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

doi:10.1016/j.ijid.2020.05.015

. 2020 Jul:96:284-287.

doi: 10.1016/j.ijid.2020.05.015. Epub 2020 May 8.

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

Jinjun Ran¹, Shi Zhao², Zian Zhuang³, Marc K C Chong⁴, Yongli Cai⁵, Peihua Cao⁶, Kai Wang⁷, Yijun Lou⁸, Weiming Wang⁹, Daozhou Gao¹⁰, Lin Yang¹¹, Daihai He¹², Maggie H Wang¹³

Affiliations

¹ School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China. Electronic address: jimran@connect.hku.hk.
² JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: zhaoshi.cmsa@gmail.com.
³ Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: larry.zhuang@polyu.edu.hk.
⁴ JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: marc@cuhk.edu.hk.
⁵ School of Mathematics and Statistics, Huaiyin Normal University, Huaian, China. Electronic address: yonglicai@hytc.edu.cn.
⁶ Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China. Electronic address: cphcc@smu.edu.cn.
⁷ Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, China. Electronic address: wangkaimath@sina.com.
⁸ Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: yijun.lou@polyu.edu.hk.
⁹ School of Mathematics and Statistics, Huaiyin Normal University, Huaian, China. Electronic address: weimingwang2003@163.com.
¹⁰ Department of Mathematics, Shanghai Normal University, Shanghai, China. Electronic address: dzgao@shnu.edu.cn.
¹¹ School of Nursing, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: l.yang@polyu.edu.hk.
¹² Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: daihai.he@polyu.edu.hk.
¹³ JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: maggiew@cuhk.edu.hk.

PMID: 32413609
PMCID: PMC7207138
DOI: 10.1016/j.ijid.2020.05.015

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

Jinjun Ran et al. Int J Infect Dis. 2020 Jul.

. 2020 Jul:96:284-287.

doi: 10.1016/j.ijid.2020.05.015. Epub 2020 May 8.

Authors

Jinjun Ran¹, Shi Zhao², Zian Zhuang³, Marc K C Chong⁴, Yongli Cai⁵, Peihua Cao⁶, Kai Wang⁷, Yijun Lou⁸, Weiming Wang⁹, Daozhou Gao¹⁰, Lin Yang¹¹, Daihai He¹², Maggie H Wang¹³

Affiliations

¹ School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China. Electronic address: jimran@connect.hku.hk.
² JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: zhaoshi.cmsa@gmail.com.
³ Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: larry.zhuang@polyu.edu.hk.
⁴ JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: marc@cuhk.edu.hk.
⁵ School of Mathematics and Statistics, Huaiyin Normal University, Huaian, China. Electronic address: yonglicai@hytc.edu.cn.
⁶ Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China. Electronic address: cphcc@smu.edu.cn.
⁷ Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, China. Electronic address: wangkaimath@sina.com.
⁸ Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: yijun.lou@polyu.edu.hk.
⁹ School of Mathematics and Statistics, Huaiyin Normal University, Huaian, China. Electronic address: weimingwang2003@163.com.
¹⁰ Department of Mathematics, Shanghai Normal University, Shanghai, China. Electronic address: dzgao@shnu.edu.cn.
¹¹ School of Nursing, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: l.yang@polyu.edu.hk.
¹² Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: daihai.he@polyu.edu.hk.
¹³ JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China. Electronic address: maggiew@cuhk.edu.hk.

PMID: 32413609
PMCID: PMC7207138
DOI: 10.1016/j.ijid.2020.05.015

Abstract

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.

Keywords: COVID-19; Hong Kong.; confirmation efficiency; early outbreak.

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Figures

**Fig. 1**
The daily SARS-CoV-2 cases time series in (a), and count of tested cases (b) and the association between detection delay (τ) and time in (c). Panel (a) shows the time series of the daily number of SARS-CoV-2 cases aggregated by the date of onset (grey horizontal bars) and by the laboratory-confirmed date (black vertical bars). Panel (b) shows the time series of the daily number of tested cases. Panel (c) shows the detection delays (τ) of the cases who are Hong Kong residence (blue dots) and of the cases who are not Hong Kong residence (red triangles) vary over the calendar date. The bold curves are the fitting results of the regression in Eqn (1), and the dashed curves are the 95% confidence interval (95%CI).

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[1] ’Pneumonia of unknown cause – China,’ Emergencies preparedness, response, Disease outbreak news, World Health Organization (WHO) [https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-ch...

[2] ’Pneumonia of unknown cause – China,’ Emergencies preparedness, response, Disease outbreak news, World Health Organization (WHO) [https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-ch...

[3] Bogoch I.I., Watts A., Thomas-Bachli A., Huber C., Kraemer M.U., Khan K. Pneumonia of unknown etiology in Wuhan, China: potential for international spread via commercial air travel. Journal of Travel Medicine. 2020 doi: 10.1093/jtm/taaa1008. - DOI - PMC - PubMed

[4] Bogoch I.I., Watts A., Thomas-Bachli A., Huber C., Kraemer M.U., Khan K. Pneumonia of unknown etiology in Wuhan, China: potential for international spread via commercial air travel. Journal of Travel Medicine. 2020 doi: 10.1093/jtm/taaa1008. - DOI - PMC - PubMed

[5] Wu J.T., Leung K., Leung GM: Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet. 2020 - PMC - PubMed

[6] Wu J.T., Leung K., Leung GM: Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet. 2020 - PMC - PubMed

[7] Summary of data and outbreak situation of the Severe Respiratory Disease associated with a Novel Infectious Agent, Centre for Health Protection, the government of Hong Kong. [https://www.chp.gov.hk/en/features/102465.html]

[8] Summary of data and outbreak situation of the Severe Respiratory Disease associated with a Novel Infectious Agent, Centre for Health Protection, the government of Hong Kong. [https://www.chp.gov.hk/en/features/102465.html]

[9] The collection of Press Releases by the Centre for Health Protection (CHP) of Hong Kong. [https://www.chp.gov.hk/en/media/116/index.html]

[10] The collection of Press Releases by the Centre for Health Protection (CHP) of Hong Kong. [https://www.chp.gov.hk/en/media/116/index.html]

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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

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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

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