CAMO-Net Uganda has secured significant new funding to scale up its groundbreaking work on antimicrobial resistance (AMR), with a focus on using machine learning (ML) to improve health outcomes.
The successful project, titled Data-Driven Infrastructure for Combating Antimicrobial Resistance IN UGanda (DARING) will receive $282,705.09 USD over 18 months from the Lacuna Fund to generate much-needed clinical outcome data and support equitable AI development in low- and middle-income countries (LMICs).
The project is funded by the Wellcome Trust and Google through the Lacuna Fund, which is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in LMICs with the resources they need to produce labelled datasets that address urgent problems in their communities. The aim of the fund is to address a key data gap: robust, representative clinical datasets that reflect the realities of LMICs and can strengthen AMR surveillance, prediction, and policy interventions.
CAMO-Net Uganda is one of five national hubs within the Centres for Antimicrobial Optimisation Network (CAMO-Net), a global collaboration working to improve antimicrobial use and outcomes through interdisciplinary research, innovation, and collaboration. Based at the Infectious Diseases Institute at Makerere University, the Uganda hub is pioneering work on AMR surveillance, gender-sensitive data analysis, and the application of AI in infectious disease management. Recent projects have included presenting economic burden data to Uganda’s Parliament and exploring antibiotic use patterns in HIV care.
The DARING project, led by Dr Ronald Galiwango at CAMO-Net Uganda, builds on findings from CAMO-Net Uganda’s machine learning work, which collected data on clinical outcomes for 599 patients with resistant and susceptible infections. While this was a major step forward, the team identified the dataset as insufficient for training reliable ML models. With this new funding, the Uganda team will collect additional clinical outcome data from nine Regional Referral Hospitals across the country. The enhanced dataset will significantly improve model training and accuracy, supporting efforts to predict AMR-related risks and improve treatment decisions.
Dr Galiwango is a highly experienced researcher in health informatics and data science, and a key member of the CAMO-Net Uganda team. His work focuses on sustainable digital health infrastructure and equitable data access, with a strong emphasis on public health impact across sub-Saharan Africa.
“This grant allows us to expand our data infrastructure in a way that can meaningfully shift how we understand and respond to antimicrobial resistance in Uganda,” said Dr Galiwango. “By collecting richer, more representative clinical data, we are laying the foundation for machine learning models that can support clinicians, inform policy, and ultimately improve patient outcomes.”
The new and existing datasets will be integrated into CAMO-Net Uganda’s expanding data warehouse, ensuring they are accessible to researchers, policymakers, and global partners. This work continues CAMO-Net’s commitment to ethical data governance, public access, and equitable knowledge-sharing. With the DARING project now officially awarded and due to begin at the end of April 2025, CAMO-Net Uganda continues to push boundaries in the global response to AMR by ensuring the data that powers policy and research reflects the populations most affected.
