Global coronavirus death toll could be 60% higher than reported
ft.com
ft.com
I say that from the media-frustrated view of an American within America, who regularly reads German and Scandinavian news online (and UK too) just for external perspective.
I reflexively think two two things: (1) title sensationalism possible, and (2) or it could be far lower than reported, but that's not sensational, and only time will tell.
Systemic undercounts can happen easily in a situation like this; for example if you are only reporting as Covid-19 deaths people who a) died in a hospital and b) had a positive test. This will undercount if you are not testing broadly enough (or the test isn't accurate) or people are dying outside the hospital in unusually high rates due to the virus. NYC is a good example of where it's pretty clear this was happening (and they have adjusted their counts upward).
Fatalities is one area with overcounts are quite unlikely, but could be happening in some places I suppose, and will have to be accounted for if it can be demonstrated.
Somebody who tests positive, and then dies in a car accident meets your above criteria. For something less contrived, so does somebody who tests positive, and then subsequently dies of an unrelated heart disease.
If you wanted to fix attribution, you’d need a coroner’s investigation into each death, which certainly isn’t happening. Even testing every death that you want to count isn’t feasible, because of test shortages and the potential for false negatives. A real world example of that is in New York, where a revision in their attribution methodology had their numbers jump up massively in one day [0]. What changed was they decided to add all deaths where Covid was a suspected cause to the count.
Whether these shortcomings in methodology would lead to an overall overcount is probably unlikely. But methodology differences from one place to the next does make it difficult to compare statistics. With some factors applying downward pressure to the stats, and other factors applying upward pressure.
One thing I’m going to be interested in looking up when this is all over is 2020s influenza deaths. I have a strong suspicion that 2020 is going to have record low flu deaths, with many of them being incorrectly attributed to Covid-19.
[0]: https://www.theguardian.com/us-news/2020/apr/15/new-york-cit...
[0]: https://www.nytimes.com/interactive/2020/04/21/world/coronav...
I agree that over time it gets muddier , but right now in places like NYC it’s pretty clear .
New York pretty clearly did the right thing here. There isn't going to be a coroners investigation, but with somewhere that large you have decent statistics on expected rates and attributing the up tick they saw was methodologically better than excluding those deaths. After all if I understand it correctly "suspected deaths" here is counting the otherwise unaccounted for increase over baseline statistics, not the baseline cases. That's the correct way to do this, and afiak it is how NY did it in reporting but I haven't double checked. It's not perfect, but that's life.
Agree that this years flu analysis will be interesting, but on the overall statistics nobody competent is going to conflate them with covid-19, there may just be larger error bars.
> with somewhere that large you have decent statistics on expected rates
I wouldn’t make that assumption. I can’t think of any place in the world that has the ability to collect this data with any sort of scientific rigour. It’s simply not possible at the moment, and without that you have no scientific basis to know what to expect.
> Agree that this years flu analysis will be interesting, but on the overall statistics nobody competent is going to conflate them with covid-19
I wouldn’t make this assumption either. If you attribution criteria includes dying in hospital of Covid-like symptoms, then it also includes dying in hospital of flu-like symptoms, because a severe case of flu and a severe case of Covid present almost identical symptoms. The US has had ~55k Covid attributed deaths so far, in last years flu season, it had ~35k flu attributed deaths. The potential for misattribution on that basis alone is significant.
The general point I was making was that not all of the confounding factors apply downward pressure to the stats, some of the provide upward pressure, and depending on methodology, you’re going to get a different set of confounding factors from place to place.
I’m disagreeing that at this moment - and with statistics like excess mortality in NYC, there is very good reason to believe that upward and downward pressure are not equally likely.
As to the first assumption I disagree . We have pretty good ideas of all causes rates in somewhere like NYC, we have pretty good numbers on things like accidents etc. And then sort of factors you point out like the effect of a recession aren’t on effect yet for the most part. So you have a bunch of excess morbidity, and you have pretty good local statistics in the gaps, at least locally. You are right that this doesn’t go apples to apples in other places but we aren’t doing that so it does matter.
There is one kind of interesting wrinkle, you may have stress related impacts that show up even on a short timeline. So there is a question if you can/should attribute those and you can pick reasonable ways, either choice .
Flu isn’t likely going to be confounded too badly because people are going to be focussing in the counfounding impacts (e.g. of isolation). It just seems strange to me to assume this will be a problem , some people involved are good at this sort of analysis . Much more likely that a decent job will be done and the estimation errors will have wider bounds.
I guess I just don’t see any data to support your pessimism , on that , but I could be wrong of course. I mean this sort of modelling isn’t easy but it is doable.
I would kinda agree, but for different reasons. I’ve seen the inner workings over several government agencies during this crisis, including a few police departments. What has been obvious to me is that there is a very significant difference from place to place in how death and infection statistics are recorded. My observation has been that people who have an obvious political incentive to record lower numbers usually find a way to do it, and vice versa for people who have an obvious political incentive to record higher numbers. I would agree because across the world, there seems to be greater political incentive to have lower numbers.
Everything you’re speculating about is plausible, and may turn out to be mostly correct. But there is no reasonable basis for the certainty you claim to have. Especially in regards to claims such as there being no potential for factors other than Covid deaths to have a statistically significant influence on overall mortality rates. That’s just your opinion, and it’s a reasonable on to have, but it’s definitely not “almost certainly” true.
>The death toll from coronavirus may be almost 60 per cent higher than reported in official counts, according to an FT analysis of overall fatalities during the pandemic in 14 countries.
The article is about reported deaths, not predicted. I doubt many countries are reporting artificially high counts.
To calculate excess deaths, the FT has compared deaths from _all causes_ in the weeks of a location’s outbreak in March and April 2020 to the average for the same period between 2015 and 2019.
so they are not counting only coronavirus related deaths but all
So naturally people get cheesed off. One side has been hit hard, another hasn't and both get grouped together to produce some arbit number.
Rather than counting country wise what would make more sense is global hotspot comparisons(town/city level).
The hotspots will see a lot of Excess Deaths over historic mortality rates I have no doubt.
I live in France where the statistics service does an accelerated counting since the beginning of the pandemic to publish a partial count of the death certificates faster than usual. It is published every week with the number of people diagnosed, and deaths in hospitals, etc.
Part of that is that I'm in rural utah and we have 40 cases in a huge 3-4 county area w/ 100k+ people. It's not like I'm in NY where I can hear the sirens all day. I'm also getting tired of frozen food and home-cooked dinners. We do order delivery or drive-thru 1-2 times per week, but I'm always paranoid when I do but I feel I'm getting more 'comfortable' and less paranoid, which could bite me in the ass as I'm higher risk (obesity, 40, sleep apnea).
probably part of it is also the longer days make it go so much slower, and even my introverted self wants to get out of the house and do something besides this all day everyday for the next year.
Good luck, if it helps, a lot of people are feeling the same way.
https://www.nytimes.com/interactive/2020/04/21/world/coronav...
If you scroll down low enough, you stumble upon per country multi-year comparisons. Notice how for Sweden, Switzerland, France or England the spike is not much higher than the seasonal 2017 flu.
Moreover the peak of the 2017 flu is cut out of the graph for France and England, as a couple weeks before/after new years are cut out from the graph for aesthetic[?!] reasons. For a publication that wants to be taken seriously, cutting out the most relevant comparison point is embarrassing.
And, of course, no breakdown by age.
Compare graph for week 15 and 16. The data in NYT are for 5 of April, but we were not done counting deaths. The true numbers are substantially higher. England is especially high.
* The spike is steep, but it appears to have quickly receded. Perhaps an artifact of what you are calling 'not done counting deaths'. Would you elaborate, what's holding back the data, when can we count [sic] on accurate counts?
* The spike is not that tall. In deaths/week, 2017 peaks at 70k deaths and 2020 peaks at 86k over all age groups. Going to the 15-64 demographics, turns out that 2018 peaks at 8.9k, whereas 2020 peaks at 9.9k. So we've got 1k extra deaths per week for a few weeks at a population of 200M+ people, the end is nigh?!
https://www.euromomo.eu/graphs-and-maps/
PS. Speaking of sensationalist, this is a great time to start presenting data using honest charts that start at zero, and not arbitrary high values [40k/7k] to magnify small variability.
PS2. Does anyone know how to get the euromomo dataset? In a middle of a global pandemic, a bit sad that a critical piece of data is unavailable for independent verification / presentation.
Ad. "So we've got 1k extra deaths per week for a few weeks at a population of 200M+ people, the end is nigh?!"
There is a question about long term health of people who got COVID-19. Based on Japanese study on Grand Princess passengers [0] and some 6 divers [1] all with mild cases from Germany around 50 to 80% of people seem to have damage to the lungs visible on CT scans after mild symptomatic or even asymptomatic infection. Two of the divers had significant oxygen deficiency when doing physical exercise after 5-6 weeks of recovery. The guess of the doctor who was inspecting them is that this is permanent damage that may take years to recover if ever.
Also, the virus didn't go away - it's still there. Depending on location 0-20% of people got infected with median probably around 1%. In places where 20% got infected the virus killed significant portions of the whole population. In Bergamo province of Italy with little bit over 1 million population and 4000 deaths the virus killed around ~0.4% of the whole population or close to 1 in 200 people. It's very unlikely that there will be any mass events in Europe this year or next year before we get vaccines. Any indoors events involving more than 100 people - especially involving talking, dancing, singing or mourning are also very unlikely.
Ad. PS. They updated their website recently. This is how it looked like before - they were reporting z-scores only and only as a picture. https://twitter.com/Isinlor/status/1249252918609526784 I count the new website as a big step up :) .
Ad. PS2. Somebody would need to write scraping script from the website. Also: > While the network fully supports data sharing, the network hub is not mandated by the participating countries to release any national data. If you are interested in exploring the possibility to access national data, please approach countries individually.
[0] https://pubs.rsna.org/doi/10.1148/ryct.2020200110
[1] https://translate.google.com/translate?sl=auto&tl=en&u=https...
* Not sure how to read the Japanese study. There were 3700 passengers on that ship, the CT study only tracks 101 of them. I could not figure out the selection process. Furthermore, how does this compare to the annual flu? Quick Internet search: "Chest CT findings of influenza virus‐associated pneumonia in 12 adult patients" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941884. Sounds ominous, and yet here we are.
* Yay for a better website!
* Who is better positioned to succeed in asking countries for permission to release the data: random citizens, or the researchers that already have connections to the respective countries health departments on this very topic? Stop hiding behind bureaucratic excuses. Pull whatever strings you have to pull to get the data published.
Edit: Another presentation of the euromomo data: https://www.economist.com/graphic-detail/2020/04/16/tracking.... Looks quite a bit more balanced than the NYT piece.
The numbers will grow further.
Especially when you consider things like the dramatic drop in reported mortality from things like heart disease the last few months according to the preliminary data.
But preliminary data isn't very good quality ever, so it is hard to tell how much of that is just bad data, how much is coronavirus killing people that were going to die in only weeks anyway, and how much is misreporting.
But in six months or so, when the data start to settle down, we will find out which direction we are miscounting in. (Clearly we are miscounting in both directions by significant amounts, but it's hard to tell the comparative magnitude)
TL;DR: more than a decade of life-time lost on average per victim that dies of novel coronavirus.