The stock market was very enthusiastic about the news last week of early positive results with the current vaccine candidate being developed by Moderna.
The only thing is, the “news” was a press release from Moderna, not a scientific evaluation. Here’s a careful look at exactly what was said and not said in that press release, and overall, it provides yet another excellent example of the danger of relying on press releases rather than hard data.
We wish it was as simple, however, as being able to say “treat press releases as the self-serving documents they are, but rely on scientific reports without question”. That would be an inappropriate simplification. Remember the hydroxychloroquine study reported in The Lancet that I critiqued on Friday? I’m not the only one with concerns about the adequacy of the analysis and results provided in that study – here’s another excellent analysis that comes to much the same conclusion as me, albeit via a slightly different reasoning route.
We find it extraordinary – and extraordinarily regrettable – that so much of our response to this terrible pandemic is being shaped by “bad science” and misinformation, rather than by rational thought and careful process. We’d really thought our doctors and our scientists were better than this. But each time we look carefully at something, we see faults and problems a plenty.
Here are the rankings for the eight states of any size with the highest infection rates.
There are two changes today, one we were expecting, and one that surprised us. Qatar, which has been shooting up the scale, has now swapped places with the Vatican City, and with its daily new case count still growing or at least staying high, there’s a possibility that in another week or so it might even displace San Marino to become the country in the world with the highest incidence of cases.
One other point about Qatar. It is a very hot country – the daily high temperature each day for the next week is over 100°F, and daily lows in the 80s. Its soaring rate of infection gives little hope that our summer weather will slow the virus down. Our summer behavior might impact on viral spread, but not the weather itself.
The other change was a surprise. Singapore, briefly touted as one of the Asian success stories, has been suffering greatly over the last few weeks, due to the virus sweeping through the high-density housing which Singapore uses for its migrant workers. The most surprising element of Singapore’s virus rate, however, is not as much its high rate of infection, but its astonishingly low rate of mortality. It has almost 32,000 cases of the virus, but only 23 deaths reported. Singapore has displaced Iceland and appeared at the #8 position.
Of note, Iceland, now hailed as a success story, dropped two places to #10. Bahrain has moved up to the ninth position.
We would not be astonished to see Mayotte displace Spain in the next few days, and possibly move up further to pass Luxembourg too.
- San Marino/665 cases/the equivalent of 19,603 cases per million people (unchanged)
- Qatar/43,714 cases/15,200 cases per million
- Vatican City/12 cases/14,981 cases per million (unchanged)
- Andorra/762/9,864 (unchanged)
Here are the top six major countries, showing death rates per million of population in the country.
Yesterday, Italy and the UK were neck and neck with Italy ahead by the slimmest of margins; today the positions have slightly shifted and Britain has moved slightly ahead of Italy. The UK has been steadily moving up the list, while Italy’s rate of growth has greatly slowed.
There are no new challengers likely to enter this top six list in the next month. Below Sweden, there is a gap before reaching the Netherlands (a long time member of the top six), now with 340 deaths/million, then the next major country beyond there is the US, just now entering the three hundreds but still palpably rising each day, and from there, a huge drop to Ecuador, with a much lower count of 176/million. :
- Belgium/9,280 deaths/801 deaths per million
- Spain/28,752 deaths/615 deaths per million
- United Kingdom/36,793/542
- Italy/32,785 deaths/542
To put those numbers into context, the death rates per million in the US/Canada are 300/170. The world average (not a very reliable number) is 44.4.
For major countries and/or outbreaks, and in general :
|US Cases/Deaths/Case rate per million||1,527,664/90,978|
|UK Cases/Deaths/Case rate per million||243,695/34,636|
|Canada Cases/Deaths/Case rate per million||77,002/5,782|
|Worst affected major country/case rate||Spain/5,940||Spain/6,040||Spain/6,050|
|Second worst country affected||Belgium/4,772||USA/5,039||USA/5,098|
It is interesting to note, in passing, that most of the top five countries have seen their case rates increase by just about 100 cases/million in the last week. But the UK has increased by over 200 and the US by almost 500. Both have moved up a rank over the last week as well, the UK going up today.
I Am Not a Doctor, But….
The controversial Swedish decision to stay open and generally avoid national bans shows us not just one outcome – the virus spread in a country not going into lockdown, but a second outcome too – how people react and respond on their own, without government mandates and decrees.
An often overlooked part of the Swedish experience is that people generally cut down on their social contacting, even without government edicts. Sure, they didn’t do so as much as other countries did under the auspices of government rules, but their people still made significant changes.
Maybe one of the things the Swedish model tells us is that most people can be relied upon to act sensibly and rationally without the government telling them what to do? We hesitate to go that far, but we have noticed for some time how people seemed to have started to add to their social distancing before any state/national bans were introduced. This can be seen on the IHME website – choose any state from the dropdown box in the center and you’ll see an estimate of movement/contact, and you’ll see how, in pretty much every state, people were cutting back on their movement before their state’s restrictions were announced. Even the very earliest state to enact restrictions (California) had cutbacks prior to that announcement (and the gathering restrictions that were the first restriction wouldn’t have had the huge result that happened, alone).
Timings And Numbers
These days citing CDC data unfortunately seems only slightly better than citing WHO/Chinese data, but we continue to hope their occasional lapses are the exception rather than the rule. I was viewing an interesting recitation of some assumptions they make in a series of planning scenarios. Most of them are either unremarkable or things that are impossible to confirm/refute. But one assumption struck me as being extraordinary, and, wouldn’t you know it, it was the assumption buried at the bottom.
See if you can guess how long it takes from a person dying of Covid-19 until their death is “officially reported”? What do you think – an hour? A day? A week? With these days and computers, you’d expect the answer to be closer to the one hour side of the hour/day/week range, wouldn’t you. But allow for inevitable backlogs and interruptions, and maybe it is closer to one day?
The actual answer? To save you reading down to the bottom of the document, I’ll reveal the answer – it is one week.
Here we are, desperate for data, with the main/ultimate source of data being deaths vs recoveries, and not only do we have to wait 20 days from exposure to possible death, but we then have to wait another 7 days from then until the number can be added to our databases.
There’s a more subtle problem too. If you look at the data on the page and in the screen shot above, you’ll see the number of days until a death is reported is either 7.1, 7.2 or 6.6 days. But look at the standard deviation value. That tells us that while deaths are reported, on average, about 7 days later, the range of delays varies widely, and as many deaths are probably reported 6 days or 5 days (or 8 days or 9 days) after they occurred, and a significant number of deaths are being reported the same/next day the death occurred, while others are being reported two weeks later.
In total, 68% of deaths are reported somewhere between 0 days and two weeks. That also means that 32% of deaths – call it one third – are reported more than two weeks after they died.
How can we move from that abomination of a data range to an accurate understanding of when people really truly actually died? Noting that there are seldom/never revised death counts for previous days, it seems the authorities record deaths as if they happened on the day they were reported, not on the day that the death actually occurred. So the number could vary by seven days down or 14 or more days up.
How can we – a sophisticated nation – have such a primitive and useless approach to death reporting? Doesn’t every death certificate contain a field to show the actual date of death (yes, they do)? So why are we not using that value on our death tables and graphs?
Closings and Openings
We’ve seen many problems with the various models and their projections over the weeks I’ve been publishing this diary. Another way of considering these models and projections is to keep in mind the oft-cited statistic that the average family has 2 1/2 children. But have you ever seen a half-child? No, me neither! So the average situation is also a situation that never exists in real life.
Averages can obscure rather than illuminate. Average rates of transmission obscure the fact that it almost never happens at that level. Instead, some activities happen at a much greater level, some at a much lower. As part of the mantra to work smarter, not harder, we need to focus on the high risk activities, and be more permissive of the low risk activities. We shouldn’t be seeking and implementing across-the-board restrictions, nor their subsequent removals. We need to selectively base our actions on relevant cost/risk/benefit analysis.
As examples, here’s a good article with a sensible ranking of activities, and here’s a similar article looking at the risks of different places we visit.
This article brings up an excellent point – our risk of infection isn’t just a matter of where we are. It is also related to how long we are there. In other words, do your shopping quickly and don’t linger.
Here’s an excellent article – well written, clear, and sensible – that looks at exactly what the situation is, as best we currently know, about the potential of gaining immunity after having had the disease.
Do you know the story of the (some versions have four, five, or six) blind men and the elephant? If you don’t, please read it now (very short easy read) because it contains a very relevant lesson within it. Most of us don’t see everything to do with an issue, and risk making mistakes by over-generalizing from the specifics of what we saw.
A related point can be stated more bluntly. If you have a hammer, every problem looks like a nail.
I make these introductory comments, because I was reminded of both while reading this article – a series of views of what the future may hold from assorted experts in assorted industries. It was remarkable how their background influenced their perceptions.
This isn’t really a directly virus related article, but it starts with, if I can paraphrase, an expectation that the economic, social, and global disruptions caused or exacerbated by the virus will lead to major changes in the future. I don’t agree with all the predictions/projections, but the statement that bringing manufacturing back to the US won’t result in more employment, just more automation, rings true. A thoughtful read for a slow Sunday/Monday.
And this is an interesting article about a company that makes flour. Again, seemingly unrelated to the virus, but a great study in how a well managed company with an excellent product has responded and adapted to the changing market as a result of Covid-19.
To end on a note similar to how I opened, here’s an interesting article about the actuality of the Moderna vaccine trial that I’d been slightly critical of, above. Another Monday read.
Please stay happy and healthy; all going well, I’ll be back again tomorrow