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; Shi Zhao; Zian Zhuang; Marc K C Chong; Yongli Cai; Peihua Cao; Kai Wang; Yijun Lou; Weiming Wang; Daozhou Gao; Lin Yang; Daihai He; Maggie H Wang

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

Int J Infect Dis. 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.

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.

MeSH terms

Betacoronavirus*
COVID-19
Coronavirus Infections / diagnosis*
Coronavirus Infections / epidemiology
Delayed Diagnosis
Disease Outbreaks
Hong Kong / epidemiology
Humans
Pandemics
Pneumonia, Viral / diagnosis*
Pneumonia, Viral / epidemiology
Proportional Hazards Models
SARS-CoV-2