Abstract
The study of the spatial differentiation of COVID-19 in cities and its driving mechanism is helpful to reveal the spatial distribution pattern, transmission mechanism and diffusion model, and evolution mechanism of the epidemic and can lay the foundation for constructing the spatial dynamics model of the epidemic and provide theoretical basis for the policy design, spatial planning and implementation of epidemic prevention and control and social governance. Geodetector (Origin version, Beijing, China) is a great tool for analysis of spatial differentiation and its influencing factors, and it provides decision support for differentiated policy design and its implementation in executing the city-specific policies. Using factor detection and interaction analysis of Geodetector, 15 indicators of economic, social, ecological, and environmental dimensions were integrated, and 143 cities were selected for the empirical research in China. The research shows that, first of all, risks of both infection and death show positive spatial autocorrelation, but the geographical distribution of local spatial autocorrelation differs significantly between the two. Secondly, the inequalities in urban economic, social, and residential environments interact with COVID-19 spatial heterogeneity, with stronger explanatory power especially when multidimensional inequalities are superimposed. Thirdly, the spatial distribution and spread of COVID-19 are highly spatially heterogeneous and correlated due to the complex influence of multiple factors, with factors such as Area of Urban Construction Land, GDP, Industrial Smoke and Dust Emission, and Expenditure having the strongest influence, the factors such as Area of Green, Number of Hospital Beds and Parks, and Industrial NOx Emissions having unignorable influence, while the factors such as Number of Free Parks and Industrial Enterprises, Per-GDP, and Population Density play an indirect role mainly by means of interaction. Fourthly, the factor interaction effect from the infected person’s perspective mainly shows a nonlinear enhancement effect, that is, the joint influence of the two factors is greater than the sum of their direct influences; but from the perspective of the dead, it mainly shows a two-factor enhancement effect, that is, the joint influence of the two factors is greater than the maximum of their direct influences but less than their sum. Fifthly, some suggestions are put forward from the perspectives of building a healthy, resilient, safe, and smart city, providing valuable reference and decision basis for city governments to carry out differentiated policy design.
Highlights
Since spatial heterogeneity of infectious diseases often contains multiple opportunities to emerge from the crisis, it is necessary to find out the connections between COVID-19 spatial heterogeneity and urban inequality
Combating the epidemic crisis requires a comprehensive understanding of the interactions between multidimensional urban inequalities in macroeconomic, social, and environmental conditions and epidemics, and needs to reveal the complex driving mechanisms between COVID-19 spatial heterogeneity and urban inequality, which are crucial for policy design for sustainable urban development and public health
This paper aims to investigate the following questions: 1 How strong is the spatial heterogeneity of COVID-19? 2 How and to what extent do various factors affect spatial differentiation of COVID-19 by integrating economic, social, and ecological environment dimensions? 3 How can the strength and nature of interaction between critical influencing factors be measured and further reveal or construct the driving mechanism of spatial differentiation of COVID-19? Geodetector is a powerful tool for analyzing spatial differentiation and its influencing factors, which has gotten attention from more scholars recently
Summary
The scientific response to the global novel coronavirus pneumonia outbreak (hereinafter referred to as COVID-19) is a major scientific research task in the context of global public health events. It requires a close intersection of the subjects including medicine, geography, management, sociology and economics, and a rapid breakthrough in scientific theories and methods for dynamic surveillance, precise prevention and control, accurate prediction, and effective response to the epidemic outbreak. Combating the epidemic crisis requires a comprehensive understanding of the interactions between multidimensional urban inequalities in macroeconomic, social, and environmental conditions and epidemics, and needs to reveal the complex driving mechanisms between COVID-19 spatial heterogeneity and urban inequality, which are crucial for policy design for sustainable urban development and public health. From the perspective of geography, planning and spatial epidemiology, the spatial spread of COVID19 is a typical spatial evolutionary phenomenon and a process of interaction between people and nature, and it is of great theoretical value and practical significance to study the spatial differentiation pattern of COVID-19 and explore the comprehensive mechanism and strategy of epidemic control
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