Dynamic Analysis of Social Distancing Ratio, Isolation Rate and Transmission Coefficient in COVID-19 Epidemic for Many Countries by SIQR Model
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Abstract
Recently SIQR model was proposed by Odagaki as the modification of conventional SIR model by adding the term for isolation of infected persons, Q(Quarantined). The exponent λ of the exponential function expressing the number of newly tested positive persons was defined as an linear equation explicitly with three important parameters, transmission coefficient, social distancing ratio x and isolation rate q. In this study, applying this model to the number of positive persons in publicly available database, daily λ values are regression analyzed, and social distancing ratio and isolation rate are derived. Analyses for 7 countries including Japan, Taiwan, South Korea, and western countries are performed and determine the dynamic locus of q-x relation on the q-x plane during epidemic propagation. Finally, the remaining parameter, the transmission coefficient is shown to closely relate to the maximum λ, λ max , and λ max (transmission coefficient) is characterized as a specific value for each country. Then, the magnitude of λ max is combined with the value of λ min to influence the total number of new cases until the convergence stage.
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SciScore for 10.1101/2020.08.04.20167882: (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
Software and Algorithms Sentences Resources Data analysis of the number of new cases: For the analysis, the number of new cases in more than 200 countries in the “Our World in Data” database4) (data coverage from 1st of Jan. 2020 to 11th of July) were used. Data”suggested: NoneResults 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 Tri…
SciScore for 10.1101/2020.08.04.20167882: (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
Software and Algorithms Sentences Resources Data analysis of the number of new cases: For the analysis, the number of new cases in more than 200 countries in the “Our World in Data” database4) (data coverage from 1st of Jan. 2020 to 11th of July) were used. Data”suggested: NoneResults 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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