A Pandemic Forecasting Framework: An Application of Risk Analysis
IMF Working Papers, August 27, 2021
Source details
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- A Pandemic Forecasting Framework: An Application of Risk Analysis
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Bibliographic details
- Authors: Allan Dizioli, Daniel Rivera Greenwood, Aneta Radzikowski
- Published: August 27, 2021
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781513594842.001
Overview and model purpose
- 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.
Key findings and applications
- 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.
Policy-relevant implications
- 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 and keywords
- 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
Content in this bundle
- Working Paper