Read about the groundbreaking AMR surveillance and data collection efforts by Ugandan researchers to safeguard our future.
Imagine a world where antibiotics, once our life-saving shields against infections, become powerless. This alarming scenario, known as Antimicrobial Resistance (AMR), poses a growing global threat. But fear not, because the Ugandan researchers are on the frontlines, armed with groundbreaking data and unwavering determination to collect AMR data across 9 sentinel surveillance sites across Uganda.
A team of researchers headed by Dr Jonathan Mayito, the principal investigator of the CAMO-Net Uganda research work stream, Project three “Combatting Antimicrobial Resistance in Uganda: A Data-Driven Approach to Optimise Antibiotic Use and Improve Patient Outcomes,” implemented a robust data collection activity across nine national human health antibiotic resistance surveillance sites in Uganda (Arua, Gulu, Lira, Soroti, Kabale, Mbarara, Masaka, Mbale and Mbale Regional Referral Hospitals. (below)
Building on our strong partnership at all sites, the teams disseminated vital programmatic insights from Fleming Fund to over 400 health workers with a strong attendance of Medicine and Therapeutics Committees at each site.
During this activity that started 7 April to 11 May 2024, our team embarked on retrospective AMR clinical outcomes and Economic costing data collection that will provide data for machine learning modelling to predicting the clinical outcomes of patients with bacterial infectious syndromes due to resistant pathogens and estimate the Cost of Illness (COI) cost per AMR case to inform policy.
The clinical parameters collected included sociodemographics, presenting complaints, site of infection, duration of symptoms, clinical vital records, AST results, antibiotic use, clinical diagnosis, prior antibiotic exposure, medical comorbidities, duration of hospital stay, mortality, time to clinical improvement, time to negative cultures, mortality, medical complications etc. The study clinical outcomes included cured, clinical improvement, referred/self-discharge, lost to follow up and died.
The cost of illness variables collected included direct medical costs (personnel, medical supplies, hospital administrative/operational costs, drug and laboratory supplies costs, AMR related training costs and infrastructure costs.
The teams learnt that effective stakeholder engagement, use of experienced data collection teams from the Fleming Fund point prevalence surveys, deployment of a robust electronic data capture system (REDCap) and utilization pre-funded infrastructure significantly enabled timely and efficient data collection. Despite the successes archive, poor records management across 7/9 RRHs made it difficult to identify and trace the patient records. We would also like to up loud Kabale and Lira Regional Referral Hospitals, who have a well-organized data management system despite their limited resources.
We appreciate the funding from the Wellcome Trust and support from our participating sites; Arua, Kabale, Mbale, Jinja, Gulu, Lira, Soroti, Masaka and Mbarara Regional Referral Hospitals (RRH) and the Ministry of Health of Uganda.
The future looks bright for our team in IDI, and data as part of our comprehensive initiative. Here are the key upcoming publications.
- Technical Report: Annual Economic Burden of AMR in Uganda (January 25, 2025).
- Activity Blog: Annual Economic Burden of AMR in Uganda (December 2024)
- Harnessing Machine Learning Techniques to Predict Clinical Outcomes in Patients with Infectious Syndromes Due to Resistant Pathogens (March 2025): This publication will explore advanced ML techniques to predict clinical outcomes, paving the way for more proactive and effective treatments.
These publications will complement the launch of IDI’s data warehouse and physician assistant app. These initiatives are more than just projects; they are steps towards a future where AMR is manageable, and patient outcomes are vastly improved.
Find out more about the incredible work we do in our CAMO-Net Uganda Hub.
