ArticleFrontiers in microbiology2024
Genomic tools for post-elimination measles molecular epidemiology using Canadian surveillance data from 2018-2020.
Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Whole genome sequencing of measles viruses: the benefit for outbreak investigation, The Netherlands, 2013-2014.Virus genes · 2026Article
- Hidden Burden of a Measles Outbreak Revealed by Genomic and Transmission Models.medRxiv : the preprint server for health sciences · 2026Article
- Measles and rubella: From global health challenges to advancements in molecular diagnostics in the elimination era.Molecular therapy. Nucleic acids · 2025Review
- Codon Usage Evolution in Viruses: Implications for Survival and Pathogenicity.Journal of molecular evolution · 2025Review
- Article
- Development and evaluation of a next-generation sequencing methodology for measles virus using Oxford Nanopore Technology.Journal of clinical microbiology · 2025Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Introduction: Measles is caused by the highly infectious measles virus, MeV, for which there is an effective vaccine. Monitoring of progress of measles elimination requires enhanced surveillance and tracking of MeV strains, including documenting the absence of an endemically circulating strain. Due to a reduction in the number of circulating genotypes, additional sequence information, beyond the standardized 450 nucleotide window of the nucleoprotein (N450), is required to corroborate the information from epidemiological investigations and, ideally, fill in gaps in the surveillance data. Methods: This study applies MeV sequencing tools, namely the N450, the non-coding region between the matrix and fusion genes (MF-NCR), and the complete coding sequence of the genome (WGS-t), to clinical specimens obtained from cases occurring over a three-year time period in Canada. This data was systematically analyzed, including with Bayesian evolutionary analysis by sampling trees (BEAST) of the WGS-t. Results and discussion: Of the 143 reported cases, N450, MF-NCR, and WGS-t sequences were obtained from 101, 81, and 75 cases, respectively. The BEAST analysis confirmed that the two most frequently detected lineages (B3 named strain MVi/Marikina City.PHL/10.18 and D8 named strain MVs/Gir Somnath.IND/42.16) were the result of repeated importations. Of the 16 outbreaks occurring during the study period, the analysis conclusively corroborated the epidemiological information for 13. BEAST analysis of the WGS-t convincingly demonstrated the expansion of two outbreaks by the inclusion of additional contemporary cases for which the epidemiological investigation had been unable to identify links. Furthermore, the analysis revealed the existence of three additional unrecognized outbreaks among the cases categorized as unknown source. One outbreak was without WGS-t and could not be resolved. Conclusion: Measles WGS-t data corroborated and expanded upon the outbreak analysis from traditional epidemiological investigations of measles outbreaks. However, both are needed for fulsome investigations in elimination settings.
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