego Montecino-Latorre1 | Bevan Federko2 | Kevin Brown2 | Jonathan Palmer3 | Chris Walzer5 | Luis Guerra5 | Mariana Montoya6 | Sarah Olson7 | Mathieu Pruvot8
- WCS – Chile; 2. Canadian Wildlife Health Cooperative; 3. WCS Conservation Technology; 4. WCS Health Program; 5. WCS – Guatemala; 6. WCS – Peru; 7. WCS Health Program; 8. University of Calgary and WCS Health Program.
Ponente: Diego Montecino-Latorre, email@example.com
Wildlife Health Surveillance (WHS) requires the generation and management of diverse data. For a WHS system to deliver intelligence for management and response, such data (e.g., geolocation, species involved, animals sampled, necropsies, samples, and tests) must be standardized, safely and securely stored, and easily shared across stakeholders. Therefore, affordable, flexible, sustainable, and easy-to-use digital tools supporting these processes are key. As part of the WildHealthNet initiative, we piloted SMART for Health (SfH) in conjunction with the Wildlife Health Intelligence Platform database (WHIP) to support data collection and management. SfH is an adaptation of the Spatial Monitoring and Reporting Tool (SMART), a suite of technological tools originally developed for law enforcement in protected areas. SfH supports the smooth digital recording of wildlife health events using smartphones. To centrally manage data we customized WHIP, a database for Wildlife Health Surveillance` developed by the Canadian Wildlife Health Cooperative. New features expand the hierarchical data structure to include observed-only individuals per species, environmental specimens, and diagnostic tests for individual samples. WHIP was also optimized to accommodate diverse surveillance designs or past surveillance efforts, and structured studies. The current versions of these tools are the outcome of field testing by stakeholders in South-East Asia; and iterative design, feedback, and improvement cycles. Their use is being expanded to Guatemala, Belize, Mexico, and Perú. Manuals, data glossaries, and training materials are available and translated. Data structure in SfH and WHIP are consistent and SMART-to-WHIP data transfer is under development. The long-term expertise embedded in SMART and WHIP, their expected sustainability, the current use of SMART in several protected areas in Latin America, and our successful deployment of these tools, underscore SMART-WHIP as a promising choice to support WHS systems regionally and globally.