ArticlePloS one2018
Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks.
Article in PloS one, 2018. 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.
- Microevolution and Its Impact on Hypervirulence, Antimicrobial Resistance, and Vaccine Escape inMicroorganisms · 2023Review
- Article
- Reactive vaccination as control strategy for an outbreak of invasive meningococcal disease caused byEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2022Article
- Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review.Pathogens (Basel, Switzerland) · 2022Review
- Using Neisseria meningitidis genomic diversity to inform outbreak strain identification.PLoS pathogens · 2021Article
- Evolution of Sequence Type 4821 Clonal Complex Hyperinvasive and Quinolone-Resistant Meningococci.Emerging infectious diseases · 2021Article
- Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2021Review
- Phylogenetic Concepts and Tools Applied to Epidemiologic Investigations of Infectious Diseases.Microbiology spectrum · 2019Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundWhile overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005-2006 and in 2010-2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns.
methodsWhole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks.
resultsNeisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the outbreak strains, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no polymorphism was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations.
conclusionsNeisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission.
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