Preprint Short Note Version 1 Preserved in Portico This version is not peer-reviewed

A Statistical Analysis on Recovery Cases of Covid19 in India

Version 1 : Received: 8 November 2020 / Approved: 9 November 2020 / Online: 9 November 2020 (16:15:21 CET)

How to cite: DATTA, J. A Statistical Analysis on Recovery Cases of Covid19 in India. Preprints 2020, 2020110284 (doi: 10.20944/preprints202011.0284.v1). DATTA, J. A Statistical Analysis on Recovery Cases of Covid19 in India. Preprints 2020, 2020110284 (doi: 10.20944/preprints202011.0284.v1).

Abstract

In this report the positive cases of Covid19 in India with effect from 7th September ,2020 to 25th October ,2020 are analysed for statistical relevance . The scattered data are used to find out a model equation correlating two variables number of recovered Covid –patient with an interval of regular seven days . The best fit regression analysis shows a significant correlation of Pearson coefficient (r) with standard error ( s ) with a probable lower mortality rate . Finally the limitations of this analysis is discussed herewith .

Subject Areas

Covid19; Best fit regression; Hyperbolic fit; Recovery rate; Reproducibity of research

Comments (2)

Comment 1
Received: 10 November 2020
Commenter: JAYDIP DATTA (Click to see Publons profile: )
The commenter has declared there is no conflict of interests.
Comment: In this article the Statistical relevance of Covid19 recovery cases in Indian scienario has been discussed . The reproducibility of Covid19 recovery is to be correlated to rapid mutation rate of Covid19 .
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Response 1 to Comment 1
Received: 11 November 2020
Commenter: JAYDIP DATTA (Click to see Publons profile: )
The commenter has declared there is no conflict of interests.
Comment: The Recovery Phase is also related to the most efficiant antiviral administration of Remdesiviral . The pharmacokinetic activity can also be correlated to Molecular bonding approach of drug-design . A better designing of the drug also enhances the recovery frequency of SARS-COV-2 pateints makes the best fit regression more relevant .

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