Contact Settings and Risk for Transmission in 3410 Close Contacts of Patients With COVID-19 in Guangzhou, China

  1. Lei Luo
  2. Dan Liu
  3. Xinlong Liao
  4. Xianbo Wu
  5. Qinlong Jing
  6. Jiazhen Zheng
  7. Fanghua Liu
  8. Shigui Yang
  9. Hua Bi
  10. Zhihao Li
  11. Jianping Liu
  12. Weiqi Song
  13. Wei Zhu
  14. Zhenghe Wang
  15. Xiru Zhang
  16. Qingmei Huang
  17. Peiliang Chen
  18. Huamin Liu
  19. Xin Cheng
  20. Miaochun Cai
  21. Pei Yang
  22. Xingfen Yang
  23. Zhigang Han
  24. Jinling Tang
  25. Yu Ma
  26. Chen Mao

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.24.20042606: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has some notable limitations. Firstly, we have not the data to show the prognosis of disease. Because many patients remained in the hospital and the outcomes were unknown at the time of data cutoff, we censored the data regarding their clinical outcomes and thus entire course of the disease cannot be fully demonstrated. Secondly, we used logistic regression analysis instead of cox proportional hazards model, because of the low incidence (2.6%) of COVID-19 among close contacts. In addition, by the end of the cohort, there were 245 close contacts remaining quarantines, but they were not likely to become COVID-19 cases, thus there was no censored data. Thirdly, there may be a recall bias of the symptoms at onset among source cases and secondary cases. In conclusion, our cohort study showed that the proportion of asymptomatic and mild infections account for almost half of the confirmed cases among close contacts. The household contacts were the main transmission mode, and clinically more severe cases were more likely to pass the infection to their close contacts. In general, the secondary cases were clinically milder than those of source cases. The results provide the evidentiary foundation for evaluating control measures, and guiding the global response.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.7326/m20-2671
  3. ScreenIT

    SciScore for 10.1101/2020.03.24.20042606: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementEthics Approval Ethics approval was obtained from the Ethics Committee of Southern Medical University.Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableResults Among 4950 closes contacts, the median age was 38.0 years, and males accounted for 50.2% (2484).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses were all performed with the SAS software (version 9.4 for Windows, SAS Institute, Inc., Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, SCR_008567)
    Morbidity and mortality weekly report 2020;69:312-3. 19. Kupferschmidt K, Cohen J.
    Cohen J
    suggested: (Lymphoma Research Foundation, SCR_004410)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.03.24.20042606v1 on medRxiv