Analysis of the Second COVID-19 Wave in India Using a Birth-Death Model
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Abstract
India is witnessing the second wave of the COVID-19 disease from the first half of February 2021. The method in [5] is applied here to analyze the second wave in India. We start with fitting a birth-death model to the active and total cases data for the period from 13 th to 28 th February 2021. This initial dataset is expanded step by step by adding the two future week’s data to it until 14 th May 2021. This resulted in six models in total. The efficacy of each model is tested in terms of predictions made for the next two weeks. The infectivity rates are found to be ever-increasing in the case of the five initial models. The infectivity rate for the sixth model, which is based on the data from 13 th February to 14 th May 2021, shows a decreasing nature with an increase in time. This indicates a decline in the second wave, which may start from 4 th June 2021 according to the fitted parameters.
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SciScore for 10.1101/2021.05.19.21257447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Fitting was done using the nlinfit function available in the MATLAB R2019b [6] software. MATLABsuggested: (MATLAB, RRID:SCR_001622)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 …
SciScore for 10.1101/2021.05.19.21257447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Fitting was done using the nlinfit function available in the MATLAB R2019b [6] software. MATLABsuggested: (MATLAB, RRID:SCR_001622)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.
Results from scite Reference Check: We found no unreliable references.
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