Peer Review History

Original SubmissionSeptember 24, 2019
Decision Letter - Mercedes Pascual, Editor, Virginia E. Pitzer, Editor
Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

Dear Dr Routledge,

Thank you very much for submitting your manuscript, 'Tracking progress towards malaria elimination in China: individual-level estimates of transmission and its spatiotemporal variation using a diffusion network approach', to PLOS Computational Biology. As with all papers submitted to the journal, yours was fully evaluated by the PLOS Computational Biology editorial team, and in this case, by two independent peer reviewers. The reviewers found the work interesting and compelling but identified some aspects of the manuscript that should be improved.

We would therefore like to ask you to modify the manuscript according to the review recommendations before we can consider your manuscript for final acceptance. Your revisions should address the specific points made by each reviewer and we encourage you to respond to the particular issues, especially the point raised on relapses and how these would modify Rc. 

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Mercedes Pascual

Associate Editor

PLOS Computational Biology

Virginia Pitzer

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: General comments / Major issues

This is a well written paper on an important topic in malaria elimination research, namely using a diffusion network approach to estimate Rc for Plasmodium vivax and falciparum cases in Yunnan province between 2011-2016. The study methods and procedures are described adequately. There are a few areas that authors might consider for improving the paper.

Major compulsory comments to be addressed:

• The evidence for lack of a P. vivax relapse is stated to be from the surveillance dataset as each patient is given a unique identifier. I would argue this does not preclude there to be a fair number of relapsed P. vivax cases. How would this have influenced the estimation of Rc? I’m assuming it would have had limited impact on these estimates, but the authors should discuss this in the discussion.

• The authors argue there are a limited number of unobserved cases in the population because of strong reporting, investigation and response. What about treatment seeking in the community, where even with mild/non-severe symptoms, an individual either does not seek treatment, or finds alterative treatment though self-medicating or through informal providers? Are there any data on treatment seeking for fevers in Yunnan? I would be particularly concerned if lack of treatment seeking were also associated with certain populations that would be more likely to travel to malaria endemic settings, such as migrants or undocumented immigrants, who also might be at increased risk of infection and importation (and being an unobserved case). How might such unobserved cases have impact spatio-temporal trends in Rc? This would also be good to bring up in the discussion.

• In trying to untangle how peaks in Rc correspond to peaks in cases, are there any season trends in Rc and cases in neighboring malaria endemic countries/areas that might help explain these season trends in Yunnan?

Reviewer #2: This is an interesting and well-written study, detailing a methodology used to quantify spatio-temporal variation in reproduction numbers for malaria, using a dataset of of P. vivax and P. falciparum cases occurring in Yunnan province in China between 2011 and 2016. The methodological approach appears thorough and the results are on the whole well presented. I have the following minor comments and suggestions:


Line 59: provide more details about the malaria elimination plan. Did this include changes in prophylaxis or vector control? Has China done anything different compared to other countries to achieve success?

Line 132: discuss probable sources of uncertainty.

Line 136: “almost certainly due to the smaller sample size” —> remove “almost certainly” or suggest other reasons.


Line 305: should j and i be reversed, e.g. case i infecting case j?

Line 321: briefly describe what a Rayleigh distribution is

Line 334: define SI on first mention

Line 309: provide more details about ref 20.

Line 359: note different reference style.

Line 362: is the backslash symbol intended?

Geostatistical model specifics

How was the geospatial model spatially and temporal structured? Include space-time indicators/explanations where relevant. What are the assumptions about chosen environmental covariates and R_c? explain. Show parameter estimates for covariates.

Figures and Table

Figure 2: change legend title from imported to ‘source of infection’ (or something along those lines), change blue label to ‘locally acquired’ and red label to ‘imported’.

In the supplementary information, consider showing a map with a similar format to Figure 2 showing the case data that informed the model.

Figure 5: use different line type for 2.5 and 97.5 percentile values.

Table 1: include spatial and temporal resolution of data. Provide more details for data source, including references. Capitalise first letter.

Non-exhaustive list of typos/suggested edits:

Line 80: it can be unclear whether —> it is unclear if

Line 119: 0.5 <= epsilon <= 0.8

Line 129: missing fullstop after (Figure 2)

Line 151: and —> an


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: Yes: Thom Eisele

Reviewer #2: No

Revision 1

Submitted filename: Response_reviewers_Routledgeetal.docx
Decision Letter - Mercedes Pascual, Editor, Virginia E. Pitzer, Editor

Dear Ms Routledge,

We are pleased to inform you that your manuscript 'Tracking progress towards malaria elimination in China: individual-level estimates of transmission and its spatiotemporal variation using a diffusion network approach' 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,

Mercedes Pascual

Associate Editor

PLOS Computational Biology

Virginia Pitzer

Deputy Editor

PLOS Computational Biology


Formally Accepted
Acceptance Letter - Mercedes Pascual, Editor, Virginia E. Pitzer, Editor


Tracking progress towards malaria elimination in China: individual-level estimates of transmission and its spatiotemporal variation using a diffusion network approach

Dear Dr Routledge,

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 | Phone +44 (0) 1223-442824 | | @PLOSCompBiol

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