ArticleScientific reports2018
Whole genome sequencing for investigations of meningococcal outbreaks in the United States: a retrospective analysis.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Invasive meningococcal B disease: Spatiotemporal cluster identification using finetype data, the Netherlands, 2005-2023.Epidemiology and infection · 2026Article
- Investigation of invasiveFrontiers in public health · 2025Article
- Statewide Outbreak of Neisseria meningitidis Serogroup Y, Sequence Type 1466 - Virginia, 2022-2024.MMWR. Morbidity and mortality weekly report · 2024Article
- Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol.Frontiers in public health · 2024Article
- Meningococcal disease in North America: Updates from the Global Meningococcal Initiative.The Journal of infection · 2022Review
- Whole Genome Analyses Accurately IdentifyInternational journal of molecular sciences · 2022Article
- Enhancing Meningococcal Genomic Surveillance in the Meningitis Belt Using High-Resolution Culture-Free Whole-Genome Sequencing.The Journal of infectious diseases · 2022Article
- Demographic Features of Invasive Meningococcal Disease in Taiwan, 1993 to 2020, and Genetic Characteristics of Neisseria meningitidis Isolates, 2003 to 2020.Microbiology spectrum · 2022Article
- An implementation science approach to evaluating pathogen whole genome sequencing in public health.Genome medicine · 2021Article
- Using Neisseria meningitidis genomic diversity to inform outbreak strain identification.PLoS pathogens · 2021Article
- Genomic Surveillance of a Globally Circulating Distinct Group W Clonal Complex 11 Meningococcal Variant, New Zealand, 2013-2018.Emerging infectious diseases · 2021Article
- Establishment and Evaluation of a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Pseudomonas aeruginosa.Journal of clinical microbiology · 2021Article
- Full Molecular Typing of Neisseria meningitidis Directly from Clinical Specimens for Outbreak Investigation.Journal of clinical microbiology · 2020Article
- Web-Based Genome Analysis of Bacterial Meningitis Pathogens for Public Health Applications Using the Bacterial Meningitis Genomic Analysis Platform (BMGAP).Frontiers in genetics · 2020Article
- Detailed Evaluation of Data Analysis Tools for Subtyping of Bacterial Isolates Based on Whole Genome Sequencing:Frontiers in microbiology · 2019Article
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11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although rare in the U.S., outbreaks due to Neisseria meningitidis do occur. Rapid, early outbreak detection is important for timely public health response. In this study, we characterized U.S. meningococcal isolates (N = 201) from 15 epidemiologically defined outbreaks (2009-2015) along with temporally and geographically matched sporadic isolates using multilocus sequence typing, pulsed-field gel electrophoresis (PFGE), and six whole genome sequencing (WGS) based methods. Recombination-corrected maximum likelihood (ML) and Bayesian phylogenies were reconstructed to identify genetically related outbreak isolates. All WGS analysis methods showed high degree of agreement and distinguished isolates with similar or indistinguishable PFGE patterns, or the same strain genotype. Ten outbreaks were caused by a single strain; 5 were due to multiple strains. Five sporadic isolates were phylogenetically related to 2 outbreaks. Analysis of 9 outbreaks using timed phylogenies identified the possible origin and estimated the approximate time that the most recent common ancestor emerged for outbreaks analyzed. U.S. meningococcal outbreaks were caused by single- or multiple-strain introduction, with organizational outbreaks mainly caused by a clonal strain and community outbreaks by divergent strains. WGS can infer linkage of meningococcal cases when epidemiological links are uncertain. Accurate identification of outbreak-associated cases requires both WGS typing and epidemiological data.
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