PONE-D-24-42356Analysing Factors Influencing Railway Accidents: A Predictive Approach Using Multinomial Logistic Regression and Data MiningPLOS ONE

Dear Dr. Mašek,

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data 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 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—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: 1. Graphical representation needed.

2. Age, sex, demographic data missing.

3. The present study should become a base for further study on prevention of such accidents, so kindly highlight the steps taken by the authors corresponding to railway officials in the discussion part.

Reviewer #2: It was a very good study and the manuscript is well prepared. Following are some of my comments:

1. Was there an attempt to see what proportion of accidents happened due to non compliance to their Railways Act ? (Act No. 513/2009 on Railways) ?

2. Is there any statistically significant impact in relation to Covid ? This information is somehow unclear in the manuscript although it says the numbers were high in the year 2021 and 2022 ?

3. Your study has identified four important predictors, which has impacted the number of accidents: interest rate, marriage rate, the month of July, and fertility rate. For the month of July you have attributed to the following factors - seasonal variations influenced by factors such as weather conditions, holidays, and reduced operational stress. In the same way what could be other probable factors in interest rate, marriage rate and fertility rate which can affect the number of train accidents. It would be nice to look at it as well.

Reviewer #3: Review Comments on Manuscript: “Analysing Factors Influencing Railway Accidents: A Predictive Approach Using Multinomial Logistic Regression and Data Mining”

Thank you for the opportunity to review this manuscript, which develops a logistic regression model to identify the key socio-economic factors with the highest explanatory power in predicting railway accident rates. The study addresses an important issue and provides valuable insights into the roles of interest rates, marriage rates, and fertility rates in correlating with accident probabilities. However, there are several areas where the manuscript could benefit from further clarification and improvement. My detailed comments are as follows:

My detailed comments are as follows:

Introduction

1.Data Clarification

On page 2, the manuscript states: “By leveraging comprehensive data over nearly two decades, the research offers robust insights into accident causation, which is vital for developing effective safety strategies.” However, there seems to be confusion regarding the time period of the data used. Why is it referred to as nearly two decades of data? Isn’t the data from 2015 to 2022? This needs to be clarified to ensure the accuracy of the statement.

Literature Review

2.Depth and Contribution

On page 2, the manuscript mentions: “Beyond technical and organisational factors, societal dynamics play a significant role in railway accidents. Some studies have explored the relationship between various societal factors, such as economic conditions, demographic trends, and mental health indicators, and the occurrence of railway accidents (Kim and Lim, 2024; Read et al., 2012; Cooper et al., 2019).” While societal factors are central to this study, the literature review is somewhat simplistic. It doesn’t sufficiently elaborate on what previous research has done, the findings they’ve uncovered, or how these studies have contributed to the knowledge gap that this study aims to address. It would strengthen the manuscript to explain how past research has informed this study’s focus and what gaps remain in the literature that this research aims to fill.

3.Citation Formatting

On page 2, the in-text citation format is inconsistent. Please ensure that the citation style is uniform throughout the manuscript for clarity and consistency.

Theoretical Background

4.The title “Theoretical Background” might not be appropriate for this section. Typically, a “Theoretical Background” section in a research paper discusses the theories, models, or frameworks that inform the study. However, this section primarily focuses on regulations, legal frameworks, and accident classifications related to railway safety, which is more descriptive than theoretical. In its current form, this section would be more appropriate as a “Regulatory Background” or “Contextual Background”, as it focuses on the legal and regulatory framework surrounding railway safety. A theoretical background section should ideally discuss accident causation theories, risk management models, or socio-economic theories relevant to the study of railway accidents, which is missing here.

Methods

5.Selection of Explanatory Factors and Exclusion of Other Variables

On page 6, Table 4 mentions that the study attempts to use all explanatory factors for the number of accidents across different months and regions of the country. However, the rationale behind selecting these explanatory factors is unclear. Could the authors explain why these specific factors were chosen for the analysis? This would help readers understand the justification for the model and its variables.

In the limitations section of the manuscript, the authors state: “Additionally, this study focuses on a limited number of socio-economic factors; therefore, future studies could explore other potential influences, such as educational levels, cultural attitudes towards safety, or the impact of technological advancements in railway systems.” However, the reasons for excluding these variables in this study are not explained as well. It would be useful to include a discussion on why these other factors were not considered.

Discussion

6.Linking Findings with Previous Research

On page 16, the manuscript identifies the four key explanatory factors with the highest explanatory power: interest rate, marriage rate, fertility rate, and the month of July. However, since these factors have been identified as significant, it would be beneficial to relate them to previous studies. The authors could explore potential reasons why these factors influence accident rates, based on existing literature or theoretical frameworks.

While I understand that the core aim of this study is to propose a robust logistic regression model for forecasting railway accidents, it would still be helpful to provide some context around these factors, explaining why they matter in the context of railway safety.

I hope the authors find my comments helpful in refining and strengthening their manuscript. I wish the authors all the best moving forward.

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Reviewer #1: Yes:  Santhosh Kumar Tumkur Narayanappa

Reviewer #2: No

Reviewer #3: No

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PONE-D-24-42356R1Analysing Factors Influencing Railway Accidents: A Predictive Approach Using Multinomial Logistic Regression and Data MiningPLOS ONE

 Dear Dr.  Mašek,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’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 Oct 06 2025 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 plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ 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 academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• 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, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Hamed Aghaei, Ph.D.

Academic Editor

PLOS ONE

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1. 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. 

2. 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.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: No

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data 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 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—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

Reviewer #4: Yes

Reviewer #5: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: 1.Railway has categorized the accidents into Classification of Accidents: Accidents are classified under following heads:-

I. Train Accidents.

II. Yard Accidents.

III. Indicative Accidents.

IV. Equipment failures.

V. Unusual incidents.

Suicidal attempt involving railway track is called Rail suicide

The railway accident and rail suicide are dealt differently as per the law of the country and hence I advise the author to look into the matter regarding the title and AIM of the study

Reviewer #2: A good effort to study an important problem which is not very often studied, in spite of its great relevance. The manuscript in the modified form looks fine for publication, from my end. They have employed the novel techniques and I am sure the information that they have brought out in this study will be a stimulus for thinkers and researchers in this area to further explore in this space there by augmenting the railway safety at large.

Reviewer #3: (No Response)

Reviewer #4: (No Response)

Reviewer #5: The comments to the authors have been uploaded in the attachment due to character count limit. Kindly go through the same. Thank you.

This manuscript addresses a critical issue with a methodologically sound and innovative approach. However, major revisions are required to strengthen the epidemiologic interpretation, improve model transparency, and clarify generalisability.

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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: Yes:  Santhosh Kumar Tumkur Narayanappa

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes:  DR GOPINATH K

Reviewer #5: Yes:  Mohammed Shoyaib Khazi

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Attachments

Attachment

Submitted filename: Comments.docx

Analysing Factors Influencing Railway Accidents: A Predictive Approach Using Multinomial Logistic Regression and Data Mining

PONE-D-24-42356R2

Dear Dr. Mašek ,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Hamed Aghaei, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewer #5:

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #5: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #5: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #5: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data 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 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—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #5: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #5: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #5: I have carefully examined the authors’ responses to my previous comments.

Adjusted Odds Ratios and Confidence Intervals

The authors have added 95% confidence intervals and reorganised the regression outputs into a clearer format. This substantially improves the transparency and interpretability of the results.

COVID Variable and Temporal Analysis

The authors have tested for autocorrelation, used the Box–Ljung test, and incorporated dummy variables for months, seasons, and years as temporal predictors. While more advanced time-series modelling could have been considered, the justification for using logistic regression is scientifically sound and acceptable.

Model Performance and Overfitting Concerns

The authors addressed overfitting concerns by reporting evaluation metrics only on the test dataset from a 75:25 split. While cross-validation or bootstrapping would have provided stronger evidence of generalisability, the explanation regarding software constraints is reasonable, and the presented metrics are sufficient to support the model’s performance.

Overall Assessment:

The authors have substantially addressed Reviewer 5’s comments. The revisions improve the clarity, robustness, and interpretability of the manuscript. The only remaining limitation is the lack of cross-validation, but given the constraints and the adequate justification provided, I find the responses satisfactory.

Recommendation:

The authors have adequately addressed my concerns, and I am satisfied with the current revision. Hence, I recommend this manuscript for publication.

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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 #5: Yes:  Dr Mohammed Shoyaib Khazi

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