Guest Post by Willis Eschenbach
I’ve been saying for some time now that the number of confirmed cases is a very poor way to measure the spread of the coronavirus infection. This, I’ve said, is because the number of new cases you’ll find depends on how much testing is being done. I’ve claimed that if you double your tests, you’ll get twice the confirmed cases.
However, that position was based on logic alone. I did not have one scrap of data to support or confirm it.
Max Roser is the data display genius behind the website Our World In Data. He has recently finished his coronavirus testing dataset, covering the patchwork quilt of testing in various countries. The data is available here.
Being a ‘Murican myself, I first looked at the US daily new testing versus number of US daily new confirmed cases. I have to confess, when I saw it, I did laugh …
Figure 1. Scatterplot, daily new tests versus daily new cases, United States. Yellow/black line is linear trend.
Just as I have been saying, in the US, new cases is a function of new tests. For every one hundred additional tests that we do, we find an additional nineteen confirmed cases of coronavirus.
Of course, when I looked further there were other countries which were nowhere near as linear as the US. Here’s Australia, for example:
Figure 2. Scatterplot, daily new tests versus daily new cases, Australia. Yellow/black line is linear trend.
However, there are also plenty of countries that are just as linear as the US.
Figure 3. Scatterplot, daily new tests versus daily new cases, Turkey. Yellow/black line is linear trend.
Poland shows the same type of mostly linear relationship.
Figure 4. Scatterplot, daily new tests versus daily new cases, Turkey. Yellow/black line is linear trend.
So … how about for the whole world? Glad you asked. Here’s that chart.
Figure 5. Scatterplot, world total daily new tests versus total daily new cases. Units are thousands of tests and thousands of cases. Yellow/black line is the linear trend. Black “whiskers” show the uncertainty (one sigma) of the individual mean values for the various days.
One item of interest is the difference in the rate of discovery of new cases in various countries. In the US there are nineteen new confirmed cases per hundred new tests; Turkey is 13/100; Poland is 4/100; Australia is 1/100; and globally, there are eleven new cases for every one hundred new tests.
I suspect that this variation depends directly on at least a couple of things — the underlying number of cases in any given country, and exactly which subgroup is being tested.
For example, in the US we’re still short of tests. So the tests are being reserved for people who are showing obvious symptoms … and as a result, the US tests would be expected to come up with more new cases than the global average.
This leads to a curious situation. In addition to being a function of the number of tests, confirmed cases can also be a function of the scarcity of tests …
Conclusion? Don’t use confirmed cases as a metric of the spread of the virus—the number of cases is indeed a function of the numbers of tests.
w.
PS—When you comment, please quote the exact words you are discussing. It avoids endless misunderstandings.
PPS—While I’m here, let me shamelessly recommend the Watts Up With That Daily Coronavirus Data Graph Page. I create the daily graphs and maintain the page. I’ll also recommend my own blog, Skating Under The Ice. I note that it’s been one full month since I publicly called at my blog for an end to the American Lockdown. Finally, I’m on Twitter here. Enjoy.
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For interested readers
https://quillette.com/2020/04/23/covid-19-superspreader-events-in-28-countries-critical-patterns-and-lessons/
Glad someone did this.
Some things I have seen looking at Korean data.
Superspreaders drive the damn thing. case case case case cluster, cluster, boom.
80/20 rule. 80% of the cases driven by 20% of the cases.
Spreading doesn’t happen in just any old social situation ( like being at the beach)
in Korea
Family, Friends, Cramped work space (call centers), Hospitals, mental wards, Nursing homes,
Gyms, Internet cafes, Singing rooms, churches.
SSE
https://quillette.com/2020/04/23/covid-19-superspreader-events-in-28-countries-critical-patterns-and-lessons/
Super spreader events:
lesson: there are specific types of situations that are KNOWN TO BE WORSE than anything else.
druken parties, funerals, church services, face to face business networking.
next:
spread is highest in cultures that kiss on the cheek, next in those that shake hands and lowest in
bowing cultures.
There might be a surgical approach to social distancing. The hammer works, but it crushes the economy
as well
You said something sensible.
Hey if you are in certain countries who you hold a religious festival … always good for a cluster or two.
Excellent link.
Thank you.
Her an “Amateur Scientist” have more of substance than WHO and diverse National Health Agencies. I think it is a shame on the scientific society.
Agree mosher Re: super spreaders. Any indication that school kids actually infect?. Ie teachers not at much risk?
The human breath coming out of the mouth is characterized by a temperature of around 35-36 ° C and a relative humidity of around 80-90%. Coronavirus infection is greatly facilitated by external environmental conditions. As the temperature of the outside air decreases and above all the relative humidity of the outside air decreases, the ideal conditions are formed for the spread of the infection. The main mechanism to consider is the expansion of water vapor which in turn regulates the expansion of the viral load in the air (see https://valedo.com/umidita-temperatura-e-sars-cov-2/ .. use the google translator as the post is in Italian).
Thanks for this report however I sligthly disagree with you with this part “For every one hundred additional tests that we do, we find an additional nineteen confirmed cases of coronavirus.”
In fact testing, and the percentage of positive case, is a good way to control whether the country has the situation under control.
2 examples: Italy. around the 18th of March they start to increase the number of daily tests. from 12.000 to 16.000 then 25.000 by 24/03, then consistently above 30.000 from 1st of april and then regularly above 50.000 and even 61.000 yesterday.
During that time the % of positive tests has been going down. Between the 11th of March and 24th of March it was between 20% and 31% positive tests. then from the 25th up to the 6th of April it was between 19% and 10% but going down. since the 7th it is always below 10% and was at 5.3% yesterday. This I believe shows that most of the cases are identified.
The same for South Korea, when the epidemy started on the 18th of February, the positive tests were around 10% and some 2.500 tests per day, South Korea increased then their testing capacity and by the 4th of March it was performing some 17.000 daily tests and around 3% were positive. Now since end of March positive tests is below 1% and now even below 0.5%
Well just checked the USA for yesterday , 311.000 tests and 27.000 positives so less than 9%, en encouraging figure which needs to be confirmed in the next couple of days. It might mean that most of the case are identified.
That`s in line with the cruise ship Princess Diamond where 85% of the peopl didn`t have it. But these American tests are still biased towards the infected as they are not testing randomly so the number is probably lower. And it doesn`t tell us how many people actually HAD the virus.
Robert
Take a look at the French aircraft carrier Charles de Gaulle which had 60% infection rate.
Perhaps isolation in a cruise liner works after all. Is this proof that a lock-down reduces infection?
I have said from the very beginning that we need random testing, before we can assess the true infection rate or death rate. How can anyone formulate a medical or political strategy, before we have that data?
Wild guesses have been made of 5% mortality, when we have no idea how many are really infected. And this has been talked up and inflated by the alarmist media, who sell newspapers and TV news through wild and exaggerated stories. And some irresponsible medics chimed in, estimating millions of deaths, in order to get their 15 minutes of fame.
But when a random sample was at last taken in Santa Clara, it unveiled infection rates that were 50 to 80 times higher than thought. And that suggests the true death rate may be 50 to 80 time LESS than thought. In which case, the Cov-19 virus is nowhere near as deadly as has been advertised – so why did politicians shut down the economy?
https://paloaltoonline.com/news/2020/04/17/stanford-study-more-than-48000-santa-clara-county-residents-have-likely-been-infected-by-coronavirus
Has this unprecedented shut-down of the world been a media-led waste of time and money, with politicians being hounded into making poor judgements and decisions based upon the baying howl of ignorant reporters?
Ralph
But when a random sample was at last taken in Santa Clara,
It wasn’t a random sample. It was a sample recruited via a Facebook ad so will almost certainly be biased in favour of those who believe they have been infected.
And that suggests the true death rate may be 50 to 80 time LESS than thought.
Not True. Chief Medical Officer made it clear that he (and colleagues) expected the true fatality rate to be below 1%. This was in a Parliamentary Select Committee meeting in February. Neil Ferguson (the modeller) has since suggested that 3-4 million people had probably been infected several weeks ago.
The Fatality rate was not the issue of most concern. Lack of immunity means that at least half the population would need to be infected before there was a significant decline in the spread of the disease. Even that might have been acceptable if it took place over, say, a 12 month period. If the virus were allowed to spread freely and assuming a fatality rate of 0.2%, there would be at least 320k deaths in the US within a 3 month period. But that assumes the US healthcare system could manage to treat the 16 million patients who require hospitalisation.
Mitigation was necessary to prevent healthcare systems becoming overwhelmed.
That is NOT the scare story that has been propagated by the media, both of the responsible and sensationalist kind. The story that had resulted in millions cowering and imprisoned in their homes, is that the mortality rate was between 2% and 5% – and thus this is a very dangerous pandemic that could kill millions.
Please give some links to popular press articles, that give the likely death-rate as being just 0.2%. Most people could live and work with a 0.2% mortality rate, without crashing the economy. While most elderly and infirm people could self-isolate. But that us not what we have ended up with – the scare stories have locked down entire nations.
Ralph
Please give some links to popular press articles, that give the likely death-rate as being just 0.2%.
I don’t read the “popular press”. I know that Neil Ferguson used a fatality rate of 0.9%. It could be lower than that but not as low as 0.2%. I used 0.2% to show that even that figure could result in over 300k deaths in the US.
Most people could live and work with a 0.2% mortality rate
Even at that rate Healthcare systems could be overwhelmed.
John
You commented about “biased in favour of those who believe they have been infected ..” Also, Facebook is going to be biased in favor of a younger group, demonstrably more active socially, and less susceptible to the virus. Facebook recruitment is anything but random.
In addition to the point John Finn makes, the antibodies tests throw out false positives, depending on the particular test at a rate somewhere between 1 and 10%, even at the low end of this error rate the results of the Santa Clara study are meaningless, across 3300 tests they got 50 positives, even at a false positive rate of just 1% they’d get 33 false positives, at a false positive rate of 1.5% there might not have been a single true positive in the entire study.
“Don’t use confirmed cases as a metric of the spread of the virus—the number of cases is indeed a function of the numbers of tests. ”
And the number of tests is a function of the number of people who have severe enough symptoms to go to the hospital where they are subsequently tested. Hence, it is a good metric for the spread of severe cases in the population. Mild cases, no doubt, parallel the severe cases, but the ratio of mild to severe is still in question.
The statistic I am most interested in, but is missing so often from reports on the progress of the pandemic that I suspect that reporting of it is being suppressed, is the median age of the dead. I have never understood why anyone would place any value on the number of cases when the testing for them is not random. Also, what is a case? A twenty year-old who is asymptomatic and a 75 year-old with emphysema are both cases. The criteria are so broad that the category has no useful meaning.
I realize that this question is profoundly offensive to many people, and the fact that I would even ask it could be evidence of moral deficiency, but why are we ruining our economies to limit the spread of a disease that mostly kills old people?
I abhor the unreasonable lengths the medical profession goes to prolong life in the elderly. My parents died of diseases of old age, which is to say, they died slowly and painfully, and each at least a year after he or she would have died if medical professionals had not compulsively and unreasonably prolonged their lives. Dying of old age is the equivalent of being held down and slowly smothered, after being stripped of every capacity that makes life worth living as a human being. My own plan for happiness in old age (and I’m 68) is, avoid doctors unless you have something they can fix. When you’re dying (and you’ll know when) don’t let them treat you. Better to die in a week and be done than over the course of a year.
There’s plenty of reporting of ages in the UK. Try the latest total announced deaths spreadsheet from here, which breaks it down by date of death as well as age ranges:
https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-daily-deaths/
Over half are 80+
Covid-19 Tracker for 20-69 year olds in UK.
https://covid.joinzoe.com/data
Contributors use mobile phone app to record symptoms. Tracker estimates probability of Covid-19 from symptoms based on learned data from actual tests. Extrapolations across regions then provides number of likely Covid-19 cases.
According to tracker there were 2 million ‘probable’ cases in UK on April 1st. Most recent estimate is 437k.
The interesting number would be the total number who have been infected. I wonder if they have the means to estimate that from their cumulative data.
If there had been enough available tests regional samples could have been tested which would have confirmed (or otherwise) the reliability of the apps data.
How do they account for people who have a negative test but then are infected afterwards?
Being tested does not provide immunity so they are possible future positive cases.
If infected post-test, are they counted in both the negative AND positive numbers?
They could be tested again if they showed symptoms and would appear in the data but, if asymptomatic, would not be counted.
There are two ways to test; use the tests to confirm suspected cases, or use the tests to track and trace the spread of the disease. The countries using the test for the former have high positive test rate, often over 20% (UK, US, Spain, France, Belgium, the Netherlands), the countries using the test for the latter have low positive test rates (South Korea, Taiwan, Iceland, Australia, New Zealand). The former countries are stumbling around in the dark, the later countries have the lights on, can see what they’re doing, and are knocking this virus over quickly.
If you want any data about what the true fatality rate of this virus is look at the data for the latter countries and the Diamond Princess and Theodore Roosevelt. It’s somewhere between 0.8 and 2% in most Western populations.
Testing solves nothing unless it leads to rapid and effective quarantine. Speed of quarantine imposition of case contacts is much more important than detecting every infectious person. Delay in quarantine allows all contacts to be spreaders. Missing the odd spreader contact will likely be picked up by infection of someone else, and further spread suppressed through that.
It doesn’t add up… April 23, 2020 at 5:13 am
Which is why lock-downs were used, everyone gets quarantined (Which is not a position on whether their use is morally justified), and obviously those with positives results know it’s important that they adhere to their quarantining.
The reason for imposing lockdown was that in urban environments, and e.g. on London’s packed tubes, it was impossible to trace contacts in any meaningful way. On the other hand, it was probably quite unnecessary in less urbanised environments where people do not go to work on public transport, and where there social interactions are much more limited: the same locals at the pub even if they still go to one, for instance – not random encounters in the queue for a sandwich at Prêt à Manger.
Just look at the enormous differences in infection rates across Wales:
https://datawrapper.dwcdn.net/7Lbsv/1/
It
It is of little value to know that someone has COVID-19 because there is no known cure accepted by the medical community. Those advocating HCQ say it can only be used on those who have high probability of recovering on their own, and it doesn’t work on those who clearly are in need of a prompt cure. As to quarantine, anybody who has flu-like symptoms should stay at home anyway, and practice social distancing and enhanced hygiene. Until such time as there is universal testing, with repeat resting, we cannot identify the asymptomatic carriers. Testing has the greatest value in determining the prevalence of the disease in the population and the rate of growth. However, it isn’t being used in that way.
The point is that quarantine needs to be enforced around identified cases. Their contacts may be asymptomatic spreaders. That is stopped by quarantining them, regardless of test results. If you wait until they also show symptoms they will have spread the virus. It is doubtful whether testing is good enough at 30-40% false negatives to let them bypass quarantine.
People are not being tested at random. People are being tested because they are symptomatic, so in that case, tests are going to reflect the incidence of the disease in question, and if more people are getting sick, the number of confirmed cases is going to go up.
The CDC has stated the following on (https://www.cdc.gov/flu/weekly/index.htm)
“Key Points
Nationally, influenza activity is now low.
With ongoing declines in influenza activity and the continued effects of the COVID-19 pandemic, FluView will be abbreviated for the remainder of the 2019-2020 season.”
In addition the government announced and that it will pay hospitals for the treatment of anyone contacting Covid-19 . This was in a response on how the uninsured will get treatment.
This incentivizes hospitals and health care providers to report everything especially deaths using the “Covid -19 codes”.
This has the potential to distort Covid -19 death statistics.
It’s beyond potential. It’s kinetic.
Willis – many moons ago when I was a young researcher at Battelle Pacific Northwest Laboratories, I took a course called Strategy of Experimentation which was developed by E.I. DuPont. Using statistics, it taught how to design an experiment with minimum number of test trials based on how many variables were being studied. Science is seldom two-dimensional so we need to remain weary of conclusions drawn from two-dimensional analysis.
.
The hypothesis is that the virus spreads widely because some carriers get the SARS-CoV-2 virus but not COVID-19 disease. If this is the case we need to know! #antibodytesting would tell the business owners which employees are safe to get back to work. #antibodytesting would let the epidemiologists make better predictions. Testing whether or not an individual has an ‘active’ case is medically correct, but not so useful to decision makers and paid prognosticators.
“Don’t use confirmed cases as a metric of the spread of the virus—the number of cases is indeed a function of the numbers of tests. ”
That is only true if tests are not exceeding the number of cases by far. Like in South Korea, Austria, Germany, Taiwan. Worldometer is suggesting a rough estimate of an at least 10-fold overtesting is able to show you the real development of cases. Otherwise there would be no curves bending.
Seems the curve has bent a bit in the US without the 10-fold overtesting.
Maybe there is now sufficient overtesting as growth rate declines and testing capacity increases. Hard to say from the available data.
Australia’s health department site (https://www.health.gov.au/news/health-alerts/novel-coronavirus-2019-ncov-health-alert) says they have done 466,000 tests with only 1.4% positive rate. They are seeing single digits of new cases many days. Their site also says they can trace the source of nearly all cases, mostly to overseas.
What have they done so differently?
“What have they done so differently?
maybe nothing.
No superspreaders.
They’ve used the test to track and trace, America and most European countries have mostly been using it to test suspected cases, hence the difference in the positive test rates.
Willis, many thanks for your most interesting article and graphs.
I downloaded into Excel the data that you recommended, from Our World in Data (I agree they are an excellent source). I can see why you wanted to do a scatterplot! If you try to plot the ratio of daily new cases to daily new tests against date, the data is horribly jumpy. Not to mention that the reporting of a test and the reporting of the resultant case may happen several days apart. Particularly in those countries (such as France and Germany) in which they only seem to be reporting tests on a weekly basis. To get around this, I’d previously been looking at the evolution of the ratio of cumulative total confirmed cases to cumulative total tests over the time frame of the epidemic.
If you look at the US numbers on that basis, you’ll see that the total cases per test to date is indeed 19%. But I think the linearity of your scatterplot is caused by the fact that, in the US, that ratio has been unusually constant compared with other countries. In fact, it has been between 18% and 19% every single day since April 8th. If you go back towards the beginning of the epidemic, the ratio of cumulative cases to cumulative tests started at 14.1% on March 7th, dropped to 8.2% on March 18th, and has since risen towards its present value of 19%. That little cluster of points at the bottom left of your graph, which is clearly below your trend line, is actually a feature of interest. It represents data from the early stages of the epidemic, when the tests were both lower in number, and showing a lower incidence of confirmed cases per test, than now. Indeed, if I disregard your trend line and that outlier at the far right, and squint hard enough, I think I can just about see a hockey stick!
I looked in a bit more detail at the UK figures. BTW, Our World in Data reports tests for the UK as per person tested, which explains the differences between these and the figures from Worldometers (which seems to be using total number of tests). The ratio of cumulative confirmed cases to cumulative tests started on January 30th at 1.1% (2 out of 177). It reached a minimum of 0.1% on February 22nd. It then climbed, relatively gently, back up to 0.3% by March 4th. On March 5th it started to accelerate upwards. By March 16th (the day the first stage UK lockdown was announced) it was up to 3.2%. By March 23rd (second stage lockdown) it had reached 6.8%. Today it is 31.4%, and still rising; though the rate of rise did begin to slacken about 10 days ago. The ratio of daily confirmed cases to daily tests has been north of 30% every day except one since March 28th.
Looking at Austria, a country which has all but beaten the epidemic, the ratio of cumulative confirmed cases to cumulative tests started out at 0.6% on February 26th. It reached a peak of 18.4% on March 31st – coincidentally (?) the same day the daily new confirmed cases started a precipitous decline after the third of three peaks. Today, it is down to 7.4%, and still falling. Individual days’ confirmed cases to tests ratios have only been above 30% twice in the whole epidemic. Since 2nd April no day has been above 10%, and the maximum in the last week has been 2.3%.
What might account for these differences? Population density is one thing; or, at least, the numbers who live, work or travel in high-density environments. The possibility of greater immunity according to how far the virus has already spread through the population is another. Shortage of test kits is a third; if you can only test those with significant symptoms, then as long as the epidemic is still expanding, you would expect the cases to test ratio to go higher and higher. I’m interested to know what others here think might have been the causes of the huge divergences in the path of the epidemic between these three countries.
You note that Australia sees only 1.4% of tests positive (of over 400,000 tests in a population of 21 million). They are seeing very few cases and their health department site also says they can trace the source of nearly all cases, mostly to overseas. From what I know, Australia had some very early cases and put in “social distancing” type measures in the same time frame as the US.
What have they done so differently to have so few cases – which seems to be for real given the amount of testing done and the low positive rate.
“Conclusion? Don’t use confirmed cases as a metric of the spread of the virus—the number of cases is indeed a function of the numbers of tests. ”
Sweden, denmark, Finland, US, Germany, Norway would make an interesting panel
final figures
Norway 27,421 tests per million 5% positive
Germany 24,738 tests per million 7.5% positive
Denmark 20,134 TPM 7% positive
Hong Kong 17,579 TPM 0.7% positive
USA 13,071 TPM 19.7% pos
Finland 12,814 TPM 6% pos
Sweden 9,357 TPM 18% pos
Germany 3.4% of urban pop tested 7.5% positive
Norway 3.3% of the urban population tested 5% positive
Denmark 2.2% of urban pop tested 7% positive
Hong Kong 1.8% of pop tested 0.7% positive
USA 1.6% of urban pop tested 19.7% pos
Finland 1.5% of urban pop tested 6% pos
Sweden 1% of urban pop tested 18% pos
23 April 2020 – Queensland has two new confirmed cases of novel coronavirus (COVID-19) raising the state total to 1,026. “… Dr Young said a total of 92,699 tests for COVID-19 has been undertaken in Queensland, with 2,539 tests undertaken in the previous 24 hours. …”
Source: https://www.health.qld.gov.au/news-events/doh-media-releases/releases/queensland-novel-coronavirus-covid-19-update-2020-04-23
Yet QLD had 2,137 tests on the 28th of March that produced 111 new cases.
Source: https://www.abc.net.au/news/2020-03-17/coronavirus-cases-data-reveals-how-covid-19-spreads-in-australia/12060704
But 2,539 tests during the past 24 hours produced 2 positive cases. So more testing does NOT produce more cases. More virus being present produces more cases, while less virus being present due to weeks of isolation, produced 55.5 times fewer cases, from 19% more tests.
“Hong Kong 1.8% of pop tested 0.7% positive”
Was this a typo in omitting “urban”?
I had no figures for rural pop in HK.
having been there many times I’d say its close to 100%
I could calculate it from source data but was lazy
Mosher
“USA 13,071 TPM 19.7% pos”
“USA 1.6% of urban pop tested 19.7% pos”
Shows that the US statistics are being driven by urban environments. It is almost as if NYC were another country.
It’s not only the US. I’ve posted maps of case rates for Wales, England and Germany below.
The use of active cases is being pushed to alarm Australians to keep them compliant with pretty tough measures by highlighting the risk of a second wave in Singapore. Yes, active cases shot up when they relaxed borders by bringing in foreign workers who live in hostel type dorms. Why understanding is that infected workers were in home detention but their families weren’t and there was community spread. But what is interesting it’s now at least two weeks and even though active cases have indeed exploded but deaths have barely moved. It may be that the number of deaths will also explode but I’m watching it closely. The number of deaths is really the clutch number . Singapore currently has the grand total of 12 deaths but are being used as an example of why we have to keep everyone locked up in Australia where as you point out we have a ridiculously rate of active cases / tests and deaths. The other thing is that also confirmed cases is not active cases and the acknowledgement of recoveries is often overlooked by the media.
Which is why the most important data point is hospitalizations.
That data point directly relates to hospital bed usage. It reflects the amount of sickness in a community and the community’s ability to deal with it. The death/cure rate of those hospitalized is easily counted and can show effectiveness or the lack of effectiveness in treating the virus.
Yet, while every newspaper in the country shows new cases and deaths, almost none show the hospitalization number.
I agree with @Dave.
Alternatively look at how much oxygen hospitals consume.
One hospital in Italy reported that they had an annual consumption of about 150 liters of oxygen. The first three and a half months this year, they spent more than 3000 liters of oxygen.
That could be a useful metric.
O2 use depends on the treatment and is not constant. High flow devices like HFNC use vastly more O2 than ventilators, and the volumes change frequently depending on physiological response.
I think hospitalization rates are being skewed in areas of high rates of infections by people choosing not to go to hospitals when they should. Either through fear of being stuck in a ward with lots of C19 +tive people or because they don’t want to burden the health system when they see others requiring the services more than they.
I agree, the number of hospitalizations (where available) is probably the best metric we have at this time.
The # of deaths would be interesting but it seems we can’t even count those that arise outside of a hospital setting (i.e. in homes, managed care facilities etc).
So along with testing those who are “at risk” or may already be showing symptoms, we will have false positives/false negatives guaranteed. Even with very reliable testing, if someone shows “negative” today how do we know they won’t catch the Wuhan virus tomorrow? Are we supposed to test everyone every day?
Willis wrote:
“Conclusion? Don’t use confirmed cases as a metric of the spread of the virus—the number of cases is indeed a function of the numbers of tests.”
I agree. I came to this same conclusion about one month ago, and have been dismissive of much of the public data since then. Most Covid-19 testing is “chasing positives” to limit contagion and thus grossly overestimates the severity of this virus.
The best data I’ve encountered is Iceland, where random testing has been performed on over 10% of the country’s entire population and the Total Fatalities/Total Infections at less than 0.1% – SIMILAR TO A TYPICAL FLU.
As I wrote in March:
https://rosebyanyothernameblog.wordpress.com/2020/03/21/end-the-american-lockdown/comment-page-1/#comment-12253
[excerpt- posted 21Mar2020]
“This full-lockdown scenario is especially hurting service sector businesses and their minimum-wage employees – young people are telling me they are “financially under the bus”. The young are being destroyed to protect us over-65’s. A far better solution is to get them back to work and let us oldies keep our distance, and get “herd immunity” established ASAP – in months not years. Then we will all be safe again.”
Have we wasted many trillions, harmed billions of young people and trashed our economies for nothing? Seems so.
https://wattsupwiththat.com/2020/04/20/un-climate-change-fund-calls-coronavirus-an-opportunity-to-re-shape-the-world/#comment-2973043
[excerpt]
In Iceland THE DEATH RATE [Total Deaths/Estimated Total Infections] IS LESS THAN 0.1%, SIMILAR TO OTHER SEASONAL FLUS.
Covid-19 appears relatively mild, often showing no symptoms among younger people, but is dangerous to the elderly and the infirm.
________________________________
I’ve also suspected that Covid-19 arrived in North America sooner than generally assumed. As I recall, the earliest mention of its occurrence in China was 17Nov2019 – I expect it hit North America by no later than Dec2019. A newly-discovered Covid-19 fatality in California on 6Feb2020 supports that hypo.
SANTA CLARA COUNTY HAD NATION’S FIRST COVID-19 DEATHS, WEEKS EARLIER THAN THOUGHT
New test results confirm the novel coronavirus was responsible for two deaths in February
By David Debolt and Kerry Crowley
Published: April 21, 2020
https://www.mercurynews.com/2020/04/21/coronavirus-earliest-covid-19-deaths-in-bay-area-occurred-in-february-not-march/
[excerpt}
Two individuals who died in Santa Clara County in February tested positive for COVID-19, health officials learned Tuesday, revealing the novel coronavirus was responsible for deaths in the Bay Area more than a month earlier than initially reported.
The individuals who tested posthumously for COVID-19 died at home on February 6 and February 17, according to autopsy results released by the county late Tuesday. The deaths appear to be the first confirmed coronavirus fatalities in the country — occurring weeks before the first U.S. death was publicly reported on Feb. 27 — adding to mounting evidence that the virus was spreading here far earlier than once believed.
Thanks to Mosh for posting this excellent video elsewhere.
This elderly Swedish gentlemen is obviously mature, expert and brilliant – and he agrees with me. 🙂
https://youtu.be/bfN2JWifLCY
EXCLUSIVE! NURSE CLAIMS: NO CORONAVIRUS EMERGENCY IN ONTARIO HOSPITALS
By David Menzies April 23, 2020
https://www.rebelnews.com/exclusive_ontario_nurse_speaks_out_no_coronavirus_emergency_in_ontario_hospitals
“In fact, at her hospital, personnel are so bored because on many days they have nothing to do as they await for a tsunami of COVID-19 cases that never materializes…”
Same in Calgary. WHAT A COSTLY STUPID DEBACLE THIS LOCKDOWN TRULY IS.
https://wattsupwiththat.com/2020/04/13/coronavirus-the-chinese-virus-lockdowns-that-have-done-their-job/#comment-2965819
Here in Alberta, the Covid-19 lock-down has resulted a debacle.
Most of our deaths are in nursing homes – our policy seems to be “Lockdown the low-risk majority but fail to adequately protect the most vulnerable.”
The global data for Covid-19 suggests that deaths/infections will total 0.5% or less – not that scary – but much higher and clearly dangerous for the high-risk group – those over-65 or with serious existing health problems.
“Elective” surgeries were cancelled about mid-March, in order to make space available for the “tsunami” of Covid-19 cases that never happened. Operating rooms are empty and medical facilities and medical teams are severely underutilized. The backlog of surgeries will only be cleared with extraordinary effort by medical teams, and the cooperation of patients who die awaiting surgery – patients who were too impatient…
This may look like 20:20 hindsight, but I called it this way in ~mid-March.
Regards, Allan
In Iceland 10 deaths out of 1791 cases is 0.56% but 10 deaths and 1509 recoveries (which is a better metric) is 0.66% which is 6 times as high as the 0.1% you quote above. You could take their random testing results which say that 0.6% of people are actually infected and infer that their total population of infected are 364,000*.0061 = 2,223 people and that would get you to an IFR of ~0.4% but I’m not seeing how you get to 0.1%. Would love to be wrong though. Either way much less than the scary numbers in the headlines. Iceland certainly has the best data but maybe not applicable to non island, non homogeneous populations.
dwe wrote:
“In Iceland 10 deaths out of 1791 cases is 0.56% but 10 deaths and 1509 recoveries (which is a better metric) is 0.66% which is 6 times as high as the 0.1% you quote”
Your stats are simply a function of the number of tests – NOT MEANINGFUL.
You need a large random testing of the population and you get 43,000 cases, ~13% of their country’s population.
Active cases peaked on 5April2020. On 4May2020 the Icelandic government will begin relaxing COVID-19 restrictions in Iceland in general. Icelandic preschools and elementary schools will return to regular operation; salons, massage parlours, and museums will reopen; and gatherings of up to 50 people will be allowed. Swimming pools, gyms, bars, and slot machines will remain closed for the time being.
Iceland Total Tests to 21Apr2020 ~43,143
Confirmed infections 1773
Population of Iceland 341,250
Total Tests/Population 12.6%
Infections/Tests = 4.1%
Extrapolating to Iceland’s population = (341,250/43,143) * 1773 = 14,023 estimated total infections in Iceland
Ten deaths have been recorded to date.
10 deaths/1773 confirmed infections = 0.56%
10 deaths/14023 estimated total infections in Iceland = 0.07% = LESS THAN 0.1% MORTALITY RATE IN THE GENERAL POPULATION OF TOTAL ESTIMATED INFECTIONS
10 deaths/341,250 population = 2.9*10^5 = 0.003%
“Extrapolating to Iceland’s population = (341,250/43,143) * 1773 = 14,023”
You’ve totally screwed that up.
“Stefansson said Iceland’s randomized tests revealed that between 0.3 to 0.8 per cent of Iceland’s population is infected with the respiratory illness, that about 50 per cent of those who test positive for the virus are asymptomatic when they are tested, and that since mid-March the frequency of the virus among Iceland’s general population who are not at the greatest risk – those who do not have underlying health conditions or signs and symptoms of COVID-19 – has either stayed stable or been decreasing.”
https://www.stuff.co.nz/national/health/coronavirus/120966816/coronavirus-icelands-mass-testing-techniques-gives-the-world-covid19-answers
Your mistake is that you’ve rolled the results from targeted testing into the results of the random testing.
Let’s assume you are correct. NUHI testes are targeted, deCode are random.
Data:
https://www.icelandreview.com/ask-ir/whats-the-status-of-covid-19-in-iceland/
https://www.icelandreview.com/sci-tech/icelands-coronavirus-testing-global-pandemic-response/
Infected/Tested NUHI*= 9.57%
Infected/Tested deCODE Genetics= 0.61%
Iceland Population= 341,250
Total Infected Est.= 2084 (using deCode 0.61% only)
Deaths/Infected= 0.5%
7/10 deaths over 70 years of age, 9/10 over age 60, 1/10 age 30-39.
Based on the data, the Swedish strategy of limited contagion (not full lockdown) is much better.
This elderly Swedish gentlemen is obviously mature, expert and brilliant – and he agrees with me. 🙂
https://youtu.be/bfN2JWifLCY
“Let’s assume you are correct.”
We don’t need to assume I’m correct, the links you provided state what I’ve said. deCODE Genetics was doing the random testing and the results were infection levels in the wider community of 0.61%.
Prof. Johan Giesecke and Anders Tegnell are the architects and main advocates of the Swedish policy, in terms of controlling Covid-19 the results say it’s not a very successful policy, especially when you can compare Sweden’s progress in controlling the virus with its Scandinavian neighbors.
https://www.worldometers.info/coronavirus/country/sweden/
https://www.worldometers.info/coronavirus/country/norway/
Given that the famous Imperial model was predicting 250-500,000 deaths in the UK absent a lockdown, I think the fact that Sweden (with its highly cosmopolitan cities being its main centres of population) I think we need to compare against the pro-rata 35-70,000 deaths implied for Sweden absent a lockdown. It seems that deaths are way, way short of those levels – which must throw lockdown policies into question at the very least.
Andrew, [snip – mod] All you did was quote a newspaper article.
Sweden has lower total deaths than many countries that chose full lockdown
See Mortality Monitoring in Europe
https://www.euromomo.eu/index.html
This Swedish expert explains the higher mortality among the elderly in Sweden vs Norway. https://youtu.be/bfN2JWifLCY
I suspect that most of these differences in total mortality in Europe are due to worse vs better control of Covid-19 infections in nursing homes. Some countries like the UK are doing a great job of killing off their elderly – you’d almost think it was deliberate. https://drmalcolmkendrick.org/2020/04/21/the-anti-lockdown-strategy/
“Sweden has lower total deaths than many countries that chose full lockdown.”
Given the later arrival of the virus in Sweden her position in 10th place in the world in deaths/million (7th if you exclude densely populated micro-states) is nothing to crow about.
The challenge is to get R0 below 1 and keep it there until the enemy has been vanquished.
The ability of countries, states and communities to do that will come down to both the threats imposed by the state and the social culture of the people in a country.
At the moment we can see that some East Asian countries have gotten R0 without the use of government imposed measures, Western cultures are different to East Asian cultures, we’re more supportive of individuality – people having the right to do their own thing, that’s a good thing when it comes to economics and things like creativity and individual freedom. But when it comes to defeating this sort of enemy it’s not so effective, a few rogues spreading the virus can defeat the efforts of the majority to contain it.
In military terms it only takes a few to break the ranks under pressure for the front to collapse. It’s the people that are on the front line in this one and Western Society, with its individuality isn’t so well equipped for this fight. The US least of all.
Posting the same youtube video again doesn’t advance your argument, as I said Prof. Johan Giesecke is one of the architects of Sweden’s policy on this, he also advises WHO – which might explain so many of WHO’s mistakes in not taking the threat this virus poses seriously.
What we have here is nothing more than a simple sampling problem. To determine the number of cases, we need to use the antibody test, not the test which only indicates CURRENT affliction. Using the antibody test, one can create a randomized sampe stratified by the affecting things, take a healthy sample – a couple of thousand would be plenty, and then calculate the total for the country. But this is specific as to the time of the tests.
I just read, that smokers are less hit by Corona, seems, the virus can’t hook on, because of nicotine is placed there.
They will start studies with nicotine pavement for medical personal and patients too.
Holy smokes, Batman!
Nicotine and the renin-angiotensin system
https://journals.physiology.org/doi/full/10.1152/ajpregu.00099.2018
But if infected you would want downregulation of ACE due to its inflammatory role in RAS, and because viral infection downregulates ACE2 and its anti-inflammatory response. So maybe good as a infection prophylaxsis, but not so good once infected.
Willis
I have been tracking Tennessee USA cases, deaths, and testing for two months. We have averaged about 250 cases a day with 3,000 to 10,000 tests. Wouldn’t anyone who feels poorly and anyone who came in contact with that person or a person that has tested positive and those that came in contact with them go get a test? So, if that assumption is true, why would increased testing lead to increased cases?
When an area reaches the top of the bell curve or starts down the slope, increased testing won’t lead to increased cases? Straighten me out, if you will.
Terry Anderson
Some states will supposedly open next week. Will Tenn be among them?
define feels poorly, slight cough for over 6 weeks, occasional recurring sore throat, random headaches not related to alcohol then nah I’m not getting tested.