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COVID-19: Pandemics, Modelling, and Policy

4.7 (126 reviews)

Explore how scientists model the spread of pandemics, and what this tells us about the policy options for managing COVID-19.

6,054 enrolled on this course

COVID-19: Pandemics, Modelling, and Policy
  • Duration2 weeks
  • Weekly study2 hours
  • LearnFree
  • Extra BenefitsFrom $59Find out more
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Discover the role forecasts and computer models play in understanding pandemics

With the world in the grip of the coronavirus pandemic, there has been a surge of interest in scientific modelling of the outbreak.

On this course, you’ll explore the social, economic, and political factors in the spread of a pandemic such as COVID-19, examining how scientists try to forecast the spread and severity of epidemics, and what we can and can’t know.

You’ll use interactive graphical programs to explore the dynamics of epidemics, learning how to critique the underlying models, and how science and computer models can support policymakers in times of pandemic crisis.

What topics will you cover?

  • 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

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

What will you achieve?

By the end of the course, you‘ll be able to...

  • 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.

Who is the course for?

This course is for anyone wanting to make sense of the conflicting information around COVID-19. This includes scientists, health professionals, policy planners, or just interested citizens.

Who will you learn with?

Jeffrey Johnson

I am Professor of Complexity Science and Design at the Open University & Vice President of the UNESCO UniTwin Complex Systems Digital Campus. I am interested in interdisciplinary science for policy.

Who developed the course?

UNESCO UNITWIN Complex Systems Digital Campus

The Complex Systems Digital Campus is an international network of individuals and institutions working together to promote research and education in complex systems science and in integrative sciences

The Open University

The Open University (OU) is the largest academic institution in the UK and a world leader in flexible distance learning, with a mission to be open to people, places, methods and ideas.

  • Established1969
  • LocationMilton Keynes, UK
  • World rankingTop 510Source: Times Higher Education World University Rankings 2020

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