ArticleScientific reports2023
A spatial analysis of TB cases and abnormal X-rays detected through active case-finding in Karachi, Pakistan.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria.PLOS digital health · 2025Article
- Article
- Geographical targeting of active case finding for tuberculosis in Pakistan using hotspots identified by artificial intelligence software (SPOT-TB): study protocol for a pragmatic stepped wedge cluster randomised control trial.BMJ open respiratory research · 2024Article
- Early detection of tuberculosis: a systematic review.Pneumonia (Nathan Qld.) · 2024Review
- Effectiveness of Using AI-Driven Hotspot Mapping for Active Case Finding of Tuberculosis in Southwestern Nigeria.Tropical medicine and infectious disease · 2024Article
- Spatial Analysis of Drug-Susceptible and Multidrug-Resistant Cases of Tuberculosis, Ho Chi Minh City, Vietnam, 2020-2023.Emerging infectious diseases · 2024Article
- Article
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9 authors.
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Abstract
Tuberculosis (TB) is the leading cause of avoidable deaths from an infectious disease globally and a large of number of people who develop TB each year remain undiagnosed. Active case-finding has been recommended by the World Health Organization to bridge the case-detection gap for TB in high burden countries. However, concerns remain regarding their yield and cost-effectiveness. Data from mobile chest X-ray (CXR) supported active case-finding community camps conducted in Karachi, Pakistan from July 2018 to March 2020 was retrospectively analyzed. Frequency analysis was carried out at the camp-level and outcomes of interest for the spatial analyses were mycobacterium TB positivity (MTB+) and X-ray abnormality rates. The Global Moran's I statistic was used to test for spatial autocorrelation for MTB+ and abnormal X-rays within Union Councils (UCs) in Karachi. A total of 1161 (78.1%) camps yielded no MTB+ cases, 246 (16.5%) camps yielded 1 MTB+, 52 (3.5%) camps yielded 2 MTB+ and 27 (1.8%) yielded 3 or more MTB+. A total of 79 (5.3%) camps accounted for 193 (44.0%) of MTB+ cases detected. Statistically significant clustering for MTB positivity (Global Moran's I: 0.09) and abnormal chest X-rays (Global Moran's I: 0.36) rates was identified within UCs in Karachi. Clustering of UCs with high MTB positivity were identified in Karachi West district. Statistically significant spatial variation was identified in yield of bacteriologically positive TB cases and in abnormal CXR through active case-finding in Karachi. Cost-effectiveness of active case-finding programs can be improved by identifying and focusing interventions in hotspots and avoiding locations with no known TB cases reported through routine surveillance.
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