Modelling, Simulations and Analysis of the First and Second COVID-19 Epidemics in Beijing
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Background
In December 2019, a novel coronavirus-induced pneumonia (COVID-19) broke out in Wuhan, China. On 19 January and on 8 June 2020, there were two wave COVID-19 epidemics happened in Beijing. Modelling, simulations and analysis for the two wave epidemics are important issues.
Methods
This study introduces a symptomatic-asymptomatic-recoverer-death differential equation model (SARDDE). It presents the conditions of the asymptotical stability on the disease-free equilibrium of the SARDDE. It proposes the necessary conditions of disease spreading for the SARDDE. Based on the reported data of the first and the second COVID-19 epidemics in Beijing and numerical simulations, it determines the parameters of the SARDDE, respectively.
Results
Numerical simulations of the SARDDE describe well the outcomes of the current symptomatic and asymptomatic individuals, the recovered symptomatic and asymptomatic individuals, and the died infected individuals, respectively. The numerical simulations obtain the following results.
-
The transmission rate of the symptomatic infections caused by the symptomatic individuals in the second Beijing epidemic is about two times higher than the one in the first Beijing epidemic.
-
Both the symptomatic and the asymptomatic individuals cause lesser asymptomatic spread than symptomatic spread.
-
The blocking rates of 89.32% and 97.48% (reaching the infection turning points) to the symptomatic infections cannot prevent the spreads of the first and the second COVID-19 epidemics in Beijing, respectively.
-
That on the day 28, the symptomatic infection blocking rates reached to 100% has made the second Beijing epidemics epidemic end on day 56.
-
That on the day 98, the symptomatic infection blocking rates reached to 100% has made the the first Beijing epidemics epidemic end on day 140.
-
Keeping the blocking rates, the recovery rates and the death rates reaching the infection turning points would make the numbers of current hospitalized infected individuals reach, on day 140, 208958 individuals and 25017 individuals for the two Beijing epidemics, respectively.
Conclusions
Virtual simulations suggest that the strict prevention and control strategies implemented by Beijing government are effective and necessary; using the data from the beginning to the days after about two weeks after the turning points can estimate well and approximately the following outcomes of the two COVID-19 epidemics, respectively. To avoid multiple epidemic outbreaks, a recommendation is that the authorities need to have maintained the prevention and control measures implemented, at least, 7 days after reaching the turning point until new current infection cases disappear. It is expected that the research can provide better understanding, explaining, and dominating for epidemic spreads, prevention and control measures.
Article activity feed
-
SciScore for 10.1101/2021.07.04.21259205: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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:…
SciScore for 10.1101/2021.07.04.21259205: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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.
Results from scite Reference Check: We found no unreliable references.
-