{"id":"doi:10.1016/j.ijregi.2026.100988","kind":"article","title":"Small-sample antimicrobial resistance surveillance using lot quality assurance sampling in Uganda, Malawi, and Zambia","authors":["Anguyo RO","Uadiale K","Chilembo P","Chilekwa JC","Ekirapa-Kiracho E","Feasey N","Ictho J","Lamadrid A","Kitutu FE","Kajumbula H","Kazimbaya K","Lochoro P","Mayora C","Mukisa P","Nkolo CL","O'Byrne T","Pagano M","Mwape K","Simuyandi M","Betts H","Roberts AP","Sharma A","Valadez JJ"],"author_count":23,"year":2026,"published":"2026-08-28","venue":"IJID regions","cited_by":0,"doi":"10.1016/j.ijregi.2026.100988","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.ijregi.2026.100988","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.ijregi.2026.100988","updated":null,"pmid":"42828091","pmcid":"PMC13631612","openalex_id":null,"pdf_url":"https://europepmc.org/articles/PMC13631612/pdf","abstract":"Objectives We evaluated lot quality assurance sampling (LQAS) adapted for antimicrobial resistance (AMR) surveillance (AMR-LQAS), a small-sample approach designed to classify district AMR prevalence against a clinically meaningful resistance threshold in Uganda, Malawi, and Zambia. Methods The study was conducted across nine districts/locations, with each country including one urban, one peri-urban, and one rural district/location. Upper and lower resistance thresholds were 20% and 5%, respectively, with predefined misclassification probabilities (α = 0.05, β = 0.10), yielding a minimum sample size of 44 per district. In Uganda, classifications were compared with larger probability samples (n ≥ 240 in each of three districts). Organisms assessed included extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae , and methicillin-resistant Staphylococcus aureus . Antibiotics assessed were those routinely used in the study countries. Results In Uganda, concordance between AMR-LQAS and probability-sample classifications was nine of 12 organism-district comparisons. Across antibiotic-district comparisons, concordance was 46/48, resulting in overall reliability of 92% (55/60 comparisons). Resistance to ciprofloxacin, gentamicin, and trimethoprim-sulfamethoxazole in ESBL-producing E. coli exceeded the 20% threshold in all districts, whereas meropenem resistance exceeded the threshold in only one district. Zambia had fewer antibiotics below resistance thresholds than Uganda and Malawi. Conclusion AMR-LQAS reliably classified district-level resistance using substantially smaller sample sizes than conventional prevalence surveys, generating actionable subnational information to support antibiotic stewardship and surveillance in low-resource settings.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Small-sample antimicrobial resistance surveillance using lot quality assurance sampling in Uganda, Malawi, and Zambia\" by Anguyo RO, Uadiale K, Chilembo P et al., https://doi.org/10.1016/j.ijregi.2026.100988, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"infectious-disease-amr","name":"Infectious Disease, Vaccines & Antimicrobial Resistance","domain_slug":"medicine"}],"cited_in_dossiers":[]}