Transmission dynamics and control measures of COVID-19 outbreak in China: a modelling study

  1. Xu-Sheng Zhang
  2. Emilia Vynnycky
  3. Andre Charlett
  4. Daniela De Angelis
  5. Zhengji Chen
  6. Wei Liu

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Abstract

COVID-19 is reported to have been brought under control in China. To understand the COVID-19 outbreak in China and provide potential lessons for other parts of the world, in this study we apply a mathematical model with multiple datasets to estimate the transmissibility of the SARS-CoV-2 virus and the severity of the illness associated with the infection, and how both were affected by unprecedented control measures. Our analyses show that before 19th January 2020, 3.5% (95% CI 1.7–8.3%) of  infected people were detected; this percentage increased to 36.6% (95% CI 26.1–55.4%) thereafter. The basic reproduction number ( R 0 ) was 2.33 (95% CI 1.96–3.69) before 8th February 2020; then the effective reproduction number dropped to 0.04(95% CI 0.01–0.10). This estimation also indicates that control measures taken since 23rd January 2020 affected the transmissibility about 2 weeks after they were introduced. The confirmed case fatality rate is estimated at 9.6% (95% CI 8.1–11.4%) before 15 February 2020, and then it reduced to 0.7% (95% CI 0.4–1.0%). This shows that SARS-CoV-2 virus is highly transmissible but may be less severe than SARS-CoV-1 and MERS-CoV. We found that at the early stage, the majority of R 0 comes from undetected infectious people. This implies that successful control in China was achieved through reducing the contact rates among people in the general population and increasing the rate of detection and quarantine of the infectious cases.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.09.20150086: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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:
    This study also has several limitations. To model complicated processes of transmission dynamics and disease reporting, Synthesis model has been simplified in several aspects. To reflect the temporal change in both ascertainment rate and transmissibility of COVID-19, two different values are assumed for each of them. The change in ascertainment rate and transmissibility may gradually take place during the outbreak as do the public awareness and interventions3. For example, Tsang et al11 found the ascertainment rate changed as the case definition for COVID-19 changed from initially narrow to gradually wider during the period from 15th January to 3rd March. In the current study, we assume the confirmed case fatality rate (cCFR) remained unchanged during the outbreak in mainland China. It may reduce with time as medical conditions and clinical treatments improved. The time-to-event intervals such as the delay from symptom onset to death may also changes as epidemic grows21,23,25. Further, in this study we ignore the heterogeneity in both geography and age 3,7,12. To provide more specific and practically useful information for control measures, it needs to look at variation in regions3,7 and age groups12. A further limit is we model the overall effectiveness of integrated intervention measures rather than the different types of control measures and therefore cannot provide specific information for their relative impacts on stopping the spread of infection (c.f.2,3,15). In conclus...

    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.

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  2. Version published to 10.1038/s41598-021-81985-z
  3. Version published to 10.1101/2020.07.09.20150086v1 on medRxiv