Dear Dr. Wood,

Thank you very much for submitting your manuscript "Modelling outbreak response strategies for preventing spread of emergent Neisseria gonorrhoeae strains in men who have sex with men in Australia" 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. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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

[1] A letter containing a detailed list of your responses to the 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.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. 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,

Roger Dimitri Kouyos

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor-in-Chief

PLOS Computational Biology

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

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Review uploaded as an attachment

Reviewer #2: 1. The Introduction section must be more detailed. It must contain review of previous works

2.The authors must clearly state whether the model is new or whether they're modifying an existing model

3. The model equations should be presented

4. The results and discussion must clearly show how this model improved on previous ones.

Reviewer #3: In their manuscript, Duan et al use an individual-based, anatomical site-specific mathematical model of Ng transmission to ask the question: what types of testing and treatment strategies would be needed if an XDR Ng strain were introduced in the Australian MSM population? They highlighted several strategies that would be able to mitigate spread/eradicate circulation of this strain, namely combining case-based and population-based strategies (nicely summarized in Table 3). The model is well constructed and will certainly be useful for others examining specific questions on Ng transmission. There are, however, some concerns that need to be addressed.

The most obvious concern is how this model relates to the spread of XDR Ng. The authors assume that if such a strain is introduced, it can be treated just as well as any other Ng strain (ln 148-149). The real supposed concern with XDR Ng is that no treatment options will be available for these infections, meaning increased risk of spread. I do agree with the authors that other treatment alternatives could be used to cure Ng, but there will be delay in curing Ng in these individuals. The authors need to incorporate some aspects of treatment efficacy and duration of unsuccessful treatment if they want to infer anything on resistant variants circulating in the population. Furthermore, XDR Ng could naturally develop within the MSM population in Australia. Although rare, it could happen and might also affect the scenarios modeled. If the authors cannot address specific questions of resistance, they need to place their focus on Ng transmission rather than Ng resistance.

Another major assumption, from what I understand, is that only one introduction is expected and the resulting transmission patterns stem from this single introduction (ln 144-146). Given the worldwide network of MSM contacts and STI transmission, there would likely be several introductions of the XDR Ng strain in the population, which could have an impact on eradication of XDR Ng. These aspects also need to be considered in the model.

It is also unclear whether the model incorporates the fact that the prevalence of Ng infections in MSM has been steadily increasing. Similarly, condomless anal sex has also increased in several studies among MSM. The inputs used in this model are calibrated to 2018 levels, but does an epidemic background of increasing Ng prevalence and more frequent condomless anal sex render these strategies less effective?

Minor comments:

- ln 46. Should this be “current _testing and treatment_ practices”?

- ln 115. Are the authors really testing “surveillance” strategies? Is Ng required to be reported to the Australian government?

- ln 116-7. Not sure how the sentence “note that this…” relates to this paragraph.

- lns 168-170. How close are these inputs to the current situation?

- ln 177. The 2.3% prevalence refers to any site? Can this be divvied out by site?

- ln 361. By how much is the estimate missed when not included in this study?

- Figure 1. It would be helpful to have blocks regrouping events that are computed within the same algorithm.

- Table 1. Missing “(“ in the second column, row “Anorectum”.

- Technical appendix: Algorithm 1, step 3. Why does the % infected at the sites not match those listed on lines 132-133?

- Technical appendix: There are two “Algorithm 3” in the manuscript.

- I would highly recommend the authors place the data and programming code on a publicly available server.

**********

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

**********

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

Reviewer #3: No

**********

Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code 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 and code 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 or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: No: 

Reviewer #3: No: I cannot find the link to any code.

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, we recommend that you deposit your 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. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Attachments

Attachment

Submitted filename: PLOS Computational Biology_March_21.docx

Dear Dr. Wood,

We are pleased to inform you that your manuscript 'Modelling response strategies for controlling gonorrhoea outbreaks in men who have sex with men in Australia' 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,

Roger Dimitri Kouyos

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor-in-Chief

PLOS Computational Biology

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

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #2: The paper can be accepted

Reviewer #3: I thank the authors for their clear responses and careful consideration of my comments.

One remaining issue is that XDR Ng strains are still the major focus of the introduction (and in one small part of the discussion). The focus needs to be placed on the imported infection, with XDR being an important example. It would be nice to add, to the discussion, how the model could be fine-tuned to address other research questions on the imported strain (e.g. XDR, one that might be more transmissible, etc.). Addressing this comment would only require adding some sentences and a slight restructuring of paragraphs.

Reviewer #4: No further comments

**********

Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code 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 and code 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 or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

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 #2: No

Reviewer #3: No

Reviewer #4: No