Project description
Smarter tools to fight childhood diarrhoeal disease in Africa
Diarrhoeal diseases remain a leading cause of illness and preventable death among young children in sub-Saharan Africa. To improve diagnosis and treatment outcomes, the EU-funded CARE-Africa project is developing an AI-powered digital decision-support system. By combining clinical data, climate and socio-economic information, and machine learning, the tool will estimate likely pathogens and antibiotic resistance risks. It will also provide treatment recommendations aligned with WHO and local guidelines. The system will be tested through clinical trials in Uganda and Ethiopia, while data modelling will generate risk maps and predictions on how environmental and socio-economic factors affect disease patterns. The project’s goal is to boost local capacity in AI and healthcare in low-resource settings.
Objective
CARE-Africa aims to reduce the burden of paediatric diarrhoeal diseases (DD) in sub-Saharan Africa (SSA) through the development, deployment, and clinical evaluation of an innovative digital decision-support system (DSS). Targeting children under five, the DSS will assist healthcare workers in diagnosing and treating diarrhoea caused by key pathogens (Shigella spp., ETEC, Vibrio cholerae, rotavirus, norovirus and Cryptosporidium), incorporating clinician-entered data, contextual climate and socio-economic information, and advanced AI analytics. The system will estimate pathogen presence likelihoods, AMR risk, and produce tailored treatment recommendations aligned with WHO and local guidelines, using explainable AI to ensure transparency.
Cluster-randomized controlled trials in Uganda and Ethiopia will assess the DSS’s effectiveness in improving clinical outcomes and antibiotic stewardship. In parallel, the project will conduct AI-driven, large-scale data mining and modelling to identify how climate and socio-economic variables influence disease burden, pathogen dynamics, and public health vulnerabilities across SSA. These insights will support the creation of predictive tools, risk maps, and targeted interventions, informing adaptive policies to mitigate DD under changing climate conditions.
The project brings together six partners from the UK, Italy, Spain, South Africa, Uganda, and Ethiopia, combining expertise in AI, data science, infectious diseases, and health information systems. By integrating AI-driven research with clinical practice, this initiative will deliver a scalable, context-aware tool for precision diagnostics and treatment of diarrhoeal diseases, with significant implications for child health, AMR control, and climate resilience in low-resource settings. The project will boost local capacity in AI and health analytics, strengthen SSA regional innovation, and enhance point-of-care and lab diagnostics and treatment of DD in SSA.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- medical and health sciences health sciences public health
- medical and health sciences health sciences infectious diseases
- natural sciences earth and related environmental sciences environmental sciences sustainability sciences
- engineering and technology environmental engineering ecosystem-based management climate change adaptation
- natural sciences computer and information sciences data science data mining
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.1 - Health
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-JU-RIA - HORIZON JU Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-JU-GH-EDCTP3-2025-04-two-stage
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
WC2R 2LS London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.