Certificate of Achievement
has completed the following course:
COVID-19: Pandemics, Modelling, and Policy
UNESCO UNITWIN Complex Systems Digital Campus and The Open University
This online course showed how mathematical, statistical and computer modelling inform policy for the COVID-19 pandemic. The basic facts of the virus were reviewed as were the policy challenges. Modelling was introduced by time series analysis and the SIR model. Hands-on computer simulations used mathematical and agent-based modelling to investigate policy options at micro, meso and macro levels. The science-policy interface was investigated including a critical review of modelling for policy.
2 weeks, 2 hours per week
Jeffrey Johnson
Professor of Complexity Science and Design
UNESCO UNITWIN Complex Systems Digital Campus
Transcript
Learning outcomes
- Explain the currently accepted facts and statistics of COVID-19 such as the incubation period, recovery time and basic reproduction rates.
- Explain what models are and how they are used in policy making
- Model the COVID-19 pandemic using computational methods including time series and implementations of the SIR (Susceptible, Infected, Recovered) model
- Evaluate and critique models and computer modelling in a policy context
- Explain the difference between macro-modelling at the level of a whole population, micro-modelling at the level of the individual, and meso-modelling at the level of organisations and social events.
- Evaluate reports used to guide policy and explain how policy makers must deal with conflicting scientific evidence.
Syllabus
- COVID-19: a brief description, the problem, and what we need to know?
- The nature of prediction – why things can or can’t be predicted
- Modelling – creating and using computational models
- Policy– how is policy made? How does policy interface to science?
- Complex systems science for exploring and planning the future
Issued on 3rd May 2021
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