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Quantifying the improvement in confirmation efficiency of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the early phase of the outbreak in Hong Kong in 2020

Ran J.,
Zhao S.,
Zhuang Z.,
Chong M.K.C.,
Cai Y.,
Cao P.,
Wang K.,
Lou Y.,
Wang W.,
Gao D.,
Yang L.,
He D.,
Wang M.H.
Document Type
Source Title
International Journal of Infectious Diseases
Elsevier B.V.


Backgrounds: The emerging virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused a large outbreak of coronavirus disease, COVID-19, in Wuhan, China, since December 2019. COVID-19 soon spread to other regions of China and overseas. In Hong Kong, local mitigation measures were implemented since the first imported case was confirmed on January 23, 2020. Here we evaluated the temporal variation of detection delay from symptoms onset to laboratory confirmation of SARS-CoV-2 in Hong Kong. Methods: A regression model is adopted to quantify the association between the SARS-CoV-2 detection delay and calendar time. The association is tested and further validated by a Cox proportional hazard model. Findings: The estimated median detection delay was 9.5 days (95%CI: 6.5 − 11.5) in the second half of January, reduced to 6.0 days (95%CI: 5.5 − 9.5) in the first half of February 2020. We estimate that SARS-CoV-2 detection efficiency improved at a daily rate of 5.40% (95%CI: 2.54 − 8.33) in Hong Kong. Conclusions: The detection efficiency of SARS-CoV-2 was likely being improved substantially in Hong Kong since the first imported case was detected. Sustaining enforcement in timely detection and other effective control measures are recommended to prevent the SARS-CoV-2 infection. © 2020 The Authors

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Index Keywords

Article; coronavirus disease 2019; delayed diagnosis; epidemic; Hong Kong; human; infection control; major clinical study; Severe acute respiratory syndrome coronavirus 2; virus detection; Betacoronavirus; Coronavirus infection; delayed diagnosis; Hong Kong; pandemic; proportional hazards model; virus pneumonia; Betacoronavirus; Coronavirus Infections; Delayed Diagnosis; Disease Outbreaks; Hong Kong; Humans; Pandemics; Pneumonia, Viral; Proportional Hazards Models