Cooling centers have played a significant role in reducing the risks of adverse health impacts of extreme heat exposure. However, there have been no comparative studies investigating cooling center preparedness in terms of population coverage, location efficiency, and population coverage disparities among different subpopulation groups. Using a catchment area method with a 0.8 km walking distance, we compared three aspects of cooling center preparedness across twenty-five cities in the U.S. We first calculated the percentage of the population covered by a single cooling center for each city. Then, the extracted values were separately compared to the city’s heat indexes, latitudes, and spatial patterns of cooling centers. Finally, we investigated population coverage disparities among multiple demographics (age, race/ethnicity) and socioeconomic (insurance, poverty) subpopulation groups by comparing the percentage of population coverage between selected subpopulation groups and reference subpopulation groups. Our results showed that cooler cities, higher latitude cities, and cities with dispersed cooling centers tend to be more prepared than warmer cities, lower latitude cities, and cities with clustered cooling centers across the U.S. Moreover, older people (≥65) had 9% lower population coverage than younger people (≤64). Our results suggest that the placement of future cooling centers should consider both the location of other nearby cooling centers and the spatial distribution of subpopulations to maximize population coverage and reduce access disparities among several subpopulations.

Community-wide vaccinations would be the most effective way to end the COVID-19 pandemic, and accessing vaccination sites would be central in this nexus. Given that the number of COVID-19 vaccines was limited to certain groups of people in the early phases of vaccine distribution, age-based prioritization may have overlooked differences in income levels and the races/ethnicities among older populations. In this vein, using two spatial accessibility measures based on spatially disaggregated hexagons, this paper assesses the disparities in spatial accessibility to vaccination sites with consideration of older populations’ (65+) income levels and their races/ethnicities at the state and the county level. To evaluate the disparities and identify counties with the greatest disparities, a non-parametric two-sample Kolmogorov–Smirnov test at the state level and the $G_i^{\ast }$ statistic at the county level are implemented. The findings of this study indicate that older blacks, older Hispanics, and older populations below the poverty level had better access compared to older whites, older non-Hispanics, and older populations above the poverty level, respectively, at the state level, whereas access disparities varied at counties and geographic locales. We thus conclude that policymakers should take into account older populations’ income levels and races/ethnicities for vaccine prioritization and should pay attention to counties with relatively high disparities in spatial access to vaccines.