Investigating the relationship between the built environment and relative risk of COVID-19 in Hong Kong

Jianwei Huang, Mei Po Kwan, Zihan Kan, Man Sing Wong, Coco Yin Tung Kwok, Xinyu Yu

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding the relationship between the built environment and the risk of COVID-19 transmission is essential to respond to the pandemic. This study explores the relationship between the built environment and COVID-19 risk using the confirmed cases data collected in Hong Kong. Using the information on the residential buildings and places visited for each case from the dataset, we assess the risk of COVID-19 and explore their geographic patterns at the level of Tertiary Planning Unit (TPU) based on incidence rate (R1) and venue density (R2). We then investigate the associations between several built-environment variables (e.g., nodal accessibility and green space density) and COVID-19 risk using global Poisson regression (GPR) and geographically weighted Poisson regression (GWPR) models. The results indicate that COVID-19 risk tends to be concentrated in particular areas of Hong Kong. Using the incidence rate as an indicator to assess COVID-19 risk may underestimate the risk of COVID-19 transmission in some suburban areas. The GPR and GWPR models suggest a close and spatially heterogeneous relationship between the selected built-environment variables and the risk of COVID-19 transmission. The study provides useful insights that support policymakers in responding to the COVID-19 pandemic and future epidemics.

Original languageEnglish (US)
Article number624
JournalISPRS International Journal of Geo-Information
Volume9
Issue number11
DOIs
StatePublished - Nov 2020

Keywords

  • Built environment
  • Geographically weighted Poisson regression
  • Global Poisson regression
  • Risk of COVID-19

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Computers in Earth Sciences
  • Earth and Planetary Sciences (miscellaneous)

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