In the UK lockdown guidance has changed constantly over time including moving to a system with different tiers throughout the country. This makes sense in a large country, rural areas would have a much different social and economic landscape to large cities. However many people were happy to move between the different tiers moving from a strict area to a less strict area for a weekend break.
This doesn’t make sense from a epidemiology standpoint and from a legal standpoint was also forbidden by the tier system. So why were people so willing to flaunt these government guidelines?
In short, there simply wasn’t any reasonable fear of repercussion nor any expected downside. With regards to the virus, people naturally underestimate their own risk of catching COVID. With regards to contravening the tier system the government introduced relatively low fines and the chance of getting caught, or that the fines would even be enforced, was minimal.
Human Risk evaluation
When evaluating risk we as humans intuitively calculate our risk as the maximum possible downside multiplied by the probability that we incur that downside.
Expected-outcome = probability-of-punishment * severity-of-punishment
For the UK the fines were in the thousands but the probability of anyone enforcing that fine against you was minimal.
Singapore on the other hand had a much earlier and effective lockdown. In early 2021 Singapore had only had a total of 29 deaths from Covid whereas the UK was dealing with around 1000 deaths a day. Even adjusting for population size, the UK is about 11.6x more populous, we can see that Singapore had a highly effective COVID-19 response. It was in fact one of the best in the world.
To look at fines, their fines were higher and implemented early on, very publicly.
Three men hoping to meet up for a drink in Singapore, in violation of lockdown rules, were fined £15,000 and banned from working in Singapore. Another gentleman looking to break quarantine in Singapore was fined £500 and sentenced to two weeks in jail; not to mention the multiple news-articles written about him that are now unfortunately the first search-results for his name on Google. These seems like quite the deterrent.
The UK, especially in the midlands did in fact hand out numerous fines, around 32,000 by the end of December. When adjusted for population size however this equates to around 54 fines per 100,000 people, as opposed to 150 fines per 100,000 people in Singapore; for a total of 8,600 fines in Singapore at the end of 2020.
Case study: Public Transport - London
Wearing a mask on public transport in London was mandated. Signs in and around London transport stations indicate a possible £200 fine; however some signs also indicate a high unlikelihood you will have to pay the fine. How-so?
Firstly the fine is reduced to £100 if paid promptly (within 14 days). In and around London public transport, staff and officials are not strict about requesting people to wear masks. Additionally a myriad of exemptions are mentioned for age, health & disability. It’s great that people who need the leeway are exempt, as they should be, but a lot of the exemptions are hard to prove, making enforcing of fines even harder.
"Eat Out To Help Out"
The government approach to lockdown was somewhat disjointed. This is highlighted by the strict lockdown in 2020 followed swiftly by the "eat-out-to-help-out" scheme. The scheme offered diners in restaurants a 50% discount on meals in an attempt to boost to the economy and get people back into restaurants that had been financially hard-hit by lockdown.
This had the desired economic effect. The effectively free money handed out to people at restaurants was naturally well received by restaurant goers, 64 million diners made use of the scheme in its first four weeks alone. In later months however the scheme was widely-criticised for contributing to a second spike in COVID cases.
Flattening the what?
"Flattening the curve" was introduced as a model for understanding various lockdown measures. Instead of focusing directly on eradicating COVID, "flattening the curve" focuses on mitigating the impact on health-services. So that if the same number of cases occur, they at least occur over a longer period of time to avoid overwhelming the health-care system.
This focus on the limits of the health-care system at least partially explains the stark difference in fatality rates across various countries. Singapore were able to dedicate better hospital resources to infected patients, leading to a fatality rate of only 0.05% of infected people. Other countries of a similar population size such as Denmark had much higher fatality rates of around 3%.
"Flattening the curve" however wasn’t an easy idea to grasp for everyone. The idea that we’re isolating so that we don’t catch COVID makes sense to most people. The idea that we’re mitigating COVID through safety-measures intended to reduce the strain on the NHS to a manageable load, but not completely eliminating it, is a harder concept to grasp.
The concept of "flattening the curve" generally relies on understanding a graph. The graph has time on the x-axis and "strain on the NHS" on the y-axis:
The idea of "flattening" effectively brings in a third variable. Making this a three-dimensional visualisation often best illustrated as an animation. Telling people they need to stay at home based on a 3 dimensional mathematics problem wasn’t exactly straightforward for most people to grasp.
Furthermore the idea of mitigating "strain on the NHS" is neither easily measurable nor precise. When attempts were made to make it more precise by counting average daily-infections and r-number, these proved to be too mathematical and people quickly tuned out.
While the idea of flattening the curve has great merit, it was poorly communicated and made it hard for the general public to grasp the importance of lockdown.
Does this mean the UK lockdown was doomed to failure? I don’t think so.
Does this mean the general public are unlikely to grasp anything complex and that lockdowns were doomed to fail from the start? I don’t think that’s quite fair. Incentives just need to be communicated properly.
If we look at the widely popular eat-out-to-help-out-scheme, people didn’t necessarily understand the economics behind it. Not everyone needed to understand that they were providing a vital cash injection, hoping to stimulate the economy and mitigate the risks of long-economic-covid. It isn’t particular complex but the bottom line was even simpler: If you want to eat out, you can save 50% off the price of your bill.
In effect, restaurants are giving out free-money.
Better Incentive Structures
Returning to our earlier look at "expected outcomes" and "risk evaluation" perhaps mandated-mask-wearing could learn something from the eat-out-to-help-out scheme. A similar approach to disincentives as incentives could have provided better outcomes. If the penalty for not wearing a mask had been considerably higher and enforced by station staff, much the way they enforce fare-evasion, it is more likely that people would simply have chosen to wear a mask on public transport.
Taking our previous formula:
Expected-outcome = probability-of-punishment * severity-of-punishment
By increasing the probability of getting caught and the maximum fine, the expected-outcome shifts from a slap on the wrists to a financial incentive to avoid getting fined. If masks were easily provided at stations, the barrier to attaining and wearing a mask would be minimal when compared to the potential outcome of a hefty fine. Wearing a mask, would have become the obvious choice, regardless of understanding the epidemiologists point of view.
One caveat to this is extremely wealthy individuals who may simply be willing to pay the fine and consider it an extra cost of their journey. Looking again to Singapore their approach seems to have been jail-time associated on top of the fine. Someone caught violating quarantine rules for a night might have just paid the £500 fine in addition to the costs of their evening, however the additional 2 weeks of jail time as well as associated public embarrassment and potential criminal record should serve as quite the hefty disincentive.
Economics of Crime and Punishment:
Becker, Gary S. "Crime and Punishment: An Economic Approach." Journal of Political Economy 76, no. 2 (1968): 169-217. Accessed May 16, 2021. http://www.jstor.org/stable/1830482.
Friesen, Lana. "Certainty of Punishment versus Severity of Punishment: An Experimental Investigation." Southern Economic Journal 79, no. 2 (2012): 399-421. Accessed May 16, 2021. http://www.jstor.org/stable/41638882.