ArticleIJID regions2026
Small-sample antimicrobial resistance surveillance using lot quality assurance sampling in Uganda, Malawi, and Zambia.
Article in IJID regions, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
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 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 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.