Inferring Incidence of Unreported SARS-CoV-2 Infections Using Seroprevalence of Open Reading Frame 8 Antigen, Hong Kong
We tested seroprevalence of open reading frame 8 antigens to infer the number of unrecognized SARS-CoV-2 Omicron infections in Hong Kong during 2022. We estimate 33.6% of the population was infected, 72.1% asymptomatically. Surveillance and control activities during large-scale outbreaks should account for potentially substantial undercounts..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
Emerging Infectious Diseases - 30(2024), 2, Seite 325-328 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Shi Zhao [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
COVID-19 |
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| doi: |
10.3201/eid3002.231332 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ096503173 |
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| 520 | |a We tested seroprevalence of open reading frame 8 antigens to infer the number of unrecognized SARS-CoV-2 Omicron infections in Hong Kong during 2022. We estimate 33.6% of the population was infected, 72.1% asymptomatically. Surveillance and control activities during large-scale outbreaks should account for potentially substantial undercounts. | ||
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