Cargando…
Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020
BACKGROUND: COVID-19, caused by SARS-CoV-2, first appeared in China and subsequently developed into an ongoing epidemic. Understanding epidemiological factors characterising the transmission dynamics of this disease is of fundamental importance. AIMS: This study aimed to describe key epidemiological...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189647/ https://www.ncbi.nlm.nih.gov/pubmed/32347198 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.16.2000155 |
_version_ | 1783527540780957696 |
---|---|
author | Kwok, Kin On Wong, Valerie Wing Yu Wei, Wan In Wong, Samuel Yeung Shan Tang, Julian Wei-Tze |
author_facet | Kwok, Kin On Wong, Valerie Wing Yu Wei, Wan In Wong, Samuel Yeung Shan Tang, Julian Wei-Tze |
author_sort | Kwok, Kin On |
collection | PubMed |
description | BACKGROUND: COVID-19, caused by SARS-CoV-2, first appeared in China and subsequently developed into an ongoing epidemic. Understanding epidemiological factors characterising the transmission dynamics of this disease is of fundamental importance. AIMS: This study aimed to describe key epidemiological parameters of COVID-19 in Hong Kong. METHODS: We extracted data of confirmed COVID-19 cases and their close contacts from the publicly available information released by the Hong Kong Centre for Health Protection. We used doubly interval censored likelihood to estimate containment delay and serial interval, by fitting gamma, lognormal and Weibull distributions to respective empirical values using Bayesian framework with right truncation. A generalised linear regression model was employed to identify factors associated with containment delay. Secondary attack rate was also estimated. RESULTS: The empirical containment delay was 6.39 days; whereas after adjusting for right truncation with the best-fit Weibull distribution, it was 10.4 days (95% CrI: 7.15 to 19.81). Containment delay increased significantly over time. Local source of infection and number of doctor consultations before isolation were associated with longer containment delay. The empirical serial interval was 4.58–6.06 days; whereas the best-fit lognormal distribution to 26 certain-and-probable infector–infectee paired data gave an estimate of 4.77 days (95% CrI: 3.47 to 6.90) with right-truncation. The secondary attack rate among close contacts was 11.7%. CONCLUSION: With a considerable containment delay and short serial interval, contact-tracing effectiveness may not be optimised to halt the transmission with rapid generations replacement. Our study highlights the transmission risk of social interaction and pivotal role of physical distancing in suppressing the epidemic. |
format | Online Article Text |
id | pubmed-7189647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | European Centre for Disease Prevention and Control (ECDC) |
record_format | MEDLINE/PubMed |
spelling | pubmed-71896472020-04-30 Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 Kwok, Kin On Wong, Valerie Wing Yu Wei, Wan In Wong, Samuel Yeung Shan Tang, Julian Wei-Tze Euro Surveill Research BACKGROUND: COVID-19, caused by SARS-CoV-2, first appeared in China and subsequently developed into an ongoing epidemic. Understanding epidemiological factors characterising the transmission dynamics of this disease is of fundamental importance. AIMS: This study aimed to describe key epidemiological parameters of COVID-19 in Hong Kong. METHODS: We extracted data of confirmed COVID-19 cases and their close contacts from the publicly available information released by the Hong Kong Centre for Health Protection. We used doubly interval censored likelihood to estimate containment delay and serial interval, by fitting gamma, lognormal and Weibull distributions to respective empirical values using Bayesian framework with right truncation. A generalised linear regression model was employed to identify factors associated with containment delay. Secondary attack rate was also estimated. RESULTS: The empirical containment delay was 6.39 days; whereas after adjusting for right truncation with the best-fit Weibull distribution, it was 10.4 days (95% CrI: 7.15 to 19.81). Containment delay increased significantly over time. Local source of infection and number of doctor consultations before isolation were associated with longer containment delay. The empirical serial interval was 4.58–6.06 days; whereas the best-fit lognormal distribution to 26 certain-and-probable infector–infectee paired data gave an estimate of 4.77 days (95% CrI: 3.47 to 6.90) with right-truncation. The secondary attack rate among close contacts was 11.7%. CONCLUSION: With a considerable containment delay and short serial interval, contact-tracing effectiveness may not be optimised to halt the transmission with rapid generations replacement. Our study highlights the transmission risk of social interaction and pivotal role of physical distancing in suppressing the epidemic. European Centre for Disease Prevention and Control (ECDC) 2020-04-23 /pmc/articles/PMC7189647/ /pubmed/32347198 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.16.2000155 Text en This article is copyright of the authors or their affiliated institutions, 2020. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made. |
spellingShingle | Research Kwok, Kin On Wong, Valerie Wing Yu Wei, Wan In Wong, Samuel Yeung Shan Tang, Julian Wei-Tze Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title | Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title_full | Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title_fullStr | Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title_full_unstemmed | Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title_short | Epidemiological characteristics of the first 53 laboratory-confirmed cases of COVID-19 epidemic in Hong Kong, 13 February 2020 |
title_sort | epidemiological characteristics of the first 53 laboratory-confirmed cases of covid-19 epidemic in hong kong, 13 february 2020 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7189647/ https://www.ncbi.nlm.nih.gov/pubmed/32347198 http://dx.doi.org/10.2807/1560-7917.ES.2020.25.16.2000155 |
work_keys_str_mv | AT kwokkinon epidemiologicalcharacteristicsofthefirst53laboratoryconfirmedcasesofcovid19epidemicinhongkong13february2020 AT wongvaleriewingyu epidemiologicalcharacteristicsofthefirst53laboratoryconfirmedcasesofcovid19epidemicinhongkong13february2020 AT weiwanin epidemiologicalcharacteristicsofthefirst53laboratoryconfirmedcasesofcovid19epidemicinhongkong13february2020 AT wongsamuelyeungshan epidemiologicalcharacteristicsofthefirst53laboratoryconfirmedcasesofcovid19epidemicinhongkong13february2020 AT tangjulianweitze epidemiologicalcharacteristicsofthefirst53laboratoryconfirmedcasesofcovid19epidemicinhongkong13february2020 |