Speaker
Description
Over the past decade, pathogen genomic surveillance has become a vital public health tool for monitoring and controlling viral outbreaks. Uncoupled from epidemiological data, the public health value of the unprecedented volume of SARS-CoV-2 genomic data is not fully realized. Here, we combine viral genomic and epidemiological data from over 134,000 Massachusetts SARS-CoV-2 genomes tested and sequenced at a single facility between November 1, 2021, and January 17, 2023, to understand the changing infection and transmission dynamics of SARS-CoV-2 across multiple scales of resolution: statewide (Massachusetts), city, facility, and down to the individual level. At the state level, we determine a minimum of 700 genomes generated per week to detect emerging and growing lineages. At the municipal level, we find that urban regions are key for establishing and propagating introductions into the state, typically detecting new lineages 16 days earlier and reaching predominance 2 days earlier than rural regions. At the outbreak level, we identified over 1000 facility-restricted clusters and found that the inclusion of genomic data decreases the observed size (15.6 to 6 individuals) and duration (15.7 to 6.7 days) of clusters, redefining potential public health targets and methods of intervention. We find that only 33% of our identified clusters contain multiple facilities, and 20% contain more than two facility types. Finally, at the individual level, we show that vaccination decreases risk of infection and individuals with increasing vaccine doses are less likely to have descendant cases. Together, these findings highlight the insights gained from integrating genomic surveillance systems with public health data while establishing quantitative guidelines for surveillance capacity.
