Distribution of COVID-19 Morbidity Rate in Association with Social and Economic Factors in Wuhan, China: Implications for Urban Development

Abstract

Social and economic factors relate to the prevention and control of infectious diseases. The purpose of this paper was to assess the distribution of COVID-19 morbidity rate in association with social and economic factors and discuss the implications for urban development that help to control infectious diseases. This study was a cross-sectional study. In this study, social and economic factors were classified into three dimensions: built environment, economic activities, and public service status. The method applied in this study was the spatial regression analysis. In the 13 districts in Wuhan, the spatial regression analysis was applied. The results showed that: 1) increasing population density, construction land area proportion, value-added of tertiary industry per unit of land area, total retail sales of consumer goods per unit of land area, public green space density, aged population density were associated with an increased COVID-19 morbidity rate due to the positive characteristics of estimated coefficients of these variables. 2) increasing average building scale, GDP per unit of land area, and hospital density were associated with a decreased COVID-19 morbidity rate due to the negative characteristics of estimated coefficients of these variables. It was concluded that it is possible to control infectious diseases, such as COVID-19, by adjusting social and economic factors. We should guide urban development to improve human health.

Keywords: COVID-19; Wuhan city; morbidity rate; social and economic factors; spatial regression analysis.

Figure 1

Study design.

Figure 2

Location of Wuhan, China.

Figure 3

Pearson correlation analysis for the influencing factors and COVID-19 morbidity rate. (a) POD (Population density), (b) CLP (Construction land area proportion), (c) ABS (Average building scale), (d) GPA (GDP per unit of land area), (e) VTA (Value-added of tertiary industry per unit of land area), (f) TRA (Total retail sales of consumer goods per unit of land area), (g) PGD (Public green space density), (h) HOD (Hospital density), (i) APD (Aged population density).

Figure 3

Pearson correlation analysis for the influencing factors and COVID-19 morbidity rate. (a) POD (Population density), (b) CLP (Construction land area proportion), (c) ABS (Average building scale), (d) GPA (GDP per unit of land area), (e) VTA (Value-added of tertiary industry per unit of land area), (f) TRA (Total retail sales of consumer goods per unit of land area), (g) PGD (Public green space density), (h) HOD (Hospital density), (i) APD (Aged population density).

Figure 4

COV (COVID-19 morbidity rate). Spatial distribution of COVID-19 morbidity rate in Wuhan. Administrative divisions: 1 (Jiang’an District), 2 (Jianghan District), 3 (Qiaokou District), 4 (Hanyang District), 5 (Wuchang District), 6 (Qingshan District), 7 (Hongshan District), 8 (Dongxihu District), 9 (Wuhan development zone including Hannan District), 10 (Caidian District), 11 (Jiangxia District), 12 (Huangpi District), 13 (Xinzhou District).