PONE-D-20-00374

Forecasting the monthly incidence rate of brucellosis in west of Iran using time series and data mining from 2010 to 2019

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Editor

Please find the comments below.

Bests,

Comments for the authors

The authors compared the performance of four machine learning methods in forecasting human brucellosis. Generally the subject is interesting and the manuscript is well written. In my concern, there are some minor issues with the manuscript as follows:

Are there other disease that could look like the case definition? How sensitive and specific to Brucellosis is that definition.

Do the patients have to have all of the signs at one time?

Do the authors mean random forest by “random accumulation”? Please correct them as random accumulation is not the usual term.

According to golden rules of reporting the numbers (BMJ publication) the numbers under 10, must be presented in letters!

The majority of the references (References: 5, 6, 20 and 22) are not up to date.

All formulas must be numbered.

Reviewer #2: Overall, I think this manuscript is well written. Just a few suggestions for the result section.

1. Table 1 and Table 2, add p values to compare the incidence between each characteristics.

2. Add a time series correlation matrix or plot to show the correlation between the characteristics in Table 4 and the time series of brucellosis.

3 Explain in detail how you optimize the parameters in your four machine learning models. For example, how did you choose the number of hidden layers for neural network. Please also list those parameters for the other models, and explain how did you determine these parameters.

4 In the discussion section, please include more discussion how to apply these models in real infectious disease surveillance.

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Reviewer #1: No

Reviewer #2: Yes: Xingyu Zhang

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Forecasting the monthly incidence rate of brucellosis in west of Iran using time series and data mining from 2010 to 2019

PONE-D-20-00374R1

Dear Dr. Cheraghi,

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

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Esteban Tlelo-Cuautle, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The updated manuscript is fine to be accepted

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: (No Response)

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Editor

There is no comments for this manuscript and the authors provided approperiate answers.

The decision is to accept.

Reviewer #2: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No