Completed on 5 Feb 2015 by Jing Helmersson.
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This paper “The seasonal reproduction number of dengue fever: Impacts of climate to transmission” has a clear introduction and background and the relevant literature referenced.
Figures are relevant to the content of the article and structure follows the acceptable format.
The English needs substantial work to make it clear and readable both grammar and missing information. See colored marks and comments on the pdf file.
This study carried out original primary research within the Aims & Scope of the Journal. The research question on climate dependent dengue reproduction number is relevant and meaningful to the health field. The modelling is conducted rigorously under certain assumptions about reality. As usual, model is not reality but representation of certain aspects of reality. The methods are described with sufficient information after corrections to be made as pointed out in the attached pdf file. The research is modelling, more theory than experiment and thus is conducted in conformity with ethical standards.
The Author showed seasonal dependent Aedes aegypti population as a function of time based on both constant and monthly average of Chiang Mai, Thailand’s temperature over the recent 10 years. The result captured the one month delay of the adult mosquito’s population (peaked at 209 days) relative to the immature mosquito (peaked at 180 days). This seems similar to the dengue case profile. It is hard to compare when using “days” for the model’s output and “month” for the dengue cases. It would be easier to compare if the author converts all the time unit from days to months or show both units. This may be done by plotting Figure 2 in two time scales, such as, Figure 2A as it is now and Figure 2B using months for time.
The author showed the reproduction number Rs as a function of temperature and time – the seasonality and stated “The greatest potential of dengue transmission occurs at temperature equal to 28.7ºC. The seasonal reproduction numbers was 0.62-3.05, above unity from February to November and reached the peak in July.” This is very interesting. However, Figure 3B showed that the peak is in June, about 180 days. It is hard to understand why the peak of Rs does not match that of the adult vector population but the immature vector. Please recheck the calculation and discuss the reason for the differences.
Overall, this paper contains new results that are relevant in the dengue research field. Temperature dependent parameters have not been so widely used in the past in dengue modelling especially for the tropical dengue endemic areas. Therefore, giving the climate change situation, it is important to carry out this type of Mathematical modelling on dengue epidemic potential even for dengue endemic areas in order to support the effort on dengue early warning and policy for dengue vector control. The result is worth of publication after carefully checking for missing details, consistency, and English, especially answering the above point regarding Figure 3B.