Relationship between Built Environment and COVID-19 Dispersal Based on Age Stratification: A Case Study of Wuhan

Abstract

The outbreak of COVID-19 (coronavirus disease 2019) has become the focus of attention in the field of urban geography. Built environment, such as the layout of public spaces like transportation hubs and urban open spaces, is an important factor affecting the spread of the epidemic. However, due to the different behavior patterns of different age groups, the intensity and frequency of their use of various built environment spaces may vary. Based on this, we selected patients that were infected, with a non-manipulated time period, and the classification of human behavior patterns; we then conducted a regression analysis study on the spatial distribution and building environment of these COVID-19 patients. The results showed that the spatial distribution of young and middle-aged patients (18–59 years old) was more homogeneous, while the spatial distribution of elderly patients (60 years old and above) had a strong clustering characteristic. Moreover, the significant built environment factors exhibited in the two populations were extremely different. More diverse urban facilities and public spaces exhibited influential properties for older patients, while middle-aged and young adults were more influenced by commuting facilities. It can be said that the built environment shows different influences and mechanisms on the transmission of respiratory infectious diseases in different populations. Therefore, the results of this paper can inform decision makers who expect to reduce the occurrence of urban respiratory infectious diseases by improving the urban built environment.

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

“…They found that schools and restaurants were the most visited places. Additionally, Niu et al (2021) found that the effect of land uses on the number of infected people is differentiated by age. For example, shopping centers were a significant factor for zones with a higher number of aged people than zones dominated by younger populations.…”

“…Walkable and physically well-designed sidewalks are associated with a lower number of cases on the neighborhood scale ( Kwok et al, 2021 ; Credit, 2020 ; Tribby and Hartmann, 2021 ; Nguyen et al, 2020 ). However, urban districts with a higher density of transportation facilities such as bus and train stations increased the likelihood of COVID-19 spreading in Tehran ( Razavi-Termeh et al, 2021 ; Khavarian-Garmsir et al, 2021 ), Hong Kong ( Kan et al, 2021 ; Huang et al, 2020 ) Wuhan ( Xu et al, 2022 ; Niu et al, 2021 ) and Huangzhou ( B. Li et al, 2021 ).…”

Conditioning factors in the spreading of Covid-19 – Does geography matter?

“… Infections ↑ He et al [ 36 ] X Guangzhou (China) Density of shopping malls, hotels, restaurants etc. Infections ↑ Karim and Chen [ 37 ] X USA Metropolitan areas Infections ↑ Li et al [ 38 ] X X USA, World Latitude Infections and Deaths ↓ Longitude Infections and Deaths ↑ Murgante et al [ 39 ] X Italy Soil consumption Infections and Deaths ↑ Nasiri et al [ 40 ] X Tehran (Iran) Commercial/residential land use Infections ↑ Niu et al [ 41 ] X X Wuhan (China) Building density, number of urban facilities Infections ↑ Distance from urban open space Infections ↓ Ramírez and Lee [ 42 ] X Colorado (USA) Urban regions Infections ↑ ...…”

“…A spatial analysis enabled Nasiri et al [ 40 ] to show that in Iran the number of COVID-19 hospitalised cases were higher in commercial and residential areas. By means of a clustering analysis, Niu et al [ 41 ] inferred that floor area ratio and building density in China are positively correlated with COVID-19 middle-aged and elderly patients. The study by Wheeler et al [ 51 ] analysed the spread of the pandemic among Minnesota (USA) rural counties which were found to host a significant number of COVID-19 hotspots.…”

Lessons learnt for enhancing hospital resilience to pandemics: A qualitative analysis from Italy

“…Learning from disasters is essential to guide future resilience-oriented designs [ 15 ], and in the post-pandemic era, both the construction and the built environment sector are expected to develop further a focus on resilience, occupant health, and/or safety [ [16] , [17] , [18] , [19] ]. Numerous settings such as urban areas [ [20] , [21] , [22] , [23] , [24] , [25] ], long-term care facilities [ [26] , [27] , [28] ], kindergartens [ 29 ], mental care facilities [ 30 ], offices [ 31 , 32 ], and residential buildings [ [33] , [34] , [35] ] have already provided suggestions for future design and spatial adaptations.…”