Ultimately, we want to be able to equip a frontline healthcare worker with a digital tool with the power to predict the most likely pathogen causing a child’s diarrhoeal infection based on their symptoms. Is it a bacterium or a virus? If it’s a bacterium, what antibiotics are known to be effective against it, and which ones should be avoided?
Tania Dottorini, Professor of AI in Science at King’s and project lead
29 April 2026
€4.8m project will harness AI to tackle children's diarrhoeal diseases in sub-Saharan Africa
An international research consortium led by King’s College London is set to develop an AI tool to help tackle diarrhoeal diseases in children under five years old in sub-Saharan Africa, with a €4.8m funding award from the European Union.
The CARE-AFRICA project aims to generate an AI tool that can predict the most likely pathogen responsible for a child’s diarrhoeal disease and provide guidance on the most effective treatment options based on that prediction.
Supported by the Global Health EDCTP3 and its members, the project brings together six partners from the UK, Italy, Spain, South Africa, Uganda and Ethiopia, combining expertise in AI, data science, infectious diseases, public health and health information systems.
The tool will be designed to run on a tablet device, with results generated in five minutes.
Aiming to addressing major global health challenges
Diarrhoea is a leading cause of mortality in children worldwide, with some of the highest death rates in children under five years of age seen in sub-Saharan Africa.1 Diarrhoeal diseases can be challenging to manage – they are caused by a variety of bacteria, viruses and parasites, making it difficult to identify the pathogen responsible and deliver the most appropriate treatment.
To develop the AI tool, the team will train an AI model on a variety of data. These will include clinical data from children in Ethiopia and Uganda infected with pathogens that cause diarrhoea, including Shigella, Vibrio cholerae, Escherichia coli and norovirus. The tool will also integrate environmental, climate, socioeconomic and demographic data linked to infections with these pathogens.
The idea is that when a patient’s clinical data is inputted about a current infection, the tool will be able to provide probabilities for the most likely pathogens causing the infection, as well as information on antibiotic resistance and recommendations for treatments.
If successful, the team hopes the AI tool will help to combat antimicrobial resistance, a major global health concern, by preventing the mis-prescribing of antibiotics.
Once developed, the team will evaluate the effectiveness of the AI tool in helping to diagnose and treat diarrhoeal diseases in children compared with standard practices.
The tool will first be tested in a pilot study in eight healthcare facilities in Ethiopia and Uganda. Based on the results, the tool will be revised and improved before it is tested in a larger scale clinical trial across 40 facilities with up to 4,700 children.
This project is truly going beyond what we do now. We’re going to move AI and digital technologies beyond the laboratory to understand how they can be harnessed in low- and middle-income countries to tackle real-world problems.
Professor Tania Dottorini
If successful, the new tool could help to speed up diagnoses, ensure children receive the treatments they need and relieve pressures on healthcare systems in places where resources are limited.
“Living in Africa as a child, I saw the impact these diseases could have. As a mother, to see your child suffering is terrible. I want to make a difference for children, mothers and families in places where there is limited access to doctors and healthcare, and I think this project offers us the chance to do that,” added Professor Dottorini.
The project partners include King’s College London, Makerere University in Uganda, the Addis Ababa City Administration Health Bureau in Ethiopia, Jembi Health Systems in South Africa, the University of Perugia in Italy and Causal Foundry Inc., in Spain.
References
- UNICEF Data (2024). Diarrhoea. Available at: https://data.unicef.org/topic/child-health/diarrhoeal-disease/ (accessed 16 April 2026)
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Professor of Artificial Intelligence for Science