Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States
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Tuesday, 4 February 2014: 9:00 AM
Room C213 (The Georgia World Congress Center )
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. Using meteorological reanalysis data from the National Land Data Assimilation System (NLDAS), we have developed several measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. These measures include daily maximum and minimum air temperatures, daily maximum heat indices and a new heat stress variable called Net Daily Heat Stress (NDHS) that gives an integrated measure of heat stress (and relief) over the course of a day. All output has been created on the NLDAS 1/8 degree (~12 km) grid and aggregated to the county level, which is the preferred geographic scale of analysis for public health researchers. County-level statistics have been made available through the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public.
We have examined the relationship between excessive heat, as characterized by the various daily heat metrics, and heat-related mortality using four different categories defined in CDC's National Center for Health Statistics ‘Multiple Causes of Death 1999-2010' dataset and supplied through the CDC WONDER system. To do this, we linked daily, county-level heat mortality counts with each of the heat metrics nationally for the period 1999-2010. The objective of this analysis is to determine (1) whether heat-related deaths can be clearly tied to excessive heat events, (2) what time lags and heat event durations are critical for predicting heat-related deaths, and (3) which of the heat metrics correlates best with heat-related deaths. Results from this research will potentially lead to improvements in our ability to anticipate and mitigate any significant impacts of extreme heat events on health.