PONE-D-22-26738Epidemic efficacy of Covid-19 vaccination against Omicron: An Innovative Approach using Enhanced Residual Recurrent Neural NetworkPLOS ONE

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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5. Review Comments to the Author

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Reviewer #1: The manuscript entitled “Epidemic efficacy of Covid-19 vaccination against Omicron: An Innovative Approach using Enhanced Residual Recurrent Neural Network” presents an enhanced version of Residual Neural Network using Gated Recurrent Unit (GRU) and LSTM units to train a reliable model for predicting the spread of Coronavirus.

Considering the great effort done by the authors, there are some issues as follows:

1) The structure of the of introduction can be improved. It is suggested to remove subsections of section 1 for an integrated text. The aim of the paper has been stated before section 1.1, and again, in section 1.2 and 1.3.

2) Please check the journal guidelines whether the first letter of the authors’ names should be written in the citations within text, or not. A modification maybe required.

3) The Comparison and reliability related results cab be extended. More accurate and competing methods should be further utilized in the result comparison. The prediction of basic ResRNN is more accurate than AR, GR, VAR. So, using these methods for comparison is not wise.

4) Identify the names of the axis in Fig.4.

5) The models can also be compared using the Mean Squared Errors.

6) Its better to present the prediction results (such as Fig. 6) considering the competitive results of the other methods.

7) It is suggested to add the pseudo code of the proposed method.

Considering the mentioned comments, the paper is required a major revision.

Reviewer #2: Thanks for the submission,

The language needs proofreading and please provide a proof if you already done this.

In 1.1 how would you proof that other previous works are limited? Could you name any research?

In 1.3 what do you mean by contribution? change the title or give more clear details please.

Have you reviewed any previous literature regarding omicron against Covid-19 vaccination? I could not find any. Please name some or highlight them for me.

There is not any table containing the dataset and your description about the columns and rows you used in your research.

The discussion part is too short.

May we have any future work regarding omicron? what would you do in the future about it?

Kind Regards

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Reviewer #1: Yes: Salar Farahmand-Tabar

Reviewer #2: Yes: Askandar H. Amin

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Epidemic efficacy of Covid-19 vaccination against Omicron: An Innovative Approach using Enhanced Residual Recurrent Neural Network

PONE-D-22-26738R1

Dear Dr. Gupta,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Tarik A. Rashid, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Make sure to cite all the equations that are not yours.

The quality of the figures need to be improved.

Reviewers' comments: