Report on COVID-19 Verification Case Study in Nine Countries Using the SIQR model
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Abstract
This report uses the SIQR model proposed by Takashi Odagaki to examine the epidemic trend of COVID-19 in nine major countries during February-May 2020, and to clarify the peculiar trend of infection in Japan. The SIQR model, which is an improvement on the conventional SIR model, is unique in that it allows us to theoretically clarify the epidemic phenomenon by separating the number of daily confirmed new cases by testing and the number of infecteds at large who remain untested, and also allows us to theoretically consider measures to control the epidemic. The infection control measures of each country were analyzed by dividing them into three groups according to the size of the decay (or growth) rate of infected at large (λ). The active group includes China and South Korea, the passive group includes the United States and Sweden, and the average group includes Germany, Italy, France, Spain, and Japan. China and South Korea are the countries with the best testing and quarantine systems, and South Korea in particular having managed to contain the infection without lockdown through early quarantine by thorough testing. On the other hand, the United States and Sweden do not have a well-developed inspection and quarantine system and have shown little restraint in social distancing. In the case of Japan, the following special factors may have contributed to the extreme lack of PCR testing : (1) The “4-day fever rule” established by the Ministry of Health, Labour and Welfare was strictly enforced. (2) Even after the decision to postpone the Olympics, the government continued to monopolize PCR testing for the sake of unified analysis of infection data, and the policy of expanding PCR testing by private companies was not implemented.
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SciScore for 10.1101/2020.10.07.20208298: (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: 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…
SciScore for 10.1101/2020.10.07.20208298: (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: 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.
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