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Spatial risk for a superspreading environment: Insights from six urban facilities in six global cities across four continents

INTRODUCTION: This study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment. METHODS: Focusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it firs...

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Detalles Bibliográficos
Autores principales: Loo, Becky P. Y., Tsoi, Ka Ho, Axhausen, Kay W., Cao, Mengqiu, Lee, Yongsung, Koh, Keumseok Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113652/
https://www.ncbi.nlm.nih.gov/pubmed/37089495
http://dx.doi.org/10.3389/fpubh.2023.1128889
Descripción
Sumario:INTRODUCTION: This study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment. METHODS: Focusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it first tests whether visitors' mobility characteristics differ systematically for different types of facility and at different locations. The study collects detailed human mobility and other locational data in Chicago, Hong Kong, London, São Paulo, Seoul and Zurich. Then, considering facility agglomeration, visitors' profile and the density of the population, facilities are classified into four potential spatial risk (PSR) classes. Finally, a kernel density function is employed to derive the risk surface in each city based on the spatial risk class and nature of activities. RESULTS: Results of the human mobility analysis reflect the geographical and cultural context of various facilities, transport characteristics and people's lifestyle across cities. Consistent across the six global cities, geographical agglomeration is a risk factor for bars. For other urban facilities, the lack of agglomeration is a risk factor. Based on the spatial risk maps, some high-risk areas of superspreading are identified and discussed in each city. DISCUSSION: Integrating activity-travel patterns in risk models can help identify areas that attract highly mobile visitors and are conducive to superspreading. Based on the findings, this study proposes a place-based strategy of non-pharmaceutical interventions that balance the control of the pandemic and the daily life of the urban population.