ArticleEmerging infectious diseases2018
Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting.
Article in Emerging infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed.
- Can a TB outbreak be detected by reviewing the surveillance data?Public health action · 2025Article
- Identification of growing tuberculosis incidence clusters in a region with a decrease in tuberculosis prevalence in Moscow (2000-2019).Journal of global health · 2023Article
- Epidemiological cluster identification using multiple data sources: an approach using logistic regression.Microbial genomics · 2023Article
- Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis.American journal of epidemiology · 2023Article
- Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters.American journal of epidemiology · 2022Article
- Molecular surveillance for large outbreaks of tuberculosis in the United States, 2014-2018.Tuberculosis (Edinburgh, Scotland) · 2022Article
- Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases.Frontiers in public health · 2021Article
- Pathogen Genomics in Public Health.The New England journal of medicine · 2019Article
- Developing National Genotype-Independent Indicators for RecentPublic health reports (Washington, D.C. : 1974)Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.
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Registered trials
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