In Brazil, event-based surveillance (EBS) aims to detect rumors in social networks and sites, considering indicators and collection of structured information in health settings. However, EBS needs to be improved to detect outbreaks in populations with limited access to health services. Therefore, this study aims to investigate the sensitivity for detecting infectious disease outbreaks using AI, warning systems, and event-based surveillance, linked to community leader engagement. The project is focused on research-service triangulation, seeking to serve a border city in the state of Mato Grosso do Sul and its capital, Campo Grande, which integrate the corridor of the Two-Ocean Route, a region with emerging ecosystem challenges that create potential health risks. It is expected that the products will have repercussions for One Health, allowing greater sensitivity of local surveillance, shorter detection time, and more rapid responses to outbreaks, mitigating the impacts on the territory from the changes. It is also expected that the method can be applied to other middle- and low-income countries. The technology involves participation by community leaders, healthcare professionals from the Centers for Strategic Information and Surveillance Response in Health (CIEVS) in Campo Grande, and the Mato Grosso do Sul State Health Department, corresponding to a “call to action ” through an unconventional strategy that seeks to mobilize the preservation of the unique ecosystem of the Cerrado-Pantanal.