Evaluating the efficiency of Tehran's healthcare services in the Covid-19 pandemic with the approach of spatial justice

A balanced spatial distribution of urban services is an essential indicator of social justice in the city. Any change in spatial justice has a direct impact on economic and social relations and income distribution in society. The present study aims to analyze the efficiency and inefficiency of the twenty-two districts of Tehran, Iran, in terms of healthcare services for COVID-19 pandemic based on spatial justice. This study is applied-developmental research and adopts a descriptive-analytical methodology. The data included 26 indexes. The data were analyzed using Shannon's entropy, data envelopment analysis (DEA), and the cross-efficiency matrix in ArcGIS and DEA Solver. The twenty-two districts of Tehran were treated as decision-making units. The DEA used the Charnes-Cooper-Rhodes constant returns-to-scale ratio model with an output-oriented approach. Research findings show the residents of the central districts in Tehran had the best accessibility (in terms of distance) to healthcare services. The accessibility of such services reduces in districts far from the central districts. The poor healthcare services and a lack of public adherence to health protection protocols in Districts 19, 15, 3, 21, and 22 increased the rate of COVID-19 infection, while the minimum infection rate was found in Districts 11, 10, 12, 17 and 16 in light of good healthcare services. The results suggest an unfair distribution of healthcare services in Tehran. This arises from polar growth policies where all services are concentrated in one or more areas.