geospatial data sets within analyses of travel time to services or catchment modeling, key constraints of health care accessibility can be quantified (Cattaneo, Nelson, & McMenomy, 2021; Weiss et al., 2018, 2020).

A research agenda focused on assessing health care disparities could proceed by adapting the URCA or FEA approaches to health care. With 90 percent of the world population living either in urban areas or within one hour of an urban center, better understanding of the distinct challenges in access to quality health care faced by populations in urban and peri-urban areas as well as rural areas is required. For instance, in many situations, it may make more sense to think of the URCA or FEA as the relevant catchment area and the health care facilities contained within it as the health care system, rather than considering the catchment area of a single health care facility. Researchers may choose between the two global data sets depending on the focus of their analysis, with FEA data more geared to urban planning and URCAs having a better coverage of rural areas and towns with fewer than 50,000 people. The exhaustive geographic coverage of the URCA approach would allow researchers to associate health care gradients with administrative-level data or survey data suitable for assessing the contextual factors described above. This approach is similar, in principle, to the many applications of the RUCC in the United States in the area of health care (Cyr, Etchin, Guthrie, & Benneyan, 2019). The novelty of the URCA data set for RUCC-like applications is that data are available for any country in the world, and at a level of granularity that can be matched to any administrative level, as we illustrated with the example on poverty levels in Nigeria in Section 3.3. This would then make it possible to provide policy makers with holistic results that lead to more informed resource allocation decisions. It would also enable benchmarking across countries.

A further area of research stems from the scarcity of data characterizing specific health care services provided at known facility locations. While initial efforts have mapped travel time to basic health care globally (Weiss et al., 2020), comprehensive assessments of the availability of specific health care services, such as care for child birth or the treatment of HIV/AIDS, are less common due to lack of data. This knowledge gap represents a substantial opportunity for enumerating and ultimately addressing disparities in health care access. Where high-quality data are available, such as the Malawi 2013-14 Service Provision Assessment (Ministry of Health (MoH) [Malawi] & ICF International, 2014), analyses quantifying spatial disparities in access to services such as pediatric emergency care are possible (Hulland et al., 2019).

Additional research that would inform assessments of disparities in health care include those focused on characterizing health care-seeking behaviors and improving the quality, completeness, and timeliness of data captured in national health care information systems. Refining our understanding of health care-seeking behavior and preferences is required for understanding how far people are willing to travel to seek care (Noor et al., 2006), how care-seeking behavior varies according to the health care service required (for example, because of the desire for privacy), and which facilities care-seekers will utilize (e.g., hospitals vs clinics). Estimating these parameters will require detailed surveys that catalogue patient behavior while also capturing their movements through detailed travel histories or GPS-equipped mobile devices. Methodologically, assessments of care-seeking may draw upon health care catchments modeling (Arambepola et al., 2020; Gao et al., 2016), which could potentially be approximated using URCA or FEA data. Lastly, continued improvement of health care information systems will be critical for accurately estimating the causes and spatial patterns of morbidity and 23