Modeling multimodal access to primary care in an urban environment

Abstract

Access to primary health care facilities is a key component of public health, and measuring that access is vital to understanding how to target interventions. Transportation is one dimension of access and measuring distance via multiple modes allows better understanding of how varied populations access health care, particularly those who do not have access to a personal vehicle. This work builds on the 2-Step Floating Catchment Area (2SFCA) method to include travel by car, bus, bicycle, and walking. Travel time data are sourced from OpenStreetMap and transit data incorporates stop and schedule information from the General Transit Feed Specification (GTFS). Open source data analysis tools are used to aid reproducibility in other geographic contexts. Modal weights are assigned to measure the population accessing each facility by each mode. Access values for Milwaukee County in Wisconsin, USA are presented, with clear differences shown among modes accessing primary healthcare. Car access is high and consistent across the county, while biking and walking access are more impacted by distance to destination. Transit access is unequal across the county with some tracts showing no access at all. The highly varied access results by mode emphasize the importance of measuring access and travel by non-car modes, particularly when targeting communities with high rates of no car ownership. Improvement of multimodal access measurement will allow for targeted interventions that account for the availability of modes in each community.

Keywords

• Spatial accessibility
• Spatial equity
• Primary healthcare
• 2-Step floating catchment area (2SFCA)
• geographic information system (GIS)
• Multimodal network