Covid-19 in numbers: Critical failures of global governments
Firstly, a disclaimer. I am by no means an expert in data or anywhere close to being a scientist. I might have a degree in Politics & IR under my belt but other than that, I am just a concerned citizen with a lot of curiosity, frustration and anger about the situation the UK has now been in for several months. The British government’s response and explanation for our situation left me feeling like the wool had somewhat been pulled over my eyes and I was being fed cherry-picked data. A grim global table of deaths per country was first produced at a daily Downing Street briefing on 30 March. The last day that table was presented was also the day it showed the UK as having the highest death toll in Europe.
I wanted full and neutral data to really grasp the scale of how badly our government has failed us. And so I went on a search for global data and explanations for how vastly different the reactions and outcomes were to COVID-19 across the world.
In this post, using statistics, I’ll be analysing the British government’s handling of the crisis compared to some of the countries that are deemed to have handled the pandemic the best (New Zealand, South Korea and Taiwan) as well as countries that have struggled (the USA, Spain and Italy). I’ll be looking at to what degree certain factors affect a country’s fatality rate.
Is testing a key factor?
Definitely. From the start, the British government downplayed the importance of testing, despite professional opinions and clear evidence from other countries that managed to keep deaths down. Instead, the government initially adopted an alarming ‘herd immunity’ strategy (described by the Australian Prime Minister as a “death sentence”). When it became clear how catastrophic an approach that would be, the government reversed its stance on ‘herd immunity’ but didn’t reconsider its stance on testing until much later.
Although the UK began ‘drive-through’ testing on 28 February for members of the public, the government made a bizarre U-turn on 13 March and decided that testing would only be offered to hospitalised cases of COVID-19. On 31 March, former WHO director Anthony Costello criticised the British response and said that the UK had the capacity to reach the level of testing being carried out by Germany (70,000 tests a day, compared to the UK’s 5,000) but the government and Public Health England (PHE) had been too slow and controlling to organise this.
Here are some numbers to put the importance of testing into perspective. 50 days after South Korea’s first case was confirmed (9 April), South Korea had about 10,423 cases and 204 deaths, with over 494,711 people having been tested. South Korea had a case fatality rate of 1.95%, which was lower than the WHO’s global case fatality rate (at the time) of 4.34%. 50 days after the UK’s first case was confirmed (20 April), the UK had only tested 72,818 people yet had 19,051 deaths. As of 14 June, South Korea has had 5 deaths per million people and the UK has had 614 deaths per million people. You might now be assuming that population density played a role in this numbers, which leads us on to the next factor.
Is population density a key factor?
To an extent. South Korea is denser than the UK, with 528 people per km2 whilst the UK has 273 people per km2. If we adjust for population density and assume the UK had the exact same density as South Korea, the UK would instead be looking at 1,188 deaths per million people compared to South Korea’s 5 deaths per million. That is a shocking disparity. Singapore, the third most densely populated state in the world, only saw 4 deaths per million people. Singapore’s density stands at 7,916 people per km2. Scaling up the UK’s population density to Singapore’s level would give the UK 17,804 deaths per million people. (But of course, although Singapore is one of the most densely populated countries in the world, it appears to have a healthcare system that acts in step with this).
But what population density in the other extreme? New Zealand has a population density of just 18 people per km2. New Zealand’s total number of COVID-19 deaths is 22, working out to be 5 deaths per million people. If we scale up New Zealand’s population density to match the UK’s, New Zealand would have had 76 deaths per million people. Again, these numbers show that population density doesn’t appear to have as significant impact as we might assume.
Is a ‘lockdown’ a key factor?
If population density doesn’t seem to be a key factor in our country cases, what about the impact of a ‘lockdown’? Surely South Korea had a strict lockdown? Actually, no. South Korea was one of very few countries to not enforce a nation-wide lockdown. Other countries that took the same approach include Taiwan, South Korea, Japan and Indonesia. And what else do all those countries have in common? Unexpectedly, a very low COVID-19 fatality rate. But crucially, they all have two other factors in common: strictly enforced face-mask wearing and large-scale social distancing.
In contrast, New Zealand enforced one of the world’s strictest lockdowns for 50 days. Was New Zealand’s very low fatality rate down to the lockdown or another factor? It’s hard to tell. Shutting their national borders 20days after their first confirmed case was probably a crucial factor, only allowing residents to enter if they quarantined for 14 days. In comparison, the UK didn’t enforce a quarantine period for all persons arriving in the UK until 12 June. That’s an unbelievable 133 days after the UK’s first confirmed COVID-19 case.
Is the use of face-coverings a key factor?
In short, yes. Research published in May 2020 by Xi He (of Guangzhou Medical University) and Eric Lau (of Hong Kong University) suggests that 44% of COVID-19 cases are caused by transmission from people without symptoms at the time of transmission. Backing up these findings is research published by The Economist which compares the effects of enforcing a lockdown and mask-wearing.
Anyone who has visited Hong Kong and Taiwan will know how ubiquitous facemask-wearing is there, even on an average day. Fear the judging eyes of fellow passengers if you so much as cough on the MTR and are not wearing a facemask. (Facemasks are so common that some of the younger generation in Hong Kong almost use them as a fashion accessory, sporting masks with all kinds of quirky prints). Like neighbouring Taiwan, Hong Kong learnt hard lessons from the deadly SARS outbreak of 2002-2004 and wearing a mask in public at the sign of any infectious illness is expected. Witnessing meticulous cleaning of lift buttons and handrails is also part of everyday Hong Kong.
Since mid-April, the Mayor of London, Sadiq Khan, had been lobbying the central government to make the use of face masks compulsory on public transport in London. The government finally conceded and made the use of face-coverings compulsory on public transport in England. India also requires them to be worn in crowded public spaces, as do France, Germany, Italy and Spain.
Is social distancing a key factor?
It seems so but is hard to effectively judge. According to a tracker maintained by the University of Oxford’s Blavatnik School of Government, the UK was slower than its European neighbours, including France and Italy, to introduce social interaction restrictions. As of 14 June, Italy’s fatality rate is 567 deaths per million people, France’s is 450 deaths and the UK’s is 614 deaths.
In Indonesia, 13 days after their first COVID-19 case was confirmed, the President called for all Indonesians to exercise social-distancing measures. By this time, some regions had already closed down schools and public places. In the UK, the government’s call for schools to close was not ordered until 18 March. That was 47 days after the UK’s first confirmed COVID-19 case. As of 14 June, Indonesia recorded 8 deaths per million. In comparison, the UK recorded 614 deaths per million.
All in all, I clearly can’t draw any meaningful conclusion. I’m definitely not a scientist or statistician. There’s an endless number of factors to compare in how COVID-19 spread, as well as data anomalies, accuracy of data estimates and so much more. This is also a virus we are still learning about. All this talk of data and factors won’t be for everyone but I hope others find it informative and sobering to see in numbers the true global cost of COVID-19 and not just the figures cherry-picked by their government. Hopefully the more we read about every COVID-related, the more we can learn and just do better.