The world has over 2 million coronavirus cases. Italy’s coronavirus epidemic has been about two weeks ahead of the US. Italy has had a slow reduction in daily cases and daily deaths from its peak.
SOURCES- Worldometers.info, University of Washington IHME model
Written By Brian Wang, Nextbigfuture.com
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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La county study has huge flaws
https://www.latimes.com/opinion/story/2020-04-21/stanford-blood-antibody-study-might-not-be-very-useful
Results way off, because participants represented those people, who has some symptoms, but unable to get tested otherwise.
I haven’t read their methods, but if I’m not mistaken, for a death to be counted as “Influenza”, it has to be a diagnosed case. In that case, that’s still CFR.
My guess is the flu CFR varies a little from year to year and is generally close to 0.1%, but can go lower.
0.1% seems actual. As in 100 deaths for 100,000 cases of the flu. Death rate was 14.3 per 100k in 2017, and if 1 out of 7 got the flu that year it matches up https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf
EDIT: whoops that was already normalized for 2017. It was 2 per 100,000 recorded flu deaths normalized to 14.3 per if 100% had contracted it.
Data from random testing in Iceland (best there is) was a 0.19% fatality rate assuming spare capacity in the hospitals.
Thats roughly consistent with the Los Angeles county numbers below – 4.1% (so about 410,000 people) and 600 fatalities. 410k times 0.19% is 779. Some of those 779-600=179 deaths are still “in process” and will show up over the next one or two weeks.
https://www.google.com/amp/s/www.cnbc.com/amp/2020/04/20/coronavirus-antibody-testing-shows-la-county-outbreak-is-up-to-55-times-bigger-than-reported-cases.html
If everyne n th population is locked down and not allowed to leave there hop the number of new cases would eventually get to zero.
However no country is totally locked down. doctors and Nurses still need to go to work as well as a lot of people that support them. Food stores are also open because people need food which means the entire food industry and truck drivers are still working. So the virus is still spreading among those still working. So we have slowed it down but we don’t know if we have done enough to get it to fall to zero.
In all likely hood the virus will continue to kill people at a slower rate until most of the population is immune or a Vaccine is developed .
Ah – the current late-stage and pre- post-Pandexit political analysis. Where we’ve been, are, and will likely be this Summer:
“…our current and coming Lockdown Socialism:
–you can stay in your residence, but paying rent or paying your mortgage is optional.
–you can obtain groceries and shop on line, but having a job is optional.
–other people work at farms, factories, and distribution services to make sure that you have food on the table, but you can sit at home waiting for a vaccine.
–people still work in nursing homes that have lost so many patients that they no longer have enough revenue to make payroll.
–professors and teachers are paid even though schools are shut down.
–police protect your property even though they are at risk for catching the virus and criminals are being set free.
–state and local governments will continue paying employees even though sales tax revenue has collapsed.
–if you own a small business, you don’t need revenue, because the government will keep sending checks.
–if you own shares in an airline, a bank, or other fragile corporations, don’t worry, the Treasury will work something out.
… might not be sustainable…”
The point: political divisions and ideological conversations may get a little intense over the next 4 – 8 weeks as we unravel this.
Still waiting for Covid19 to rip India to pieces.
In my limited experience with mass surveys, asking a question like that would give answers that were completely useless.
Something like 1/3 of the population wouldn’t understand it, and so wouldn’t answer.
1/3 would think they understand it, but not.
And most of the rest would shade their answers depending on how clever it made them seem, or how they now feel about the question, or whether this was more or less likely to get them an insurance/pension payout.
I think that’s already happened.
In the near future, it will be people debating about whether a job/education/activity should be moved to being “on location” rather than left “from home”.
You don’t get to remove NYC from your national total unless you are on the verge of actually expelling them from your country.
It’s the USA’s fault. The British ended up in control of NYC at the end of the revolutionary war. You guys are the ones who negotiated it back, instead of swapping it for New Zealand or somewhere.
No, after you, I insist!
China gave us deaths. Remember that.
They are in the minds of the panic mongers who “master bait” on panic porn. They long for millions and millions of deaths.
After you, chum. Your widow will benefit greatly from your absence.
Compare the deaths per 1 million for Italy with that for the US. Then subtract the deaths from third world New York City to give a better national comparison. The two trajectories are not at all parallel.
Oh, it’s a conspiracy now is it?
No, mortality rates are incredibly hard to make accurate calculations for. For example, we still don’t really know the mortality rate of SARS.
Excellent, then the strategy is working. As you were.
Fine, but you can be the first to die to improve the performance of my investments.
In Italy actual rates are almost certainly 10 – 12x higher than recorded rates, in Germany they’re probably about 3x, in the US about 4x, in South Korea, Australia and New Zealand more like 1.1 – 1.5x.
But people have questioned the false positives while ignoring the false negatives.
First, that study that shows 50 to 85 more cases is questionable, as others have pointed out.
Second, seasonal flu’s CFR (case fatality rate) is “0.1%”, and actually I’ve seen it quoted as “less than 0.1%”. CFR is defined as deaths per diagnosed cases only. Flu has plenty of mild undiagnosed cases that people treat on their own at home and never get reported. So it’s actual death rate for all its cases is lower.
Social distancing and other measures should lower the R0 from well above 1 to a lower value. But how much lower, depends on how well these measures are observed. It needs to get below 1 for new cases to start dropping. If it’s only down to 1, you get a linear progression (constant new cases).
At least that’s how I understand it. I may be off on the R0 value where you go linear, but pretty sure there is such a value. And the R0 needs to be brought down below that.
And of course there is lag due to the incubation period; if you’re looking at a total, there’s contributions from several local curves with different timings and R0’s; and so on.
are undoubtedly at least 10x higher than recorded rates. BUT the mortality rate is accurate. What this means is the virus is a lot less lethal than we’ve been told
Early antibody tests are showing prevalence of COVID19 to be 50 to 85 times more than confirmed cases.
Official mortality rate for COVID19 is between 3 and 4%.
Influenza has a mortality rate of about 0.1%.
If the prevalence of COVID19 is indeed 50 to 85 times more than the confirmed cases then this means the death rate is actually between 0.04 and 0.06%.
Is that type of mortality rate worth ruining the world for? Especially given the vast majority of people who have died have died due to co-morbidites and not the virus itself?
The percentages of actual and projected positives are small enough that the false positive rate is critical to knowing the value of this study.
But the paper claims to have adjusted for false positives based on the specificity they measured. Are you saying the test specificity is worse than what they measured?
They do discuss the impact of specificity being poorer, which I read as saying that if it is 97.9% or lower, their results may be meaningless.
I wonder if running the same test again on those testing positive would be useful. Would they just test positive again, or is the nature of the test such that errors are more or less random, and a second test would come up negative for most of the false positives?
It’s too soon to say this for sure – but so far it’s looking like ‘flattening the curve’ has actually just plateaued the curve of new cases in the US near the peak. I.e the ‘peak’ is looking too wide. Even states that went over a clear peak of new cases and declined seem to have leveled off well above zero.
This goes against the common idea that number of new cases should start to fall toward zero after hitting a peak.
It might be due to lag as some of the slower-starting states get up to speed. Or maybe the fall-off will have to wait for a vaccine or herd immunity. Or possibly there’s a counter-trend of new cases among “essential” workers?
I think you’re ignoring category 4.
Those who can’t (or won’t) learn so they end up being a burden on everyone else.
Here’s an important data point in that discussion.
Why has this post of mine not appeared?
Early antibody tests are showing prevalence of COVID19 to be 50 to 85 times more than confirmed cases:
https://www.weforum.org/agenda/2020/04/coronavirus-covid19-flu-influenza/
Official mortality rate for COVID19 is between 3 and 4%:
https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
Influenza has a mortality rate of about 0.1%.
If the prevalence of COVID19 is indeed 50 to 85 times more than the confirmed cases then this means the death rate is actually between 0.04 and 0.06%.
Is that type of mortality rate worth ruining the world for? Especially given the vast majority of people who have died have died due to co-morbidites and not the virus itself?
It might be a conspiracy against you or it could be you’re using a guest account to post links.
Why are posts not appearing
One way to check the impact of self-selection: they could do a follow-up poll of test participants asking “Did the results of your test validate or invalidate a prior suspicion on your part that you might have had COVID19? If so, what symptoms did you previously see?
Not perfect, but it’d give some idea of the impact of self-selection.
They reported specificity rates of 99.5% and 100%, which is the “True Negative” rate, which seems to imply very small false positives.
One of their sensitivity rates (“True Positive”) was only 67% (other was 96.6%), which could allow for a fair number of false negatives. The large difference in those tests does seem to indicate a possible problem in their test kit validation plan.
Am I mis-interpreting something? It seems to me that if the (Stanford) authors are competent, they would not have published if their false positive rate was high enough to invalidate their results.
The self-selection issue is perhaps another matter. I.e. what if people signed up because they thought they might have had a mild form of COVID19 and wanted to verify it. To their credit, they do mention that possibility in the paper.
We may have to adapt the way we work and learn because of the virus. We will have to increase the percentage of people who work and learn from home.
Who told you this is over? This will go on until there is an effective treatment or a cure. My guess it that people will be dying next year this time. And maybe even the following year, this time.
The US epidemic is not one epidemic. It is thousands. Each disjointed geographic area is having its own epidemic. Don’t let the flattening curve fool you in thinking this will soon be over because it won’t.
There are three kinds of people in the world. Them who learn by suffering, them who learn by seeing others suffer and them who can’t learn so they die out.
What a disaster these politicians with their gestapo lockdowns are creating. Nazi cheerleaders egg them on. Shame.
Right. Let’s make the economic disaster even worse. More will already die of the economic fallout than would have succumbed to a virus with a IFR of 0.1%, as indicated by Stanford researchers.
You can’t assume that 700,000 positive tests were all clinical cases, they were not.
But the study you sight is wrong anyway, the countries that have done lots of testing and gotten the disease under control don’t find 50x or 85x asymptomatic rates of Covid – 19, more like 2x – 5x, same range as the Diamond Princess.
“Most <i>industrialized countries</i> are past the peak”
Ahh, there’s the rub, what about the rest of the world?
It was an online opt in study, not randomized. Definitely good news but needs to be understood for what it is. I can easily accept a 10x multiplier, maybe even 20x but 85x in society is pushing it.
A 85x multiplier would imply that 17 million New Yorkers have contracted the virus out of a population of 19.5 million. I’m doubtful that we are that lucky.
Ah, yes, let’s compare total deaths of the multi-year swine flu to a (for most of the world) few month old coronavirus. The logic is impeccable.
I laugh and I downvote. Let’s not celebrate partisan deaths even in jest.
Just saying
So few words, so true:
“…The aged: lovely in theory, disposable in fact..”
discuss.
The Stanford data need to be confirmed by other large-scale serological studies in other countries… Anyway, even with an x85 ratio between clinical cases and total of infected, only 3% of population has developed antibodies.
If the 50x claim was accurate about 100% of the people living in NYC would already be infected. A recently released NYC study on pregnant women found actual rates that suggested asymptomatic rates were nothing like at that level, but perhaps 10x the symptomatic rate, though with uncertainties because not a random sample.
https://www.nbcnewyork.com/news/local/nyc-hospital-finds-high-covid-19-infection-rate-but-few-symptoms-in-pregnant-women/2372863/
Congrats… all the lockdowns have converted exponential growth Y=A e^kx Into linear growth…. y=Mx+b….the only problem is that the slope of the linear growth is very steep..
The conclusions of that non-peer-reviewed paper have a lot of uncertainties: The antibody tests have been shown to be unreliable and given the low incidence of Covid-19 in the Santa Clara it would have only taken a 1.5% rate of false positives to take to detected rate of anti-bodies in the sample population from zero to the 1.5% rate seen.
There are several problems with that study — self-selected sample (hence not random), and the false positive rate of the test used was comparable to the positive rate they reported, so the actual rate of people who had antibodies could easily be much, much lower than reported.
There are lots of questionable points to that recent antibody test done in Santa Clara County, California, which is what I imagine you are referring to. 1: The people tested were self-selected (the testing team posted an ad on Facebook to recruit the people to be tested). 2: The test they used has a known false-positive rate of approximately the same rate of the positive results they reported, so the actual percent of people tested that actually had antibodies could be much, much lower than what they reported.
So the results are somewhat interesting, but don’t draw very much of a good feeling from them unless further testing that can be better relied on gives similar results.
me to it.
Early antibody tests are showing prevalence of COVID19 to be 50 to 85 times more than confirmed cases:
https://www.weforum.org/agenda/2020/04/coronavirus-covid19-flu-influenza/
Official mortality rate for COVID19 is between 3 and 4%:
https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
Influenza has a mortality rate of about 0.1%.
If the prevalence of COVID19 is indeed 50 to 85 times more than the confirmed cases then this means the death rate is actually between 0.04 and 0.06%.
Is that type of mortality rate worth ruining the world for? Especially given the vast majority of people who have died have died due to co-morbidites and not the virus itself?
Here’s one. It’s a preprint publication, not yet peer reviewed.
https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
https://www.nature.com/articles/d41586-020-01095-0
That’s really interesting. Could you provide a link?
Interesting. Link?
Please
This means go slow on restarting the economy.
Even if effective treatments are developed they still have be useful at the start of the infection to lower it’s severity and not something just saves people once hospitalized. The reason is that we would still run the risk of overloading the hospital system.
This could lower the death rate to put it on par with the more acceptable yearly rates(12k-80k) for flu.
If you wanted millions dead, you should have convinced the world to follow your preferred path to maximize death by doing nothing, which would allow uncontrolled spread and overwhelm the medical system.
The poorly educated always find it difficult to believe one can mitigate negative results by taking mitigating actions, actions have consequences. How defective must a mind be to expect shutting down non-essential business, working from home, PPE, social distancing etc, should have no effect on outcomes.