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FUNAAB Set to Launch AI-Powered Infectious Disease Research Initiative

ValidViewNetwork by ValidViewNetwork
August 19, 2025
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The Federal University of Agriculture, Abeokuta (FUNAAB) is poised to deepen its role in fighting infectious diseases with the imminent launch of two groundbreaking Artificial Intelligence (AI)-driven research projects. The initiatives are led by the university’s Artificial Intelligence Applications for One Health (AIA4OneHealth) research group within the Department of Computer Science.

These pioneering projects recently secured international research funding from the Artificial Intelligence for Pandemic and Epidemic Preparedness (AI4PEP) Network based at the University of Toronto, Canada. Funders include the International Development Research Council (IDRC) and the United Kingdom’s Foreign, Commonwealth and Development Office (FCDO). AI4PEP is a global South-led collaborative network focused on strengthening public health systems through responsible AI applications to enhance early detection, warning, and response to infectious disease outbreaks.

The projects will initially focus on upgrading and integrating existing Nigerian infectious disease surveillance systems such as SORMAS (Surveillance, Outbreak Response Management and Analysis System) and TATAFO to boost real-time data capture, reporting, and predictive analytics. Ogun State is selected as the pilot site with plans to extend nationally as further funding becomes available.

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FUNAAB’s official project launch is scheduled for Wednesday, August 27, 2025, at 12 noon in the Centre of Excellence in Agricultural Development and Sustainable Environment (CEADESE) Conference Room on campus. Vice-Chancellor Prof. Babatunde Kehinde will act as Chief Host. The event will host key stakeholders from the Nigeria Centre for Disease Control (NCDC), Ogun State Ministry of Health, and other partners for strategic collaboration.

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Prof. Adesina Sodiya, the project team leader, underscores the initiative’s commitment to deploying AI technologies for proactive infectious disease management. The goal is to develop intelligent early warning systems employing machine learning, natural language processing, and predictive decision-making models to fortify Nigeria’s public health response capacity.

SORMAS, one of the platforms targeted for enhancement, has been pivotal in Nigeria since 2015 for managing outbreaks of diseases including Lassa Fever, Cholera, and COVID-19 by enabling coordinated real-time disease surveillance across all local government areas. The integration of AI aims to scale its capabilities further for improved epidemic preparedness and rapid response.

This functionally rich collaboration marks a significant advancement in leveraging cutting-edge technology to mitigate health threats, setting a strong precedent for AI-led epidemic management within Nigeria and across the Global South.

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