An Offline-First Mobile Reporting System for Digital One Health Surveillance in Resource-Constrained Settings
DOI:
https://doi.org/10.58190/ijamec.2026.172Keywords:
One Health surveillance, mobile health (mHealth),, Design Science Research Methodology, offline-first systems, conversational AI, public health informaticsAbstract
The increasing interdependence of human, animal, and environmental health highlights the need for integrated One Health surveillance systems capable of supporting timely and coordinated disease reporting. In many low- and middle-income settings, existing surveillance workflows remain fragmented, paper-based, and poorly suited for field conditions. This study employs the Design Science Research Methodology (DSRM) to design, develop, and evaluate a mobile One Health surveillance application that addresses these limitations. The proposed solution is a cross-platform, offline-capable mobile system supporting structured digital reporting, local data storage, and an AI-assisted conversational reporting interface aimed at reducing reporting burden. The artifact was demonstrated through simulated real-world usage scenarios and evaluated using functional testing and usability assessment. Results show a System Usability Scale (SUS) score of 78.4, indicating good overall usability, while the conversational interface reduced average reporting time despite a higher learning curve. The findings demonstrate the feasibility of offline-first mobile surveillance systems for improving One Health data capture in resource-constrained environments.
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