Dataset Information

Molecular evidence of SARS-CoV-2 in New York before the first pandemic wave.

ABSTRACT: Numerous reports document the spread of SARS-CoV-2, but there is limited information on its introduction before the identification of a local case. This may lead to incorrect assumptions when modeling viral origins and transmission. Here, we utilize a sample pooling strategy to screen for previously undetected SARS-CoV-2 in de-identified, respiratory pathogen-negative nasopharyngeal specimens from 3,040 patients across the Mount Sinai Health System in New York. The patients had been previously evaluated for respiratory symptoms or influenza-like illness during the first 10 weeks of 2020. We identify SARS-CoV-2 RNA from specimens collected as early as 25 January 2020, and complete SARS-CoV-2 genome sequences from multiple pools of samples collected between late February and early March, documenting an increase prior to the later surge. Our results provide evidence of sporadic SARS-CoV-2 infections a full month before both the first officially documented case and emergence of New York as a COVID-19 epicenter in March 2020.

SUBMITTER: Hernandez MM

PROVIDER: S-EPMC8187428 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Molecular evidence of SARS-CoV-2 in New York before the first pandemic wave.

Hernandez Matthew M MM Gonzalez-Reiche Ana S AS Alshammary Hala H Fabre Shelcie S Khan Zenab Z van De Guchte Adriana A Obla Ajay A Ellis Ethan E Sullivan Mitchell J MJ Tan Jessica J Alburquerque Bremy B Soto Juan J Wang Ching-Yi CY Sridhar Shwetha Hara SH Wang Ying-Chih YC Smith Melissa M Sebra Robert R Paniz-Mondolfi Alberto E AE Gitman Melissa R MR Nowak Michael D MD Cordon-Cardo Carlos C Luksza Marta M Krammer Florian F van Bakel Harm H Simon Viviana V Sordillo Emilia Mia EM

Nature communications 20210608 1

Numerous reports document the spread of SARS-CoV-2, but there is limited information on its introduction before the identification of a local case. This may lead to incorrect assumptions when modeling viral origins and transmission. Here, we utilize a sample pooling strategy to screen for previously undetected SARS-CoV-2 in de-identified, respiratory pathogen-negative nasopharyngeal specimens from 3,040 patients across the Mount Sinai Health System in New York. The patients had been previously e ...[more]

PMID: 34103497

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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that was first reported in Wuhan, China in December of 2019 and has since caused a global pandemic resulting in millions of deaths and tens of millions of patients testing positive for infection. Analysis of different viral strains has identified a D614G change in the spike protein that is correlated with the virus becoming more transmissible. While studies have shown G614 viruses to be more transmissible, the effects of this mutation on the host response, especially on the cellular level, are yet to be fully elucidated. In this experiment we infected NHBE cells with the Washington (D614) strain or the New York (G614) strains of SARS-CoV-2. We generated RNA sequencing data at three different time points to improve our understanding of how the intracellular host response differs between infections with these two strains. We analyzed these data with a bioinformatics pipeline that identifies differentially expressed genes, enriched Gene Ontology terms and dysregulated signaling pathways. We detected over 2,000 differentially expressed genes, over 600 Gene Ontology terms, and 29 affected pathways between the two treatments. Many of these entities play a role in immune signaling and response. When comparing the different strains and different time points we found more overall similarities between matched time points than across different time points with the same strain. When specifically comparing the affected pathways, we saw that the 24hr time point of the New York strain was more similar to the 12hr time point of the Washington strain with a large number of pathways related to translation being inhibited in both strains at these time points. These results suggest that D614G substitution in the spike protein, combined with other nonsynonymous changes in the viral gene products cause distinct responses in infected host cells, especially relating to how quickly translation is dysregulated after infection. These observed differences in the intracellular host response to infection could play a role in driving the increase in pathogenicity and mortality seen in the New York outbreaks versus the Washington outbreaks at the beginning of the SARS-CoV-2 pandemic.

Project description:BackgroundUnderstanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood.MethodsUsing high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread.ResultsWe find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing.ConclusionsThe Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

Project description:BackgroundAs the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear.MethodsIn this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening).FindingsDuring the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older.InterpretationOur results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds.FundingNational Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.

Dataset Information

Molecular evidence of SARS-CoV-2 in New York before the first pandemic wave.

Publications

Molecular evidence of SARS-CoV-2 in New York before the first pandemic wave.

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