Hospital Accessibility Catchment Areas as a Fuzzy Lattice Data Structure
Keywords: Catchment Areas, Fuzzy Lattice Data, Semi-supervised, Label Propagation, Label Connected
Abstract. The accessibility to basic facilities and services plays a pivotal role in every society and city planning. Spatial accessibility can vary between cities and countries and is mainly defined by the ease at which facilities can be accessed by communities. Facilities can provide essential services and/or products such as pharmacies, clinics, schools, universities, etc. Spatial accessibility is dependent on the spatial impedance between a facility and the target population and can be illustrated with catchment areas. We propose a fuzzy lattice catchment area method which uses a semi-supervised learning algorithm to create overlapping catchment areas. This methodology is applied to determine the accessibility to hospitals in South Africa and provides an illustration on the difference for regions with high accessibility compared to low accessibility. The application can easily be adapted in a variety of fields based on industry type, drive-time thresholds, supply capacity and the target population.