Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias
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 inf...
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Veröffentlicht in: | The Journal of infectious diseases 2022-11, Vol.226 (10), p.1704-1711 |
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container_title | The Journal of infectious diseases |
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creator | 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 |
description | 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.
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.
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.
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. |
doi_str_mv | 10.1093/infdis/jiac348 |
format | Article |
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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.
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.
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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.
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.
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.</description><subject>COVID-19 - epidemiology</subject><subject>Health Personnel</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Infection Control</subject><subject>Pandemics - prevention & control</subject><subject>SARS-CoV-2 - genetics</subject><issn>0022-1899</issn><issn>1537-6613</issn><issn>1537-6613</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo9kU9v1DAQxS0EokvhyhH5yCWt_yR2fCzbApVaUdH2HE3sSeUqsRfbqZTPxJckyy6cRjN6896MfoR85OyMMyPPfRicz-fPHqys21dkwxupK6W4fE02jAlR8daYE_Iu52fGWC2VfktOZGOM5FxtyO_H4DDlAsH58ESvII0LvVs7nLyl9_iCCemFnQvSn5h3PkGJaaH3S3ApTki3McUALz7NmQr6kCDkyefsY6A-UKC36LyFkW4xFEy0X-h1sDHt4mq0D7yb-_Fv0K8Zg91PLqFADxkzLZHe-uKfYA3_4iG_J28GGDN-ONZT8vj16mH7vbr58e16e3FTWSmbUslet0Lq1tYANVdiqGurrVTcKmF7h0w70dvGGoG8Nqha0GiNa3s5sBaNkqfk88F3l-J6Vi7d-pLFcYSAcc6d0KyRphW6WaVnB6lNMeeEQ7dLfoK0dJx1e0DdAVB3BLQufDp6z_2E7r_8HxH5B43XkmA</recordid><startdate>20221111</startdate><enddate>20221111</enddate><creator>Turcinovic, Jacquelyn</creator><creator>Schaeffer, Beau</creator><creator>Taylor, Bradford P</creator><creator>Bouton, Tara C</creator><creator>Odom-Mabey, Aubrey R</creator><creator>Weber, Sarah E</creator><creator>Lodi, Sara</creator><creator>Ragan, Elizabeth J</creator><creator>Connor, John H</creator><creator>Jacobson, Karen R</creator><creator>Hanage, William P</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-7808-955X</orcidid></search><sort><creationdate>20221111</creationdate><title>Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias</title><author>Turcinovic, Jacquelyn ; 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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.
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.
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.
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><cop>United States</cop><pmid>35993116</pmid><doi>10.1093/infdis/jiac348</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-7808-955X</orcidid><oa>free_for_read</oa></addata></record> |
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source | Oxford University Press Journals All Titles (1996-Current); MEDLINE; Alma/SFX Local Collection |
subjects | COVID-19 - epidemiology Health Personnel Hospitals Humans Infection Control Pandemics - prevention & control SARS-CoV-2 - genetics |
title | Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias |
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