COVID-19: Optimal Lockdown

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:3 publications

Grant number: EP/V025899/1

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Key facts

  • Disease

  • Known Financial Commitments (USD)

  • Funder

    UK Research and Innovation (UKRI)
  • Principle Investigator

  • Research Location

    United Kingdom, Europe
  • Lead Research Institution

    University of Warwick
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags


  • Study Subject


  • Clinical Trial Details

    Not applicable

  • Broad Policy Alignment


  • Age Group


  • Vulnerable Population


  • Occupations of Interest



The current COVID-19 pandemic has caused whole countries to lockdown, with a huge effect on people's lives and in the economy. Naturally, there are questions about how efficient this lockdown is, and increasing interest in how our country will reduce social distancing measures and eventually go back to normal. We propose to answer some of these questions by using cutting edge epidemiological models for the spread of COVID-19 in the UK using census data to model the typical behaviour of the UK population accurately and then combining this with the increasingly available data from the NHS, PHE and the ONS, which will help us model the spread of COVID-19 in our communities. These models will then be explored in order to design an optimal mitigation strategy based on closing public and commercial venues, or shutting down transport links, and an exit strategy from our lockdown, which will be achieved by reopening such venues or gradually restoring public transports. These strategies will be adapted frequently in response to daily data. Our resulting models and control strategy will be publicly available on a dedicated website, which will be updated frequently as new data becomes available.

Publicationslinked via Europe PMC

Last Updated:38 minutes ago

View all publications at Europe PMC

Bayesian inference of polymerase dynamics over the exclusion process.

Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning.

Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic.