Real-Time Genomic Epidemiology Approaches to a Measles Outbreak Response in Utah

As vaccination rates have declined, large measles outbreaks have taken hold in vulnerable populations. In 2025, the United States saw the highest number of measles cases since 1991. After Utahs first case in June 2025, the Utah Public Health Laboratory (UPHL) began performing whole genome sequencing (WGS) on clinical measles samples. As Utahs outbreak grew, public health professionals used WGS data to identify clusters of disease, and combined genomic and epidemiologic data to identify factors that may fuel the spread of disease throughout the state. This study used sequenced samples from 65% of reported measles cases in Utah. Time-scaled and maximum likelihood phylogenetic trees were generated. A single nucleotide polymorphism (SNP) threshold of one was used to generate genomic clusters, and a Fishers Exact test was used to determine association between genomic cluster and epidemiological variables. Epidemiological clusters were assessed using annotated phylogenetic trees. We found multiple introductions of measles into Utah, with one accounting for the majority of cases. As measles spread, two phylogenetic clades emerged with differing geographical case compositions. We identified a significant association between shared school and genomic clustering, and we reconstructed transmission chains within schools and emerging from school sporting events. This study demonstrates the utility of WGS in real-time outbreak investigations. Sequencing data allowed for gaps in epidemiological data to be filled, revealing undetected transmission and clarifying whether cases belong to a known outbreak. We also highlight that schools and high-contact sporting events played a significant role in fueling transmission across the state.