Integrated analysis of doubly disadvantaged neighborhoods by considering both green space and blue space accessibility and COVID-19 infection risk

Dong Liu; Mei-Po Kwan

doi:10.1371/journal.pone.0273125

Integrated analysis of doubly disadvantaged neighborhoods by considering both green space and blue space accessibility and COVID-19 infection risk

PLoS One. 2022 Nov 2;17(11):e0273125. doi: 10.1371/journal.pone.0273125. eCollection 2022.

Authors

Dong Liu^{1

2}, Mei-Po Kwan³

Affiliations

¹ Human Environments Analysis Laboratory, The University of Western Ontario, Social Sciences Centre, London, Ontario, Canada.
² Department of Geography and Environment, The University of Western Ontario, Social Sciences Centre, London, Ontario, Canada.
³ Department of Geography and Resource Management and Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong.

Abstract

The ongoing COVID-19 pandemic has taken a heavy toll on the physical and mental health of the public. Nevertheless, the presence of green and blue spaces has been shown to be able to encourage physical activities and alleviate the mental distress caused by COVID-19. However, just as the impact of COVID-19 varies by geographical region and area, the distribution of green and blue spaces is also different across different neighborhoods and areas. By using Hong Kong as the study area, we determine the local neighborhoods that suffer from both high COVID-19 infection risk as well as low green and blue space accessibility. The results show that some of the poorest neighborhoods in the territory such as Sham Shui Po, Kwun Tong and Wong Tai Sin are also among the most doubly disadvantaged in terms of COVID-19 infection risk as well as green and blue space accessibility.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19* / epidemiology
Exercise
Humans
Pandemics
Parks, Recreational*
Residence Characteristics

Grants and funding

This work was supported by grants from the Hong Kong Research Grants Council (General Research Fund Grant no. 14605920, 14611621; Collaborative Research Fund Grant no. C4023-20GF; Research Matching Grants RMG 8601219, 8601242), and Grant no. 3110156 and a grant from the Research Committee on Research Sustainability of Major Research Grants Council Funding Schemes (3133240) of the Chinese University of Hong Kong, all awarded to MPK.