Epidemiologic Characteristics of COVID-19 in Guizhou Province, China

  1. Kaike Ping
  2. Mingyu Lei
  3. Yun Gou
  4. Zhongfa Tao
  5. Guanghai Yao
  6. Can Hu
  7. Qin Tao
  8. Zhiting Zou
  9. Dingming Wang
  10. Shijun Li
  11. Yan Huang

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Introduction: At the end of 2019, the COVID-19 broke out, and spread to Guizhou province in January of 2020. Methodology: To acquire the epidemiologic characteristics of COVID-19 in Guizhou province, we collected data from 169 laboratory-confirmed COVID-19 related cases. We described the demographic characteristics of the cases and estimated the incubation period, serial interval and the effective reproduction number. We also presented two representative case studies in Guizhou province: Case Study 1 was an example of the asymptomatic carrier; while Case Study 2 was an example of a large and complex infection chain that involved four different regions, spanning three provinces and eight families. Results: Two peaks in the incidence distribution associated with COVID-19 in Guizhou province were related to the 6.04 days (95% CI: 5.00 – 7.10) of incubation period and 6.14±2.21 days of serial interval. We also discussed the effectiveness of the control measures based on the instantaneous effective reproduction number that was a constantly declining curve. Conclusions: As of February 2, 2020, the estimated effective reproduction number was below 1, and no new cases were reported since February 26. These showed that Guizhou Province had achieved significant progress in preventing the spread of the epidemic. The medical isolation of close contacts was consequential. Meanwhile, the asymptomatic carriers and the super-spreaders must be isolated in time, who would cause a widespread infection.

Article activity feed

  1. Version published to 10.3855/jidc.12818
  2. ScreenIT

    SciScore for 10.1101/2020.03.01.20028944: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: It is part of a continuing public health outbreak investigation and exempted from institutional review board assessment.
    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:
    Measures such as community screening, isolation of close contacts, public transportation limitation, extended population of PCR testing, enhanced disinfection, and health education etc. could be taken. Our findings provide more epidemiologic data to this incident of COVID-19, which contribute to the further analysis and the control of this disease. In addition to the evidence of the human-to-human transmission, it is likely that there exists infectiousness to some extend during the incubation period, and the presence of “super-spreaders”. The median incubation period was 8.2 days (95% CI: 7.9 – 9.5) in our study, which is longer than a recent report of 425 patients (8.2 days vs. 5.2 days), this may be a results of recall bias, during epidemiological investigation, we found that some cases actually have had shown mild symptoms days before the date they reported so as to their ignorance. We estimated the R0 as 1.09 (95% CI: 1.9 – 1.2), which means each patient can infect other 1.09 people on average. In commonly used infection models, when R0 > 1 the infection will be able to start spreading in a population, but not if R0 < 1. However, it should be treated with caution that the basic reproduction number R0 was calculated under the assumptions that an infected individual but has no symptoms does not yet infect others, which assumes that all index cases should show symptoms before their secondary cases. However, as the investigation went on, Guizhou CDC found that there existed i...

    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.

  3. Version published to 10.1101/2020.03.01.20028944 on medRxiv