ArticleInternational journal of health geographics2013
Using statistical methods and genotyping to detect tuberculosis outbreaks.
Article in International journal of health geographics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.BMC medicine · 2018Pooled it
- Spatial heterogenicity of tuberculosis and dengue in Nepal.Scientific reports · 2025Article
- Model-Based Analysis of Impact, Costs, and Cost-effectiveness of Tuberculosis Outbreak Investigations, United States.Emerging infectious diseases · 2025Article
- Epidemiological Characteristics and Spatio-Temporal Distribution of Hepatitis A in Spain in the Context of the 2016/2017 European Outbreak.International journal of environmental research and public health · 2022Article
- 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
- Tuberculosis Genotype Clusters and Transmission in the U.S., 2009-2018.American journal of preventive medicine · 2021Article
- Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions.Molecular biology and evolution · 2019Article
- Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting.Emerging infectious diseases · 2018Article
- Use of Activity Space in a Tuberculosis Outbreak: Bringing Homeless Persons Into Spatial Analyses.Open forum infectious diseases · 2017Article
- Validation of genotype cluster investigations for Mycobacterium tuberculosis: application results for 44 clusters from four heterogeneous United States jurisdictions.BMC infectious diseases · 2016Article
- Article
- Typhoid fever acquired in the United States, 1999-2010: epidemiology, microbiology, and use of a space-time scan statistic for outbreak detection.Epidemiology and infection · 2015Article
- Developing National Genotype-Independent Indicators for RecentPublic health reports (Washington, D.C. : 1974)Article
- Representativeness of Tuberculosis Genotyping Surveillance in the United States, 2009-2010.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly identification of outbreaks remains a key component in continuing to reduce the burden of infectious disease in the United States. Previous studies have applied statistical methods to detect unexpected cases of disease in space or time. The objectives of our study were to assess the ability and timeliness of three spatio-temporal methods to detect known outbreaks of tuberculosis.
methodsWe used routinely available molecular and surveillance data to retrospectively assess the effectiveness of three statistical methods in detecting tuberculosis outbreaks: county-based log-likelihood ratio, cumulative sums, and a spatial scan statistic.
resultsOur methods identified 8 of the 9 outbreaks, and 6 outbreaks would have been identified 1-52 months (median=10 months) before local public health authorities identified them. Assuming no delays in data availability, 46 (59.7%) of the 77 patients in the 9 outbreaks were identified after our statistical methods would have detected the outbreak but before local public health authorities became aware of the problem.
conclusionsStatistical methods, when applied retrospectively to routinely collected tuberculosis data, can successfully detect known outbreaks, potentially months before local public health authorities become aware of the problem. The three methods showed similar results; no single method was clearly superior to the other two. Further study to elucidate the performance of these methods in detecting tuberculosis outbreaks will be done in a prospective analysis.
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