Introduction to Week 2
Resumé of Week 1
Previously we reviewed some of the vital statistics of COVID-19 and the crises in healthcare systems. The Kermac-McKendrick SIR model was presented as the basis for discussing herd immunity and flattening the curve. The Imperial College report was seen as a policy changer in the UK. We considered prediction and forecasting in policy making, noting that some systems are inherently unpredictable but useful things can be known about their future behaviour. Complex Systems Science was presented as a way ahead to support policymakers.
This week the focus is on modelling and data analysis to support policy. Although this necessarily involves some technical ideas it is written to be accessible to everyone.
At social gatherings if anyone mentions mathematics someone usually says “Oh. That was my worst subject at school”. If maths was your worse subject at school we will try very hard to make the ideas intuitive and easy to understand. We certainly won’t ask you to do any sums. And if you like maths you may find thinking about these ideas attractive.
In the next step you will be able to experiment with the SIR model you met last week. After this we’ll explain more formally what we mean by a model and introduce the notions of micro-, meso- and macro- modelling. You will see an Agent-Based Model which simulates the microlevel interactions between human agents and the consequent spread of an epidemic. After this you will be introduced to time series analysis and the problem of extrapolating the SIR curves into the future based on data from the past.
In May 2020 many countries will see their curves of infection and death begin to peak. At the same time lockdown policies are becoming increasingly unpopular and government are under enormous pressure to let people go back to work, let children go back to school, let grandparents cuddle their grandchildren, let friends meet in the pub, let people sunbathe in the park, let us go on holiday, and so on. Politically there is great pressure to get the economy going again and to limit the damage in terms of businesses failing and people losing their jobs. Is this the right time to relax lockdown?
How to manage the recovery is a great challenge. Relax the constraints too early and the virus may reappear in a damaging second wave. Relax the constraints too late and more businesses will fail with more people losing jobs and more cost to the treasury. You will have the opportunity to participate in a policy making exercise: should people wear face masks?
We will bring the course towards an end with a section on real world modelling. The models used on this course have all been very simple. Even so, our models have much in common with those used for real policy making but inevitably ours lack depth, detail and scale.
Finally we will consider the future as our nations recover. Many countries have never experienced such economic damage in peacetime and we will not be able to go back to business as usual. In this context we will consider how complex systems science and modelling can help policy makers and citizens design the future.
© The UNESCO UniTwin CS-DC and The Open University