Managing Air for Greener Inner Cities

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:11 publications

Grant number: EP/N010221/1

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2015
    2021
  • Funder

    UK Research and Innovation (UKRI)
  • Principle Investigator

    Pending
  • Research Location

    United Kingdom, Europe
  • Lead Research Institution

    University of Cambridge
  • Research Category

    Infection prevention and control

  • Research Subcategory

    Barriers, PPE, environmental, animal and vector control measures

  • Special Interest Tags

    Gender

  • Study Subject

    Unspecified

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Estimates of personal exposure, critical to determine safe procedures in hospitals and in public places (e.g. shops and restaurants), are needed now and post-lockdown. It is also essential that ventilation strategies, the effectiveness of PPE and other containment measures (e.g. curtains, air locks etc.) are evaluated to avoid unnecessary spread of the infection. WHO guidelines suggest ventilation rates in hospitals should be 160 l/s/person. This is based on inefficient modes of ventilation and is not achievable in most cases. The MAGIC team has interdisciplinary expertise that can recommend alternative ventilation strategies that are urgently needed. This work will also provide better information and advice if there were to be subsequent waves in the future.

Publicationslinked via Europe PMC

Last Updated:39 minutes ago

View all publications at Europe PMC

Do we need high temporal resolution modelling of exposure in urban areas? A test case.

Assessing uncertainty and heterogeneity in machine learning-based spatiotemporal ozone prediction in Beijing-Tianjin- Hebei region in China.

Data Assimilation Predictive GAN (DA-PredGAN) Applied to a Spatio-Temporal Compartmental Model in Epidemiology.

An evaluation of the risk of airborne transmission of COVID-19 on an inter-city train carriage.

Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic.

Numerical study of COVID-19 spatial-temporal spreading in London.

Variability of physical meteorology in urban areas at different scales: implications for air quality.

Effects of ventilation on the indoor spread of COVID-19.