The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020
© 2022. The Author(s)..
BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown.
METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020.
RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases.
CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.
| Errataetall: | |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
BMC infectious diseases - 22(2022), 1 vom: 18. Juni, Seite 556 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Knight, Gwenan M [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 21.06.2022 Date Revised 06.03.2024 published: Electronic UpdateOf: Res Sq. 2022 Mar 03;:. - PMID 35262072 Citation Status MEDLINE |
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| doi: |
10.1186/s12879-022-07490-4 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM342384430 |
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| 100 | 1 | |a Knight, Gwenan M |e verfasserin |4 aut | |
| 245 | 1 | 4 | |a The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020 |
| 264 | 1 | |c 2022 | |
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| 500 | |a Date Completed 21.06.2022 | ||
| 500 | |a Date Revised 06.03.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a UpdateOf: Res Sq. 2022 Mar 03;:. - PMID 35262072 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2022. The Author(s). | ||
| 520 | |a BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown | ||
| 520 | |a METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020 | ||
| 520 | |a RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases | ||
| 520 | |a CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Mathematical modelling | |
| 650 | 4 | |a Nosocomial transmission | |
| 650 | 4 | |a SARS-CoV-2 | |
| 700 | 1 | |a Pham, Thi Mui |e verfasserin |4 aut | |
| 700 | 1 | |a Stimson, James |e verfasserin |4 aut | |
| 700 | 1 | |a Funk, Sebastian |e verfasserin |4 aut | |
| 700 | 1 | |a Jafari, Yalda |e verfasserin |4 aut | |
| 700 | 1 | |a Pople, Diane |e verfasserin |4 aut | |
| 700 | 1 | |a Evans, Stephanie |e verfasserin |4 aut | |
| 700 | 1 | |a Yin, Mo |e verfasserin |4 aut | |
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| 700 | 1 | |a Bhattacharya, Alex |e verfasserin |4 aut | |
| 700 | 1 | |a Hope, Russell |e verfasserin |4 aut | |
| 700 | 1 | |a Semple, Malcolm G |e verfasserin |4 aut | |
| 700 | 0 | |a ISARIC4C Investigators |e verfasserin |4 aut | |
| 700 | 0 | |a CMMID COVID-19 Working Group |e verfasserin |4 aut | |
| 700 | 1 | |a Read, Jonathan M |e verfasserin |4 aut | |
| 700 | 1 | |a Cooper, Ben S |e verfasserin |4 aut | |
| 700 | 1 | |a Robotham, Julie V |e verfasserin |4 aut | |
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| 700 | 1 | |a Barnard, Rosanna C |e investigator |4 oth | |
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| 700 | 1 | |a Mee, Paul |e investigator |4 oth | |
| 700 | 1 | |a McCarthy, Ciara V |e investigator |4 oth | |
| 700 | 1 | |a Quaife, Matthew |e investigator |4 oth | |
| 700 | 1 | |a Kucharski, Adam J |e investigator |4 oth | |
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| 700 | 1 | |a Medley, Graham |e investigator |4 oth | |
| 700 | 1 | |a Tully, Damien C |e investigator |4 oth | |
| 700 | 1 | |a Wong, Kerry L M |e investigator |4 oth | |
| 700 | 1 | |a Liu, Yang |e investigator |4 oth | |
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| 700 | 1 | |a Munday, James D |e investigator |4 oth | |
| 700 | 1 | |a Chapman, Lloyd A C |e investigator |4 oth | |
| 700 | 1 | |a Hué, Stéphane |e investigator |4 oth | |
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| 700 | 1 | |a Villabona-Arenas, C Julian |e investigator |4 oth | |
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