Charley Says Social Distancing

Charley was a character in UK Public Information Films in the 1970s. Here he is in ‘Charley Says Social Distancing’

“Treat everyone else as if they’re about to catch fire and you’re a lit match.”

Charley: Miaoweeaawwwoa [I can’t believe I’m writing this]

Narrator: This is you. You’re a match. And these are your friends. You catch the virus and you’re on fire. You’re too close – now all your friends are alight – you’ve infected them with the virus.

Tony, the Boy: Charley says that if ever you see a box of matches lying around, tell mummy because they can hurt you.

Narrator: We’d like the virus to spread slowly so to match the capacity of the health service. It takes a few days before your friends get ill, so you can’t see it spreading.

The virus is spreading rapidly so we need to slow it down. If you’re older or have an underlying medical condition, you need to stay apart.

That’s better. Keep apart. Treat everyone else as if they’re about to catch fire and you’re a lit match.

Charley: Awoooarwah.


For advice on COVID-19, see:HM Government NHS (UK National Health Service) WHO (World Health Organization) US CDC (Centers for Disease Control and Prevention) US NIH (National Institutes of Health)

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I am concerned about the UK Government’s approach to social distancing

The real problem with Coronavirus Covid-19 is that when the health service becomes overloaded, the death rate goes up significantly. So, it is imperative that we keep the number of cases at any one time below or as near as possible to NHS capacity.

The Government’s model relies on shifting the peak. I am not clear that we are doing this fast enough. We are an outlier compared to other countries in our social distancing policy response.

There is a tension between epidemiologists – those who study how diseases spread (a very established science started around the time of the Spanish Flu 100 years ago), and behavioural scientists who study how people behave and react.

Epidemiologists have models validated against past pandemics. Behavioral scientists do not.

There are economic and social costs of social distancing. But if you delay social distancing too much, there are potentially very real human costs in increased mortality. Doctors will need to make very difficult moral decisions on who to treat and who not to treat.

I do not understand why, if the intention is to create herd immunity, why we are not isolating our vulnerable population, especially those in care homes.

Behavioral insights are great when you are trying to get people to pay their tax bills on time. And if people don’t, it doesn’t really matter. With a pandemic, if you get the timing wrong, more people die unnecessarily. Then you look back from your computer and say, yes, we got that behavioral model wrong while doctors and nurses on the front line are exposed to extra cases that could put their own lives at risk.

Here’s a video to show what we should be trying to do:

Social Distancing using Play-Doh and Matches

There has been much talk about using social distancing as a response to the Coronavirus outbreak. Here’s a video of how social distancing can be used:

  • Close Contact, where the population is infected very rapidly. This is not A Good Thing – the national health service is overwhelmed, and the death rate goes up as a result
  • Extreme Distancing, where the viral spread takes too long. This is not A Good Thing – the social and economic costs are huge
  • Optimal Distancing, where the spread is controlled and the human, social, and economic costs are optimized. This is A Good Thing. It is also very tricky to get right.

Coronavirus: The First Big Test of Behavioral Science

The United Kingdom is at a crossroads, an ideological battle between natural science and behavioral science. Let’s hope for all our sakes we get this one right.

Boris Johnson, the UK Prime Minister, is facing a dilemma. When do we go from the so-called containment phase for controlling Covid-19 Coronavirus, to the delay phase.

In the medical / natural science corner, is the Chief Medical Officer, Professor Chris Whitty, who has presented himself calmly, reassuringly, as completely on top of his brief. He is a physician and an epidemiologist (as well as a lawyer, and an MBA). His evidence at the newly formed House of Commons Coronavirus Committee was calm, frank, precise. He is exactly the sort of advisor that any government would be proud to have. Flatten the peak. Delay the virus spread. Keep the height of the peak low. Save lives.

Mitigation efforts like social distancing help reduce the disease caseload on any given date, and can keep the healthcare system from becoming overwhelmed.
Image: New York Times adapted from CDC/Economist

In the behavioral science corner is, well, I am not sure who. Maybe it’s the Chief Scientific Advisor, who highlighted the need to take account of behavioral science. Yes, please do. It’s a wicked problem, and please include more complex social modelling.

But what we are now seeing is what the Director General of the World Health Organization (up until now also criticised for its seemingly political response to the issue) could be referring to as ‘alarming levels of inaction’.

I do hope, however, that Boris Johnson is being guided by the science, both behavioral and epidemiological, and not by advisors who profess to be superforecasters. You don’t have to be a superforecaster to forecast that if we get this wrong, many will die unnecessarily.

Contagion: How to Model It and What R-nought (R0) Actually Means

The 2011 film Contagion, starring the spectacularly ill-fated Gwyneth Paltrow, is a dramatization of a viral pandemic starting in pretty analagous circumstances to the current Wuhan Coronavirus (2019-nCoV) outbreak. It’s a good film, and is a great introduction to the work of Centers for Disease Control (CDCs) that monitor the spread – the epidemiology – of the disease. There are two scenes where R-nought, or R0, are described:

Despite the blogger character in the clip describing the spread, using a R0 of 2, as being a problem you can do on a napkin, it takes a little more thinking about. He also seems a bit confused about R0, talking about growth from 2 to 4 to 16, to 256, to 65,536 each day. That’s not what R0 is – it is not a rate, and actually if the rate was 2, this would mean 2 to 4 to 8 to 16 to 32 etc., each time doubling the number. It is possible that he is thinking that there are two generations each per day, but that’s not whatR0 is.

So, on to the professionals:

The CDC epidemiologist in the clip is more on point (despite having sloppy notation with no subscripts). This is better – it shows the reproduction number for the infection – note again, this is not a rate – no time dimension is involved – it basically shows the number of cases on average each case generates.

This population modelling – so called SIR (Susceptible, Infected, Recovered) system dynamics modelling – is just one of several approaches that can be used to model contagion across a population. My recent paper ‘Spatial Transmission Models: A Taxonomy and Framework’ sets out a review of what they are and the advantages and disadvantages of each. In brief, we can model the population numbers, the individual agents that carry the virus, the network of contacts between infected individuals, or the regions or cells in which individuals are located (city districts, for example). The paper is available to read by clicking on the link here.