城市自然与社会环境对新型冠状病毒肺炎发病率的影响

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Abstract This study explored the effects of both natural and socio-economic factors, such as city size and healthcare capacity, on the spreading of COVID-19 in China’s urban population from January 1 to March 5, 2020. Several statistical models and machine learning methods were used to identify the key determinants of the incidence rate of COVID-19. Based on the interpretable machine learning framework, possible nonlinear relationships between incidences and key impact factors were explored. The results showed that the incidence rate of COVID-19 in cities was influenced by several factors simultaneously. Among the factors, the population inflow rate from Wuhan was the factor that showed the highest correlation coefficient (0.43), followed by the population growth rate (0.38). Population migration size, city size and healthcare capacity were the key influencing factors. Nonlinear relationships existed between the key influencing factors and incidence rates. To be specific, the inflow rate from Wuhan had a S-shaped relationship and reaches an asymptote after 2%; the population density had an approximately linear relationship; the per capita GDP showed an evident inverted U curve with the per capita GDP over 100,000yuan as the inflection point. City development needs to pay more attention to population density control and economic growth in order to bring more health benefits.

Key words： incidence natural factors socioeconomic factors XGBoost model all-subset regression SHAP

Received: 30 June 2021

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	Articles by authors
	WANG Yue-yao
	LIANG Ze
	DING Jia-qi
	SUN Fu-yue
	LI Shuang-cheng

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WANG Yue-yao,LIANG Ze,DING Jia-qi等. Identify the natural and socio-economic influencing factors of the new coronavirus pneumonia（COVID-19） incidence rates in Chinese cities[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(3): 1418-1426.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I3/1418

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