Association Between Legionnaires’ Disease Incidence and Meteorological Data by Region and Time on the Island of Crete, Greece

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Comments to the Author

Manuscript ID - water-3772975

The manuscript of Efstathios Koutsostathis et al., entitled "Association between Legionnaires' disease incidence and meteorological data by region and time in the island of Crete, Greece” is a statistical analysis of Legionnaires disease depend on various meteorological data using machine learning techniques. The authors have been used Poisson and the Negative Binomial (NB) models to investigate the data. The objectives of the manuscript are clear; but the current form of the manuscript is not sufficient to publish in this journal.

 

1. Why authors have been used particularly Poisson and the Negative Binomial (NB) models in this analysis.
2. The TALD affected mostly on male people. What is the reason for that. Explain it.
3. Rewrite the last line of the abstract.
4. In some cases, temperature is most important factor for this TALD; and some cases is not. Explain it.

 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In this article by Koutsostathis et al., the authors study the occurrence of Legionnaires’ disease in Crete from January 2000 to December 2022. The authors have obtained seasonal, temperature, wind, and regional metadata for these years to find correlation between these variables and LD. Here are some comments which I believe will make this article more appealing to the public.

I would suggest the authors to add current epidemiology of LD and TALD in the Introduction section. It will be good to have a comparison on the disease statistics worldwide vs in Crete, to add significance to this study. Is LD currently a public health concern in the island of Crete? Based on Table 1, it does not seem that the number of cases is increasing every year from 2000 to 2022. So why did the authors chose to perform this study? I believe currently this study is lacking significance because similar studies have been published in the past. The authors need to emphasize in the Abstract and Introduction sections why this study specifically needed to be conducted and presented to the public (additional to safety of residents and tourists on Crete). .

In the results sections "year effects", "seasonal effects" and regional effects", kindly add a short description on why 2022, autumn, and Chania were chosen as the references?

Under results section "Environmental variables", Figures 1, 2, and 3 are mislabelled. In Figure 2, graphically it does not seem that there is a significant correlation between Tmax and number of cases, especially because the Tmax does not vary much year-wise. Maybe adding a seasonal or monthly Tmax (cumulative of all years) correlation analysis with number of cases will be more valuable. That will also increase the sample size. The Tmax and number of cases can then be plotted on x- and y- axis respectively, to determine if there is any linear/logarithmic correlation.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

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Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf