Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: May 15, 2025
Date Accepted: Jul 21, 2025
Collaborative Surveillance: Using a Minimum Set of Key Data Parameters for One Health Participatory Surveillance
ABSTRACT
Early detection of a newly emerging or re-emerging infectious disease is crucial to minimize the impact of such a threat on lives and livelihoods. With three out of four pathogens capable of causing epidemics or pandemics arising first in animals and spreading to humans as zoonosis, a One Health approach to early detection is paramount. One Health participatory surveillance, defined as the bidirectional receiving and transmitting data for action through direct engagement of the target population, is an effective form of collaborative surveillance to enhance global health security. Participatory surveillance systems can vary greatly when developed for a specific purpose or to meet a particular community’s needs. Different geographies, languages, customs, beliefs, and practices often influence the breadth and depth of the data collected within each system. Imagine, however, if each of these varied systems could ‘speak’ to each other, sharing their aggregated de-identified data to create a comprehensive, real-time view of planetary health. The key is to collect the same information from users in each system, or at least a minimum set of key data parameters, to generate One Health surveillance greater than that of any individual system. To enable this vision, we propose a minimum set of key data paraments for One Health participatory surveillance that could be collected in any system through self-reporting by the general public. This real-time collaborative surveillance could be the earliest indicator of a human, animal, or environmental health threat as it does not require an interaction with a healthcare facility or provider where most disease surveillance traditionally occurs. One Health participatory surveillance that can detect major syndromes of potential emerging or re-emerging pathogens through self-reporting on human, animal, or environmental health is a practical, scalable solution to identify and respond to rapidly spreading contagions.
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