Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study.


Journal

The Lancet. Infectious diseases
ISSN: 1474-4457
Titre abrégé: Lancet Infect Dis
Pays: United States
ID NLM: 101130150

Informations de publication

Date de publication:
10 2020
Historique:
received: 16 04 2020
revised: 22 05 2020
accepted: 26 05 2020
pubmed: 21 6 2020
medline: 21 10 2020
entrez: 21 6 2020
Statut: ppublish

Résumé

As of June 8, 2020, the global reported number of COVID-19 cases had reached more than 7 million with over 400 000 deaths. The household transmissibility of the causative pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains unclear. We aimed to estimate the secondary attack rate of SARS-CoV-2 among household and non-household close contacts in Guangzhou, China, using a statistical transmission model. In this retrospective cohort study, we used a comprehensive contact tracing dataset from the Guangzhou Center for Disease Control and Prevention to estimate the secondary attack rate of COVID-19 (defined as the probability that an infected individual will transmit the disease to a susceptible individual) among household and non-household contacts, using a statistical transmission model. We considered two alternative definitions of household contacts in the analysis: individuals who were either family members or close relatives, such as parents and parents-in-law, regardless of residential address, and individuals living at the same address regardless of relationship. We assessed the demographic determinants of transmissibility and the infectivity of COVID-19 cases during their incubation period. Between Jan 7, 2020, and Feb 18, 2020, we traced 195 unrelated close contact groups (215 primary cases, 134 secondary or tertiary cases, and 1964 uninfected close contacts). By identifying households from these groups, assuming a mean incubation period of 5 days, a maximum infectious period of 13 days, and no case isolation, the estimated secondary attack rate among household contacts was 12·4% (95% CI 9·8-15·4) when household contacts were defined on the basis of close relatives and 17·1% (13·3-21·8) when household contacts were defined on the basis of residential address. Compared with the oldest age group (≥60 years), the risk of household infection was lower in the youngest age group (<20 years; odds ratio [OR] 0·23 [95% CI 0·11-0·46]) and among adults aged 20-59 years (OR 0·64 [95% CI 0·43-0·97]). Our results suggest greater infectivity during the incubation period than during the symptomatic period, although differences were not statistically significant (OR 0·61 [95% CI 0·27-1·38]). The estimated local reproductive number (R) based on observed contact frequencies of primary cases was 0·5 (95% CI 0·41-0·62) in Guangzhou. The projected local R, had there been no isolation of cases or quarantine of their contacts, was 0·6 (95% CI 0·49-0·74) when household was defined on the basis of close relatives. SARS-CoV-2 is more transmissible in households than SARS-CoV and Middle East respiratory syndrome coronavirus. Older individuals (aged ≥60 years) are the most susceptible to household transmission of SARS-CoV-2. In addition to case finding and isolation, timely tracing and quarantine of close contacts should be implemented to prevent onward transmission during the viral incubation period. US National Institutes of Health, Science and Technology Plan Project of Guangzhou, Project for Key Medicine Discipline Construction of Guangzhou Municipality, Key Research and Development Program of China.

Sections du résumé

BACKGROUND
As of June 8, 2020, the global reported number of COVID-19 cases had reached more than 7 million with over 400 000 deaths. The household transmissibility of the causative pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains unclear. We aimed to estimate the secondary attack rate of SARS-CoV-2 among household and non-household close contacts in Guangzhou, China, using a statistical transmission model.
METHODS
In this retrospective cohort study, we used a comprehensive contact tracing dataset from the Guangzhou Center for Disease Control and Prevention to estimate the secondary attack rate of COVID-19 (defined as the probability that an infected individual will transmit the disease to a susceptible individual) among household and non-household contacts, using a statistical transmission model. We considered two alternative definitions of household contacts in the analysis: individuals who were either family members or close relatives, such as parents and parents-in-law, regardless of residential address, and individuals living at the same address regardless of relationship. We assessed the demographic determinants of transmissibility and the infectivity of COVID-19 cases during their incubation period.
FINDINGS
Between Jan 7, 2020, and Feb 18, 2020, we traced 195 unrelated close contact groups (215 primary cases, 134 secondary or tertiary cases, and 1964 uninfected close contacts). By identifying households from these groups, assuming a mean incubation period of 5 days, a maximum infectious period of 13 days, and no case isolation, the estimated secondary attack rate among household contacts was 12·4% (95% CI 9·8-15·4) when household contacts were defined on the basis of close relatives and 17·1% (13·3-21·8) when household contacts were defined on the basis of residential address. Compared with the oldest age group (≥60 years), the risk of household infection was lower in the youngest age group (<20 years; odds ratio [OR] 0·23 [95% CI 0·11-0·46]) and among adults aged 20-59 years (OR 0·64 [95% CI 0·43-0·97]). Our results suggest greater infectivity during the incubation period than during the symptomatic period, although differences were not statistically significant (OR 0·61 [95% CI 0·27-1·38]). The estimated local reproductive number (R) based on observed contact frequencies of primary cases was 0·5 (95% CI 0·41-0·62) in Guangzhou. The projected local R, had there been no isolation of cases or quarantine of their contacts, was 0·6 (95% CI 0·49-0·74) when household was defined on the basis of close relatives.
INTERPRETATION
SARS-CoV-2 is more transmissible in households than SARS-CoV and Middle East respiratory syndrome coronavirus. Older individuals (aged ≥60 years) are the most susceptible to household transmission of SARS-CoV-2. In addition to case finding and isolation, timely tracing and quarantine of close contacts should be implemented to prevent onward transmission during the viral incubation period.
FUNDING
US National Institutes of Health, Science and Technology Plan Project of Guangzhou, Project for Key Medicine Discipline Construction of Guangzhou Municipality, Key Research and Development Program of China.

Identifiants

pubmed: 32562601
pii: S1473-3099(20)30471-0
doi: 10.1016/S1473-3099(20)30471-0
pmc: PMC7529929
mid: NIHMS1606620
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1141-1150

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI116770
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI139761
Pays : United States
Organisme : NIAID NIH HHS
ID : R37 AI032042
Pays : United States

Commentaires et corrections

Type : UpdateOf
Type : CommentIn

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

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Auteurs

Qin-Long Jing (QL)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Ming-Jin Liu (MJ)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.

Zhou-Bin Zhang (ZB)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Li-Qun Fang (LQ)

State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.

Jun Yuan (J)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

An-Ran Zhang (AR)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA; State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China; Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.

Natalie E Dean (NE)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.

Lei Luo (L)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Meng-Meng Ma (MM)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Ira Longini (I)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.

Eben Kenah (E)

Division of Biostatistics, College of Public Health, Ohio State University, Columbus, OH, USA.

Ying Lu (Y)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Yu Ma (Y)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China.

Neda Jalali (N)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.

Zhi-Cong Yang (ZC)

Guangzhou Center for Disease Control and Prevention, Guangzhou, China. Electronic address: yangzc@gzcdc.org.cn.

Yang Yang (Y)

Department of Biostatistics, College of Public Health and Health Professions, Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA. Electronic address: yangyang@ufl.edu.

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