Dear Dr Parag,

Thank you very much for submitting your manuscript "Using information theory to optimise epidemic models for real-time prediction and estimation" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

I congratulate the author's on a very nice manuscript that was well received by the reviewers. Both reviewers were complimentary of the methods, though they raised a number of concerns about the presentation. I would encourage the authors to revisit the figures, as both reviewers found that they were challenging to interpret. Specifically:

1. Please increase the font size for figure labeling

2. If possible, consider limiting the number of scenarios presented in the multi-panel figures (particularly Fig 2). This could be reduced to a smaller number of exemplary scenarios (e.g. a,f,c,e where the latter two reflect scenarios exemplary of interventions)

3. Figure 1 is quite dense and I agree with R2 that breaking this up into panels that could be labelled, and this referenced in the legend, would help with interpretation.

4. consider using a color palettes that have greater contrasts.

Both reviewers comment on the tendency for k* to be estimated at the minimal (both reviewers) or maximal (R2) values. Please elaborate on this phenomenon.

Please consider the suggestion 1 of R2. If it is possible to clarify the applicability in real-time, I suspect that would appeal to readers.

Please address the minor comments of R2 and comments 1&2 of R1.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Matthew (Matt) Ferrari

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

I congratulate the author's on a very nice manuscript that was well received by the reviewers. Both reviewers were complimentary of the methods, though they raised a number of concerns about the presentation. I would encourage the authors to revisit the figures, as both reviewers found that they were challenging to interpret. Specifically:

1. Please increase the font size for figure labeling

2. If possible, consider limiting the number of scenarios presented in the multi-panel figures (particularly Fig 2). This could be reduced to a smaller number of exemplary scenarios (e.g. a,f,c,e where the latter two reflect scenarios exemplary of interventions)

3. Figure 1 is quite dense and I agree with R2 that breaking this up into panels that could be labelled, and this referenced in the legend, would help with interpretation.

4. consider using a color palettes that have greater contrasts.

Both reviewers comment on the tendency for k* to be estimated at the minimal (both reviewers) or maximal (R2) values. Please elaborate on this phenomenon.

Please consider the suggestion 1 of R2. If it is possible to clarify the applicability in real-time, I suspect that would appeal to readers.

Please address the minor comments of R2 and comments 1&2 of R1.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: This was an interesting paper that adds to the suite of methods for analysing case report data. In particular it provides a useful measure of the “window size” over which the reproductive ratio Rt should be calculated. As such, this could prove to be a powerful tool.

On the whole I found the paper to be extremely well written, and I only have a few minor comments.

1. In the abstract, I find the phrase “most succinctly describes” to be rather vague and confusing, could the authors seek a more informative description?

2. Page 9, the choice of a Gamma distribution for the posterior should be better motivated.

3. Figures: I found these hard to read. I realise that most people view on-line and therefore can greatly magnify figures, but a printed version is unreadable. In figure 7, I wonder if plotting Rt on a log-scale would help?

4. The paper ends on a whimper, with it being unclear if the k=2 found from real data is true or an artifact of a noisy system. I’m surprised that the authors didn’t test the method against simulations that were made sequentially noisier, this would seem an obvious test. I also feel that the speculation in the last paragraph of the results would sit far better in the discussion.

Reviewer #2: See attached

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

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Reproducibility:

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Attachments

Attachment

Submitted filename: plos_renewal_review.docx

Dear Dr Parag,

Thank you very much for submitting your manuscript "Using information theory to optimise epidemic models for real-time prediction and estimation" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

I thank the authors for their careful revisions. I do not see the need to send this back to review, but I would ask the authors to correct the legend for Figure 8 before I recommend this for publication. I assume the "(solid blue, left y axis)" and "(dotted red, right y axis)" refer to the points in the figure, but it isn't clear if I am assuming correctly or if there are elements missing from the figure. With this clarified, I will submit a final recommendation of "accept".

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Matthew (Matt) Ferrari

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

I thank the authors for their careful revisions. I do not see the need to send this back to review, but I would ask the authors to correct the legend for Figure 8 before I recommend this for publication. I assume the "(solid blue, left y axis)" and "(dotted red, right y axis)" refer to the points in the figure, but it isn't clear if I am assuming correctly or if there are elements missing from the figure. With this clarified, I will submit a final recommendation of "accept".

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/ploscompbiol/s/submission-guidelines#loc-materials-and-methods

Dear Dr Parag,

We are pleased to inform you that your manuscript 'Using information theory to optimise epidemic models for real-time prediction and estimation' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Matthew (Matt) Ferrari

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor

PLOS Computational Biology

***********************************************************

I thank the authors for their attention the reviewer comments and commend them on a fine manuscript.