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Data Analytics Could Enable Early SARS-CoV-2 Variant Detection, Study Says

With the application of efficient data analytics to available sequence data, the Omicron variant of SARS-CoV-2 could have been detected much earlier, according to study appearing this week in JAMA Network Open. Now the dominant SARS-CoV-2 variant in the US, Omicron was first reported by South Africa in late November 2021 and by the US Centers for Disease Control and Prevention shortly thereafter. To determine if the variant could have been detected earlier — which could have provided an opportunity to better control its spread — a group led by Fred Hutchinson Cancer Research Center scientists applied a statistical learning strategy (SLS) to viral genomic sequence data collected from 63,686 African individuals and 531,827 people in the US between the start of 2020 and the end of 2021. The investigators find that Omicron was detectable in South Africa as early as Dec. 31, 2020 and that it could have been declared a variant of concern nearly a month sooner than the official declaration. Earlier detection of SARS-CoV-2 variants could help the global effort in disease prevention and control, the study's authors write. "To optimize early detection, efficient data analytics, such as SLS, could assist in the rapid identification of new variants as soon as they emerge, with or without lineages designated, using viral sequence data from global surveillance."