Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Since December 1, 2019, the spread of COVID-19 is increasing every day. It is particularly important to predict the trend of the epidemic for the timely adjustment of the economy and industries. We proposed a Flow-SEHIR model in this paper to perform the trends of 2019-nCoV (COVID-19) in China.
The results show that the number of daily confirmed new cases reaches the inflection point on Feb. 6 – 10 outside Hubei. For the maximum of temporal infected cases number, the predicted peak value in China except Hubei was estimated to be 21721 (95% CI: 18764 - 24929). The peak arrival time is on March 3 - 9. The temporal number of patients in most areas of China outside Hubei will peak from March 12 to March 15. The peak values of more than 73.5% provinces or regions in China will be controlled within 1000. According to Flow-SEHIR model and estimations from the data of evacuation of nationals from Wuhan, the real peak cumulative number of patients in Hubei is estimated to be 403481 (95% CI: 143284 – 1166936).
Article activity feed
-
SciScore for 10.1101/2020.02.09.20021444: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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 …
SciScore for 10.1101/2020.02.09.20021444: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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.
- No funding statement was detected.
- No protocol registration statement was detected.
-
-
-
-
-