Accessibility calculation and equality evaluation of medical facilities for COVID-19 pandemic treatment: A case study of the Wuhan metropolitan development zone

Abstract

Medical facility equality is a critical metric for determining equal access to medical care. Their spatial distribution is important for effective pandemic treatment and daily prevention in cities. This paper used the Kernel Density Two-Step Floating Catchment Area (KD2SFCA) and shortest distance methods to calculate the accessibility of designated COVID-19 Fangcang hospitals and fever clinics in the Wuhan Metropolitan Development Zone. Their equality was evaluated by the Gini coefficient and Lorentz curve. Several results were obtained: (1) The facilities’ accessibility declines radial from the central to peripheral areas. (2) Most of the demand points in the study area can reach the medical facilities for COVID-19 pandemic treatment within 60 minutes. (3) For the spatial distribution of these facilities, the equality evaluated for different time thresholds differed significantly, with long time thresholds having better equality than for short time thresholds. (4) While the distances distribution of fever clinics is balanced, the equality gap in various areas remains enormous when considering population distribution. Suggestions for optimizing the spatial distribution of pandemic treatment medical facilities in Wuhan are proposed, and which will serve as references for the planning of Wuhan’s pandemic medical facilities in the future.

A Community-Oriented Accessibility Index of Public Health Service Facilities: A Case Study of Wuchang District, Wuhan, China

“…In this regard, it is important to highlight the alignment of this paper with the findings of Shen, X. [6], which emphasize enlarging the scale of facilities and increasing the number of doctors and nurses according to population density to meet the medical needs. At present, research related to medical facility planning in Wuhan focuses on urban suburbs or new urban areas, all with the goal of ensuring the equitable and optimal allocation of limited resources [28].…”

“…A recent study combined text sentiment analysis techniques with geographic information system technology and used a coordination degree model to evaluate the dynamic demand for medical facilities in Wuhan based on social media data and medical facility data [5]. The Kernel Density Two-Step Floating Catchment Area (KD2SFCA) and shortest distance methods were used to calculate the accessibility of designated COVID-19 Fangcang hospitals and fever clinics in the Wuhan Metropolitan Development Zone [6]. These works proposed methods of evaluating instruments for the government and urban planners that aim at the planning of the urban distribution of medical facilities.…”

An analysis of the spatio-temporal behavior of COVID-19 patients using activity trajectory data

“…As a result, numerous research projects using GIS for spatiotemporal analysis have emerged. These studies have included building an outbreak big data information system [ 5 ], using mobile data to explore spatial and temporal trends in COVID-19 transmission over time [ 7 , 8 ], predicting or simulating COVID-19 transmission [ 9 , 10 ], examining the association between COVID-19 transmission and other variables [ 11 , 12 ], and assessing the current status and supply-demand balance of health resources and health care delivery systems [ 13 , 14 ]. Through geospatial analysis, these studies have assessed the dynamics and trends of the COVID-19 pandemic and provided varying degrees of support for pandemic prevention and control, as well as the deployment and transportation of pandemic preparedness items.…”