One Health, Many Gaps: Rethinking Epidemic Intelligence in Resource-Limited Settings to Prepare for the Global Threat of Disease X

Abstract

The emergence of high-threat pathogens—such as Ebola, Lassa fever, and most recently SARS-CoV-2—has highlighted critical weaknesses in global surveillance systems, particularly in resource-limited settings where many zoonotic spillovers originate. Despite the World Health Organization’s (WHO) prioritization of these diseases for research and development (R&D), the current surveillance infrastructures in these regions remain under-resourced, fragmented, and often reactive rather than anticipatory. This narrative review explored the literature and structured relevant findings in three key dimensions: (i) the structural and operational limitations of existing surveillance systems for the WHO priority diseases in resource-limited settings including challenges in data integration, laboratory capacity, workforce, and community engagement; (ii) how these surveillance gaps could delay detection and hinder the response to future emerging threats, particularly a hypothetical but inevitable Disease X; and (iii) innovative and context-adapted strategies to strengthen epidemic intelligence including integrated One Health surveillance, digital and genomic tools, participatory approaches, and regional data-sharing mechanisms. We argue that building agile, equity-centered, and decentralized surveillance systems is not only essential for managing known threats, but also foundational to the early detection and rapid containment of the next public health emergency in resource-limited settings. This review uniquely frames surveillance limitations in resource-limited settings as a global security concern and outlines context-adapted, equity-centered innovations to strengthen epidemic intelligence in preparation for Disease X.