Maps highlighting county-level variation in disability prevalence and the risk of natural disasters
In this series of interactive maps, we highlight county-level variation in disability prevalence and the risk of natural disasters. The increase in frequency and intensity of natural disasters such as hurricanes, wildfires, and extreme cold weather events have focused attention to the disproportionate vulnerability of certain populations, such as people with disabilities, to natural hazards.
The map on the left displays county-level variation in the overall disability prevalence, as well as for a number of demographic subgroups (race, ethnicity, gender, age, and impairment type).
The map on the right displays the results from a spatial analysis that examines county-specific relationships between the risk of natural disasters and the prevalence of disability. The map helps to describe whether people with disabilities are more or less likely to live in counties with a higher risk of natural disasters. The values, which are derived from a statistical model called Multiscale Geographically Weighted Regression (MGWR), represent how the risk of natural disasters (measured using the Expected Annual Losses) would expect to change with a one percent increase in the prevalence of disability. The methodology for this analysis is described in a forthcoming journal article.
Use the dropdown options below, or click on a state on the map, to select a series and a county of interest. To compare a county-specific statistic to its state-level result, select a state and then hover over the counties on the map or download the data.
Data Sources: We measure the percent of people with disabilities and subgroups using the American Community Survey 2015-2019 5-year estimates. The Expected Annual Losses hazard risk data come from Federal Emergency Management Agency’s 2020 National Risk Index.
Notes: N/A implies that the sample size was too small in the county to derive an estimate from the Multiscale Geographically Weighted Regression (MGWR) model. The Expected Annual Losses scores run from 0-100, wherein values closer to 100 imply higher expected losses due to natural hazards.
For further inquiries, please contact Amal Harrati.
We’d like to acknowledge Huihua Lu for her contribution to the development of these maps.
