Association of built environment attributes with the spread of COVID-19 at its initial stage in China

Li, Shuangjin; Ma, Stefan; Zhang, Junyi

doi:10.1016/j.scs.2021.102752

Cited by 84 publications

(56 citation statements)

References 77 publications

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“…In a basic fixed parameter model with only population density, regional auto centrality index, tree canopy and nonmetropolitan county indicator as key explanatory variables, density variable and nonmetropolitan county indicator were statistically significantly and negatively correlated with COVID-19 infection rate. The negative association between (population) density and infection rate in the fixed parameter model is consistent with other studies ( Khavarian-Garmsir, Sharifi, & Moradpour, 2021 ; Li, Peng, He, Wang, & Feng, 2021 ) – while acknowledging that there could be differences in the construction of density measures in these studies. Whereas regional auto centrality index was positively correlated with infection rate.…”

supporting

confidence: 89%

Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Frank

Wali²

2021

Sustainable Cities and Society

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Compact walkable environments with greenspace support physical activity and reduce the risk for depression and several obesity-related chronic diseases, including diabetes and heart disease. Recent evidence confirms that these chronic diseases increase the severity of COVID-19 infection and mortality risk. Conversely, denser transit supportive environments may increase risk of exposure to COVID-19 suggesting the potential for contrasting chronic versus infectious disease impacts of community design. A handful of recent studies have examined links between density and COVID-19 mortality rates reporting conflicting results. Population density has been used as a surrogate of urban form to capture the degree of walkability and public transit versus private vehicle travel demand. The current study employs a broader range of built environment features (density, design, and destination accessibility) and assesses how chronic disease mediates the relationship between built and natural environment and COVID-19 mortality. Negative and significant relationships are observed between built and natural environment features and COVID-19 mortality when accounting for the mediating effect of chronic disease. Findings underscore the importance of chronic disease when assessing relationships between COVID-19 mortality and community design. Based on a rigorous simulation-assisted random parameter path analysis framework, we further find that the relationships between COVID-19 mortality, obesity, and key correlates exhibit significant heterogeneity. Ignoring this heterogeneity in highly aggregate spatial data can lead to incorrect conclusions with regards to the relationship between built environment and COVID-19 transmission. Results presented here suggest that creating walkable environments with greenspace is associated with reduced risk of chronic disease and/or COVID-19 infection and mortality.

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supporting

confidence: 89%

Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Frank

Wali²

2021

Sustainable Cities and Society

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“…This result is somewhat consistent with findings from previous research [ 32 ] that suggested that dense places do not necessarily lead to more infection but more connected places, as measured by a metropolitan size and an enplanement rate, were positively associated with the infection rates. Another study conducted in China also found that connectivity, as measured by the betweenness centrality of the road networks of 255 Chinese cities, was one of the key determinants of infection rates [ 64 ].…”

Section: Discussionmentioning

confidence: 99%

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Hong

Sung

2021

IJERPH

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COVID-19 has sparked a debate on the vulnerability of densely populated cities. Some studies argue that high-density urban centers are more vulnerable to infectious diseases due to a higher chance of infection in crowded urban environments. Other studies, however, argue that connectivity rather than population density plays a more significant role in the spread of COVID-19. While several studies have examined the role of urban density and connectivity in Europe and the U.S., few studies have been conducted in Asian countries. This study aims to investigate the role of urban spatial structure on COVID-19 by comparing different measures of urban density and connectivity during the first eight months of the outbreak in Korea. Two measures of density were derived from the Korean census, and four measures of connectivity were computed using social network analysis of the Origin-Destination data from the 2020 Korea Transport Database. We fitted both OLS and negative binomial models to the number of confirmed COVID-19 patients and its infection rates at the county level, collected individually from regional government websites in Korea. Results show that both density and connectivity play an important role in the proliferation of the COVID-19 outbreak in Korea. However, we found that the connectivity measure, particularly a measure of network centrality, was a better indicator of COVID-19 proliferation than the density measures. Our findings imply that policies that take into account different types of connectivity between cities might be necessary to contain the outbreak in the early phase.

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“…However, it is too costly to collect sufficiently large-scale samples that can represent the whole population. A few studies have investigated the large-scale inter/intra-city contacts on public transportation through smart card data of railways 6 and flight information 7 , but such data cannot reflect human mobility in various urban facilities.…”

Section: Introductionmentioning

confidence: 99%

Diverse and nonlinear influences of built environment factors on COVID-19 spread across townships in China at its initial stage

Zhang

2021

Sci Rep

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The built environment can contribute to the spread of the novel coronavirus disease (COVID-19) by facilitating human mobility and social contacts between infected and uninfected individuals. However, mobility data capturing detailed interpersonal transmission at a large scale are not available. In this study, we aimed to objectively assess the influence of key built environment factors, which create spaces for activities—“inferred activity” rather than “actually observed activity”—on the spread of COVID-19 across townships in China at its initial stage through a random forest approach. Taking data for 2994 township-level administrative units, the spread is measured by two indicators: the ratio of cumulative infection cases (RCIC), and the coefficient of variation of infection cases (CVIC) that reflects the policy effect in the initial stage of the spread. Accordingly, we selected 19 explanatory variables covering built environment factors (urban facilities, land use, and transportation infrastructure), the level of nighttime activities, and the inter-city population flow (from Hubei Province). We investigated the spatial agglomerations based on an analysis of bivariate local indicators of spatial association between RCIC and CVIC. We found spatial agglomeration (or positive spatial autocorrelations) of RCIC and CVIC in about 20% of all townships under study. The density of convenience shops, supermarkets and shopping malls (DoCSS), and the inter-city population flow (from Hubei Province) are the two most important variables to explain RCIC, while the population flow is the most important factor in measuring policy effects (CVIC). When the DoCSS gets to 21/km2, the density of comprehensive hospitals to 0.7/km2, the density of road intersections to 72/km2, and the density of gyms and sports centers to 2/km2, their impacts on RCIC reach their maximum and remain constant with further increases in the density values. Stricter policy measures should be taken at townships with a density of colleges and universities higher than 0.5/km2 or a density of comprehensive hospitals higher than 0.25/km2 in order to effectively control the spread of COVID-19.

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Association of built environment attributes with the spread of COVID-19 at its initial stage in China

Cited by 84 publications

References 77 publications

Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Density or Connectivity: What Are the Main Causes of the Spatial Proliferation of COVID-19 in Korea?

Diverse and nonlinear influences of built environment factors on COVID-19 spread across townships in China at its initial stage

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