Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias. (22nd August 2022) - Turcinovic, Jacquelyn; Schaeffer, Beau; Taylor, Bradford P; Bouton, Tara C; Odom-Mabey, Aubrey R; Weber, Sarah E; Lodi, Sara; Ragan, Elizabeth J; Connor, John H; Jacobson, Karen R; Hanage, William P
Abstract: Background: Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited. Methods: We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes. Results: Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%–84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread. Conclusions: We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission. Abstract : Outbreak analyses using genomic sequences spuriously identify transmission when genomically similar pathogens in the outside community infect cohort members. We show how to avoid this by example--leveraging community sequences within a SARS-CoV-2 outbreak at Boston Medical Center during early 2020.