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Insights into COVID-19 Epidemiology and Control from Temporal Changes in Serial Interval Distributions in Hong Kong

28 Pages Posted: 4 Oct 2022

See all articles by Sheikh Taslim Ali

Sheikh Taslim Ali

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Dongxuan Chen

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Wey Wen Lim

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Amy Yeung

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Dillon C. Adam

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Yiu Chung Lau

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Eric H.Y. Lau

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Jessica Y. Wong

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Jingyi Xiao

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Faith Ho

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Huizhi Gao

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Lin Wang

University of Cambridge - Department of Genetics; The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

X-K Xu

Dalian Minzu University - College of Information and Communication Engineering

Zhanwei Du

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Peng Wu

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Gabriel Leung

The University of Hong Kong - School of Public Health

Benjamin J. Cowling

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

More...

Abstract

Background: The serial interval distribution is used to approximate the generation time distribution, an essential parameter to infer the transmissibility (Rt) of an epidemic. However, serial interval distributions may change as an epidemic progresses rather than remaining constant.

Method: We examined detailed contact tracing data on laboratory-confirmed cases of COVID-19 in Hong Kong during the five waves from January 2020 to July 2022. We reconstructed the transmission pairs and estimated time-varying effective serial interval distributions using Bayesian inferential framework with a sliding window of 7-14 days. We used regression models to identify the factors of temporal changes in serial intervals and quantify their respective impacts. Finally, we assessed the biases in estimating transmissibility using constant over time-varying serial interval distributions.

Findings: 2497 transmission pairs were identified for the ancestral strain of SARS-CoV-2 during the first two years of the COVID-19 pandemic in Hong Kong. We found clear temporal changes in mean serial interval estimates within each epidemic wave studied and across waves, with mean serial intervals ranged from 5.5 days (95% CrI: 4.4, 6.6) to 2.7 (95% CrI: 2.2, 3.2) days. The mean serial intervals shortened or lengthened over time, which were found to be closely associated with the temporal variation in COVID-19 case profiles and public health and social measures and could lead to the biases in predicting Rt.

Interpretation: Accounting for the impact of these factors, the time-varying quantification of serial interval distributions could lead to improved estimation of Rt, and provide additional insights into the impact of public health measures on transmission.

Funding Information: This study was supported by the Health and Medical Research Fund (project no. 20190712); the Collaborative Research Fund of the Research Grants Council of the Hong Kong Special Administrative Region, China (project No. C7123-20G); AIR@InnoHK administered by Innovation and Technology Commission, European Research Council (grant no. 804744); the Grand Challenges ICODA pilot initiative, delivered by Health Data Research UK and funded by the Bill & Melinda Gates Foundation and the Minderoo Foundation.

Declaration of Interests: BJC received honoraria from AstraZeneca, Fosun Pharma, GSK, Moderna, Pfizer, Roche, and Sanofi. The authors report no other potential conflicts of interest.

Suggested Citation

Ali, Sheikh Taslim and Chen, Dongxuan and Lim, Wey Wen and Yeung, Amy and Adam, Dillon C. and Lau, Yiu Chung and Lau, Eric H.Y. and Wong, Jessica Y. and Xiao, Jingyi and Ho, Faith and Gao, Huizhi and Wang, Lin and Xu, Xiao-Ke and Du, Zhanwei and Wu, Peng and Leung, Gabriel and Cowling, Benjamin J., Insights into COVID-19 Epidemiology and Control from Temporal Changes in Serial Interval Distributions in Hong Kong. Available at SSRN: https://ssrn.com/abstract=4237731 or http://dx.doi.org/10.2139/ssrn.4237731

Sheikh Taslim Ali

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Dongxuan Chen

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Wey Wen Lim

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Amy Yeung

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Dillon C. Adam

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Yiu Chung Lau

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Eric H.Y. Lau

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Jessica Y. Wong

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Jingyi Xiao

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Faith Ho

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Huizhi Gao

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Lin Wang

University of Cambridge - Department of Genetics ( email )

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Xiao-Ke Xu

Dalian Minzu University - College of Information and Communication Engineering ( email )

Dalian, 116600
China

Zhanwei Du

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Peng Wu

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Hong Kong
China

Gabriel Leung

The University of Hong Kong - School of Public Health ( email )

Benjamin J. Cowling (Contact Author)

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

7 Sassoon Road
Hong Kong
China
+852 3917 6711 (Phone)