Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review.

COVID-19 Environmental models Multimedia environment One-health Risk assessment Virus transmission

Journal

Sustainable cities and society
ISSN: 2210-6715
Titre abrégé: Sustain Cities Soc
Pays: Netherlands
ID NLM: 101735304

Informations de publication

Date de publication:
Jun 2022
Historique:
received: 14 12 2021
revised: 10 03 2022
accepted: 12 03 2022
entrez: 23 3 2022
pubmed: 24 3 2022
medline: 24 3 2022
Statut: ppublish

Résumé

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.

Identifiants

pubmed: 35317188
doi: 10.1016/j.scs.2022.103840
pii: S2210-6707(22)00167-6
pmc: PMC8925199
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

103840

Informations de copyright

© 2022 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Zunaira Asif (Z)

Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.

Zhi Chen (Z)

Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.

Saverio Stranges (S)

Department of Epidemiology and Biostatistics, Western University, Ontario, Canada.
Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.

Xin Zhao (X)

Department of Animal Science, McGill University, Montreal, Canada.

Rehan Sadiq (R)

School of Engineering (Okanagan Campus), University of British Columbia, Kelowna, BC, Canada.

Francisco Olea-Popelka (F)

Department of Pathology and Laboratory Medicine, Western University, Ontario, Canada.

Changhui Peng (C)

Department of Biological Sciences, University of Quebec in Montreal, Canada.

Fariborz Haghighat (F)

Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada.

Tong Yu (T)

Department of Civil and Environmental Engineering, University of Alberta, Canada.

Classifications MeSH