Background: Antimicrobial resistance (AMR) is an emerging public health crisis in Uganda. The World Health Organization (WHO) Global Action Plan recommends that countries should develop and implement National Action Plans for AMR. We describe the establishment of the national AMR program in Uganda and present the early microbial sensitivity results from the program. Objective: The aim of this study is to describe a national surveillance program that was developed to perform the systematic and continuous collection, analysis, and interpretation of AMR data. Methods: A systematic qualitative description of the process and progress made in the establishment of the national AMR program is provided, detailing the progress made from 2015 to 2020. This is followed by a report of the findings of the isolates that were collected from AMR surveillance sites. Identification and antimicrobial susceptibility testing (AST) of the bacterial isolates were performed using standard methods at both the surveillance sites and the reference laboratory. Results: Remarkable progress has been achieved in the establishment of the national AMR program, which is guided by the WHO Global Laboratory AMR Surveillance System (GLASS) in Uganda. A functional national coordinating center for AMR has been established with a supporting designated reference laboratory. WHONET software for AMR data management has been installed in the surveillance sites and laboratory staff trained on data quality assurance. Uganda has progressively submitted data to the WHO GLASS reporting system. Of the 19,216 isolates from WHO GLASS priority specimens collected from October 2015 to June 2020, 22.95% (n=4411) had community-acquired infections, 9.46% (n=1818) had hospital-acquired infections, and 68.57% (n=12,987) had infections of unknown origin. The highest proportion of the specimens was blood (12,398/19,216, 64.52%), followed by urine (5278/19,216, 27.47%) and stool (1266/19,216, 6.59%), whereas the lowest proportion was urogenital swabs (274/19,216, 1.4%). The mean age was 19.1 (SD 19.8 years), whereas the median age was 13 years (IQR 28). Approximately 49.13% (9440/19,216) of the participants were female and 50.51% (9706/19,216) were male. Participants with community-acquired infections were older (mean age 28, SD 18.6 years; median age 26, IQR 20.5 years) than those with hospital-acquired infections (mean age 17.3, SD 20.9 years; median age 8, IQR 26 years). All gram-negative (Escherichia coli, Klebsiella pneumoniae, and Neisseria gonorrhoeae) and gram-positive (Staphylococcus aureus and Enterococcus sp) bacteria with AST showed resistance to each of the tested antibiotics. Conclusions: Uganda is the first African country to implement a structured national AMR surveillance program in alignment with the WHO GLASS. The reported AST data indicate very high resistance to the recommended and prescribed antibiotics for treatment of infections. More effort is required regarding quality assurance of laboratory testing methodologies to ensure optimal adherence to WHO GLASS–recommended pathogen-antimicrobial combinations. The current AMR data will inform the development of treatment algorithms and clinical guidelines.

Background: Antimicrobial resistance (AMR) is a global health security threat and is associated with increased morbidity and mortality. One of the key drivers of AMR is the inappropriate use of antibiotics. A key component of improving antibiotic use is conducting antimicrobial use (AMU) surveillance. Methods: USAID Medicines Technologies and Pharmaceutical Services Program has supported the implementation of antimicrobial stewardship activities, including setting up systems for AMU surveillance in Tanzania and Uganda. Results from both countries have been previously published. However, additional implementation experience and lessons learned from addressing challenges to AMU surveillance have not been previously published and are the subject of this narrative article. Results: The team identified challenges including poor quality data, low digitalization of tools, and inadequate resources including both financial and human resources. To address these gaps, the Program has supported the use of continuous quality improvement approaches addressing gaps in skills, providing tools, and developing guidelines to fill policy gaps in AMU surveillance. Recommendations to fill these gaps, based on the Potter and Brough systematic capacity building model have been proposed. Conclusions: Strengthening AMU surveillance through using a capacity-building approach will fill gaps and strengthen efforts for AMR control in both countries.

High coverage of pre-exposure prophylaxis (PrEP) will reduce HIV transmission and help end the HIV/AIDS pandemic. However, PrEP users face challenges, including long-term adherence. The study aimed to document the proportions of individuals who restart HIV PrEP after they stop and the reasons for restarting PrEP. This study is a systematic review and meta-analysis. We systematically searched CINAHL, Embase, Emcare, Global Health, Medline, Scopus, and PsychINFO for peer-reviewed with no date restrictions. A grey literature search was conducted through Google search, a search of abstract books of AIDS conferences and the websites of WHO and UNAIDS. The data search was conducted in April 2023 and updated in February 2024. Two authors extracted data on the proportion of people who stopped and then restarted PrEP, reasons for restarting, and strategies to support people restarting PrEP. Two authors appraised the data using the Joanna Briggs Institute Appraisal Tools. We used a random-effects meta-analysis to pool estimates of restarting. We conducted meta-regression to determine potential sources of heterogeneity. This study is registered with PROSPERO, CRD42023416777. However, we deviated from our original plan as we did not identify enough studies for strategies to support restarting PrEP (primary objective). Subsequently, we revised our plan to strengthen our secondary objective to quantify the proportion of people who stopped and restarted PrEP, and explore possible reasons for its heterogeneity. Of 988 studies, 30 unique studieswere included: 27 reported the proportion restarting PrEP, and of these, 7 also reported reasons for restarting PrEP, and 3 studies reported only on the reasons for restarting PrEP. No study evaluated interventions for restarting PrEP. For the meta-analysis, we included 27 studies. Most studies were from high-income countries (17/27, 63%) or the USA (15/27, 56%). Overall, 23.8% (95% CI: 15.9–32.7, I² = 99.8%, N = 85,683) of people who stopped PrEP restarted PrEP. There was a lower proportion of restarting in studies from middle-income countries compared to high-income countries (adjusted odds ratio (aOR) 0.6, 95% CI: 0.50–0.73, p < 0.001). There was higher restarting in studies from Africa compared to the USA (aOR 1.55, 95% CI: 1.30–1.86), heterosexual populations compared to men who have sex with men or transgender women (aOR 1.50, 95% CI: 1.25–1.81, p < 0.001) and in studies defining restarting as those who had stopped PrEP for >1 month compared to those who stopped <1 month (aOR 1.20, 95% CI: 1.06–1.36, p < 0.001). Reasons for restarting PrEP included perceived higher risk for HIV acquisition and removal of barriers to access PrEP. In terms of quality assessment, overall, both randomised controlled trials had a low risk of bias, while the observational studies used in the meta-analysis had some potential risk of bias related to not explicitly addressing potential confounders (15/25, 60%) or not describing strategies to address incomplete follow-up (24/25, 96%). About a quarter of people who stopped PrEP would restart, with substantial variation across countries and populations. It is important to understand the motivations and contextual factors influencing restarting PrEP and the support systems to enable restarting PrEP for those at ongoing risk. Australian National Health and 10.13039/501100000265 Medical Research Council .

Background Appropriate antimicrobial use is essential for antimicrobial stewardship (AMS). Ugandan hospitals are making efforts to improve antibiotic use, but improvements have not been sufficiently documented and evaluated. Methods Six Ugandan hospitals implemented AMS interventions between June 2019 and July 2022. We used the WHO AMS toolkit to set-up hospital AMS programmes and implemented interventions using continuous quality improvement (CQI) techniques and targeting conditions commonly associated with antibiotic misuse, that is, urinary tract infections (UTIs), upper respiratory tract infections (URTIs) and surgical antibiotic prophylaxis (SAP). The interventions included training, mentorship and provision of clinical guidelines to support clinical decision-making. Quarterly antibiotic use surveys were conducted. Results Data were collected for 7037 patients diagnosed with UTIs. There was an increase in the proportion of patients receiving one antibiotic for the treatment of UTI from 48% during the pre-intervention to 73.2%, p<0.01. There was a 19.2% reduction in the number of antimicrobials per patient treated for UTI p<0.01. There was an increase in use of nitrofurantoin, the first-line drug for the management of UTI. There was an increase in the use of Access antibiotics for managing UTIs from 50.4% to 53.8%. The proportion of patients receiving no antimicrobials for URTI increased from 26.3% at pre-intervention compared with 53.4% at intervention phase, p<0.01. There was a 20.7% reduction in the mean number of antimicrobials per patient for URTI from the pre-intervention to the intervention phase, from 0.8 to 0.6, respectively, p<0.001 and reduction in the number of treatment days, p=0.0163. Among patients undergoing surgery, 49.5% (2212) received SAP during the pre-intervention versus 50.5% (2169) during the intervention. Conclusions Using CQI approaches to focus on specific causes of inappropriate antibiotic use led to desirable overall reductions in antibiotic use for URTI and UTI.

Background: It is projected that drug-resistant infections will lead to 10 million deaths annually by 2050 if left unabated. Despite this threat, surveillance data from resource-limited settings are scarce and often lack antimicrobial resistance (AMR)–related clinical outcomes and economic burden. We aim to build an AMR and antimicrobial use (AMU) data warehouse, describe the trends of resistance and antibiotic use, determine the economic burden of AMR in Uganda, and develop a machine learning algorithm to predict AMR-related clinical outcomes. Objective: The overall objective of the study is to use data-driven approaches to optimize antibiotic use and combat antimicrobial-resistant infections in Uganda. We aim to (1) build a dynamic AMR and antimicrobial use and consumption (AMUC) data warehouse to support research in AMR and AMUC to inform AMR-related interventions and public health policy, (2) evaluate the trends in AMR and antibiotic use based on annual antibiotic and point prevalence survey data collected at 9 regional referral hospitals over a 5-year period, (3) develop a machine learning model to predict the clinical outcomes of patients with bacterial infectious syndromes due to drug-resistant pathogens, and (4) estimate the annual economic burden of AMR in Uganda using the cost-of-illness approach. Methods: We will conduct a study involving data curation, machine learning–based modeling, and cost-of-illness analysis using AMR and AMU data abstracted from procurement, human resources, and clinical records of patients with bacterial infectious syndromes at 9 regional referral hospitals in Uganda collected between 2018 and 2026. We will use data curation procedures, FLAIR (Findable, Linkable, Accessible, Interactable and Repeatable) principles, and role-based access control to build a robust and dynamic AMR and AMU data warehouse. We will also apply machine learning algorithms to model AMR-related clinical outcomes, advanced statistical analysis to study AMR and AMU trends, and cost-of-illness analysis to determine the AMR-related economic burden. Results: The study received funding from the Wellcome Trust through the Centers for Antimicrobial Optimisation Network (CAMO-Net) in April 2023. As of October 28, 2024, we completed data warehouse development, which is now under testing; completed data curation of the historical Fleming Fund surveillance data (2020-2023); and collected retrospective AMR records for 599 patients that contained clinical outcomes and cost-of-illness economic burden data across 9 surveillance sites for objectives 3 and 4, respectively. Conclusions: The data warehouse will promote access to rich and interlinked AMR and AMU data sets to answer AMR program and research questions using a wide evidence base. The AMR-related clinical outcomes model and cost data will facilitate improvement in the clinical management of AMR patients and guide resource allocation to support AMR surveillance and interventions. International Registered Report Identifier (IRRID): PRR1-10.2196/58116

Background: Antimicrobials are crucial for animal health and food security. However, their overuse in animals can lead to the emergence of resistant microorganisms. Antimicrobial resistance (AMR) poses a global public health threat that impacts both animal and human health. The objective of this study was to estimate the antimicrobial consumption (AMC) of veterinary antimicrobials at the national level using import data from January to December 2021, available from the Uganda National Drug Authority (NDA). Methods: The World Organization for Animal Health (WOAH) methodology was applied using the Anatomical Therapeutic Chemical classification codes for veterinary medicines. Results: Approximately 88,387.37 kg (88.39 tonnes) of veterinary antimicrobials were consumed in 2021. Parenteral veterinary antimicrobials accounted for 63.8% (56,375.65 kg) and oral veterinary antibacterials accounted for 36.2% (32,011.71 kg). Tetracyclines were the single most consumed veterinary antimicrobial class, accounting for 62.7% of total consumption. Oxytetracycline was the most consumed antibacterial (58.4%), followed by sulphadiazine + trimethoprim (11.1%), penicillin g/dihydrostreptomycin (7.4%), penicillin G procaine + dihydrostreptomycin (6.8%), and tetracycline (3.5%), respectively. Out of all imported veterinary antimicrobials, 76% belonged to the World Health Organization (WHO)’s Highly Important Antimicrobials (HIA) category, 16% to the Critically Important (CIA), and 9% to the Highest Priority Critically Important (HPCIA) categories. Imported colistin accounted for 0.1% of total veterinary consumption. Conclusions: This study contributes to understanding antimicrobial consumption in Uganda’s livestock sector and, for the NDA, leaves in place a system for routine surveillance at a national level. We recommend strict regulatory oversight on the importation and use of colistin and macrolides to address AMR.