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Biomathematical methodology to obtain accurate COVID-19 pandemic estimates from incomplete data

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:0 publications

Grant number: C19-IUC-134

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Key facts

  • Disease

    COVID-19

  • Start & end year

    N/A

  • Funder

    UK Research and Innovation (UKRI)

  • Principal Investigator

    Prof. Federico Turkheimer

  • Research Location

    Italy

  • Lead Research Institution

    MRC Centre for Neurodevelopmental Disorders at King's College London

  • Research Priority Alignment

    N/A

  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease transmission dynamics

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

To assess the asymptomatic infection rate using Italian and world-wide data as part of a collaboration with ISPI (Bocconi University, Italy). To use these estimates to inform policy and inform simulations of end-of-lockdown scenarios