Case Fatality Risk of the First Pandemic Wave of Coronavirus Disease 2019 (COVID-19) in China

  1. Xiaowei Deng
  2. Juan Yang
  3. Wei Wang
  4. Xiling Wang
  5. Jiaxin Zhou
  6. Zhiyuan Chen
  7. Jing Li
  8. Yinzi Chen
  9. Han Yan
  10. Juanjuan Zhang
  11. Yongli Zhang
  12. Yan Wang
  13. Qi Qiu
  14. Hui Gong
  15. Xianglin Wei
  16. Lili Wang
  17. Kaiyuan Sun
  18. Peng Wu
  19. Marco Ajelli
  20. Benjamin J Cowling
  21. Cecile Viboud
  22. Hongjie Yu

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Abstract

Background

To assess the case fatality risk (CFR) of COVID-19 in mainland China, stratified by region and clinical category, and estimate key time-to-event intervals.

Methods

We collected individual information and aggregated data on COVID-19 cases from publicly available official sources from 29 December 2019 to 17 April 2020. We accounted for right-censoring to estimate the CFR and explored the risk factors for mortality. We fitted Weibull, gamma, and log-normal distributions to time-to-event data using maximum-likelihood estimation.

Results

We analyzed 82 719 laboratory-confirmed cases reported in mainland China, including 4632 deaths and 77 029 discharges. The estimated CFR was 5.65% (95% confidence interval [CI], 5.50–5.81%) nationally, with the highest estimate in Wuhan (7.71%) and lowest in provinces outside Hubei (0.86%). The fatality risk among critical patients was 3.6 times that of all patients and 0.8–10.3-fold higher than that of mild-to-severe patients. Older age (odds ratio [OR], 1.14 per year; 95% CI, 1.11–1.16) and being male (OR, 1.83; 95% CI, 1.10–3.04) were risk factors for mortality. The times from symptom onset to first healthcare consultation, to laboratory confirmation, and to hospitalization were consistently longer for deceased patients than for those who recovered.

Conclusions

Our CFR estimates based on laboratory-confirmed cases ascertained in mainland China suggest that COVID-19 is more severe than the 2009 H1N1 influenza pandemic in hospitalized patients, particularly in Wuhan. Our study provides a comprehensive picture of the severity of the first wave of the pandemic in China. Our estimates can help inform models and the global response to COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.04.20031005: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics: The study was approved by the Institutional review board from School of Public Health, Fudan University (IRB#2020-02-0802).
    RandomizationThey were randomly selected as discharge or death according to probability calculated using the density of interval from hospital admission to discharge/death.
    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 limitations. First, in the individual dataset, the clinical profile of patients was not available. Hence, we could not provide direct estimates of fatality risk stratified by clinical categories using survival analysis. Instead, we divided the estimated CFR among all cases by the proportions of different clinical categories obtained from the aggregated dataset. This is a reasonable approach method because all deaths occurred among critical cases 5. Second, the analyzed individual records were retrieved from publicly available official sources, ensuring accuracy and reliability of information. However, we were only able to collect few individual records in Hubei because they did not release complete individual information. And thus, we were unable to estimate CFR in Hubei using survival analyses. Moreover, assessment of clinical severity in Hubei, especially in the epicenter of the outbreak in Wuhan, is challenging because disease severity may be increased by bottlenecks in local healthcare capacity, as COVID-19 cases surged. In addition, case surveillance and clinical management were biased towards severe cases in Hubei, especially in the early phase of the epidemic. Our estimates of the CFR in Hubei and Wuhan using Garske’s method11 should be viewed cautiously as the sensitivity of surveillance of both deaths and cases remains unclear. Our study only addresses CFR among detected cases. The level of ascertainment of mild cases remains unclear. More estimate...

    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 10.1093/cid/ciaa578
  3. Version published to 10.1101/2020.03.04.20031005 on medRxiv