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Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

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Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 236 SARS-CoV2 sequences from cases in the New York City metropolitan area during the initial stages of the 2020 COVID-19 outbreak. The majority of cases throughout the region had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that the majority were most related to cases from Europe. Our data are consistent with numerous seed transmissions from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of real-time genomic surveillance in addition to traditional epidemiological indicators.

No abstract