AI Article Synopsis

  • COVID-19 is considered the most significant global health crisis of the 21st century, necessitating a deeper understanding of its transmission dynamics and environmental influences due to potential future waves.
  • The paper reviews various advanced modeling tools, including GIS, risk assessment, and AI technologies, that can help monitor and predict COVID-19 spread while examining how environmental factors like weather and air quality contribute to virus transmission.
  • It suggests a multidisciplinary approach, particularly the 'One-Health' concept, to enhance decision-making for public health strategies and risk mitigation related to COVID-19.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8925199PMC
http://dx.doi.org/10.1016/j.scs.2022.103840DOI Listing

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