ArticleEnvironment and planning. B, urban analytics and city science2023
Spatial variations of the third and fourth COVID-19 waves in Hong Kong: A comparative study using built environment and socio-demographic characteristics.
Article in Environment and planning. B, urban analytics and city science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- How People's COVID-19 Induced-Worries and Multiple Environmental Exposures Are Associated with Their Depression, Anxiety, and Stress during the Pandemic.International journal of environmental research and public health · 2023Article
- Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia.BMC public health · 2023Article
- An overview of urban analytical approaches to combating the Covid-19 pandemic.Environment and planning. B, urban analytics and city science · 2023Article
- The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study.Diseases (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
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Abstract
Since the first confirmed case was reported in January 2020, Hong Kong has experienced multiple waves of COVID-19 outbreaks. Recent literature has explored the spatial patterns of disease incidence and their relationships with the built environment and demographic characteristics. Nonetheless, few studies aim at the comparative patterns of different epidemic waves occurring in the same spatial context. This study analyses spatial patterns of the third and fourth COVID-19 epidemic waves and then evaluates the spatial relationship between case incidence and built environment and socio-demographic characteristics. By collecting local-related cases, this study incorporates a two-fold analytical strategy: (1) Using rank-size distribution and log-odd ratio to depict the spatial pattern of COVID-19 incidence rates; (2) through global and local regression models, investigating incidence's associations with the urban built environment and socio-demographic characteristics. The results reveal that the two different epidemic waves have far distinct spatial tendencies to their infection risk factors, reflecting location-specific associations with the built environments and socio-demographics. Collectively, we discover that the third and fourth COVID-19 waves are likely associated with residential context and urban activities, respectively. Practical implications are discussed that would be of interest to policymakers and health professionals.
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