By Neil Lock

This is a follow-up to my June paper on the numbers relating to the COVID epidemic world-wide. That paper is at https://wattsupwiththat.com/2020/06/20/covid-19-understanding-the-numbers-coronavirus/. This time, the main focus will be on the question: how well have lockdowns worked in different countries? I will look first at those countries in Western Europe, which show evidence (or not) of the various lockdowns having had a significant effect on the daily new case counts. Then, I will visit some of the more “interesting” countries (from a COVID statistics point of view at the present time) in other parts of the world.

As for the first paper, my data comes from Our World in Data. It can now be downloaded from https://ourworldindata.org/coronavirus-source-data. They are still keeping their spreadsheet (now 34,600 rows and counting) updated each day. They have also added a “stringency index” column to the daily record, which indicates how tightly the particular country was locked down on the particular day. I’ll discuss that soon. All the data I use in this paper came from their spreadsheet dated August 4^th, 2020.

But before I begin, an explanation for non-Brits of the word “cock-up” in the title. The Cambridge Dictionary defines it as “something that is done wrong or badly.” A North American equivalent might be “snafu,” although it usually takes many cock-ups to make a full snafu. Cock-up is to snafu, roughly, as dime to dollar.

The question I aim to answer is: Is there evidence that the “lockdown” reactions to the epidemic of governments around the world have significantly helped to alleviate the effects of the virus, compared with what would have happened without those lockdowns? Or has it, perhaps, been a lot of pain for no, or little, real gain? You shall judge.

The Stringency Index

The “stringency index” is a summary number (expressed as a percentage) of how far a country is locked down. 0% is business as usual, while 100% represents maximum restrictions for all the criteria considered. The stringency data supplied to Our World in Data, and the supporting .csv file of daily data, both come from the Blavatnik School of Government, which like Our World in Data is a part of Oxford University. The file I used was the version from August 5^th.

You can download the .csv file from https://www.bsg.ox.ac.uk/research/research-projects/coronavirus-government-response-tracker. (They now have an additional secondary dataset on US states’ responses to COVID-19.) The guide which explains the individual data fields is at https://github.com/OxCGRT/covid-policy-tracker/blob/master/documentation/codebook.md. The full codebook (working paper) and the documentation on the new US data are available as PDFs from https://www.bsg.ox.ac.uk/research/publications/variation-us-states-responses-covid-19.

There are nine factors included in the stringency index. They are: school closing, workplace closing, cancel public events, restrictions on gathering size, close public transport, stay at home requirements, restrictions on internal movement, restrictions on international travel, and public information campaign. In calculating the stringency index, they weight all nine factors equally; an approach which, for me at least, seems as good as any.

I did, however, identify what seem to me to be a couple of things missing from their nine-factor system. Firstly, there is no mention of mask-wearing requirements at all. And secondly, they have only a single “workplace closing” factor, whereas I would have preferred two. One for workplaces open to the public, such as shops, restaurants and bars; and one for other workplaces, such as offices and factories. This is because some countries, including the UK, have locked down considerably harder on the first than the second; and have also loosened that lockdown in several phases. It’s unfortunate that, because of the conflation of the two types of workplaces, none of these relaxations appear as changes in the stringency index for the UK at all.

All that being said, it’s the best data I’ve got, so I’m going to explore it!

The underlying mathematics

My first question on how to assess the lockdowns was: What should I plot the stringency index against, to try to get an idea of how changes in it might (or might not) have affected new cases? To make that decision, I needed to learn a (very) little about the epidemiological mathematics.

Since I was only interested in new cases, I only needed to think about one transition: the one from Susceptible to Infected. Obviously, the number of infections that are detected as new cases will depend on the level of testing being done, as well as the number of new infections. But it’s rare for the level of testing to change significantly and very suddenly. (Sweden at the beginning of June is the only case I know of). So, if I keep my time horizon short enough – say, a week – it should be a reasonable assumption that the number of new cases (eventually) detected will be roughly in proportion to the number of new infections.

Now, the most appropriate of the epidemiological models to COVID is probably the SEIR model. But if I make the (over-) simplifying assumption that the incubation period is roughly constant, then I can just use a basic SIR model. Such models have a new infection rate of the following form:

An extra complication is that the number of new cases in an epidemic has its own dynamics. To mis-quote Larry Wall’s Harvard Law: “Under controlled conditions of light, temperature, humidity, social interaction and other factors, the organism will do as it damn well pleases.” So, I thought it wouldn’t be useful to try to look for the effects of lockdown or release directly in the new case numbers. Instead, I thought, I’ll look at the rate of change of new cases. The effects of a lockdown or release ought to be visible as a “knee-bend” (maybe not instantly, but certainly within a couple of weeks) in this rate of change.

How I graphed the lockdowns for the UK

In my earlier paper, I used a graph of daily growth of weekly averaged new cases, to enable me to pick out early outbreaks of the virus which were too small to be easily visible on the headline graph of daily cases and deaths. So, I adapted this into a graph of growth of new cases on a weekly basis. I started out by trying to plot the ratio of the raw new case count to the count from 7 days previously; but the data proved to be too noisy for that to be useful. So, I had to settle for the week-on-week change in new case counts which were already weekly averaged. The purist in me gags at such a kludge; but climate scientists can get away with doing such things, so why can’t I?

So, the weekly growth percentage shown for a given day is the ratio of the (already weekly averaged) new cases 4 days after that day, to the new cases 3 days before that day. The date underneath a point on the graph is as close as I could make it to the centre of the period from which its data was taken.

I also decided, in order to keep the height of the graph within reasonable bounds, to cap the weekly growth percentages at a maximum of 200%. Anything above 200% is simply shown as if it was 200%. The resulting graph for the UK, my starting point for this journey, comes out like this:

The blue line tells us that the week-on-week growth has been negative for most of the time since late April; superficially at least, good. Though it has crept up again a bit in July. It also suggests that the week-to-week new case growth had already started to come down from its peak, before any significant lockdown was put in place.

To confirm that last statement, I made a version of the graph that didn’t constrain the growth percentage to 200%. To be doubly certain, I also switched back to using the raw data instead of the weekly averaged data. The result was remarkable:

Say what? The week-on-week growth in cases was already well on its way down, before any kind of legislative lockdown was even contemplated. Now I’ll grant you, divide a small number from a noisy and uncertain distribution by another small number from the same distribution, and the result is uncertain in spades. But there’s a decline there, and it isn’t a hidden one.

Now, what might have caused this decline? My best guess is that when expanding into new, fresh fields, the virus (which takes time, 2 to 12 days I’m told, to incubate) can’t keep up with its old rate of progress. It’s always going to be the first cluster that expands fastest.

The April to July changes, on the other hand, show just as clearly on the basic daily cases and deaths graph:

The suspicious among you may be thinking: “But that isn’t a bit like the graph you showed us last time!” No, indeed. Here’s the one from six weeks ago:

The reason for this revisionist tendency in the UK’s data is that, since June, they have moved from showing new cases against the day they were reported, to showing them against the day the test was done; just as the Swedes were in the process of doing at the time of my earlier paper. The effect is to separate the main peak into two, and to move the first peak earlier by a few days. (Notice, also, that the second peak comes shortly after the Easter week-end.)

Another effect of this means of reporting – not visible on this graph, but you can see it in several other countries’ data – is that new case counts for the very latest few days will usually be understated. They will be added to as delayed test results come in. So, if you see an apparent downturn in new cases in the last few days before the end of the data, it’s very probably spurious, and should not be taken into account in any conclusions. Similarly, perhaps, for an apparent upturn; maybe reports from the cities come in quicker than those from the boondocks?

To return to the plot of weekly case growth against lockdown stringency. I used the raw daily data provided by the Blavatnik people to produce a history of the changes in UK regulations over the epidemic so far. (The texts in the “Measure” column are my own summaries, in text form, of the numeric codings which are used for each of the nine factors in the Blavatnik stringency data). Here’s the result:

Date	Measure	Scope	Stringency %
February 2nd	Co-ordinated public information campaign	National	11
March 16th	Recommended workplace closing	National	15
March 17th	Recommended public event cancellations	National	20
March 21st	Required some workplaces to close	National	30
	Mandatory public event cancellations	National
March 22nd	Recommended not to travel	National	35
March 23rd	Mandatory all schools to close	National	70
	Restrictions on small gatherings (<=10 people)	National
	Required stay at home with exceptions	National
	Mandatory restrictions on internal travel	National
March 26th	Recommended public transport closures	National	76
May 13th	Recommended stay at home	National	69
	Mandatory restrictions on internal travel	Regional
June 1st	Mandatory all schools to close	Regional	68
June 8th	Quarantine international arrivals from high-risk regions		73
June 15th	Recommended stay at home	Regional	71
July 4th	Restrictions on small gatherings (<=10 people)	Regional	70
July 6th	Recommended not to travel	Regional	64
August 1st	Mandatory restrictions on internal travel	Regional	68
No stay-at-home measures

I was tempted to insert in there: “April 12^th (Easter Sunday): Prime minister Boris Johnson comes back from the dead!”

Now, look back at that graph of weekly case growth versus stringency limit. The hypothesis that lockdowns and relaxations ought to trigger drops and increases in weekly case growth would suggest that the blue line ought to move in the opposite direction to the brown, soon – or, at most, in a week or two – after it. Since the big lockdown in March, does that graph show any evidence of such a movement? Not to my eyes. Remember, also, that shops and pubs re-opened in three phases on June 1^st, June 15^th and July 4^th, none of which show up in the Blavatnik data. If I squint hard, I can maybe see a tiny upward knee-bend in the blue line in the first week of June; but it’s not conclusive.

A tour of Western Europe

Next, I thought, I’ll re-visit some of the Western European countries I looked at last time round. First, Iceland. Six weeks ago, it was the land of the perfect bell-curve. Now:

Hmmm… Ma Bell has spawned Baby Bell, and there’s a third bell just starting. Here are the growth rates and lockdown stringencies:

The Icelanders managed to snuff out the first phase of the epidemic completely in just two months from the first case, or six weeks from lockdown. Pretty impressive. What was it down to – low population density, good track and trace, strong Viking constitutions? Or could it have been due to the government locking down? Let’s have a look at the Icelandic timeline:

Date	Measure	Scope	Stringency %
January 23rd	Co-ordinated public information campaign	Regional	8
January 28th	Co-ordinated public information campaign	National	11
January 29th	Quarantine international arrivals from high-risk regions		17
March 15th	Restrictions on medium size gatherings (11-100 people)	National	25
March 16th	Required some schools to close	National	51
	Required some workplaces to close	National
	Mandatory public event cancellations	National
March 20th	Ban on international arrivals from some regions		54
May 4th	Schools open		46
May 25th	Workplaces open		36
	Restrictions on large gatherings (101-1000 people)	National
June 15th	Quarantine international arrivals from high-risk regions		33
July 31st	Recommended workplace closing	National	40
	Restrictions on medium size gatherings (11-100 people)	National

Well, there you have it. As in the UK, the weekly case growth was declining before any effects on Icelanders of even the first lockdown edict could kick in. Moreover, the first cases for more than a month appeared right after they went from banning high-risk international arrivals back to quarantining them. They did close bars and close-proximity businesses like hairdressers from late March to May. But otherwise, I think the Icelanders have got the job done; maximum protection at minimal cost. It will be interesting to see how quickly the latest outbreak of new cases dies down.

Next, to two central Western European countries I looked at in detail last time. First, Italy. Here’s the weekly case growth versus stringency:

The maximum lockdown level in Italy was 94%, and they were at over 85% all the way from March 11^th to May 4^th. Ouch.

Now, there are a couple of instances here of what I would have expected to see when a lockdown, which has had a real effect, is lifted. There’s a definite knee-bend in weekly case growth around May 4^th, and another more debatable one about June 4^th. According to the Blavatnik data, on May 4^th there was a package of five measures:

1. “Recommended workplace closing” (had previously been “Mandatory all but essential workplaces to close”),
2. “Public transport open” (had previously been “Mandatory public transport closures”),
3. “Recommended stay at home” (had previously been at a mixture of “Required stay at home with exceptions” and “Mandatory stay at home with minimal exceptions”),
4. “Recommended not to travel” (had previously been “Mandatory restrictions on internal travel”),
5. “Quarantine international arrivals from high-risk regions” (had previously been “Ban on international arrivals from some regions”).

And on June 2^nd and 3^rd all restrictions on travel were ended, both internal and international.

Here’s the daily cases and deaths graph:

There has been a small increase in new daily cases since early June. But it’s piffling compared with the horrors back in March. Barring some unexpected development, the Italians do seem now to be through the worst.

To Switzerland:

The measures since late April have been:

Date	Measure	Scope	Stringency %
April 27th	Required some workplaces to close (previously Mandatory all but essential workplaces to close)	National	69
May 11th	Required some schools to close (previously Mandatory all schools to close)	National	66
May 30th	Restrictions on medium size gatherings (11-100 people) (previously Restrictions on small gatherings (<=10 people))	National	63
June 6th	Schools open	National	46
Recommended workplace closing (previously Required some workplaces to close)	National
	No restrictions on internal travel (previously Recommended not to travel)	National
June 22nd	Recommended workplace closing	Regional	35
Restrictions on very large gatherings (>1000 people)	National
	No stay-at-home measures (previously Recommended stay at home)
July 3rd	Restrictions on medium size gatherings (11-100 people)	Regional	39

Two of these seem to have been followed by increases in the weekly growth rate, both a couple of weeks afterwards. One was the re-opening of many schools. The other was the major package of measures on June 6^th. The change on July 3^rd seems to have had a more immediate effect in the opposite direction, even though only implemented regionally.

It looks as if medium or larger gatherings of people are one of the major sources of spread of the infection. Which, indeed, was what happened over Carnival week-end in the Netherlands and Belgium at the very beginning of the outbreak. It seems that the Icelanders agree with this, since the measure they chose to enact very recently in an attempt to halt their third wave of the infection was re-lowering the limit on gathering size.

Now, for the one (I hope) you’ve all been waiting for: Sweden. Ah, Sweden.

Pay no attention to that vast crevasse in the second half of June! Sweden shut down for the 3-day long summer solstice holiday. And even COVID testing all but stopped. Remembering that the big jump at the start of June was caused by a sudden expansion of testing, it looks now as if the Swedish hands-off strategy, which so many freedom-hating moaners have criticized, may well have been right all along. (The recent apparent jump, I won’t comment on today, as it hasn’t yet gone on long enough to draw any conclusions).

Here’s the timeline:

Date	Measure	Scope	Stringency %
March 9th	Co-ordinated public information campaign	National	11
March 12th	Restrictions on large gatherings (101-1000 people)	National	17
March 18th	Recommended school closing	National	20
March 19th	Ban on international arrivals from some regions		29
March 25th	Recommended workplace closing	National	32
March 29th	Restrictions on medium size gatherings (11-100 people)	National	35
April 1st	Recommended public event cancellations	National	41
April 4th	Recommended not to travel	National	46
June 13th	No restrictions on internal travel		41
June 15th	Recommended school closing	Regional	39

Look at that graph again. By the time the stringency reached its peak on April 4^th, the weekly case growth was already down below 50%, and soon approached zero. And although the stringency peaked at 46%, only the restrictions on gatherings and the ban on international arrivals from badly affected regions were actually mandatory. Moreover, the ban on international arrivals seems to have been restricted mainly to those from China, Iran and Italy.

Now, the Swedes have taken a lot of flak from the moaners for their high deaths per million (570 as at August 10^th). This puts them eighth in the world in that particular stakes, though still well behind Belgium, the UK, Spain and Italy. But like those countries, a very high proportion of their COVID deaths have been in care homes. There’s not much anyone could have done about those.

The Swedes were also pro-active in upping the testing rate as early as they could. As a result, they are second among major Western European countries (behind Luxembourg and ahead of Spain) in cases per million population. On all the evidence, I think the Swedes have done as good a job as they could reasonably have been expected to do under the circumstances. They deserve a round of cheers. Skål!

But the really interesting question is this. If countries like the UK and Italy had taken the Swedish approach, instead of messing up the economy and people’s lives for months on end, would the end result in terms of COVID cases and deaths have been much, or indeed any, different? Looking at the Swedish graph during March and early April, I’m coming to doubt it.

Next, Portugal, which back in June was starting to look a bit unpredictable.

Now, that’s odd. They seemed to have it under control for a while in April, then suddenly, up she goes! At least two weeks after the last change in stringency. What the Portuguese did, so the Blavatnik data shows, is bring in mandatory travel restrictions for two short periods, April 9^th to 14^th and May 1^st to 4^th – Easter week-end and May Day week-end respectively. Maybe a lot of people just ignored the bans, particularly the second? Well, it didn’t do much harm on either occasion, as you can see from the subsequent down-turns. Since then, it doesn’t look too alarming. And there doesn’t seem to be much correlation between lockdown level and weekly case growth.

Last on my tour of Western Europe, a country I didn’t even look at last time: Luxembourg. This is the only country, among all those whose figures I’ve examined so far, which has actually gone the whole way to complete release of all lockdowns. As I noted earlier, they have the highest cases per million population among major Western European countries (over 11,000). And yet, in deaths per million (191), they are only 10^th. So, they must have been doing some things right, even before it came to releasing their lockdowns.

Here are the graphs:

Now, that’s an epidemic management strategy I like. Use the first peak to work out exactly what the limits are on your health care resources. Then relax the lockdowns bit by bit, and don’t worry about how many new cases you get, until you are getting near the limits of your resources. If that does threaten to happen, re-introduce the most effective lockdown you have available.

“Genius, Holmes!” “Elementary, my dear Watson.”

So, they unlocked everything on July 16^th. On July 19^th, they re-introduced “Restrictions on medium size gatherings (11-100 people).” The effect, if I can believe my graphs, seems to have been both instant and spectacular. So, as the Blavatnik data tells (but my graph cuts off the day before), they unlocked again on July 28^th. Well done the Letzebuergesch! (That’s what they call themselves in their own language). And now, they know they can do the same thing again if they ever need to.

It’s a pity that buffoons like Boris Johnson don’t have ideas (or even advisors) as good as these.

A whistle-stop world tour

So, let’s see how the rest of the world is doing, shall we?

The most obvious feature of the world cases graph is that the third wave of the epidemic (world-wide) is far more spread out in time than the first (mainly South and East Asian) and second (mainly Western European). It’s also fair to say that the apparent drop-off towards the end may well be an artefact, caused by late reporting of tests.

But the deaths per case graph is encouraging for the longer term. As the virus spreads, it seems to be becoming steadily less lethal. I wonder if, maybe, a less virulent strain is now mixing with the nasty one, which arrived in February in Iran, Italy and the USA? It’s even conceivable that we may not, in the end, actually need to exterminate the damned thing; it might, perhaps, mutate itself back into just another variant of its brothers, the common cold coronaviruses.

In my world tour, while I’ll usually show the lockdown graph just to give an overview, I won’t go into details. That’s because to make proper sense of the data, for most of the large countries I would need it broken down by state, province or whatever else is the local unit of sub-division.

So, I’ll start with our Iranian camel friend. He was pretty much down on his knees back in June. Has he managed to get up?

All I can say is, Ouch. Though to their credit, the Iranians have generally refrained from trying to lock down too hard.

Let’s take a look at Kuwait, about whose handling of the epidemic I had some good things to say back in June:

That’s a full 100% lockdown right there, from May 10^th to May 30^th. More ouch. Now I know how they produced that slowdown in cases, and now I’ve seen six more weeks of their data, I’m not so sure I was right to praise them.

How about the USA?

Is that a watershed around the middle of July? Maybe. The sustained drop in weekly case growth since mid-June looks encouraging, but there’s still a long way to go.

Canada?

Nothing much to see in the first graph, but something really weird in the second. Canada seems to have stopped reporting any stringency index figures at all since July 19^th! Even the Blavatnik raw data shows “no data” for all dates since then. That, and the sudden drop in case figures right after, suggest that something is afoot. Perhaps they are following Sweden and the UK, and changing the way they allocate cases to dates? I’ll simply shrug my shoulders, and move on to Mexico.

That’s bad on both the cases and deaths fronts, and even worse when you look at the deaths per case and cases per test ratios:

But the weekly case growth graph tells another story. In fact, two stories.

First, the weekly case growth has been going, slowly but fairly surely, down since April. Long may that continue! And second, if there is a country whose data suggests that the Harvard Law is right, and this virus really just does do what it damn well pleases – no matter what governments or individuals do to try to nudge it – then Mexico is that country. I’ve only been to Mexico once, and while I do recall the people being rather noisy, I didn’t find them particularly law-breaking, compared with some other places I’ve been. So, if these lockdowns are being enforced, they aren’t having much, if any, effect. That calls into question the entire lockdown idea, and all that goes with it.

So, to South America. Brazil is more than a little like Mexico. I won’t bother with the daily cases and deaths, but here’s the lockdown graph:

The graphs from Ecuador and Chile do not fill me with any confidence that the numbers they portray are accurate enough to make it worth while publishing them. Which leaves Peru as my only other stop in South America:

There have been some significant recent upward adjustments to their deaths data, and the cases don’t seem to be going too well, either. As to lockdown, they have been up above 90% for a long time, and they don’t seem to be having much success with their cautious attempts at regional unlocks.

After all those troubles in Central and South America, my next port of call, South Africa, seems at first sight like a different and better world:

The cases per test percentage is still high and rising. But though the lockdown level is high, they have started to unlock. On July 12^th, though, they mandated “Required stay at home with exceptions,” thus going back to the March régime after it had been relaxed at the beginning of June. This does appear to have been successful in terms of “turning the corner.” But whether the drop in new cases will continue, time will tell.

So, to my final continent: Asia. First, Pakistan.

They have done a lot of unlocking already, and their approach is to re-impose lockdowns at the provincial level where they are warranted. It seems to be working well for them, and I think this particular patient is probably already out of danger; if, of course, I can believe the figures in the first place. For such a big country, that’s a remarkable achievement. If it’s real, of course.

Not so for next-door India, though:

They have been all the way up to 100% lockdown, and are still almost at 80%. But nothing seems to be working for them.

My Indonesian friends, although they haven’t “turned the corner,” are doing better than the Indians. And without ever raising the lockdown level above 75%:

The one lockdown measure they have re-imposed is total closure of the borders, planned to last until September. From June 23^rd to July 10^th, the status was “Screening of international travellers.” My graph shows a knee-bend, which actually precedes the border closure! Perhaps they announced it some days in advance.

Singapore’s data is rather confused. I think this is because it’s a cross-roads, and so always vulnerable to new infections from outside; and yet, for economic survival, the Singaporeans can’t afford to be too strict about keeping people out. So, I’ll move on, to Japan:

So much for the idea that Japanese formality and their less physical ways of socializing would keep them safe from the dreaded COVID! But kudos to the Japanese for not panicking. Yet, at least. It will be interesting to see how this one pans out.

So, to the final stop on my world tour; the track-and-trace capital of the world, South Korea.

The level-headed Koreans, for the last few months, have let the virus bumble along at the bottom of its range, where it doesn’t pose much of a threat. They could eradicate it from their country if they wanted to. But there’s no point trying to do that until everyone else is ready to do the same.

All that said, track and trace on its own wasn’t enough for them. They took their lockdown stringency up to 82% at one point. And that included a period, from April 6^th to April 19^th, of “Mandatory all but essential workplaces to close.” But, while the increasing lockdowns did seem to produce “knee-bends” in the weekly case growth, they didn’t seem cumulatively to have an enormous effect. Until they were relaxed, of course.

Lock-downs, or cock-ups?

So, have the COVID lock-downs been cock-ups – or even, perhaps, fully-fledged snafus? The evidence from much of the world points, in my view, to the answer Yes. Mexico and Brazil, in particular, suggest that in those countries at least, many, if not all, of the lockdown measures haven’t had much influence on what the virus ended up doing. Sweden, too, points in this direction, as does the lack of a strong increase in new cases as the UK has slowly unlocked. The jury will not be able to bring in its verdict until full cost versus benefit analyses are in from each country; but at this point, it isn’t looking good for the Lockdown Party.

There is evidence, particularly from Sweden and Luxembourg, as well as from Belgium and the Netherlands at the very start of the epidemic, that close gatherings of many people, who stay together for a considerable time, do help to spread the virus. Those with memories may also recall religious gatherings in France and South Korea, which helped give it its start in those countries.

There is also, perhaps, some evidence from South Africa that stay-at-home restrictions help to lessen the spread of the virus. Although the measure in question has been in force for less than a month, and more time is needed to confirm its effect. In any case, confinement to barracks is a blunt instrument to bash people over the head with. On the other hand, there is evidence from Portugal that when people disobey travel restrictions, it leads to a short-term increase in new cases; but things very soon return to the course they were on before.

Another point to note is that, of the biggest countries in the world (with 2018 populations above 200 million), India, the USA, Indonesia and Brazil are all floundering; some worse than others. It seems that in epidemic control, smaller countries tend – as you might expect – to do better. Of course, due to exceptional bad luck at the start of the epidemic, you will lose some: San Marino, Andorra. But you will win others: Iceland, Liechtenstein and many more. And the “jewel in the crown,” the best example of all on how to keep death rates down and how to release lockdowns: Luxembourg.

It remains only for me to castigate the UK government for all the crap they’ve thrown at us in this “sceptred isle” over the last five months. To be fair, on the presumption that lockdowns were necessary, and would actually do what they were designed to do, the choices of what to lock down were not unreasonable compared to some other countries. But were they really necessary at all? And was the guff we were told about “not letting health care resources get overloaded,” perhaps, no more than a smokescreen put out by politicians, bureaucrats and biased media, that didn’t want to risk making the National Health Service sacred cow look bad?

But failing even to screen incoming travellers until June was a glaring error; and closing small shops was way over the top. The UK government’s attempts to slant the data on tests carried out – on which they were caught out by statistician Sir David Norgrove in early June, and by me a month later, see https://wattsupwiththat.com/2020/07/02/is-the-uk-government-misleading-the-public-on-covid-tests/ –  wasn’t a clever move, either. Moreover, the UK, like Italy, has been far too slow to take risks in early unlocking. As a result, there seems to be forming a “consensus” that big changes are needed in the UK’s public health systems, and perhaps even in the NHS as a whole. Some heads may roll, I expect. But not nearly enough.

…and a final trip to the Faeroes

Oh, but I’ve saved the best until last. Is there, I had been thinking, some place on the planet where the government didn’t do anything much at all about locking down, compared to other countries around the same time? Is there somewhere I can use to test the hypothesis that very few, if any, of the many and varied lockdown measures that have been implemented in different places, have shown any significant efficacy at all?

Fortunately, the answer is Yes. That place is the Faeroe Islands. What happened there is that the virus, once introduced, went through the population – of the major islands, at least – like the proverbial dose of salts. Within just a few days of the government’s first reaction, the chief medical officer was saying that he thought most of those, who were going to be infected, had already been infected. Here are the graphs:

One difficulty presents itself: there is no stringency index data for the Faeroes, even in the Blavatnik daily data. But fortunately, a kind soul has put on to the Faeroes coronavirus page at Wikipedia, https://en.wikipedia.org/wiki/COVID-19_pandemic_in_the_Faroe_Islands, a detailed account. Thank you, thank you to whoever did this. It’s become fashionable in some quarters to pooh-pooh Wikipedia; but in matters like this, it is an absolutely vital resource.

Here, directly quoted from Wikipedia, is what the Faeroes government did on March 12^th:

• All international travel is strongly discouraged, unless absolutely necessary.
• All municipalities are urged to take measures regarding passenger cruise ships on their way to the Faroe Islands.
• Anyone arriving in the Faroe Islands from overseas must take the utmost precaution and stay at home.
• Restrictions on visitors to hospitals and nursing homes will apply. Further guidelines will be issued by the health and local council authorities.
• The school system, including tertiary, secondary and primary schools, will close. Students and pupils will wherever possible have access to remote teaching.
• Children’s activity centres, preschools and day care facilities will also close. Childcare will be offered to those who, for particular reasons, are not able to have their children at home during working hours.
• All employees in the public sector who do not deal with the most essential services should work from home. Staff will receive further instructions from their respective directors.
• Measures have already been taken in the private sector to guard against infection.
• Bars, venues and restaurants are urged to close by 22:00 for the next two weeks.

I’m not sure they would even have bothered to do that much, if the Danes hadn’t decided to lock down the previous day. And after March 12^th, the only further measure they brought in was on March 17^th, that “no more than 10 people should be together at once, inside or outside.” Essentially the same restriction as in Iceland at the time. Beyond that, two fuel station chains closed their shops – but not the fuel pumps. And that was all. This is not to say that people in the Faeroes did not suffer, personally and economically; they did. Scan the footnotes to the Wikipedia article, if you seek evidence.

Now, there has recently been a new outbreak of cases in the Faeroes. How caused? Once again, Wikipedia springs to the rescue. The three first cases reported “had been attending the national festival Ólavsøka where many people gathered in Tórshavn.” My graphs show only the very start of this; and it has got worse since then. Which is unfortunate for the people of the Faeroes; but fortunate for me, because it leads me directly to my…

Conclusions

Of all the countries, the Icelanders and Faeroe Islanders got closest to right in deciding what to lock down. And the Swedes, too. You can ask: Did the Faeroe Islanders need to close all schools, when the Icelanders didn’t? Or, did the Icelanders need to close some workplaces, when the Faeroe Islanders didn’t? But these are quibbles.

It appears to me that only four of the lockdown measures, which have been used, have been proven effective. In increasing order of stringency to ordinary people:

1. Screen arriving international travellers, and quarantine, or at need ban, those from high-risk areas.
2. Ban football matches, public parades and large events, at which thousands may gather.
3. Restrict the number of people who may assemble in one group, or at a small event.
4. As an absolute last resort, confine people to their homes for a short period, with exceptions like shopping and exercise.

The effectiveness of anything beyond these four is unproven. The pain, though, is obvious.

As to relaxing lockdowns, three cheers for Luxembourg. Who, unlike many other governments, have approached the whole matter with commendable common sense.