In order to prepare for extreme heat, Americans need to be aware that it is a serious threat to human health. Using a 0 – 100 scale (where 0 = no perceived risk from extreme heat & 100 = maximum risk), this tool maps how Americans perceive the health risks of extreme heat events (heat waves) at the state and county level in the U.S. Higher values indicate that people perceive greater risks from heat waves to their own health, the health of their families, and the health of their local communities. More detailed maps (on the next tab) show census tract-level geographic variations in risk perceptions for the 100 most populous US counties. The data underlying these maps are publicly available at no cost for download on the “Data” tab.
Risk perception estimates are produced using a statistical model based on national survey data (n = 9,217). The heat risk perception index ranges from 0 to 100, with higher values indicating higher risk perceptions. People with higher risk perceptions were 1) more likely to think that a heat wave would occur in their community; 2) more likely to think that a heat wave, were it to happen in their community, would affect the health of themselves, their family, and others in their community; and 3) more worried about the effects of heat waves.
For details and to cite these data, please refer to the following paper:
Howe, Peter D., Jennifer R. Marlon, Xinran Wang, and Anthony Leiserowitz. “Public perceptions of the health risks of extreme heat across U.S. states, counties, and neighborhoods.” Proceedings of the National Academy of Sciences. Available online at https://www.pnas.org/lookup/doi/10.1073/pnas.1813145116.
An additional interactive data visualization of geographic variations in heat wave risk perceptions at the census tract to state level is also available here.
This research was supported by a grant from the National Science Foundation Decision, Risk, and Management Sciences program (SES-145990), led by Peter D. Howe (Utah State University) and Jennifer R. Marlon (Yale University).
This site provides estimates of how Americans perceive the health risks of extreme heat events at the state, county, and census tract level. The estimates are derived from a statistical model using multilevel regression with post-stratification (MRP) on a large national survey dataset (n=9,217), along with demographic and geographic population characteristics.
The survey data were collected from a U.S. national sample in 10 waves at two-week intervals during Summer 2015 using a probability-sampled online panel, the GfK Knowledgepanel.
We validated these results by comparing model estimates against independently conducted surveys in two randomly selected census tracts and eight randomly selected states. Compared against the two tract-level surveys, the mean absolute error of our MRP model estimates was 2.7 points. Compared against the state-level surveys, the mean absolute error of the MRP model estimates was 1.6 points, and the correlation between the two datasets was 0.82. Since the underlying survey data are distributed by population, estimates for geographic areas with larger populations are likely to be more accurate than those for smaller populations. Likewise, estimates at broader geographic scales (states and counties) tend to be more accurate than those at finer scales (census tracts).
For more details and to cite these data, please refer to the following paper:
Howe, Peter D., Jennifer R. Marlon, Xinran Wang, and Anthony Leiserowitz. “Public perceptions of the health risks of extreme heat across U.S. states, counties, and neighborhoods.” Proceedings of the National Academy of Sciences. Available online at https://www.pnas.org/lookup/doi/10.1073/pnas.1813145116.
The original US survey data from this NSF-supported research is available via the Utah State University Digital Commons and also via the Open Science Framework Project Page.