Dear Mr. Tsirtsis,

Thank you very much for submitting your manuscript "Pooled Testing of Traced Contacts Under Superspreading Dynamics" 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.

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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,

Alex Perkins

Associate Editor

PLOS Computational Biology

Tom Britton

Deputy Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The authors present an interesting new method to optimize test pooling in the context of contact tracing procedures. The work is well executed, both from a formal and experimental analysis point of view. The paper is well written and clear.

Some major remarks:

- My major concern with this work, is that the impact on the actual epidemic is not investigated. If I understand it correctly, temporal (e.g. viral load progression) and contact-related aspects of the epidemic are all aggregated in the clinical sensitivity/specificity (line 170). However, missing contacts, especially in an overdispersed epidemic context, could have implications on the overall attack rate. The authors mention (in the discussion), that this could be investigated through randomized control studies, yet I would argue that this could also be analysed by using an individual-based model to investigate the impact of your testing strategy? To this end, perhaps one of these individual-based models could be used [2,3,4]?

- One of your assumptions, early in the paper (line 100), where you assume that perfect tracing is possible, is quite a though one. While I understand that this assumption is necessary for your theoretical framework, I believe it would be good to acknowledge that this is not necessarily realistic and refer to the section where you empirically challenge this assumption (line 298).

Some minor remarks:

- Is there a reason why you use small r instead of R_0? This makes it an easier symbol to spot, and the symbol is quite commonly used in literature.

- Did you consider any additional population structures next to the contact tracing contacts (e.g., households), and how would this fit in your work?

- Adjacent to this, the related work section was quite complete, however I believe that the work on household-based pooling [1] could also be interesting to discuss.

- I found Figure 1 (b) a bit strange and hard to interpret at first sight. It looks strange with the negative percentages, could you perhaps show the test distributions for both methods instead next to each other?

- Why is Figure 2 ragged along the y-axis? Is this related to the experimental resolution you used to build this figure?

References:

[1] https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008688

[2] https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009149

[3] https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009146

[4] https://www.nature.com/articles/s41467-021-21747-7

Reviewer #2: Please see attached file.

Reviewer #3: The paper studies the problem of pooled testing in which the goal is identify an optimal pooling scheme that balances between testing costs and misclassification errors. The novel component is that the authors assume that arrivals are all contact traced to one person. The author model this using a truncated negative binomial distribution. The authors then show that their formulation can be solved via dynamic programming. Finally, the authors conduct an extensive numerical study in which they measure the benefits of their approach compared to classical Dorfman testing. Overall the paper is well-written and generally easy to follow. I do have some concerns about the modeling assumptions in addition to some clarifications which I list below. I recommend a major revision.

- Why use a truncated normal binomial and not some other mixture model? It would be interesting to observe the impact of that on the optimization outcome. The benefit of using a mixture model is that allows for more flexibility in choosing population variance which allows for the calibration of that variance using data.

- Page 4/33 line 142, what are the bounds of the summation in the objective function? The reason I ask this question is that it seems that the number of summands in the objective varies as you add more pools, which in itself is a decision in this problem.

- General comment on the case study. Since you are interested in minimizing a weighted sum of expected number of tests, false-negatives, and false-positives, then why don't you report the value of that objective function in your comparison of you approach with the Dorfman scheme?

- General question about the Dorfman scheme. It is not clear how this was implemented in the paper. How did you partition the set of N patients into pools to be tested using a Dorfman scheme? Maybe adding a paragraph about this in the experimental design section would help clarify this.

- Would it be possible to run your by only accounting for false negatives? It would be interesting to compare your approach to Dorfman testing if the only goal is to minimize negative misclassification errors.

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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 #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Figure Files:

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Attachments

Attachment

Submitted filename: PCOMPBIOL-D-21-01826_Review.pdf

Dear Mr. Tsirtsis,

Thank you very much for submitting your manuscript "Pooled Testing of Traced Contacts Under Superspreading Dynamics" 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.

Please address the one minor comment by Reviewer 1.

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,

Alex Perkins

Associate Editor

PLOS Computational Biology

Tom Britton

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: I thank the authors for their answers and improvements of the manuscript.

One more remark: on my comment regarding the impact on the testing strategy on the epidemic, the authors state:

"That being said, we agree with the reviewer that it would be very interesting to investigate the

impact of different testing methods on the epidemic under a limited testing capacity using

individual-based models."

It would be good to indeed mention this in the discussion.

Reviewer #2: The authors addressed all my comments.

Reviewer #3: The authors addressed all of my comments and I have no further comments to add.

**********

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 #1: Yes

Reviewer #2: Yes

Reviewer #3: 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

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

References:

Review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Dear Mr. Tsirtsis,

We are pleased to inform you that your manuscript 'Pooled Testing of Traced Contacts Under Superspreading Dynamics' 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,

Alex Perkins

Associate Editor

PLOS Computational Biology

Tom Britton

Deputy Editor

PLOS Computational Biology

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