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KNUST Leverages AI for Early Detection of Vector-Borne Diseases in Ghana

Published 25 Jun 2024
AI4PEP

The Kwame Nkrumah University of Science and Technology (KNUST) is leading an innovative public health initiative aimed at early detection of vector-borne diseases in Ghana through the use of Artificial Intelligence (AI). The project is designed to bolster the country's surveillance system, enabling early identification of potential disease outbreaks and thereby mitigating the impact on public health.

AI4PEP

Dr. Kingsley Badu from the Department of Biological Sciences at KNUST, the Principal Investigator of the project, highlighted the critical need for a robust surveillance system. He noted that the absence of such a system allows infections to spread unnoticed among vulnerable populations, only to be detected when they have escalated into pandemics that overwhelm Ghana's healthcare infrastructure.

Dr. Franklin Asiedu-Bekoe,
Dr. Franklin Asiedu-Bekoe,

“A risk-targeted early detection surveillance system supported by Responsible AI, edge computing, and climate-driven predictive models will identify novel circulating viruses in insect vectors, humans, and animals before diseases become apparent on a scale that becomes difficult to contain,” Dr. Badu explained. “The project will leverage the existing surveillance system set up by the National Malaria Elimination Programme (NMEP) for malaria, expanding its scope to detect all vector-borne diseases.”

Vector-borne diseases, transmitted by parasites, viruses, and bacteria through vectors like bloodsucking insects, pose significant health risks. These vectors, after feeding on an infected host, can transmit disease-causing germs to new hosts, leading to illnesses such as malaria, dengue, and yellow fever. According to the World Health Organization (WHO), vector-borne diseases account for over 17% of all infectious diseases, causing more than 700,000 deaths annually.

The project, dubbed "Responsible AI for Developing a Robust Public Health Surveillance System: Early Detection and Prediction of Vector-borne Viral Zoonotic Pathogens (AI4PEP RAPiD-VBP)," aims to enhance the capacity of public health systems to detect, prepare for, and respond to health threats effectively

At the project's inception and stakeholder engagement workshop in Kumasi, Dr. Franklin Asiedu-Bekoe, Director of Public Health at the Ghana Health Service and a project team member, expressed concern about the high prevalence of these diseases in poor tropical and subtropical regions like Ghana. He emphasized the importance of early detection in controlling pandemics, stating, “No matter the type of pandemic, it can be controlled even with limited resources. So this project, which focuses on the early detection of pathogens, is crucial for the public health division.”

Dr. Keziah Malm, Programme Manager of the National Malaria Elimination Programme, pledged close collaboration with the project team to achieve its objectives. Similarly, Prof. Ellis Owusu-Dabo, Pro Vice-Chancellor of KNUST, underscored that the project's goals align with the university's mission of societal development. “The four pillars of this project – early detection, early warning system, early response, and passive development – align perfectly with our mission and vision as a university, particularly in problem-driven solutions,” he said.

The AI4PEP RAPiD-VBP project is a collaborative effort involving Mahidol University in Thailand and is supported by the International Development Research Centre (IDRC) of Canada and the University of York in Canada.