Dear Mrs Ledien,

Thank you very much for submitting your manuscript "Linear and Machine Learning Modelling for Spatiotemporal Disease Predictions: Force-of-Infection of Chagas Disease" for consideration at PLOS Neglected Tropical Diseases. 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.

Before your manuscript can be accepted. Please kindly address the concerns of Reviewer Number 2. You may accept or rebutt his/her concerns. Thank you.

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,

Uwem Friday Ekpo, PhD

Associate Editor

PLOS Neglected Tropical Diseases

Robert Reiner

Deputy Editor

PLOS Neglected Tropical Diseases

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

Before your manuscript can be accepted. Please kindly address the concerns of Reviewer Number 2. You may accept or rebutt his/her concerns. Thank you.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: (No Response)

Reviewer #2: The Github repository may be private? It's not accessible using the link provided. The only repository associated with the user does not contain analysis scripts

How were correlated variables dealt with? Particularly with LM?

How were training and testing datasets chosen? Were these random or stratified across space and time?

Reviewer #3: The aim is to compare the performance of two Machine Model frameworks (Bosted Regression Tree - BRT; Random Forest - RF) with a Linear Model regression.

From the theoretical field, it is well designed and explained. The analysis is well established and methodologically corresponds to the objectives.

It is observed that the study population results from historical data and grouped at the community level, for which there is a bias in estimating that the risk of infection is distributed randomly when the result of the new infection results from environmental conditions. (housing, environmental interventions and insecticide use), of the person in terms of exposure (influenced by age, socioeconomic status and activity), vector (density, location, etc.) and parasites (density and dispersion)

It is expected that this situation will produce bias in the final results.

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: (No Response)

Reviewer #2: Can the discussion of the results discuss

1) Model performance for median FOI predictions. Also including a discussion of different predictors and how the direction and magnitude of these predictors varied between models.

2) Then discuss the overlap with posterior (ability to capture uncertainity)

Now it jumps between evaluation metrics, response variables and models and is difficult to follow. If this section is more linked to specific research questions, I think it would be easier to follow

Reviewer #3: The presentation of the results is adequate and they are shown clearly.

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: (No Response)

Reviewer #2: What are the key outcomes of this research?

How applicable is this to other settings? Presumably without FOI estimates from age seroprevalence data, this would be very difficult to do.

Reviewer #3: The conclusions adequately inform the data presented, informing the limitations of the analysis as well as the diverse conditions that are presented.

The authors present their data and propose the continuation of analyzes of this type.

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: The authors adequately express the objective of comparing the performance of two Machine Model frameworks, the results are adequately presented and in the discussion they address the different topics, clearly establishing the limitations and application of what is proposed.

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: This work compared the ability of machine learning algorithms (here: random forest and boosted regression trees) and linear models to quantify the uncertainty around central estimates such as means or medians. The authors further compared the performance of all three modelling frameworks and their ability to predict the force of infection of Chagas disease across space and time. They have used robust age-stratified serological data from Colombia as well as relevant remotely-sensed covariates to perform all analyses. The work concluded that machine learning algorithms out-performed linear models in capturing accurate estimates for central tendency. However, linear models provided more robust estimates of uncertainty.

This work is particularly important given the recent popularity and use of machine learning algorithms in medicine research and disease prediction. The Objectives of the study were clearly articulated and are relevant in the current sphere of disease modelling methodologies. The Methods and Results were appropriate without any ambiguities. Similar sets of data were used in all three modelling frameworks, allowing for a more complete comparison. Results were complete with ample information to aid unbiased interpretation. Authors provided plentiful important details, and often overlooked information, such as those provided in Table 5. I found this interesting. Discussion/Conclusions was balanced. This is an all-round excellent paper. I recommend that it can be published as it is, without any revision.

Reviewer #2: This paper compares the ability of ML (RF & BRT) and LM to identify key predictors of T. cruzi FOI over space and time in Colombia. Observed FOI estimates come from previous work conducted by some of the research team and used age-seroprevalence data to estimate FOI by year and municipality. Both the median FOI estimate and the full posterior distribution were used as response variables in LM and ML models.

While it is clear a lot of work went into this paper, it’s very difficult to follow in its current form. More consistent terms throughout should help the reader follow which methods and which tests are used. For example, “FoI estimates” is used to describe the previous age-seroprevalence estimates but also the LM and ML predictions. Using these interchangeably creates unnecessary confusion and makes the key findings difficult to disentangle from previous work.

Reviewer #3: (No Response)

--------------------

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 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

Please 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 Mrs Ledien,

We are pleased to inform you that your manuscript 'Linear and Machine Learning Modelling for Spatiotemporal Disease Predictions: Force-of-Infection of Chagas Disease' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

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 Neglected Tropical Diseases.

Best regards,

Uwem Friday Ekpo, PhD

Associate Editor

PLOS Neglected Tropical Diseases

Robert Reiner

Deputy Editor

PLOS Neglected Tropical Diseases

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

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: Yes

**********

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: Yes

**********

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: Yes

**********

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: NA

**********

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: (No Response)

**********

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