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The fine-scale associations between socioeconomic status, density, functionality, and spread of COVID-19 within a high-density city

BACKGROUND: Motivated by the need for precise epidemic control and epidemic-resilient urban design, this study aims to reveal the joint and interactive associations between urban socioeconomic, density, connectivity, and functionality characteristics and the COVID-19 spread within a high-density cit...

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Detalles Bibliográficos
Autores principales: Zhang, Anshu, Shi, Wenzhong, Tong, Chengzhuo, Zhu, Xiaosheng, Liu, Yijia, Liu, Zhewei, Yao, Yepeng, Shi, Zhicheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8936044/
https://www.ncbi.nlm.nih.gov/pubmed/35313829
http://dx.doi.org/10.1186/s12879-022-07274-w
Descripción
Sumario:BACKGROUND: Motivated by the need for precise epidemic control and epidemic-resilient urban design, this study aims to reveal the joint and interactive associations between urban socioeconomic, density, connectivity, and functionality characteristics and the COVID-19 spread within a high-density city. Many studies have been made on the associations between urban characteristics and the COVID-19 spread, but there is a scarcity of such studies in the intra-city scale and as regards complex joint and interactive associations by using advanced machine learning approaches. METHODS: Differential-evolution-based association rule mining was used to investigate the joint and interactive associations between the urban characteristics and the spatiotemporal distribution of COVID-19 confirmed cases, at the neighborhood scale in Hong Kong. The associations were comparatively studied for the distribution of the cases in four waves of COVID-19 transmission: before Jun 2020 (wave 1 and 2), Jul–Oct 2020 (wave 3), and Nov 2020–Feb 2021 (wave 4), and for local and imported confirmed cases. RESULTS: The first two waves of COVID-19 were found mainly characterized by higher-socioeconomic-status (SES) imported cases. The third-wave outbreak concentrated in densely populated and usually lower-SES neighborhoods, showing a high risk of within-neighborhood virus transmissions jointly contributed by high density and unfavorable SES. Starting with a super-spread which considerably involved high-SES population, the fourth-wave outbreak showed a stronger link to cross-neighborhood transmissions driven by urban functionality. Then the outbreak diffused to lower-SES neighborhoods and interactively aggravated the within-neighborhood pandemic transmissions. Association was also found between a higher SES and a slightly longer waiting period (i.e., the period from symptom onset to diagnosis of symptomatic cases), which further indicated the potential contribution of higher-SES population to the pandemic transmission. CONCLUSIONS: The results of this study may provide references to developing precise anti-pandemic measures for specific neighborhoods and virus transmission routes. The study also highlights the essentiality of reliving co-locating overcrowdedness and unfavorable SES for developing epidemic-resilient compact cities, and the higher obligation of higher-SES population to conform anti-pandemic policies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07274-w.