Jessica Tan
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Researcher at Icahn School of Medicine at Mount Sinai
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Video Abstract (AI generated)
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Preprint
Background: Nosocomial respiratory virus outbreaks represent serious public health challenges. Rapid and precise identification of cases and tracing of transmission chains is critical to end outbreaks and to inform prevention measures. Methods: We combined conventional surveillance with Influenza A virus (IAV) genome sequencing to identify and contain a large IAV outbreak in a metropolitan healthcare system. A total of 381 individuals, including 91 inpatients and 290 health care workers (HCWs), were included in the investigation. Results: During a 12-day period in early 2019, infection preventionists identified 89 HCWs and 18 inpatients as cases of influenza-like illness (ILI), using an amended definition, without the requirement for fever. Sequencing of IAV genomes from available nasopharyngeal (NP) specimens identified 66 individuals infected with a nearly identical strain of influenza A H1N1 (43 HCWs, 17 inpatients, and 6 with unspecified affiliation). All HCWs infected with the outbreak strain had received the seasonal influenza virus vaccination. Characterization of five representative outbreak viral isolates did not show antigenic drift. In conjunction with IAV genome sequencing, mining of electronic records pinpointed the origin of the outbreak as a single patient and a few interactions in the emergency department that occurred one day prior to the index ILI cluster. Conclusions: We used precision surveillance to identify and control a large nosocomial IAV outbreak, mapping the source of the outbreak to a single patient rather than HCWs as initially assumed based on conventional epidemiology. These findings have important ramifications for more effective prevention strategies to curb nosocomial respiratory virus outbreaks.
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Video Abstract (AI generated)
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Preprint
New York City (NYC) emerged as a coronavirus disease 2019 (COVID-19) epicenter in March 2020, but there is limited information regarding potentially unrecognized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections before the first reported case. We utilized a sample pooling strategy to screen for SARS-CoV-2 RNA in de-identified, respiratory pathogen-negative nasopharyngeal specimens from 3,040 patients across our NYC health system who were evaluated for respiratory symptoms or influenza-like illness during the first 10 weeks of 2020. We obtained complete SARS-CoV-2 genome sequences from samples collected between late February and early March. Additionally, we detected SARS-CoV-2 RNA in pooled specimens collected in the week ending 25 January 2020, indicating that SARS-CoV-2 caused sporadic infections in NYC a full month before the first officially documented case.
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Video Abstract (AI generated)
Paper
Preprint
By conducting a retrospective, cross-sectional analysis of SARS-CoV-2 seroprevalence in a sentinel group (enriched for SARS-CoV-2 infections) and a screening group (representative of the general population) using >5,000 plasma samples from patients at Mount Sinai Hospital in New York City (NYC), we identified seropositive samples as early as in the week ending February 23, 2020. A stark increase in seropositivity in the sentinel group started the week ending March 22 and in the screening group in the week ending March 29. By the week ending April 19, the seroprevalence in the screening group reached 19.3%, which is well below the estimated 67% needed to achieve community immunity to SARS-CoV-2. These data potentially suggest an earlier than previously documented introduction of SARS-CoV-2 into the NYC metropolitan area.