COVID-19 Intervention Modelling for East Africa (CIMEA)

  • Funded by Foreign, Commonwealth & Development Office (FCDO), Wellcome Trust
  • Total publications:0 publications

Grant number: unknown

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2022
  • Known Financial Commitments (USD)

    $1,699,974.39
  • Funder

    Foreign, Commonwealth & Development Office (FCDO), Wellcome Trust
  • Principle Investigator

    Pending
  • Research Location

    United Kingdom, Europe
  • Lead Research Institution

    University of Warwick
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease transmission dynamics

  • Special Interest Tags

    Gender

  • Study Subject

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

COVID-19 is a global threat to health, with many countries reporting extended outbreaks. To date 9 countries in Africa have recorded infection and it seems imminent that East Africa will have introductions and onward transmission. The SARS-CoV-2 virus (the aetiological agent of COVID-19) spreads rapidly (R0~2, serial interval about 1 week), and hence control will be difficult. National plans for dealing with this public health emergency will benefit from predictions of the expected rate, distribution and extent of spread in countries throughout the region, and on the likely impact and feasibility of isolation and contact tracing interventions. We will support the emergency preparations through bespoke modelling, incorporating known demographic population structure, age-related contact patterns and existing mobile phone population movement data. In Uganda and Kenya we will collect epidemiological, genomic and behavioural data through health facility surveillance, household follow-up and contact studies to quantify uncertainties of SARS-CoV-2 virus epidemiology and contact patterns in well and unwell individuals. Results from the study will be rapidly communicated to the relevant authorities, and modelling code and analysis, and data including sequences, placed in the public domain in near real-time. This project could have lasting impact on the role of research in policy decisions.