Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment

Abstract

Medical facilities are an important part of urban public facilities and a vital pillar for the survival of citizens at critical times. During the rapid spread of coronavirus disease (COVID-19), Wuhan was forced into lockdown with a severe shortage of medical resources and high public tension. Adequate allocation of medical facilities is significant to stabilize citizens’ emotions and ensure their living standards. This paper combines text sentiment analysis techniques with geographic information system (GIS) technology and uses a coordination degree model to evaluate the dynamic demand for medical facilities in Wuhan based on social media data and medical facility data. This study divided the epidemic into three phases: latent, outbreak and stable, from which the following findings arise: Public sentiment changed from negative to positive. Over half of the subdistricts in three phases were in a dysfunctional state, with a circular distribution of coordination levels decreasing from the city center to the outer. Thus, when facing major public health emergencies, Wuhan revealed problems of uneven distribution of medical facilities and unreasonable distribution of grades. This study aims to provide a basis and suggestions for the city to respond to major public health emergencies and optimize the allocation of urban medical facilities.

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

“…The problems generated by the space planning of medical facilities in urban areas and the existing theoretical gaps have motivated the development of medical facility planning studies in recent years in Wuhan and other cities. 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].…”