Epidemiological and Clinical Characteristics of Coronavirus Disease 2019 in Shenzhen, the Largest Migrant City of China

  1. Ying Wen
  2. Lan Wei
  3. Yuan Li
  4. Xiujuan Tang
  5. Shuo Feng
  6. Kathy Leung
  7. Xiaoliang Wu
  8. Xiong-Fei Pan
  9. Cong Chen
  10. Junjie Xia
  11. Xuan Zou
  12. Tiejian Feng
  13. Shujiang Mei

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Abstract

We conducted a retrospective study among 417 confirmed COVID-19 cases from Jan 1 to Feb 28, 2020 in Shenzhen, the largest migrant city of China, to identify the epidemiological and clinical features in settings of high population mobility. We estimated the median incubation time to be 5.0 days. 342 (82.0%) cases were imported, 161 (38.6%) cases were identified by surveillance, and 247 (59.2%) cases were reported from cluster events. The main symptoms on admission were fever and dry cough. Most patients (91.4%) had mild or moderate illnesses. Age of 50 years or older, breathing problems, diarrhea, and longer time between the first medical visit and admission were associated with higher level of clinical severity. Surveillance-identified cases were much less likely to progress to severe illness. Although the COVID-19 epidemic has been contained in Shenzhen, close monitoring and risk assessments are imperative for prevention and control of COVID-19 in future.

Article Summary Line

We characterized epidemiological and clinical features of a large population-based sample of COVID-19 cases in the largest migrant city of China, and our findings could provide knowledge of SARS-CoV-2 transmission in the context of comprehensive containment and mitigation efforts in similar settings.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.22.20035246: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Data collection in the epidemiological investigation was part of the continuing public health investigation of an emerging outbreak and therefore the individual informed consent was waived.
    IRB: The study was approved by the ethics committees of Shenzhen Center for Disease Control and Prevention.
    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:
    Although our study had major strengths such as population-wide case identification in a major migrant city, a large sample size, and complete profiling of epidemics along the timeline of population interventions, there were several limitations that should be acknowledged. First, since some patients were still under treatment so far, we could not yet report the complete data of the disease progression on severity or assess predictors of clinical outcomes. Second, important information, such as timelines of possible exposure, illness onset, and medical visits, was self-reported in the epidemiological investigations, which might be subject to recall bias. Third, we did not have enough information on comorbid conditions,laboratory testing, and radiological examination, which restricted the scope of our analyses. Thus, more detailed clinical characteristics related to COVID-19 could facilitate further analyses in future studies. In conclusion, our study indicated there was limited local transmission of SARS-CoV-2 in the presence of intensive interventions in Shenzhen, where imported cases accounted for the majority of the confirmed cases. A substantial proportion of the cases were surveillance-identified with less severe illness. Although the intensive and comprehensive measures and interventions have effectively contained the epidemic in Shenzhen, there is still high risk of rebound of COVID-19 cases due to the return of migrants for work, reopening of schools, removal of restric...

    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 10.1101/2020.03.22.20035246v1 on medRxiv