Peer Review History

Original SubmissionOctober 15, 2019
Decision Letter - Jennifer A. Flegg, Editor, Virginia E. Pitzer, Editor

Dear Dr Garira,

Thank you very much for submitting your manuscript 'The Research and Development Process for Multiscale Models of Infectious Disease Systems' for review by PLOS Computational Biology. Your manuscript has been fully evaluated by the PLOS Computational Biology editorial team and in this case also by independent peer reviewers. The reviewers appreciated the attention to an important problem, but raised some substantial concerns about the manuscript as it currently stands. While your manuscript cannot be accepted in its present form, we are willing to consider a revised version in which the issues raised by the reviewers have been adequately addressed. We cannot, of course, promise publication at that time.

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.

Your revisions should address the specific points made by each reviewer. Please return the revised version within the next 60 days. If you anticipate any delay in its return, we ask that you let us know the expected resubmission date by email at ploscompbiol@plos.org. Revised manuscripts received beyond 60 days may require evaluation and peer review similar to that applied to newly submitted manuscripts.

In addition, when you are ready to resubmit, please be prepared to provide the following:

(1) A detailed list of your responses to the review comments and the changes you have made in the manuscript. We require a file of this nature before your manuscript is passed back to the editors.

(2) A copy of your manuscript with the changes highlighted (encouraged). We encourage authors, if possible to show clearly where changes have been made to their manuscript e.g. by highlighting text.

(3) A striking still image to accompany your article (optional). If the image is judged to be suitable by the editors, it may be featured on our website and might be chosen as the issue image for that month. These square, high-quality images should be accompanied by a short caption. Please note as well that there should be no copyright restrictions on the use of the image, so that it can be published under the Open-Access license and be subject only to appropriate attribution.

Before you resubmit your manuscript, please consult our Submission Checklist to ensure your manuscript is formatted correctly for PLOS Computational Biology: http://www.ploscompbiol.org/static/checklist.action. Some key points to remember are:

- Figures uploaded separately as TIFF or EPS files (if you wish, your figures may remain in your main manuscript file in addition).

- Supporting Information uploaded as separate files, titled Dataset, Figure, Table, Text, Protocol, Audio, or Video.

- Funding information in the 'Financial Disclosure' box in the online system.

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.

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. For instructions see here

We are sorry that we cannot be more positive about your manuscript at this stage, but if you have any concerns or questions, please do not hesitate to contact us.

Sincerely,

Jennifer A. Flegg

Guest 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]

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: This manuscript proposes a general framework for developing and using multi scale models of infectious disease systems, to address the lack of standardisation in the way that these types of models have been developed and used to date. This has been submitted as a research article, however it does not fit the usual format of such an article, i.e., introduction which describes a research question and context of the work, results, discussion, methods. It may be more suited to being a review (although there is limited literature cited here beyond the authors own work) or an eduction piece.

Major Comments

1. It is not made clear how this framework relates to those the author has previously proposed in references [1,2]. There are a different number of levels of organisation proposed in each of these works. Why is the update /extension necessary?

2. The proposed framework incorporating sub-systems/levels/scales is complex. The author has provided a number of schematic diagrams to aide understanding. However, I think linking back to biological examples of the boundaries and interactions within/between these different levels of organisation would also be helpful, along with, where appropriate, citing examples in the literature of exemplar multi-scale models and their research questions.

3. It is not clear that the pathogen subsystem proposed is able to encapsulate processes of horizontal gene transfer, e.g., via phage or plasmids, which can occur between pathogen species that occupy the same niche/host and between strains of the same species during co-infection. This is especially important for the spread of antibiotic resistance in pathogen populations, and for vaccine escape, such as that which occurred for Pneumococcus (see Corander et al., 2017: https://doi.org/10.1038/s41559-017-0337-x)

4. It is known that households provide the opportunity for prolonged close mixing between individuals and it is generally assumed that the risk of infection transmission between household contacts far exceeds that in the wider community. Also many interventions target households. Yet, households do not appear in the framework. This should at least be discussed, or incorporated into the framework.

5. Section 2.6: Levels and scales are also linked by exchange of phage, and other mobile genetic elements, not just the pathogen, hosts, host products, etc. This should at least be discussed, or incorporated into the framework.

6. Related to comment 2 above: points a-e, page 22. Reference to exemplar research questions and models would aide understanding of these reasons for model selection

7. Stage III. Point 3.3, page 29. There are two different, but related, types of analyses that should be conducted for any ID model: sensitivity analysis (which parameters are the outputs most sensitive too? i.e., using partial rank correlation coefficient), and uncertainty analysis (how does uncertainty in inputs affect uncertainty in outputs? i.e., using Latin Hypercube sampling of parameter space). This should be acknowledged.

Minor comments

1. The author uses the terms “actual scale” and “characteristic scale” throughout, which I assume mean the same thing. It would be more clear to use one of these terms consistently, especially give ghere is considerable terminology being introduced in the paper around scales/levels/sub-systems.

2. Point (a) on page 3. “the inability to distinguish between local infections and imported infections in the … is because of using single scale modelling instead of multi scale modelling”. Isn’t this a data collection and analysis issue rather than a modelling issue? Such errors can be overcome by collected the right data, e.g., genomic data of isolates, or meta-data associated with isolates

3. Point (c) on page 5. The use of the term “local interactions” is misleading here as it suggests interactions only within a subsystem. Consider using just “interactions”

4. Figure captions should include all details necessary to understand this figure. E.g., what do (i)-(vii) refer to in Figure 1, what do arrows mean? what do (a)-(f) refer to in Figure 4

5. Page 10: throughout points (a)-(d) you use the phrase “is clear”. It is not clear. Please just say what the boundary is.

6. Page 11: model categories I-V need to be described. Also provide examples from literature.

7. Use of the term “super-infection” throughout. When this term is first used it should be defined, as there is not consensus in literature. It is used to mean both strain replacement (superseding infection) as well as co-infection (co-existence) of strains within a host.

8. Page 17: Is it not true that global exchange of organisms can also play a role in disease persistence? E.g, pathogen moving to population with higher levels of susceptibility, and being re-introduced after a period of time, or TB bacteria moving from airways to granuloma where it can persist for long periods of time?

9. Point e, page 31. How do mass drug administrations fit in here? They are treatments, but given to people not necessarily infected.

Reviewer #2: The authors make good case for multiscale modeling of infectious diseases from a complex systems perspective. The paper provides developmental process maps for multiscale modeling systems, in particular the integration of four different multiscaling approaches to address the infectious disease dynamics is interesting.

Despite some interesting ideas, the reviewer finds that the manuscript needs some additional work to be published in a high impact journal.

(1) In the vast literature of epidemic modeling examples of each aspect of multiscale nodeling system proposed by the author.

correlating the existing studies for a well studied epidemic (e.g. AIDS, H1N1, Ebola etc) into the hierarchical format suggested by the author in figure 2 would help identify where the specialized studies fit in a complex systems approach.

(2) The same comment for the integration of multiscale modeling approaches in figure 4. It would be helpful to identify examples of past research that fits into each category. This would be needed to bring out the interplay between different modeling approaches for the suggested integrated system.

**********

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

**********

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

Revision 1

Attachments
Attachment
Submitted filename: COVER_LETTER_ PCOMPBIOL.R1.pdf
Decision Letter - Jennifer A. Flegg, Editor, Virginia E. Pitzer, Editor

Dear Prof. Garira,

We are pleased to inform you that your manuscript 'The Research and Development Process for Multiscale Models of Infectious Disease Systems' 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 within two working days 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,

Jennifer A. Flegg

Guest Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor

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: In the revised manuscript the author has addressed my main concerns. A couple of minor comments:

- I think the concept of super-infection needs only to be defined once on page 17, not three times, also remove from page 35

- Include references for methods listed in lines 1445, 1447. Some suggestions: https://doi.org/10.1098/rsif.2012.1018, https://doi.org/10.2307/1403510

Reviewer #2: The authors have addressed the reviewers comments adequately.

**********

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

**********

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

Formally Accepted
Acceptance Letter - Jennifer A. Flegg, Editor, Virginia E. Pitzer, Editor

PCOMPBIOL-D-19-01717R1

The Research and Development Process for Multiscale Models of Infectious Disease Systems

Dear Dr Garira,

I am pleased to inform you that your manuscript has been formally accepted for publication in PLOS Computational Biology. Your manuscript is now with our production department and you will be notified of the publication date in due course.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript.

Soon after your final files are uploaded, unless you have opted out, the early version of your manuscript will be published online. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting PLOS Computational Biology and open-access publishing. We are looking forward to publishing your work!

With kind regards,

Laura Mallard

PLOS Computational Biology | Carlyle House, Carlyle Road, Cambridge CB4 3DN | United Kingdom ploscompbiol@plos.org | Phone +44 (0) 1223-442824 | ploscompbiol.org | @PLOSCompBiol

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .