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From Herd Immunity to Flattening the Curve

Italy's health service was overwhelmed by COVID-19 cases requiring intensive care. See how the SIR curve is used other countries to avoid this
© UNESCO UniTwin CS-DC & The Open University

This is an additional video, hosted on YouTube.

In this video Prof Chris Whitty, Chief Medical Officer of the National Health Service briefly summarises the British Government’s policy to save the NHS and save lives:

  • only go out when necessary
  • always try to stay two metres apart
  • do not meet others outside your household – even friends and family

This ‘lockdown’ policy will have a massive impact on the finances of the UK as illustrated by this tweet from the Office of Budget Responsibility:

In our scenario, the shock to the economy and the huge Government policy response raise this year’s budget deficit by around £220bn to around 14% of GDP and public debt to around 100% of GDP..

How did the UK Government conclude that it had to implement a policy that would shut down most of the economy for months at great social and financial cost?

When making policy governments have a major choice – do something versus do nothing. As Bridget Rosewell explains, ‘do nothing’ may appear to be a policy option for no change but could result in drifting into the unknown. However:

‘doing something’ has the additionality problem, namely showing the benefits over doing nothing or something else. All investment impacts are on the balance of probabilities. Risk free investment and risk free policies are not possible in a complex world. What matters is to have a strong story, backed up by strong evidence on the main elements of the story. Then take a bet. [1]

Herd Immunity

In the UK the Government’s first bet was on herd immunity. The idea is that as the number of susceptible members of the population decreases the virus finds it increasingly difficult to find hosts and the population of viruses dies out, as shown in Figure 8.1.

Figure 8.1. Herd immunity grows as the susceptible population falls Graphs illustrating herd immunity

The risk of a policy depending on herd immunity is that the epidemic will overwhelm the available intensive care resources, as shown in Figure 8.2.

Figure 8.2. Herd immunity policies may overwhelm care provision graph showing the supply of intensive care resources is less than required at the peak of the epidemic

Herd immunity is usually a policy objective when a vaccine has been developed. The principle of vaccination is that it gives individuals immunity against a virus and reduces the proportion of susceptible people in the population. You will be able to experiment with this approach in Week 2. Currently these is no effective vaccine against COVID-19 but, under WHO’s coordination, a group of experts with diverse backgrounds is working towards the development of vaccines against COVID-19 [2].

Flattening the Curve

Figure 8.3. illustrates the possibility of flattening the curve of number of infected people so that there is sufficient provision of intensive care for the health service not be overwhelmed.

Figure 8.3. Flattening the curve saves the NHS from being overwhelmed graph showing the supply of intensive care resources is greater than required if the epidemic is flattened

What do you think

Do you think herd immunity is a good policy? Do you think flattening the curve might help protect the health service? Can you think of any policies for flattening the curve that would not be socially or economically disruptive?

Reference

[1] Bridget Rosewell, ‘Complexity Science and the Art of Policy Making’, in Non-Equilibrium Social Science and Policy, 159-178. Editors J. Johnson, A. Nowak, P. Ormerod, B. Rosewell, Y-C Zhang, Springer Open, 2017. https://link.springer.com/chapter/10.1007/978-3-319-42424-8_11

[2] World Health organisation, “Public statement for collaboration on COVID-19 vaccine development”, 13 April 2020 updated 16 April 2020 https://www.who.int/news-room/detail/13-04-2020-public-statement-for-collaboration-on-covid-19-vaccine-development

© UNESCO UniTwin CS-DC & The Open University
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COVID-19: Pandemics, Modelling, and Policy

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