A GRAVITY MODEL FOR ASSESSING SPATIAL INEQUALITY IN ACCESS TO HEALTHCARE SERVICES: A CASE STUDY OF SVERDLOVSK OBLAST
S.V. Begicheva
Ural State University of Economics, Yekaterinburg, Russia
Keywords: potential spatial accessibility, gravity model, healthcare, regional economy, territorial inequality, medical and economic risks, typology of municipalities, accessibility index
Abstract
This article addresses the issue of territorial inequality in access to healthcare services in Sverdlovsk Oblast of Russia. The research hypothesis is that a modified gravity-based model of potential spatial accessibility, with an empirically calibrated distance decay parameter λ , can identify stable territorial disparities in structural inaccessibility of healthcare and associated medico-economic risks, statistically linked to staffing, logistical, and institutional constraints at the municipal level. The aim of the study is to develop a model for evaluating potential spatial accessibility that accounts for territorial heterogeneity and disparities in healthcare resource availability. To achieve this, a modified gravity model was applied, incorporating double normalization and empirical calibration of the distance decay parameter λ . The accessibility index Ai was calculated for 65 municipalities in Sverdlovsk Oblast. These values were used to classify territories into three accessibility levels: high, moderate, and low (risk zones). The results reveal consistent differences among these groups in terms of physician availability, frequency of medical consultations, and medical-economic indicators. Low accessibility in several municipalities is associated with structural inaccessibility, reflected in reduced disease detection rates, fewer preventive visits, uneven distribution of workload among healthcare professionals, and rising local economic losses. These findings are supported by statistical analysis. The proposed model can be applied for monitoring healthcare accessibility, guiding workforce and investment priorities, adjusting patient routing, and informing intergovernmental fiscal policies. The Ai index may serve as an indicator of territorial vulnerability and the resilience of local healthcare systems.
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