PNTD-D-26-00625

Climate-driven spatiotemporal dynamics of Aedes infestation and dengue transmission in Porto Alegre, Southern Brazil.

PLOS Neglected Tropical Diseases

Dear Dr. Cupertino de Freitas,

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Quanhui Liu, Ph.D.

Academic Editor

PLOS Neglected Tropical Diseases

Audrey Lenhart

Section Editor

PLOS Neglected Tropical Diseases

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

orcid.org/0000-0003-4304-636XX

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

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5) In the online submission form, you indicated that Entomological data from MosquiTRAP surveillance were obtained under institutional agreements and ethical approval from the Research Ethics Committee of the Municipal Health Department of Porto Alegre (CEP SMSPA). Due to these restrictions, raw data are not publicly available. Data can be made available from the corresponding author upon reasonable request and with permission from the relevant authorities.. All PLOS journals now require all data underlying the findings described in their manuscript to be freely available to other researchers, either

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Reviewers' Comments:

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: The study is methodologically sound, addresses a relevant and timely question, and uses an impressive, high-resolution dataset (2018–2025) from a under-studied temperate region.

Reviewer #2: To the best of my knowledge, the methods are appropriate for addressing the proposed research questions.

Reviewer #3: The study design is generally appropriate for exploring the associations among climate, Aedes infestation, and dengue incidence. However, several methodological issues should be addressed. The methods are promising, but stronger justification, validation, and adjustment for key population factors are needed to support the conclusions.

First, the proposed Vector-Fitness Infestation Index (VFII = MFAI × Index P) needs stronger justification and validation. The authors should explain why a multiplicative index was used and whether the two components were standardized. They should also compare models using MFAI alone, Index P alone, and VFII to demonstrate whether VFII provides additional predictive value.

Second, the description of the LASSO models might be over optimistic. Additional performance metrics, such as MAE, R², calibration measures, and prediction intervals, should be reported. Because the data are time-series data, random ten-fold cross-validation may cause temporal information leakage. A time-based validation strategy, such as train-test split by year or rolling validation, might be more appropriate.

Third, the dengue models do not account for population size or population distribution. Since dengue burden is strongly affected by the exposed population, the authors should clarify whether case counts or incidence rates were modeled and whether population size was included as an offset, covariate, or standardization factor.

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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: The results are scientifically sound and support the conclusions, but figure quality and a few missing analytical details reduce clarity.

Reviewer #2: The results are meaningful and well presented throughout the manuscript. I have one comment that may induce an extension of the analysis:

One of the key results was the stronger association between variables with higher lag. This was observed both between climatic variables and mosquito abundance (Table 1 all variables except for Ae. aegypti vs precipitation) and between mosquito abundance and dengue incidence (Table 2, all variables). Since the analysis was performed for lags between 0 and 4 weeks, I was left wondering if maximum correlation is reached at 4 weeks of lag, of if it keeps increasing at higher lags - which would be somewhat striking as a result.

Would it be possible to extend the analysis for a few extra weeks of lag (even as a Supplementary analysis/table)? That could help readers with the same question I had when reading. If not feasible, please describe the reasons so readers understand the limitation of up to 4 weeks.

Reviewer #3: The results generally match the analysis plan described in the Methods. The authors present the entomological surveillance results, spatial clustering analyses, climate–mosquito associations, dengue incidence patterns, and predictive modeling results in a logical order.

However, several minor issues should be addressed to improve clarity. First, the legend of Fig 2 is not sufficiently clear, and the figure legend should more explicitly explain what the mapped values represent. Second, Table S6 appears to use commas instead of decimal points in some numerical values. This should be corrected for consistency and readability.

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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: The conclusions are largely supported by the data, and the public health relevance is clearly articulated.

Reviewer #2: The discussed conclusions are supported by the presented results.

I only recommend authors to include a paragraph describing study limitations in the discussion, disclaiming any points that readers should be aware of before generalizing the result (e.g. single study site, data collection biases, etc.).

Reviewer #3: The main conclusions are generally supported by the data presented. The manuscript clearly discusses how integrated climatic, entomological, and epidemiological surveillance data can improve our understanding of dengue risk in a temperate urban setting. The public health relevance is also well addressed, particularly regarding early warning, targeted vector control, and resource allocation.

However, the conclusions related to Ae. albopictus should be stated more cautiously. The number of Ae. albopictus captured was much lower than that of Ae. aegypti, which may limit the robustness of correlation and modeling results for this species.

In addition, the limitations of the analysis could be described more explicitly, particularly regarding model validation, possible reporting bias in dengue surveillance data, and the absence of population-related covariates.

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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: Minor Revision

The manuscript is scientifically sound and well-organized. The required changes are primarily editorial (typos, diacritical marks, formatting) and data presentation improvements (figure alignment, table restructuring, supplementary table clarity).

Reviewer #2: I have no recommended editorial or data modifications.

Reviewer #3: Minor Revision

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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 manuscript by Silva and colleagues investigates the spatiotemporal relationships between climatic variables, Aedes mosquito infestation, and dengue incidence in Porto Alegre, Brazil, from 2018 to 2025. The study integrates high-resolution entomological surveillance data with climatic data and dengue case reports, employing spatial autocorrelation, Kendall correlation, polynomial regression, and LASSO regression. Overall, the study is methodologically sound and addresses a timely and relevant question. The dataset is rich, the analytical approaches are largely appropriate, and the public health implications are clearly articulated. However, several issues need to be addressed. In particular, the clarity of the presentation and the quality of the figures require improvement, as summarized below:

1. ”climatic surveil in Porto Alegre" in Line 58 --"climatic surveillance in Porto Alegre"

2. Please check the usage of 'Gloria' and 'Glória' in this manuscript and ensure consistent spelling throughout.

3. Please check the usages in this manuscript and ensure consistent spelling throughout, for example, mosquitoes and mosquitos.

4. Panel labels (a, b, c, d) are present in figure 1 but not clearly distinguished from figure content. Also, check other figures.

5. Panels A, B, C are misaligned with the x-axis labels (0-5, 0-10, etc.) in figure 4. Please fix the layout.

6. The Methods section describes the use of ANOVA, but no related results are reported in the Results section.

Reviewer #2: The manuscript describes a spatiotemporal analysis of Aedes species abundance and dengue incidence along with climate and land cover data, with focus on the Brazilian municipality of Porto Alegre. The study addresses a current and relevant issue, given the health burden created by the spatial expansion of dengue in the Americas. The manuscript is overall well written, well structured, and fits the scope of PLOS Neglected Tropical Diseases.

Reviewer #3: This manuscript uses entomological surveillance, climatic data, and dengue case data from Porto Alegre between 2018 and 2025 to investigate climate-driven Aedes population dynamics and their relationship with dengue transmission. The authors also developed LASSO-based predictive models. The topic falls within the scope of PLOS NTD and has clear public health relevance.

However, its main findings, including the positive association between temperature and mosquito abundance, the influence of rainfall on mosquito density, and the several-week lag between mosquito indices and dengue cases, are broadly consistent with existing literature. The authors should further clarify the novelty of the study and strengthen the model construction, causal interpretation, and evaluation of predictive performance.

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Reviewer #2: No

Reviewer #3: No

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Dear Ms Cupertino de Freitas,

We are pleased to inform you that your manuscript 'Climate-driven spatiotemporal dynamics of Aedes infestation and dengue transmission in Porto Alegre, Southern Brazil.' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

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Best regards,

Audrey Lenhart

Section Editor

PLOS Neglected Tropical Diseases

Audrey Lenhart

Section Editor

PLOS Neglected Tropical Diseases

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

orcid.org/0000-0003-4304-636XX

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

orcid.org/0000-0003-1765-0002

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