Review Report Form - Reviewer 1
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Comments and Suggestions for Authors
Evaluating the utility of downscaled heat indices for climate and health studies
The study critically evaluates downscaled Global Climate Models (GCM) for human health
applications. Specifically, the study compares the ability of two statistical downscaling methods
and GCM to reproduce historic climatic conditions. The downscaling methods differ in their
ability to reproduce the seasonality and other important temporal patterns such as sequential
daily temperature values. The study discusses important considerations for public health
practitioners using GCM.
Major Comments

There are strong mechanistic linkages between temperature and Salmonella spp.
reproduction and the number of new human cases. However, no published study linked
heat indices with Salmonella infections. On the contrary, some published studies
suggest humidity is not related to Salmonella infections (Kovats 2004). Although the
metrics are related, focusing on the heat index detracts from and weakens the study’s main
message. While heat indices are associated with maximum temperatures, this is not a great
reason for using an indirect measure of Salmonella risk.
RESPONSE: We agree with the reviewer that no studies have linked
occurrences of Salmonella infections with the type of a heat index that is an indicator of the
combined effects of temperature and humidity on the human body and which attempts to
estimate how a person would feel when his/her body is impacted by high humidity levels in
addition to high temperatures and thus the opportunities for the body to cool itself through
perspiration and subsequent evaporation of the sweat are diminished. That is why in our study
we do not use such type of a heat index. We use a set of temperature-based heat indices that
have been defined by us in table XX, and which indicate that a hot day or night are occurring
within a given time period.
The authors should either:
1) Report the differences between average daily-weekly temperatures produced by the
downscaling methods instead of heat indices.
RESPONSE: We have included a short evaluation of the correlation between the
occurrence of hot days within a week, as indicated by the temperature-based heat indices, and
the mean weekly temperatures in order to support our choice of the listed heat indices. The
results from the evaluation indicate that the number of hot days in a week can be a reasonable
proxy for high average weekly temperatures which have been linked to occurrences of
Salmonella infections.
2) Remove or substantially alter the paragraph starting at line 555 in the Results and
Discussion section. Specifically, “The shortcomings of climate models in representing the HD30
variability on intra- and inter-annual time scales are large enough and they may overwhelm the
subtleties of the Salmonella relation to temperature.” This statement is too speculative. The
study would need to report how existing statistical relationships between temperature and
Salmonella infections may be altered by projected climatic changes.
RESPONSE: We agree that this statement could be considered somewhat
speculative and will reword the statement.
If we were to explore the potential future changes in Salmonella infections due to climate
change and projected increases in temperature, we would have considered the assumption that
the statistical relationship would have remained unchanged and based on the potential changes
in future occurrences of hot days we would have commented on our expectation of the changes
in occurrences of Salmonella infections in a future world. Since the focus of this study, however,
is rather to present considerations for and an example of a historical evaluation of the utility of
temperature-based heat indices obtained from downscaled data, we do not explore the potential
future changes in Salmonella infections due to changes in temperature.

The study must explicitly discuss 1) the specific type of reported heat indices (e.g. National
Weather Service and 2) how the heat indices were calculated.
RESPONSE: We have included detailed information about the definition of the
heat indices that we have used and how they were calculated. Again, please note that the
indices we are using do not have anything to do with the type of a Heat index calculated as a
combination of temperature and humidity.

Similarly, it is unclear why the study analyzed days above a heat threshold. In
some international locations, the only temperatures above a threshold increase
Salmonella risk.
Please explicitly state whether the heat indices correspond to
empirically derived threshold in specific countries. If they do not, the authors should
explicitly state they are presenting a hypothetical measure of risk. This is an important
distinction since the results focuses on days above a threshold. In general, the average
weekly temperature is more important than days above a threshold.
RESPONSE: Our goal was to highlight the utility of temperature-based
heat indices calculated from two widely available downscaled datasets to represent
adequately the potential for Salmonella occurrences. We based our analyses not on the
actual daily temperature data but on the easily available calculated indices, as means to
simplify the evaluation approach. The heat indices that we are using do not match any
empirically derived thresholds that could be linked to Salmonella occurrence, however,
one of the motivations for choosing HD30 was that the 30°C threshold was biologically
relevant for salmonella and other infections. We wanted to consider a threshold above
which the potential for occurrence of Salmonella infections could become a serious
public health concern. We understand the reviewer's concern and we will make a
note in the text regarding these indices being rather a hypothetical measure of
risk. Finally, thresholds of 30° and 35°C are used often in climate impacts studies. In
addition, the CDC has used HD35 to project potential future climate impacts on human
health.

How is the selection of the study areas based on temperature and mortality
relevant for selecting Salmonella spp. study areas? The authors state: “These
locations were chosen to support the goals of assessing and modeling population
vulnerability to climate change in cities with strong associations between temperature
and mortality and in which we had pre-existing connections with community and
governmental stakeholders.” The processes how temperature promotes
Salmonella
infections are very different than the process where temperature increases heat
mortality.
RESPONSE: We agree with the reviewer that the processes of how
temperature promotes Salmonella infections are very different compared to the process
in which temperature contributes to increases in heat mortality. While the study areas
were selected initially as focus areas of heat impacts studies, at a later stage of our
investigation we decided to research the potential for use of climate information in
relation to Salmonella infections in these same areas using our general understanding
about the relationships that have already been established between Salmonella
infections and temperatures in the US and around the world.

What was the rationale for focusing on the months of April to September? Most
temperature and Salmonella infection studies analyze cases throughout the entire
year.
RESPONSE: Given that this study is an example of how to use GCM
downscaled data in an informed way rather than a complete epidemiological study for
these areas, we focus on the warm season since recent research has shown that the
peak of disease followed the annual peak in daily temperature with a lag of 2-14 days
(Naumova et al. 2007).

The units of the boxplots (Figures 3-5) should be rescaled to more accurately
depict range of the data. Perhaps restricting the y-axis units to -5 to 5 ?
RESPONSE: We have tried different scales and the finer scales
somewhat artificially enhance the differences between the downscaled GCM data and
the observed data which are quite minimal and usually between 1-3 days. We will
make an attempt to plot the box plots using a different scale, as the reviewer
suggests but we reserve the right to make the decision for the final plots.
Minor comments:
What version of R did you use?
RESPONSE: The version of R we used is: R v.3.2.1. We will add this detail to the
manuscript.
Date & Signature
Date of manuscript submission
19 Aug 2015 04:40:57
Date of this review
02 Oct 2015 02:02:26