دورية أكاديمية
Universal Community Nucleic Acid Testing for Coronavirus Disease 2019 (COVID-19) in Hong Kong Reveals Insights Into Transmission Dynamics: A Cross-Sectional and Modeling Study.
| العنوان: | Universal Community Nucleic Acid Testing for Coronavirus Disease 2019 (COVID-19) in Hong Kong Reveals Insights Into Transmission Dynamics: A Cross-Sectional and Modeling Study. |
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| المؤلفون: | Yang B; World Health 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, Chinaand., Tsang TK; World Health 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, Chinaand., Gao H; World Health 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, Chinaand., Lau EHY; World Health 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, Chinaand.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong Special Administrative Region, China., Lin Y; World Health 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, Chinaand., Ho F; World Health 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, Chinaand., Xiao J; World Health 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, Chinaand., Wong JY; World Health 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, Chinaand., Adam DC; World Health 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, Chinaand., Liao Q; World Health 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, Chinaand., Wu P; World Health 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, Chinaand.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong Special Administrative Region, China., Cowling BJ; World Health 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, Chinaand.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong Special Administrative Region, China., Leung GM; World Health 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, Chinaand.; Laboratory of Data Discovery for Health Limited, Hong Kong Science Park, New Territories, Hong Kong Special Administrative Region, China. |
| المصدر: | Clinical infectious diseases : an official publication of the Infectious Diseases Society of America [Clin Infect Dis] 2022 Aug 24; Vol. 75 (1), pp. e216-e223. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Oxford University Press Country of Publication: United States NLM ID: 9203213 Publication Model: Print Cited Medium: Internet ISSN: 1537-6591 (Electronic) Linking ISSN: 10584838 NLM ISO Abbreviation: Clin Infect Dis Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Jan. 2011- : Oxford : Oxford University Press Original Publication: Chicago, IL : The University of Chicago Press, c1992- |
| مواضيع طبية MeSH: | COVID-19*/diagnosis , COVID-19*/epidemiology , Nucleic Acids*, Bayes Theorem ; COVID-19 Testing ; Cross-Sectional Studies ; Hong Kong/epidemiology ; Humans ; SARS-CoV-2 |
| مستخلص: | Background: Testing of an entire community has been used as an approach to control coronavirus disease 2019 (COVID-19). In Hong Kong, a universal community testing program (UCTP) was implemented at the fadeout phase of a community epidemic in July to September 2020. We described the utility of the UCTP in finding unrecognized infections and analyzed data from the UCTP and other sources to characterize transmission dynamics. Methods: We described the characteristics of people participating in the UCTP and compared the clinical and epidemiological characteristics of COVID-19 cases detected by the UCTP versus those detected by clinical diagnosis and public health surveillance (CDPHS). We developed a Bayesian model to estimate the age-specific incidence of infection and the proportion of cases detected by CDPHS. Results: In total, 1.77 million people, 24% of the Hong Kong population, participated in the UCTP from 1 to 14 September 2020. The UCTP identified 32 new infections (1.8 per 100000 samples tested), consisting of 29% of all local cases reported during the two-week UCTP period. Compared with the CDPHS, the UCTP detected a higher proportion of sporadic cases (62% vs 27%, P<.01) and identified 6 (out of 18) additional clusters during that period. We estimated that 27% (95% credible interval: 22%, 34%) of all infections were detected by the CDPHS in the third wave. Conclusions: We reported empirical evidence of the utility of population-wide COVID-19 testing in detecting unrecognized infections and clusters. Around three quarters of infections have not been identified through existing surveillance approaches including contact tracing. (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.) |
| فهرسة مساهمة: | Keywords: COVID-19; disease burden; mass testing; surveillance; transmission dynamics |
| المشرفين على المادة: | 0 (Nucleic Acids) |
| تواريخ الأحداث: | Date Created: 20211031 Date Completed: 20220829 Latest Revision: 20221011 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1093/cid/ciab925 |
| PMID: | 34718464 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1537-6591 |
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| DOI: | 10.1093/cid/ciab925 |