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Exploring the Quantitative Assessment of Spatial Risk in Response to Major Epidemic Disasters in Megacities: A Case Study of Qingdao

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  • Qimeng Ren

    (School of Landscape, Northeast Forestry University, Harbin 150040, China)

  • Ming Sun

    (School of Landscape, Northeast Forestry University, Harbin 150040, China)

Abstract

With the global spread of various human-to-human epidemics, public health issues have become a focus of attention. Therefore, it is of great importance to improve the quantitative risk assessment of the construction of resilient cities in terms of epidemic disasters. Starting with the dimensions of social activities and material space, this paper took Qingdao, China, with a population of 5 million, as an example, and took its seven municipal districts as the research scope. In this paper, five risk factors, including the Population density index, Night light index, Closeness index of roads, Betweenness index of roads and Functional mixed nuclear density index were selected for weighted superposition analysis. We conducted a quantitative assessment of the spatial risk of epidemic disaster so as to obtain the classification and spatial structure of the epidemic disaster risk intensity. The results show that: ① The roads with a large traffic flow are most likely to lead to the risk of urban spatial agglomeration, and the areas with a large population density and large mixture of infrastructure functions are also important factors causing the risk of epidemic agglomeration. ② The analysis results regarding the population, commerce, public services, transportation, residence, industry, green space and other functional places can reflect the high-risk areas for epidemic diseases with different natures of transmission. ③ The risk intensity of epidemic disasters is divided into five risk grade areas. Among them, the spatial structure of epidemic disasters, composed of the first-level risk areas, is characterized by “one main area, four secondary areas, one belt and multiple points” and has the characteristics of spatial diffusion. ④ Catering, shopping, life services, hospitals, schools and transportation functional places are more likely to cause crowd gathering. The management of these places should be focused on prevention and control. At the same time, medical facilities should be established at fixed points in all high-risk areas to ensure the full coverage of services. In general, the quantitative assessment of the spatial risk of major epidemic disasters improves the disaster risk assessment system in the construction of resilient cities. It also focuses on risk assessment for public health events. It is helpful to accurately locate the agglomeration risk areas and epidemic transmission paths that are prone to outbreak or cause epidemic transmission in cities so as to assist the relevant practitioners in containing the epidemic from the initial stage of transmission in a timely manner and prevent the further spread of the epidemic.

Suggested Citation

  • Qimeng Ren & Ming Sun, 2023. "Exploring the Quantitative Assessment of Spatial Risk in Response to Major Epidemic Disasters in Megacities: A Case Study of Qingdao," IJERPH, MDPI, vol. 20(4), pages 1-24, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3274-:d:1066778
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    1. Qi Chen & Yibo Yan & Xu Zhang & Jian Chen, 2022. "A Study on the Impact of Built Environment Elements on Satisfaction with Residency Whilst Considering Spatial Heterogeneity," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    2. Kaili She & Chunyu Li & Chang Qi & Tingxuan Liu & Yan Jia & Yuchen Zhu & Lili Liu & Zhiqiang Wang & Ying Zhang & Xiujun Li, 2021. "Epidemiological Characteristics and Regional Risk Prediction of Hemorrhagic Fever with Renal Syndrome in Shandong Province, China," IJERPH, MDPI, vol. 18(16), pages 1-12, August.
    3. Meifang Li & Xun Shi & Xia Li & Wenjun Ma & Jianfeng He & Tao Liu, 2019. "Epidemic Forest: A Spatiotemporal Model for Communicable Diseases," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 109(3), pages 812-836, May.
    4. Chaogui Kang & Dongwan Fan & Hongzan Jiao, 2021. "Validating activity, time, and space diversity as essential components of urban vitality," Environment and Planning B, , vol. 48(5), pages 1180-1197, June.
    5. Tongwen Wang & Ya Li & Haidong Li & Shuaijun Chen & Hongkai Li & Yunxing Zhang, 2022. "Research on the Vitality Evaluation of Parks and Squares in Medium-Sized Chinese Cities from the Perspective of Urban Functional Areas," IJERPH, MDPI, vol. 19(22), pages 1-23, November.
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    Cited by:

    1. Ming Sun & Xueyu Jiao, 2023. "Quantitative Identification Study of Epidemic Risk in the Spatial Environment of Harbin City," Sustainability, MDPI, vol. 15(9), pages 1-22, May.

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