Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong

Kwok, Coco Yin Tung; Wong, Man Sing; Chan, Kang Cheung; Kwan, Mei Po; Nichol, Janet Elizabeth; Liu, Chun Ho; Wong, Janet Yuen Ha; Wai, Abraham Ka Chung; Chan, Lawrence Wing Chi; Xu, Yang; Hon, Li; Huang, Jianwei; Kan, Zihan

doi:10.1016/j.scitotenv.2020.144455

Cited by 62 publications

(80 citation statements)

References 67 publications

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“…Like various studies worldwide (Ahasan et al, 2020;Asante & Mills, 2020;Cao et al, 2020;Kwok et al, 2020), our study proved that the spatial relationship tools have the power to discover associations amid COVID-19 infection rate and socioeconomic variables and predicting the future of COVID-19 at various scales. The models built in this study can be used against the spread of COVID-19 in Oman for various control management purposes.…”

Section: Discussionsupporting

confidence: 73%

Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach

et al. 2021

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Local, bivariate relationships between coronavirus 2019 (COVID-19) infection rates and a set of demographic and socioeconomic variables were explored at the district level in Oman. To limit multicollinearity a principal component analysis was conducted, the results of which showed that three components together could explain 65% of the total variance that were therefore subjected to further study. Comparison of a generalized linear model (GLM) and geographically weighted regression (GWR) indicated an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local coefficient of determination (R2) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, including percentages of Omani and non-Omani population at various age levels; spatial interaction; population density; number of hospital beds; total number of households; purchasing power; and purchasing power per km2. No direct correlation between COVID- 19 rates and health facilities distribution or tobacco usage. This study suggests that Poisson regression using GWR and GLM can address unobserved spatial non-stationary relationships. Findings of this study can promote current understanding of the demographic and socioeconomic variables impacting the spatial patterns of COVID-19 in Oman, allowing local and national authorities to adopt more appropriate strategies to cope with this pandemic in the future and also to allocate more effective prevention resources.

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Section: Discussionsupporting

confidence: 73%

Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach

et al. 2021

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“…In particular, levels of air pollutants—including NO 2 and PM 2.5 , which are considered major sources of anthropogenic emissions in public health issues—were altered. Meanwhile, researchers have discussed the potential impacts of working locations and parks due to movement restrictions [ 40 , 41 ]. This study adapted data on exposure to NO 2 and PM 2.5 and the frequencies of visits to parks and workplaces to depict variances in air pollution and human activity patterns.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic

Meng

Wong

Xing

et al. 2021

IJERPH

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The impact of Coronavirus Disease 2019 (COVID-19) on cause-specific mortality has been investigated on a global scale. However, less is known about the excess all-cause mortality and air pollution-human activity responses. This study estimated the weekly excess all-cause mortality during COVID-19 and evaluated the impacts of air pollution and human activities on mortality variations during the 10th to 52nd weeks of 2020 among sixteen countries. A SARIMA model was adopted to estimate the mortality benchmark based on short-term mortality during 2015–2019 and calculate excess mortality. A quasi-likelihood Poisson-based GAM model was further applied for air pollution/human activity response evaluation, namely ground-level NO2 and PM2.5 and the visit frequencies of parks and workplaces. The findings showed that, compared with COVID-19 mortality (i.e., cause-specific mortality), excess all-cause mortality changed from −26.52% to 373.60% during the 10th to 52nd weeks across the sixteen countries examined, revealing higher excess all-cause mortality than COVID-19 mortality in most countries. For the impact of air pollution and human activities, the average country-level relative risk showed that one unit increase in weekly NO2, PM2.5, park visits and workplace visits was associated with approximately 1.54% increase and 0.19%, 0.23%, and 0.23% decrease in excess all-cause mortality, respectively. Moreover, compared with the impact on COVID-19 mortality, the relative risks of weekly NO2 and PM2.5 were lower, and the relative risks of weekly park and workplace visits were higher for excess all-cause mortality. These results suggest that the estimation based on excess all-cause mortality reduced the potential impact of air pollution and enhanced the influence of human activities compared with the estimation based on COVID-19 mortality.

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“…Al mismo tiempo, en la literatura internacional de los últimos seis meses es posible observar la relación entre el contagio por COVID-19 y diferentes condiciones urbanas y socioeconómicas, también desde una perspectiva caracterizada fuertemente por la desigualdad. Entre éstas, se pueden mencionar: características demográficas de edad, origen étnico u ocupación para el caso de Estados Unidos (Andersen et al, 2021), la infraestructura de transporte en el distrito urbano de Huangzhon, cercano a Wuhan (Li et al, 2021), la geometría urbana y la ocupación en Hong Kong (Kwok et al, 2021); las condiciones de vivienda y acceso a servicios sanitarios en India (Das et al, 2021); el porcentaje de viviendas bajo condiciones de hacinamiento y la tasa de mortalidad infantil, para las capitales regionales de Brasil (Dayrell et al, 2020) y la densidad poblacional para el caso específico de São Paulo (Nakada & Urban, 2020); también el hacinamiento (y no la densidad), junto con el tamaño de las viviendas para la ciudad de Nueva York (Hamidi & Hamidi, 2021); la población mayor de 65 años y finalmente, (en este caso sí) la densidad urbana en Omán (Mansour et al, 2021…”

Section: 1unclassified

COVID-19 y ciudad: hacia un modelo integrado de vivienda, microbiología, ambiente y urbanismo

Encinas¹,

Soto-Liebe²,

Núñez³

et al. 2021

ACE: Architecture, City and Environment

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A partir de mayo de 2020, la crisis sanitaria global causada por el virus SARS-CoV-2 traslada su epicentro hacia Latinoamérica, con foco en ciudades que presentan altos índices de pobreza, segregación y hacinamiento. Los avances en microbiología posibilitan comprender en profundidad las relaciones entre ciudad, COVID-19 y otros microorganismos, pero falta establecer un marco conceptual que las articule, especialmente en contextos donde las determinantes sociales son tan relevantes. Este artículo tiene como objetivo el proponer una aproximación integrada de microbiología, vivienda, ambiente y urbanismo, a partir de un modelo de interacciones y un análisis empírico para Santiago de Chile. En base a esto, se pudo analizar cómo el proceso de propagación en la ciudad se ve potenciada por vulnerabilidades de índole socio espacial, sanitaria intradomiciliaria y urbana, más una aproximación desde el concepto de pobreza energética. Al mismo tiempo, se pudo comprobar como las variables asociadas a estas vulnerabilidades permitían explicar la tasa de incidencia de casos confirmados por cada 100 000 habitantes a través de las distintas comunas en el área metropolitana de Santiago de Chile. Dentro de éstas, destacan el nivel de hacinamiento de las viviendas, la cantidad de hogares con jefes/as de hogar en trabajo precario y los viajes hacia el distrito central de negocios de la ciudad. Finalmente, se establece la necesidad de proponer una agenda de investigación para este nuevo equipo multidisciplinario de “Microbioma Urbano” en relación con la necesidad de realización de muestreos microbiológicos que permitan mejorar las condiciones de viviendas, barrios y ciudades, aportando en la superación de las vulnerabilidades identificadas en este estudio. A partir de maig de 2020, la crisi sanitària global causada pel virus SARS-CoV-2 trasllada el seu epicentre cap a Llatinoamèrica, amb focus en ciutats que presenten alts índexs de pobresa, segregació i amuntegament. Els avenços en microbiologia permeten entendre en profunditat les relacions entre ciutat, COVID-19 i altres microorganismes, però cal establir un marc conceptual que les articuli, especialment en contextos on les determinants socials són tan rellevants. Aquest article té com a objectiu el proposar una aproximació integrada de microbiologia, habitatge, ambient i urbanisme, a partir d'un model d'interaccions i una anàlisi empírica per a Santiago de Xile. En base a això, es va poder analitzar com el procés de propagació a la ciutat es veu potenciada per vulnerabilitats d'índole soci espacial, sanitària intra-domiciliaria i urbana, més una aproximació des del concepte de pobresa energètica. Al mateix temps, es va poder comprovar com les variables associades a aquestes vulnerabilitats permetien explicar la taxa d'incidència de casos confirmats per cada 100 000 habitants a través de les diferents comunes a l'àrea metropolitana de Santiago de Xile. Dins d'aquestes, destaquen el nivell d'amuntegament dels habitatges, la quantitat de llars amb caps de la llar en treball precari i els viatges cap al districte central de negocis de la ciutat. Finalment, s'estableix la necessitat de proposar una agenda de recerca per a aquest nou equip multidisciplinari de "Microbioma Urbà" en relació amb la necessitat de realització de mostrejos microbiològiques que permetin millorar les condicions d'habitatges, barris i ciutats, aportant en la superació de les vulnerabilitats identificades en aquest estudi. As of May 2020, the global health crisis caused by the SARS-CoV-2 virus moves its epicentre to Latin America, with cities showing high rates of poverty, segregation, and overcrowding. Current advances in microbiology make it possible to understand in depth the relationships between cities, COVID-19, and other microorganisms, but a conceptual framework to articulate them is lacking, especially in contexts where social determinants are so relevant. This article proposes an integrated approach to microbiology, housing, environment, and urbanism, based on a model of interactions and an empirical analysis applied to Santiago de Chile. It was possible to analyse how the propagation of COVID-19 in the city is enhanced by vulnerabilities of socio-spatial, residential and urban health, including an approach from the concept of energy poverty. At the same time, it was possible to verify how the variables associated with these vulnerabilities allowed to explain the incidence rate per 100 000 inhabitants through the different communes of Santiago de Chile. Among these, the level of housing overcrowding, the number of households with heads of household in precarious employment, and travel to the central business district stand out. Finally, the need for microbiological sampling to improve housing conditions, neighbourhoods, and cities propose a new research agenda for this Urban Microbiome" multidisciplinary team, contributing to overcoming the vulnerabilities identified in this research.

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Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong

Cited by 62 publications

References 67 publications

Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach

Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic

COVID-19 y ciudad: hacia un modelo integrado de vivienda, microbiología, ambiente y urbanismo

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