I don’t pretend to have a single, definitive answer to this, but I do have an opinion – and if that’s good enough for the President of the United States of America, it’s good enough for me.
It is worth saying that the (very successful) Behavioural Insights Team was apparently involved in formulating policy around the UK’s response to COVID-19 – and this is covered in more detail elsewhere. As will be, I'm sure, the pros and cons of the UK's response. This article then is not about apportioning blame, but about suggesting some reasons why, even once the message was made clear, we still see a number of people ignoring the calls around social distancing.
On the face of it, we know that human beings are not rational creatures, and so the ineffectiveness of appealing to their rational sensibilities by asking them to stay indoors and not to rush down the pub within 7 seconds of hearing they’re being closed, shouldn’t have been overly surprising to the Government (and probably wasn’t).
However, beyond the glib ‘behavioural economics did it’ type response, what specifically might we be dealing with?
Availability bias: we think things that come readily to mind are more representative than they actually are
For the vast majority of us, a pandemic is not an every day occurrence. Indeed, the last pandemic in which the UK was involved, swine flu, occurred in 2009 and killed 392 people – infecting around 200,000. This is in itself a large number of people, but it occurred 11 years ago and the impact on day to day life was minimal. The availability bias is a tendency in humans to think that examples of previous similar events that come readily to mind are more representative than is actually the case. For example, because aeroplane crashes or shark attacks are well and (relatively) regularly reported, they come readily to mind and thus we overestimate the chance of either of these events happening to us.
In this situation, the opposite is true. Pandemics are not regularly reported, most people do not have particularly direct experience of them and thus we under-estimate the potential risk. Perhaps more concerning, those who are least likely to have been exposed to pandemics or similar events (e.g. younger people) are least likely to obey advice on social distancing, but are very able to transfer the virus to others.
71% reported changing behaviour in response to government guidance. This was lower (53%) for young adults (18-24 year-olds).
Optimism bias: People tend to overestimate the probability of positive events and underestimate the probability of negative events happening to them in the future.
The optimism bias cuts through gender, ethnicity, nationality and age – we all do it. Moreover, numerous academic studies show that we are idealistically optimistic even when the risks are very high. This raises particular issues around those in more vulnerable groups, some of whom have been ignoring the request to self-isolate.
At an overall level though, our optimism bias can encourage us to take more risks, or to ignore potential risks.
Anchoring effect: the tendency to focus on the first piece of information acquired when making a decision.
Obviously, we are able to alter our thinking, but our anchor point has a disproportionate impact on our decision making. There is little argument that the UK government moved relatively slowly at the outset – whether too slowly or not is for someone else to judge – but Public Health England only moved the risk level from ‘Very Low’ to ‘Low’ towards the end of January, and the Prime Minister only asked people to begin working from home on March 16th. There is an argument that the British public’s initial anchoring around the level of risk from COVID-19 was anchored at quite a low level, and it has taken some time to address that initial state.
Narrative fallacy: a good story trumps good facts
We are hard-wired to believe stories over statistics. Daniel Kahneman said:
“System 1 is highly adept in one form of thinking — it automatically and effortlessly identifies causal connections between events, sometimes even when the connection is spurious.”
Possibly, this is because those who assigned meaning to potentially meaningless events were most likely to survive – assume a rustle in the grass is a predator and you’ve not lost a lot if you’re wrong, assume it’s not and it is, and you don’t pass your genes on.
Much of the discussion around coronavirus has been framed around mathematical models and graphs – flatten the curve; 3-day doubling, days since 100 cases. It’s been focused on facts, perhaps at the expense of a cohesive, memorable, unifying narrative. By comparison, 'Do it for Dawn' type posts - many of which have been promoted on social media - have had a much bigger impact because it tells a clear story centred around an individual. A medic, physically and emotionally exhausted from fighting the pandemic, breaks down as she describes the frustration of finding the shelves stripped of provisions she desperately needs; stripped by the people she’s trying to help.
This is something we are increasingly beginning to see.
Framing, endowment and the identifiable victim effect
Framing: we decide on options based on whether the options are presented with positive or negative connotations; e.g. as a loss or as a gain. People tend to avoid risk when a positive frame is presented but seek risks when a negative frame is presented.
Endowment effect: people are more likely to retain an object they own than acquire that same object when they do not own it. We value something more if we have, than if we don't.
Identifiable victim: tendency of individuals to offer greater aid when a specific, identifiable person ("victim") is observed suffering, as compared to a large, vaguely defined group with the same need.
The way in which social distancing was initially framed was negative.
On March 16th, when Boris Johnson requested that people begin to avoid all unnecessary social distancing, the reason that the request hadn’t been made earlier was given as follows:
“The answer is that we are asking people to do something that is difficult and disruptive of their lives.”
And on March 20th:
“Bit by bit, day by day, by your actions, your restraint and your sacrifice…”
From the perspective of the individual the policy of self-isolation has been framed in negative terms – disruption, sacrifice and loss of liberty.
Moreover, the Government have been asking people to give up their freedom and make sacrifices to save a broadly defined group, rather than a specific individual. The thought that one death is a tragedy, but 1000 deaths are a statistic is an apt description for the identifiable victim effect – the idea that we all have a tendency to respond more strongly to the plight of single identifiable person than we do to a large group.
Normalcy bias: people believe things will continue to function the way they normally have functioned in the past, and therefore underestimate both the likelihood of a disaster and its possible effects.
Normalcy bias is to some degree the culmination of the combined impact of the above. The bias describes people’s tendency to drastically underestimate the impact of a disaster. For instance, Roman citizens living in Pompeii watched for several hours as Mt. Vesuvius erupted, thousands of Louisiana residents didn’t flee the state as hurricane Katrina approached, why we are still using plastic and oil as the seas rise and our climate heats up, and why until the 23rd March thousands of British citizens were still congregating in groups.
We just don’t believe it can be that bad.
Scientists actually have a term for the period of 'waiting for the disaster to happen', called milling (as in, 'milling about') and it is typically planned in to any form of disaster response. It is likely to be particularly visible when a situation strikes quickly, and the level of preparedness is low.
Ironically, one evolutionary explanation for the normalcy bias is that paralysis was sometimes the best thing to do in a disastrous situation – for many predators, prey is harder to spot if it is not moving. As humans have evolved our paralysis has become cognitive rather than physical in some cases.
If only we could wind that evolutionary clock back a little bit, and just stay put.
References & attributions
Tiger image by: R_Winkelmann via Pixabay
 Social norming around tax payments, increasing tax collection rates, reciprocity for organ donation, among others.
 Weinstein, Neil D.; William M. Klein (1995). "Resistance of Personal Risk Perceptions to Debiasing Interventions". Health Psychology. 14 (2): 132–140. Bränström, Richard; Yvonne Brandberg (2010). "Health Risk Perception, Optimistic Bias, and Personal Satisfaction". American Journal of Health Behavior. 34 (2): 197–205. Kahneman, Daniel; Tversky, Amos (1982). "Intuitive prediction: Biases and corrective procedures".