PCOMPBIOL-D-25-00277

Sub-national estimation of surveillance sensitivity to inform declaration of disease elimination: A retrospective validation against the elimination of wild poliovirus in Nigeria

PLOS Computational Biology

Dear Dr. Nightingale,

Thank you for submitting your manuscript to PLOS Computational Biology. After careful consideration, we feel that it has merit but does not fully meet PLOS Computational Biology's publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Juliette Paireau

Academic Editor

PLOS Computational Biology

Benjamin Althouse

Section Editor

PLOS Computational Biology

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note that two reviews are uploaded as attachments.

Reviewer #1: Reviewer comments for PCOMPBIOL-D-25-00277

This is a well-written manuscript which seeks to quantify the sensitivity of Nigeria’s polio surveillance system and derive a statistical framework which provides a probability of freedom from infection (FFI). This is then retrospectively validated against two periods of empirical absence of WPV1. The principal findings from the framework are concordant with the true virus transmission status and aim to provide a quantitative, spatially specific decision aid in polio eradication scenarios.

I think this manuscript is suitable for publication in PLoS Comp. Biol. after a few minor revisions.

Abstract

1) The opening sentence is a bit clumsy and could probably do with being split into two, something like:

‘Which duration of absence of polio infection qualifies as regional elimination is a key question in the global drive towards eradication of the disease. The safe withdrawal of the polio vaccine is naturally contingent upon this.’

2) Perhaps expand on ‘sensitivity over time and space’, introduce the time and spatial scales (as you have in the methods) more explicitly here so the reader can get a better feel for the size of the study.

Introduction

1) The independence between cases of AFP and detection of the virus via ES has been assumed, is there a suitable reference for this? A couple of lines stating/explaining this, as you did with vaccination would be helpful.

Methods

1) It would be good to include a summary of the sensitivity analyses you’ve conducted for some of the key assumptions (such as the design prevalence, prior FFI and ES catchment) in the main text rather than just stating you’ve done them. Please also refer to the specific item in the supplement (which for Plos comp biol is something like ‘Fig B in S1 Text’).

2) Treating AFP and ES as independent will over-estimate combined sensitivity should these two variables be influenced by the same external factors, might be worth mentioning or a simple correlation test.

3) Citation for lab test sensitivity?

4) Minor typo in ‘LGAs followers the approach’

Results

Figures look great and their message is clear. My only comment here is that it’s quite an ‘explosion of colour’ in some of the panels, perhaps describing the lines/colours in the legend could be helpful, particularly for colourblind readers.

Discussion

1) Could contrast your findings more explicitly with Dietz and Eichner’s 3-year rule.

2) I think the suggestion of ES superseding AFP surveillance might need further caveating, they’re fundamentally different things and the ability of ES to supersede may not be relevant in all foci.

3) The overall structure of the discussion gets a little jumpy and some of the paragraphs are long. Consider breaking it up into a more organised flow i.e. Implications – Limitations – Future work

Conclusion

1) GCC not GGC in the opening line

2) A concise statement about broader generalisability outside of Nigeria (Pakistan, Afghanistan etc) could provide a nice way to strengthen the conclusion.

Reviewer #2: Review attached.

Reviewer #3: There is a review uploaded as an attachment 'comments'

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Attachments

Attachment

Submitted filename: review1.docx

Attachment

Submitted filename: Comments.docx

PCOMPBIOL-D-25-00277R1

Sub-national modelling of surveillance sensitivity to inform declaration of disease elimination: A retrospective validation against the elimination of wild poliovirus in Nigeria

PLOS Computational Biology

Dear Dr. Nightingale,

Thank you for submitting your manuscript to PLOS Computational Biology. After careful consideration, we feel that it has merit but does not fully meet PLOS Computational Biology's publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Feb 10 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at ploscompbiol@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pcompbiol/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

* A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. This file does not need to include responses to formatting updates and technical items listed in the 'Journal Requirements' section below.

* A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

* An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, competing interests statement, or data availability statement, please make these updates within the submission form at the time of resubmission. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Benjamin Althouse

Section Editor

PLOS Computational Biology

Benjamin Althouse

Section Editor

PLOS Computational Biology

Additional Editor Comments:

The paper is ready to be accepted. Please revise the typos pointed out by the reviewer and it will be ready.

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #2: Uploaded as an attachment.

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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 #2: Yes

**********

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Reviewer #2: No

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Attachments

Attachment

Submitted filename: Review2.docx

Dear Dr Nightingale,

We are pleased to inform you that your manuscript 'Sub-national modelling of surveillance sensitivity to inform declaration of disease elimination: A retrospective validation against the elimination of wild poliovirus in Nigeria' has been provisionally accepted for publication in PLOS Computational Biology.

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

Best regards,

Benjamin Althouse

Section Editor

PLOS Computational Biology

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