Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in mainland China: Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection

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Abstract

Background

Knowledge on the epidemiological features and transmission patterns of COVID-19 is accumulating. Detailed line-list data with household settings can advance the understanding of COVID-19 transmission dynamics.

Methods

A unique database with detailed demographic characteristics, travel history, social relationships, and epidemiological timelines for 1,407 transmission pairs that formed 643 transmission clusters in mainland China was reconstructed from 9,120 COVID-19 confirmed cases reported during January 15 - February 29, 2020. Statistical model fittings were used to identify the super-spreaders and estimate serial interval distributions. Age and gender-stratified hazard of infection were estimated for household versus non-household transmissions.

Results

There were 34 primary cases identified as super-spreaders, with 5 super-spreading events occurred within households. Mean and standard deviation of serial intervals were estimated as 5.0 (95% CrI: 4.4, 5.5) and 5.2 (95% CrI: 4.9, 5.7) days for household transmissions and 5.2 (95% CrI: 4.6, 5.8) and 5.3 (95% CrI: 4.9, 5.7) days for non-household transmissions, respectively. Hazard of being infected outside of households is higher for age between 18 and 64 years, whereas hazard of being infected within households is higher for young and old people.

Conclusions

Non-negligible frequency of super-spreading events, short serial intervals, and a higher risk of being infected outside of households for male people of working age indicate a significant barrier to the identification and management of COVID-19 cases, which requires enhanced non-pharmaceutical interventions to mitigate this pandemic.

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Most cited references 4

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Hospital Outbreak of Middle East Respiratory Syndrome Coronavirus

Abdullah Assiri, Allison McGeer, Trish M. Perl … (2013)

In September 2012, the World Health Organization reported the first cases of pneumonia caused by the novel Middle East respiratory syndrome coronavirus (MERS-CoV). We describe a cluster of health care-acquired MERS-CoV infections. Medical records were reviewed for clinical and demographic information and determination of potential contacts and exposures. Case patients and contacts were interviewed. The incubation period and serial interval (the time between the successive onset of symptoms in a chain of transmission) were estimated. Viral RNA was sequenced. Between April 1 and May 23, 2013, a total of 23 cases of MERS-CoV infection were reported in the eastern province of Saudi Arabia. Symptoms included fever in 20 patients (87%), cough in 20 (87%), shortness of breath in 11 (48%), and gastrointestinal symptoms in 8 (35%); 20 patients (87%) presented with abnormal chest radiographs. As of June 12, a total of 15 patients (65%) had died, 6 (26%) had recovered, and 2 (9%) remained hospitalized. The median incubation period was 5.2 days (95% confidence interval [CI], 1.9 to 14.7), and the serial interval was 7.6 days (95% CI, 2.5 to 23.1). A total of 21 of the 23 cases were acquired by person-to-person transmission in hemodialysis units, intensive care units, or in-patient units in three different health care facilities. Sequencing data from four isolates revealed a single monophyletic clade. Among 217 household contacts and more than 200 health care worker contacts whom we identified, MERS-CoV infection developed in 5 family members (3 with laboratory-confirmed cases) and in 2 health care workers (both with laboratory-confirmed cases). Person-to-person transmission of MERS-CoV can occur in health care settings and may be associated with considerable morbidity. Surveillance and infection-control measures are critical to a global public health response.

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Superspreading and the effect of individual variation on disease emergence

J. O. Lloyd-Smith, S. J. Schreiber, P. E. Kopp … (2005)

Coughs and sneezes... From Typhoid Mary to SARS, it has long been known that some people spread disease more than others. But for diseases transmitted via casual contact, contagiousness arises from a plethora of social and physiological factors, so epidemiologists have tended to rely on population averages to assess a disease's potential to spread. A new analysis of outbreak data shows that individual differences in infectiousness exert powerful influences on the epidemiology of ten deadly diseases. SARS and measles (and perhaps avian influenza) show strong tendencies towards ‘superspreading events’ that can ignite explosive epidemics — but this same volatility makes outbreaks more likely to fizzle out. Smallpox and pneumonic plague, two potential bioterrorism agents, show steadier growth but still differ markedly from the traditional average-based view. These findings are relevant to how emerging diseases are detected and controlled. Supplementary information The online version of this article (doi:10.1038/nature04153) contains supplementary material, which is available to authorized users.

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Transmission dynamics and control of severe acute respiratory syndrome.

Marc Lipsitch, Ted Cohen, Ben Cooper … (2003)

Severe acute respiratory syndrome (SARS) is a recently described illness of humans that has spread widely over the past 6 months. With the use of detailed epidemiologic data from Singapore and epidemic curves from other settings, we estimated the reproductive number for SARS in the absence of interventions and in the presence of control efforts. We estimate that a single infectious case of SARS will infect about three secondary cases in a population that has not yet instituted control measures. Public-health efforts to reduce transmission are expected to have a substantial impact on reducing the size of the epidemic.

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Author and article information

Journal

Journal ID (nlm-ta): Clin Infect Dis

Journal ID (iso-abbrev): Clin. Infect. Dis

Journal ID (publisher-id): cid

Title: Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America

Publisher: Oxford University Press (US )

ISSN (Print): 1058-4838

ISSN (Electronic): 1537-6591

Publication date (Electronic): 18 June 2020

Electronic Location Identifier: ciaa790

Affiliations

[1 ] College of Information and Communication Engineering, Dalian Minzu University, Dalian, China

[2 ] Web Mining Lab, Department of Media and Communication, City University of Hong Kong, Hong Kong Special Administrative Region, China

[3 ] Computational Communication Research Center, Beijing Normal University, Zhuhai, China

[4 ] School of Journalism and Communication, Beijing Normal University, Beijing, China

[5 ] 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, China

[6 ] Department of Integrative Biology, University of Texas at Austin, Austin, Texas, USA

[7 ] Department of Genetics, University of Cambridge, Cambridge, UK

[8 ] Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, CNRS, Paris, France

Author notes

Corresponding author: Lin Wang ( lw660@ 123456cam.ac.uk ), Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, United Kingdom. Tel: +33 632115679

These authors contributed equally to this study.

Article

Publisher ID: ciaa790

DOI: 10.1093/cid/ciaa790

PMC ID: 7337632

PubMed ID: 32556265

SO-VID: 5d49603e-55c2-4f37-807f-0a76f9a1e1a7

License:

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

History

Date received : 15 April 2020

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article-lifecycle PAP

edited-state accepted-manuscript

ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: covid-19,transmission,super-spreading event,serial interval,hazard of infection

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ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: covid-19, transmission, super-spreading event, serial interval, hazard of infection

Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in mainland China: Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection

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Abstract

Background

Methods

Results

Conclusions

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 4

Hospital Outbreak of Middle East Respiratory Syndrome Coronavirus

Superspreading and the effect of individual variation on disease emergence

Transmission dynamics and control of severe acute respiratory syndrome.

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