Evidence map›Paper›PMID 32511590›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Household Secondary Attack Rate of COVID-19 and Associated Determinants.

Qin-Long Jing, Ming-Jin Liu, Jun Yuan, Zhou-Bin Zhang, An-Ran Zhang, Natalie E Dean, Lei Luo, Mengmeng Ma, Ira Longini, Eben Kenah and 6 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 90 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 2 countries.

Qin-Long JingGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Ming-Jin LiuDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Jun YuanGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Zhou-Bin ZhangGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
An-Ran ZhangDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Natalie E DeanDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Lei LuoGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Mengmeng MaGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Ira LonginiDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Eben KenahDepartment of Biostatistics, School of Public Health, Ohio State University, Columbus, U. S. A.
Ying LuGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Yu MaGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Neda JalaliDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Zhi-Cong YangGuangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China.
Yang YangDepartment of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A.
Guangzhou Center for Disease Control and Prevention · CNUniversity of Florida Health · USInstitute of Microbiology · CNShandong University · CNThe Ohio State University · US

Funding

Design and Analysis of Vaccine Trials for Emerging Infectious Disease ThreatsR01AI139761 · NIAID · UNIVERSITY OF FLORIDA · PI DEAN, NATALIE EXNER · 2018 to 2022
$3.6M
Regression, Phylogenetics, and Study Design in Infectious Disease EpidemiologyR01AI116770 · NIAID · UNIVERSITY OF FLORIDA · PI KENAH, EBEN · 2016 to 2020
$1.8M
NIAID NIH HHS R01 AI116770NIAID NIH HHS R01 AI139761
6 · The paper itself

Abstract

backgroundAs of April 2, 2020, the global reported number of COVID-19 cases has crossed over 1 million with more than 55,000 deaths. The household transmissibility of SARS-CoV-2, the causative pathogen, remains elusive.

methodsBased on a comprehensive contact-tracing dataset from Guangzhou, we estimated both the population-level effective reproductive number and individual-level secondary attack rate (SAR) in the household setting. We assessed age effects on transmissibility and the infectivity of COVID-19 cases during their incubation period.

resultsA total of 195 unrelated clusters with 212 primary cases, 137 nonprimary (secondary or tertiary) cases and 1938 uninfected close contacts were traced. We estimated the household SAR to be 13.8% (95% CI: 11.1-17.0%) if household contacts are defined as all close relatives and 19.3% (95% CI: 15.5-23.9%) if household contacts only include those at the same residential address as the cases, assuming a mean incubation period of 4 days and a maximum infectious period of 13 days. The odds of infection among children (<20 years old) was only 0.26 (95% CI: 0.13-0.54) times of that among the elderly (≥60 years old). There was no gender difference in the risk of infection. COVID-19 cases were at least as infectious during their incubation period as during their illness. On average, a COVID-19 case infected 0.48 (95% CI: 0.39-0.58) close contacts. Had isolation not been implemented, this number increases to 0.62 (95% CI: 0.51-0.75). The effective reproductive number in Guangzhou dropped from above 1 to below 0.5 in about 1 week.

conclusionSARS-CoV-2 is more transmissible in households than SARS-CoV and MERS-CoV, and the elderly ≥60 years old are the most vulnerable to household transmission. Case finding and isolation alone may be inadequate to contain the pandemic and need to be used in conjunction with heightened restriction of human movement as implemented in Guangzhou.

Identifiers

PMID32511590
PMCPMC7276017
OpenAlexW3017157467

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.