Spread of COVID-19 in India: A Simple Algebraic Study
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Abstract
The number of patients, infected with COVID-19, began to increase very rapidly in India from March 2020. The country was put under lockdown from 25 March 2020. The present study is aimed at providing a simple algebraic analysis of the trend that is evident in the spread of the disease in this part of the world. The purpose of this algebraic approach is to simplify the calculation sufficiently by deviating from the standard techniques that are conventionally used to construct mathematical models of epidemics. The predictions, obtained from this algebraic study, are found to be in reasonable agreement with the recorded data. Using this mathematical formulation we have determined the time variation of the number of asymptomatic patients, who are believed to play a major role in spreading the disease. We have discussed the effect of lockdown in reducing the rate of transmission of the disease. On the basis of the proposed models, predictions have been made regarding the possible trend of the rise in the number of cases beyond the withdrawal of lockdown. All these things have been calculated by using very simple mathematical expressions which can be easily understood and used by those who have a rudimentary knowledge of algebra.
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SciScore for 10.1101/2020.05.10.20097691: (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 10.1101/2020.05.10.20097691: (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.
- 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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