Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong
Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections 1 – 6 . For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but the...
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| Published in | Nature Medicine Vol. 26; no. 11; pp. 1714 - 1719 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article Magazine Article |
| Language | English |
| Published |
New York
Nature Publishing Group US
01.11.2020
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections
1
–
6
. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19
7
,
8
. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4–7 SSEs across 51 clusters (
n
= 309 cases) and estimated that 19% (95% confidence interval, 15–24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (
P
= 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (
P
= 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9–107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission.
Cases linked to superspreading events are estimated to account for 80% of all local transmission of SARS-CoV-2 in Hong Kong in a study with implications for public health policies. |
|---|---|
| AbstractList | Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections.sup.1-6. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19.sup.7,8. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission. Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections1–6. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-197,8. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4–7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15–24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9–107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission.Cases linked to superspreading events are estimated to account for 80% of all local transmission of SARS-CoV-2 in Hong Kong in a study with implications for public health policies. Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections . For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19 . Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission. Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections 1 – 6 . For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19 7 , 8 . Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4–7 SSEs across 51 clusters ( n = 309 cases) and estimated that 19% (95% confidence interval, 15–24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age ( P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases ( P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9–107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission. Cases linked to superspreading events are estimated to account for 80% of all local transmission of SARS-CoV-2 in Hong Kong in a study with implications for public health policies. Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections.sup.1-6. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-19.sup.7,8. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission. Cases linked to superspreading events are estimated to account for 80% of all local transmission of SARS-CoV-2 in Hong Kong in a study with implications for public health policies. Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections1-6. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-197,8. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission.Superspreading events (SSEs) have characterized previous epidemics of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infections1-6. For SARS-CoV-2, the degree to which SSEs are involved in transmission remains unclear, but there is growing evidence that SSEs might be a typical feature of COVID-197,8. Using contact tracing data from 1,038 SARS-CoV-2 cases confirmed between 23 January and 28 April 2020 in Hong Kong, we identified and characterized all local clusters of infection. We identified 4-7 SSEs across 51 clusters (n = 309 cases) and estimated that 19% (95% confidence interval, 15-24%) of cases seeded 80% of all local transmission. Transmission in social settings was associated with more secondary cases than households when controlling for age (P = 0.002). Decreasing the delay between symptom onset and case confirmation did not result in fewer secondary cases (P = 0.98), although the odds that an individual being quarantined as a contact interrupted transmission was 14.4 (95% CI, 1.9-107.2). Public health authorities should focus on rapidly tracing and quarantining contacts, along with implementing restrictions targeting social settings to reduce the risk of SSEs and suppress SARS-CoV-2 transmission. |
| Audience | Academic |
| Author | Lau, Eric H. Y. Adam, Dillon C. Cauchemez, Simon Tsang, Tim K. Leung, Gabriel M. Wu, Peng Wong, Jessica Y. Cowling, Benjamin J. |
| Author_xml | – sequence: 1 givenname: Dillon C. surname: Adam fullname: Adam, Dillon C. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, Biosecurity Program, Kirby Institute, University of New South Wales – sequence: 2 givenname: Peng orcidid: 0000-0003-1157-9401 surname: Wu fullname: Wu, Peng email: pengwu@hku.hk organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region – sequence: 3 givenname: Jessica Y. surname: Wong fullname: Wong, Jessica Y. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region – sequence: 4 givenname: Eric H. Y. orcidid: 0000-0002-6688-9637 surname: Lau fullname: Lau, Eric H. Y. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region – sequence: 5 givenname: Tim K. surname: Tsang fullname: Tsang, Tim K. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region – sequence: 6 givenname: Simon orcidid: 0000-0001-9186-4549 surname: Cauchemez fullname: Cauchemez, Simon organization: Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur – sequence: 7 givenname: Gabriel M. surname: Leung fullname: Leung, Gabriel M. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region – sequence: 8 givenname: Benjamin J. orcidid: 0000-0002-6297-7154 surname: Cowling fullname: Cowling, Benjamin J. organization: WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32943787$$D View this record in MEDLINE/PubMed https://pasteur.hal.science/pasteur-04095246$$DView record in HAL |
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| SubjectTerms | 692/699/255 692/700/478/174 Biomedical and Life Sciences Biomedicine Cancer Research Carrier State - epidemiology Cluster Analysis Clustering Confidence intervals Contact Tracing Coronaviridae Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - transmission Disease transmission Distribution Female Health Policy History Hong Kong - epidemiology Households Humans Infectious Diseases Letter Life Sciences Male Metabolic Diseases Models, Theoretical Molecular Medicine Neurosciences Pandemics Patient Isolation - legislation & jurisprudence Public health Public Health - legislation & jurisprudence Quarantine - legislation & jurisprudence Respiratory diseases SARS-CoV-2 - physiology Severe acute respiratory syndrome coronavirus 2 Travel-Related Illness Viral diseases |
| Title | Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong |
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