Genomic tools for post-elimination measles molecular epidemiology using Canadian surveillance data from 2018–2020 - Hiebert, Joanne; Zubach, Vanessa; Schulz, Helene; Severini, Alberto (Frontiers in Microbiology, 2024)
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 to document 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 3 year time period in Canada. This data was systematically analysed, 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 thirteen. BEAST analysis of the WGS-t convincingly demonstrated the expansion of 2 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 3 additional unrecognized outbreaks amongst the cases categorized as unknown source. One outbreak was without WGS-t and couldn’t be resolved. Conclusion: Measles WGS-t data corroborated and expanded the outbreak analysis from traditional epidemiological investigations of measles outbreaks. However, both are needed for fulsome investigations in elimination settings.