{
  "title": "A Pandemic Forecasting Framework: An Application of Risk Analysis",
  "publication": "IMF Working Papers, August 27, 2021",
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  "summary": "This paper introduces a simple, frequently and easily updated, close to the data epidemiological model that has been used for near-term forecast and policy analysis. We provide several practical examples of how the model has been used.",
  "sections": [
    {
      "heading": "Overview and model purpose",
      "content": "- Introduces a simple, frequently and easily updated, close to the data epidemiological model used for near-term forecast and policy analysis.\n- Model used for practical examples and policy analysis focused on epidemic development and short-term forecasting."
    },
    {
      "heading": "Key findings and applications",
      "content": "- The model explains epidemic development in the UK, the USA and Brazil through the model lens.\n- The model would have predicted that a super infectious variant, such as the delta, would spread.\n- Current vaccination levels in many countries are argued to be not enough to curb other waves of infections in the future.\n- Brief discussion of the importance of how to model re-infections in epidemiological models."
    },
    {
      "heading": "Policy-relevant implications",
      "content": "- Frequent and easily updated, data-close models can inform near-term forecasting and policy analysis.\n- Vaccination coverage levels should be evaluated against the risk of more infectious variants to assess vulnerability to future waves.\n- Modeling of re-infections matters for accurate epidemic projections and policy design."
    },
    {
      "heading": "Subjects and keywords",
      "content": "- Subjects: Aging, COVID-19, Emerging and frontier financial markets, Financial markets, Health, Population and demographics\n- Keywords: Aging, COVID-19, COVID-19, Emerging and frontier financial markets, epidemiology modelling, Global, Google mobility, vaccination assumption, vaccination data, vaccine hesitancy, vaccines impact, virus variant, virus variants and testing\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2021/08/27/a-pandemic-forecasting-framework-an-application-of-risk-analysis-464810"
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    "Authors: Allan Dizioli, Daniel Rivera Greenwood, Aneta Radzikowski",
    "Published: August 27, 2021",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781513594842.001",
    "Introduces a simple, frequently and easily updated, close to the data epidemiological model used for near-term forecast and policy analysis.",
    "Model used for practical examples and policy analysis focused on epidemic development and short-term forecasting.",
    "The model explains epidemic development in the UK, the USA and Brazil through the model lens.",
    "The model would have predicted that a super infectious variant, such as the delta, would spread.",
    "Current vaccination levels in many countries are argued to be not enough to curb other waves of infections in the future.",
    "Brief discussion of the importance of how to model re-infections in epidemiological models.",
    "Frequent and easily updated, data-close models can inform near-term forecasting and policy analysis.",
    "Vaccination coverage levels should be evaluated against the risk of more infectious variants to assess vulnerability to future waves.",
    "Modeling of re-infections matters for accurate epidemic projections and policy design.",
    "Subjects: Aging, COVID-19, Emerging and frontier financial markets, Financial markets, Health, Population and demographics",
    "Keywords: Aging, COVID-19, COVID-19, Emerging and frontier financial markets, epidemiology modelling, Global, Google mobility, vaccination assumption, vaccination data, vaccine hesitancy, vaccines impact, virus variant, virus variants and testing",
    "**Working Paper**"
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