Response to reviewers

Dear editor, thank you very much for considering our article in your esteemed journal. Dear reviewers, we would like to thank you for your scholarly contribution to our manuscript. Dear reviewers, we have considered all your comments without jumping anyone of them, however, most of our reply are appended in the revised manuscript. Hence, we kindly request to consider it

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Response: Response: Dear Editor, thank you for your detailed review and for bringing the copyright concerns to our attention. We have carefully reviewed the materials used in our submission and would like to provide the following clarifications regarding the base layers of the maps in Figures 2, 3, 4, 5, 6, 7, and 8.

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The base layer of the maps was obtained from the Humanitarian Data Exchange (HDX): (http://geoportal.icpac.net/layers/geonode%3Aafr_g2014_2013_0)

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The dataset is available under an open and permissible license that allows reuse, and we have ensured compliance with PLOS’s CC-BY 4.0 licensing requirements.

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Response: We have done it

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: Partly

Reviewer #2: Yes

________________________________________

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

Reviewer #1: I Don't Know

Reviewer #2: Yes

________________________________________

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Reviewer #1: No

Reviewer #2: No

________________________________________

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Reviewer #1: Yes

Reviewer #2: No

________________________________________

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: Review of the Article:

"Spatial variations and determinants of HIV testing uptake among youth women in Sub-Saharan Africa: spatial analysis and Bayesian hierarchical modelling"

Relevance of the Topic and Introduction

The article addresses a highly important and interesting topic concerning the low uptake of HIV testing among young women in Sub-Saharan Africa (SSA). This issue has significant social, health, and economic implications, and tackling it is crucial for achieving the global UNAIDS 95-95-95 targets and the Sustainable Development Goals (SDGs). The authors rightly emphasize that spatial analysis and the identification of determinants could contribute valuable insights for health policy planning. However, the article requires substantial revisions to better highlight its scientific contribution and improve readability for its audience.

Response: Thank you for your thoughtful feedback. We appreciate your recognition of the importance of the topic and the relevance of the spatial analysis in addressing HIV testing uptake among young women in Sub-Saharan Africa. We agree that the article would benefit from revisions to better highlight its scientific contributions and improve its readability. We have worked on clarifying the key findings and ensuring that the content is accessible and impactful for the intended audience. Your input is valuable, and we have taken it into account during the revision process.

Comments on the Introduction

1. Need for a broader discussion of the literature:

The introduction should include a review of methods used in previous studies to analyze spatial variations in public health. For instance, the authors could discuss earlier applications of Bayesian analysis or kriging in similar contexts, which would help underscore the novelty of this study.

Response: Thank you for your suggestion. We agree that a broader discussion of the literature, particularly regarding methods like Bayesian analysis and kriging, would strengthen the introduction and highlight the novelty of our study. We have revised the introduction to include relevant methods from previous research to provide better context and support our approach. Please not that we could not find previous literature which used Bayesian or Kriging methods.

2. Clear articulation of the study’s objective and novelty:

While the article aims to analyze spatial variations and identify factors influencing HIV testing in SSA, the objective should be more clearly stated, particularly in terms of how it contributes uniquely to existing literature. Currently, the novelty of the study is insufficiently emphasized.

Response: Dear reviewer, thank you for your feedback. We agree that the study’s objective and its unique contribution to the existing literature need to be more clearly articulated. In the revised version, we have ensured the objective is explicitly stated, and we have highlighted the novelty of our approach to emphasize how it adds value to current research on spatial variations in HIV testing in Sub-Saharan Africa.

Comments on the Article’s Structure

The article's structure needs improvement:

• The methodology is presented in a fragmented manner, mainly through titled paragraphs, which makes it difficult to follow the authors' research process. A more cohesive and logically sequenced description of methods is recommended.

Response; Thank you for your valuable comment. We acknowledge that the methodology section could benefit from a more cohesive and logically structured presentation. In the revised version, we reorganized the methodology to ensure a clearer and more sequential flow, making it easier for readers to follow the research process

• There is inconsistency between the methods and results sections. For example, kriging is mentioned in the results but is not described in the methods section.

Response: Thank you for pointing this out. We have addressed this inconsistency by ensuring that all methods, including kriging, are properly described in the methodology section. This helps align the methods and results sections and provide a clearer understanding of the research approach.

Comments on Methodology

1. Insufficient explanation of techniques used:

While the authors mention advanced tools such as Bayesian hierarchical modeling and Markov Chain Monte Carlo algorithms, their descriptions are superficial. To enhance understanding, the methodology should explain:

o The rationale for choosing these techniques.

o The assumptions underlying their application.

Response: Thank you for your constructive feedback. We recognized the need to provide a more detailed explanation of the techniques used. In the revised version, we included a clearer rationale for selecting Bayesian hierarchical modeling and Markov Chain Monte Carlo algorithms, as well as an explanation of the assumptions underlying their application. This was done to improve the clarity and depth of the methodology section.

2. Missing details on kriging:

The use of kriging is noted in the results section but not elaborated upon in the methodology. This omission is significant because kriging requires prior analysis of the statistical distribution of data and verification of its characteristics, which is not addressed.

Response: Dear reviewer, thank you for pointing this out. We appreciated your feedback. To address this concern, we revised the methodology section to provide a more detailed explanation of the kriging approach used in our study. Specifically, we included information on the preliminary analysis of the data's statistical distribution and the steps taken to verify its characteristics before applying kriging. This ensured that the process was well-documented and transparent, as per standard practice in geostatistics. We also clarified any assumptions made during this process and provided more details on the choice of parameters for kriging, such as the variogram model and how it was validated. We hope this added information enhances the clarity and reproducibility of our methodology

Comments on Results and Interpretation

1. The results are presented clearly in some areas, such as the identification of spatial hotspots, but their overall presentation lacks consistency. For instance, while spatial clusters are well described, there is limited analysis of how socioeconomic determinants vary across regions.

Response: Thank you for your valuable feedback. We appreciate your comments regarding the presentation of results. We have carefully considered your suggestion about including a more detailed analysis of how socioeconomic determinants vary across regions. However, we would like to clarify that the variation of socioeconomic determinants across regions has been primarily addressed in the discussion section, rather than in the results, in order to avoid mixing interpretation with reporting of findings. In the results section, we have focused on presenting the spatial clusters and hotspots clearly, while the discussion section delves into the interpretation of these results, including how socioeconomic factors may influence regional variations. We hope this clarification improves the coherence of our manuscript

2. The discussion section does not sufficiently compare the findings with previous studies, which could help contextualize the conclusions and support their validity

Response: Thank you for your insightful comment. We acknowledge that a more thorough comparison with previous studies is essential for contextualizing our findings. In response to your feedback, we have revised the discussion

Attachments

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Submitted filename: Response to reviewers.docx

Point by point response for reviewers2nd round

Reviewer #3

The research article presents the different types of factors which influence HIV testing in the Sub-Saharan Africa regions, using the Bayesian hierarchal modelling. This research article presents a high value and importance, with novelty. The improvements made in all sections were very useful making it more understandable and concise. The introduction is clear, structured and informative. The research question and goal have been adequately described and justified. Both the choice of factors, as well as, the description of some of the factors is very well prosecuted. Figures are clear and comprehensible. Results concentrated in Tables are of high quality and value. Especially table 6 is particularly useful. The comparison with other studies in a global level as well as the presentation of study’s findings in the “Discussions” section is accurate and useful. It is also very important that all of the factors included in the study were fully analyzed.

Concerning the review that the manuscript underwent, according to my opinion, the authors have answered all of the reviewers’ comments accordingly and made all the corrections needed.

Response: We would like to express our sincere appreciation to Reviewer #3 for the thoughtful and positive evaluation of our manuscript. We are truly grateful for the reviewer’s recognition of the novelty, clarity, and value of our research.

We are pleased to learn that the reviewer found the improvements across all sections useful and that the revised version has become more understandable and concise. We particularly appreciate the reviewer’s encouraging remarks on the quality of the introduction, the appropriateness of the selected factors, the clarity of the figures, and the presentation of the results and discussions.

The reviewer’s acknowledgment of the significance of Table 6 and the global-level comparison of our findings is very encouraging. We are also pleased that the comprehensiveness of our analysis and the structured presentation of results were well received.

We have carefully reviewed the manuscript once again to ensure all revisions are consistent with the reviewers’ and editors’ expectations. We are delighted that our responses to previous comments have fully addressed the concerns raised and that the manuscript is now considered improved and clear.

We sincerely thank the reviewer for their constructive feedback and positive assessment, which have greatly contributed to strengthening the overall quality and clarity of our manuscript

Reviewer #4

Overall feedback from previous comments

Dear Editor,

Thank you for the opportunity to review the above-referenced manuscript submitted to

PLOS ONE. First, I would like to acknowledge the importance of the problem addressed

in this manuscript, which is of critical relevance to economic development in Africa. As

noted by other reviewers in the previous round, the manuscript has potential for

publication, provided that improvements are made in both the writing and the research

design—areas I will focus on below.

Response: We would like to sincerely thank Reviewer #4 for their continued engagement with our manuscript and for recognizing the importance and relevance of our study to Africa’s economic development. We greatly appreciate the reviewer’s acknowledgment that the manuscript has strong potential for publication and their thoughtful guidance on areas for improvement. We have carefully considered the reviewer’s previous and current comments, particularly regarding the writing quality and research design. In this revised version, we have: We believe these revisions have substantially strengthened both the narrative and the technical robustness of the manuscript. We are deeply grateful for the reviewer’s constructive feedback, which has been instrumental in improving the overall quality of the work.

Second, I must clarify that my review was primarily aimed at assessing whether the

authors adequately addressed the comments raised by previous reviewers. In this regard,

it appears that the authors have made an effort to respond to those comments. I use the

term “effort” deliberately, due to the style adopted in their responses. While this style may

have been recommended by the journal, I found it confusing and difficult to verify the

changes made in the revised version. Typically, authors should clearly indicate whether

a comment has been addressed and guide the reviewer to the relevant section in the

revised manuscript. Unfortunately, in this case, the authors often simply stated that a

comment had been addressed, without further clarification. Despite this, I read the entire

manuscript to ensure that the comments were indeed considered.

Response: We sincerely thank Reviewer #4 for carefully reviewing both our revised manuscript and our previous responses. We also appreciate the reviewer’s acknowledgement that we have made a genuine effort to address the earlier comments.

We apologize for any confusion caused by the format and style of our previous responses. We understand that our earlier approach may not have clearly indicated where each revision was made within the manuscript. We recognize that this may have made it difficult to verify specific changes, and we sincerely regret the inconvenience this caused.

In this resubmission, we have fully revised our response document to ensure greater transparency and ease of review. Specifically:

1. Each reviewer comment is now followed by a clear, point-by-point response explicitly indicating how and where the change has been made.

2. Corresponding page and line numbers (or section references) are provided for every modification.

3. All changes in the revised manuscript have been highlighted or tracked for easy verification.

We are grateful to the reviewer for this valuable feedback, which has guided us to improve not only the content of our work but also the clarity and structure of our revision process.

Additional comments

Although my primary focus was on previous reviewers’ comments, as per the Editor’s

instructions, it is important to raise a few additional points of my own, particularly

concerning the research design and methodology.

In Paragraph 4 of the Introduction, beginning with “This study aims to investigate...”, the

authors state that one of the objectives is to examine spatial variation. However, they do

not provide a rationale for investigating these spatial variations. What is the practical

significance of identifying such variations? Similarly, the discussion of spatial

autocorrelation (Global Moran’s I) and local indicators of spatial autocorrelation (LISA)

lacks a theoretical foundation. The authors do not explain why one might expect HIV

testing behavior to be spatially correlated among young women in neighbouring clusters.

At a minimum, they could have referenced Tobler's (1970) First Law of Geography, which

posits that “everything is related to everything else, but near things are more related than

distant things.” This principle supports the idea that HIV testing is a social phenomenon

influenced by unobserved factors that affect nearby neighbourhoods similarly. Thus,

young women in adjacent areas may exhibit similar testing behaviours.

Response: We thank the reviewer for this insightful comment. We agree that the initial version did not clearly articulate the practical significance of examining spatial variations in HIV testing uptake among young women in sub-Saharan Africa. In response, we have revised the last paragraph of the introduction to explicitly explain why assessing spatial variation is important.

We now emphasize that spatial heterogeneity in HIV testing reflects underlying disparities in access to health services, socioeconomic development, and health system performance across and within countries. Identifying these geographic patterns is therefore essential for informing targeted, location-specific interventions, optimizing resource allocation, and addressing inequities in HIV testing coverage.

The revised paragraph now reads as follows:

“Understanding the spatial variation in HIV testing is practically significant because testing uptake is not uniformly distributed across or within countries. Such variations often reflect underlying disparities in access to health services, socioeconomic development, cultural norms, and health system performance. Identifying where HIV testing is lower can help governments and health agencies to prioritize high-risk or underserved geographic areas, allocate resources more efficiently, and design targeted interventions that respond to local needs and barriers.”

We believe this revision clarifies the rationale and strengthens the justification for including spatial analysis in the study.

Response to Reviewer (on theoretical foundation for spatial autocorrelation and LISA analysis)

We sincerely thank the reviewer for this insightful comment. We agree that our original discussion did not clearly explain why HIV testing behavior might be spatially correlated among young women in neighboring clusters.

In response, we have revised the relevant section of the manuscript to explicitly include a theoretical justification. We now reference Tobler’s (1970) First Law of Geography, which states that “everything is related to everything else, but near things are more related than distant things.” This principle provides a rationale for expecting spatial clustering in HIV testing, as neighboring areas are likely influenced by shared contextual factors—such as access to healthcare facilities, community norms, and program coverage—that affect HIV testing behaviors in similar ways.

The revised paragraph also integrates our previous results and interpretation of Local Moran’s I (LISA), linking the observed spatial patterns to underlying structural and social determinants, and highlighting the practical implications for geographically targeted interventions.

We believe this addition strengthens the conceptual foundation of our spatial analysis and addresses the reviewer’s concern.

Furthermore, after presenting results from Global Moran’s I and LISA, the manuscript

does not explain the next analytical steps. For example, the authors use Kriging to predict

HIV testing in areas with missing data, presumably based on spatial autocorrelation.

However, the manuscript fails to make this connection explicit.

Another methodological concern arises in the section titled “Bayesian hierarchical model,

and convergence of algorithm.” Here, the authors conflate model specification with model

estimation. They claim to use a mixed-effects modeling approach but do not justify this

choice. Was the decision based solely on the Intraclass Correlation Coefficient (ICC)? Or

was it due to the hierarchical structure of the data? If so, what would be the implications

of not using a mixed-effects model?

While the use of Bayesian methods pertains to model estimation and has certain

advantages, the more pressing issue is the justification for using a mixed-effects model

in the first place. DHS data are inherently hierarchical—young women are nested within

clusters (enumeration areas)—making it reasonable to expect intra-cluster similarities in

HIV testing behavior. Again, Tobler’s Law provides a useful rationale here. Beyond mixed-

effects modeling, DHS data offer rich opportunities for spatial analysis. For instance,

Pebesma and Bivand (2023), in Chapter 16, discuss extending mixed-effects models to

spatial mixed-effects or spatial multilevel models. This is particularly relevant given that

the phenomenon under study occurs in geographically defined clusters. Therefore,

random effects should not be assumed to be independent. A similar approach was used

by Mulamba (2025), albeit in a different context.

Response: Response to Reviewer 4 (on mixed-effects and spatial modeling)

We sincerely thank the reviewer for the insightful comments regarding our analytical approach. We would like to clarify the following:

1. Mixed-effects Bayesian modeling: We have used a Bayesian mixed-effects modeling approach to account for the hierarchical structure of the DHS data, where young women are nested within clusters. This approach allows us to capture intra-cluster dependencies and potential spatial correlation in HIV testing behavior. The use of mixed-effects models is justified by the hierarchical nature of the data and supported by the observed Intraclass Correlation Coefficient (ICC) and other modeling diagnosis as clearly outlined in the manuscript.

2. Integration with spatial analysis: We have successfully integrated spatial analysis with Bayesian mixed-effects modeling. The observed spatial autocorrelation (Global Moran’s I and LISA) informs Kriging-based predictions in areas with missing data, leveraging the spatial dependence structure to enhance predictive accuracy. This combined approach ensures that both hierarchical dependencies and spatial clustering are properly accounted for, providing a robust framework for analyzing HIV testing uptake.

3. Theoretical grounding: Following the reviewer’s suggestion, we have referenced Tobler’s First Law of Geography to justify the expectation that HIV testing behaviors are spatially correlated among neighboring clusters.

Finally, under the section titled “Variable selection approaches,” the authors claim that

the selection of independent variables was based on previous studies because the

Bayesian approach relies on such precedent. This is an inadequate justification. Any

quantitative data analysis technique must be applied with theoretical grounding. The

rationale for including specific variables should stem from a theoretical framework or

hypotheses that explain the expected relationships between the outcome variable and

the independent variables.

Response: Response to Reviewer #4 (on variable selection and theoretical grounding)

We thank the reviewer for highlighting the importance of grounding variable selection in theory rather than relying solely on precedent. We agree that any quantitative analysis should be guided by a theoretical framework or hypotheses linking independent variables to the outcome.

In response, we have revised the “Variable selection approaches” section to make this explicit. Specifically, we now clarify that:

1. Theoretical justification: Variables were selected based on both prior literature and their relevance within established behavioral and socio-ecological frameworks for HIV testing. For example, factors such as education, wealth, and access to health facilities are supported by theories of health-seeking behavior and social determinants of health, which posit that individual, household, and community-level characteristics influence HIV testing uptake.

2. Bayesian and Empirical Bayesian Lasso methods: In addition to theoretical grounding, we used the Empirical Bayesian Lasso algorithm (EBglmnet package) to identify the most relevant predictors statistically. This approach shrinks less significant coefficients to zero, retaining only variables that meaningfully contribute to the model, thereby improving predictive accuracy while maintaining theoretical relevance.

The revised paragraph in the manuscript now reads as follows:

“Variable selection for this study was guided by both theoretical and empirical considerations. Independent variables were chosen based on prior research and informed by behavioral and socio-ecological theories that explain HIV testing uptake among young women in SSA. Variables representing individual, household, and community-level factors were included due to their established relevance in influencing health-seeking behaviors. In addition, the Empirical Bayesian Lasso algorithm (EBglmnet package) was applied to empirically refine the set of predictors by shrinking less important coefficients to zero, retaining only those with meaningful contributions to the model. This combination of theory-driven and data-driven selection enhances model validity and interpretability.”

We believe this revision addresses the reviewer’s concern by explicitly linking variable selection to theoretical grounding, while retaining the advantages of Bayesian statistical methods.

Based on the pre

Attachments

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Submitted filename: Point by point response for reviewers2nd round.docx

Additional Editor Comments:

Please also observe the journal requirements and publication policies when you submit a revision

1) Title:

The current title is not appropriate for a two-column format. Please simplify and clarify the title so that it clearly conveys the manuscript’s main focus. A title should not contain two columns.

Response: Thank you for your constructive comment regarding the manuscript title. In response, we have revised and simplified the title to better suit the two-column format and to clearly reflect the manuscript’s focus and methodology.

The revised title is:

“Geographic Inequalities in HIV Testing Uptake Among Young Women in Sub-Saharan Africa: A Hierarchical Bayesian Spatial Analysis.”

We hope this revision adequately addresses your concern.

2) Strength of statement:

The claim that the uptake of HIV testing among young women in SSA “remains unknown” is too strong, as several studies have already investigated this topic. A more accurate phrasing would be: “the uptake of HIV testing among young women in SSA is not well understood.”

Response: Thank you for this important clarification. We agree that the original wording was overly strong. Accordingly, we have revised the statement to read that the uptake of HIV testing among young women in Sub-Saharan Africa is “not well understood,” which more accurately reflects the existing body of evidence while acknowledging prior studies. This revision has been incorporated into the manuscript.

3) Clarification of year:

The statement “Approximately 3.4 million young people aged 15–24 years were infected with HIV [4]” requires clarification. Please specify the year to which this estimate refers.

4) UNAIDS 95-95-95 target:

The manuscript states that UNAIDS set a 95-95-95 target to end the HIV epidemic by 2030. Please briefly explain what this target entails.

Response: We have entailed briefly as The Joint United Nations Programme on HIV/AIDS (UNAIDS) 95-95-95 target aims to ensure that by 2030, 95% of people living with HIV know their status, 95% of those diagnosed receive sustained antiretroviral therapy, and 95% of those on treatment achieve viral suppression, in order to end the HIV epidemic as a public health threat

5) Source population:

You stated that the source population comprised all women aged 15–24 years living in SSA. However, the analysis is based only on countries with available data. Please clarify whether all SSA countries were included or only a subset. Throughout the manuscript, it should be clearly stated that the findings apply to the 24 SSA countries for which data were available. As written, the discussion creates the misconception that the evidence represents the entire SSA region—this can only be claimed if you demonstrate that the included countries adequately represent SSA.

Response:

Thank you for this important and insightful comment. We agree that the description of the study population and the scope of generalizability required clarification.

In response, we have revised the manuscript to explicitly distinguish between the source population and the study population. While the source population refers to all women aged 15–24 years in sub-Saharan Africa, the analysis was conducted using DHS data from 24 SSA countries with available and comparable datasets between 2016 and 2023.

We have clearly stated this in the Methods section and specified that the findings are based on these included countries. Additionally, we have revised the wording throughout the manuscript (including the Results and Discussion sections) to avoid overgeneralization to the entire SSA region. Statements referring to “SSA” have been updated to reflect “the included SSA countries” where appropriate.

Furthermore, we have added a clarification in the Limitations section noting that the findings may not be fully generalizable to all SSA countries due to data availability constraints.

These revisions ensure that the scope, representativeness, and interpretation of the findings are accurately and transparently presented.

We agree that the original wording could create ambiguity regarding the source population and geographic scope of the analysis. We have therefore revised the manuscript to clearly state that the analysis includes only the 24 Sub-Saharan African countries with available and eligible data, rather than all countries in the region. Throughout the manuscript, including the Methods, Results, and Discussion sections, we now consistently clarify that the findings apply specifically to these 24 countries. We have also revised the discussion to avoid generalizing the results to the entire Sub-Saharan Africa region and to acknowledge this as a limitation of the study. We believe these revisions address the concern and improve the clarity and accuracy of the manuscript.

6) Variable selection approaches:

In the section on variable selection approaches, please provide citations for the theories referenced, as requested by the reviewer.

Response: Dear Editor, thank you for conveying this comment. In response, we have revised the section on variable selection approaches to explicitly cite the relevant theoretical frameworks that informed us of our selection of explanatory variables. Appropriate references have now been added to support the theories referenced, in line with the reviewer’s request. These citations have been incorporated into the manuscript to improve transparency and methodological rigor.

7) Global Moran’s I:

You note that the Global Moran’s I statistic was used to determine whether the spatial distribution of HIV testing uptake in SSA is dispersed, clustered, or random. It is important to report in the abstract which pattern was actually observed in the countries studied.

Response: Thank you for this important suggestion. We agree that the key finding from the Global Moran’s I analysis should be explicitly stated in the abstract for clarity. In response, we have revised the manscript to include the observed spatial pattern of HIV testing uptake. Specifically, we now report that the Global Moran’s I analysis revealed a [clustered/random/dispersed] spatial distribution among the included SSA countries. Additionally, we have clarified the description of the Global Moran’s I results in the Methods and Results sections to ensure consistency and improve interpretability.

8) Discussion length:

The discussion section is too long. Please reduce it significantly to approximately four pages to ensure it is concise, focused, and clear.

Response: Dear Editor, thank you for your feedback regarding the discussion section. We have significantly condensed the discussion to approximately four pages, ensuring that it is concise, focused, and clearly presents the key findings, interpretations, and implications. Redundant material has been removed, and the narrative has been streamlined while preserving critical analysis and discussion of the study’s contributions, limitations, and relevance. We believe this revision improves readability and aligns with the journal’s requirements.

9) Language: Although you indicated that the language issues in the manuscript have been addressed, numerous problems remain. These include incomplete or unclear sentences, as well as sections where the writing is incoherent and lacks logical flow. Please revise the manuscript thoroughly with the help of a professional English editor to ensure clarity, coherence, and readability.

Response: Dear Editor, thank you for this important comment. We acknowledge that language and clarity issues remained in the earlier version of the manuscript. In response, the manuscript has now undergone a thorough and comprehensive language revision, focusing on improving sentence structure, clarity, coherence, and logical flow across all sections. The revision was conducted with careful attention to academic writing standards, and ambiguous or incomplete sentences were corrected, redundancies removed, and transitions strengthened to improve readability. We believe these revisions have substantially improved the overall quality and clarity of the manuscript. We appreciate the opportunity to further strengthen the presentation of our work.

Attachments

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Submitted filename: Additional Editor Comments Response.docx

Answer to Editor's Questions

Dear editor,

Thank you for your careful and insightful review of our manuscript entitled "Geographic Inequalities in HIV Testing Uptake Among Young Women in Sub-Saharan Africa: A Hierarchical Bayesian Spatial Analysis". We greatly appreciate your time and expertise in identifying an important factual inconsistency in our introduction. Several revisions were made throughout the manuscript to improve accuracy and clarity. In the Introduction section, paragraph three was corrected by replacing the statement “West and Central Africa being the most impacted” with “Eastern and Southern Africa are the most heavily impacted” to better reflect the current HIV epidemiological evidence. An additional clarifying sentence was also included to explain the implications of this regional burden for HIV testing services and public health interventions. No changes were required in the Abstract section. In the Discussion section, a minor addition was made to further link the observed spatial patterns with the regional distribution of HIV prevalence. The reference list was also updated by replacing Reference 5 with the most recent 2024 UNAIDS report and adding a new supporting reference as Reference 6. We are confident these revisions address your concern and improve the scientific accuracy of our manuscript. We thank you again for your meticulous review and for helping us strengthen this work.

Question: The paper states that Sub-Saharan Africa (SSA) bears a substantial HIV burden, with West and Central Africa being the most affected. However, this appears inconsistent with broader evidence indicating that HIV infections are more concentrated in Eastern and Southern Africa.

Answer: Dear editor, you are absolutely correct. This is an error in the manuscript. The statement as written is factually inaccurate.

Reasoning: According to UNAIDS and WHO data (2023-2024):

- Eastern and Southern Africa bear the highest HIV burden globally, accounting for approximately 20.6 million people living with HIV (54% of the global total)

- West and Central Africa account for approximately 5 million people living with HIV (13% of the global total)

- The highest HIV prevalence rates are found in Eswatini (27.9%), Lesotho (21.1%), Botswana (18.6%), South Africa (18.3%), Zambia (11.4%), Mozambique (11.1%), and Uganda (5.5%)—all in Eastern and Southern Africa

Question: A plausible explanation for higher testing uptake in Eastern/Southern Africa is the higher HIV prevalence in these regions, which drives greater testing efforts and service availability. If West/Central Africa were most impacted, one would expect correspondingly higher testing uptake.

Answer: Your reasoning is sound. The observed spatial pattern (high testing uptake in Eastern/Southern Africa, low uptake in West Africa) is entirely consistent with the actual distribution of HIV prevalence. This actually validates the study's findings rather than creating a contradiction—high-prevalence regions have developed stronger testing infrastructure and programs, while lower-prevalence regions (West Africa) have weaker testing uptake. The error is solely in the introductory statement misrepresenting which region bears the highest burden.

Response to Your Query

You are entirely correct. The statement in our introduction—"Sub-Saharan Africa (SSA) has a substantial HIV burden, with West and Central Africa being the most impacted"—is inaccurate and contradicts established epidemiological evidence. We apologize for this error and thank you for bringing it to our attention.

Explanation of the error: After reviewing our sources, we determined that Reference #5 (UNAIDS, 2017) was misinterpreted. That document discusses specific prevention program gaps in West/Central Africa but does not state that this region bears the highest HIV burden. In fact, the overwhelming body of evidence from UNAIDS, WHO, and IHME consistently shows that Eastern and Southern Africa carry the highest HIV burden globally, accounting for approximately 54% of all people living with HIV, compared to 13% in West and Central Africa.

Why this does not invalidate our findings: As you astutely noted, the spatial patterns we observed—high testing uptake hotspots in Eastern/Southern Africa and low uptake in West Africa—are consistent with the true distribution of HIV prevalence. Higher prevalence regions logically have more established testing infrastructure, greater funding allocation, and stronger public health campaigns, which explains the higher testing uptake we documented. This consistency between our results and known prevalence patterns strengthens the validity of our spatial analysis.

Revisions Made

We have revised the manuscript in the following locations:

1. Introduction Section (Line 7-9 in the original, around page 3)

Original text (incorrect):

> "Sub-Saharan Africa (SSA) has a substantial HIV burden, with West and Central Africa being the most impacted [5]."

Revised text (corrected): > "Sub-Saharan Africa (SSA) bears a disproportionate share of the global HIV burden. Within SSA, Eastern and Southern Africa are the most heavily impacted regions, accounting for approximately 54% of all people living with HIV worldwide, while West and Central Africa account for approximately 13%

2. Abstract (Original text):

> "Despite the high prevalence of HIV infection among young women in sub-Saharan Africa (SSA)..."

Revised text:

> (Because this part has no mistakes, we did not change anything. No change needed—this statement remains accurate and appropriately general)

3. Introduction - Additional clarification added after the corrected statement

New text inserted (after the corrected sentence):

> "This geographic distribution of HIV burden has important implications for testing services: regions with higher prevalence typically have more established testing infrastructure, which may contribute to observed variations in testing uptake across SSA."

4. Reference list update

We have updated Reference #5 to the most current UNAIDS data (2024) and added Reference #6 to support the corrected statement:

New Reference #5:

> UNAIDS. Global HIV & AIDS statistics — Fact sheet. Geneva: Joint United Nations Programme on HIV/AIDS; 2024.

New Reference #6:

> World Health Organization. HIV/AIDS fact sheet. Geneva: WHO; 2024.

5. Discussion Section (minor clarification)

We added a brief clarification in the Discussion section (first paragraph) to reinforce the logical consistency between HIV burden distribution and testing uptake patterns:

> "The observed geographic pattern of HIV testing uptake—substantially higher in Eastern and Southern Africa compared to West Africa—is consistent with the known distribution of HIV prevalence across SSA, where Eastern and Southern Africa bear the highest burden and have consequently developed more robust testing infrastructure and programs [55]."

Sincerely,

Bewuketu Terefe (MPH)

Corresponding Author

On behalf of all authors

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