ArticlePloS one2016
Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The opportunities for and barriers to antimicrobial resistance surveillance by lot quality assurance sampling in livestock: Findings from interviews with stakeholders in Germany.One health (Amsterdam, Netherlands) · 2025Article
- Pulmonary tuberculosis screening in anti-retroviral treated adults living with HIV in Kenya.BMC infectious diseases · 2021Article
- Article
- Article
- Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling.American journal of epidemiology · 2019Article
- Prevalence of Drug Resistance Mycobacterium Tuberculosis among Patients Seen in Coast Provincial General Hospital, Mombasa, Kenya.PloS one · 2016Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
objectiveTo classify the prevalence of multi-drug resistant tuberculosis (MDR-TB) in two different geographic settings in western Kenya using the Lot Quality Assurance Sampling (LQAS) methodology.
designThe prevalence of drug resistance was classified among treatment-naïve smear positive TB patients in two settings, one rural and one urban. These regions were classified as having high or low prevalence of MDR-TB according to a static, two-way LQAS sampling plan selected to classify high resistance regions at greater than 5% resistance and low resistance regions at less than 1% resistance.
resultsThis study classified both the urban and rural settings as having low levels of TB drug resistance. Out of the 105 patients screened in each setting, two patients were diagnosed with MDR-TB in the urban setting and one patient was diagnosed with MDR-TB in the rural setting. An additional 27 patients were diagnosed with a variety of mono- and poly- resistant strains.
conclusionFurther drug resistance surveillance using LQAS may help identify the levels and geographical distribution of drug resistance in Kenya and may have applications in other countries in the African Region facing similar resource constraints.
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