Posted on 04/17/2020 5:40:53 PM PDT by absalom01
Just saw on Ingraham Angle....
NYC has a higher death rate than any other COUNTRY, per capita.
NYC Pop. 8.4M Cases 124,146 Deaths 8,632 Deaths/100K 102
India Pop 1.4B Cases 13,835 Deaths 452 Deaths/100K .03
This seems to be a running theme with Communists.
A Los Alamos report puts the Ro at 5.7 versus a figure less than half that. Need 82% for herd to kick in.
Sh*t happens when you keep taking the subways.
Agree!!
The subways should’ve been shut down WEEKS ago.
And, DeBlob took forever to close schools.
Big time. Dropping this crap way down into the flu or below range.
We’ve been lied to by the fear-mongers the entire time.
Yes we have AND I knew from the beginning it would turn out this way!!
No, it’s somewhere between 5-15%.
Significant, but no herd immunity at that level.
Well Los Alomos should know about modeling chain reactions...
And moderation.
The only way to really analyse this is to compare yearly averages. People who might have died later this year might be taken earlier by the virus.
Don’t forget that Fauxcy’s NIH was paying the Wuhan Lab ~$3 million per year.
Most US Counties have yugely overachieved.
If we could actually shut the borders to personal travel, we could snuff it out.
Almost as useful as Fake News talking about "anonymous sources"...until more long-term data is available...the continued testing and antibody testing will give actual data...this "study" had almost zero to work with...because we have just started garnering the devices required for such a study to have a chance of having any meaning.
I have been wondering about that. A recent bout of the common cold *could* provide some protection against Covid-19. Or it could contribute to the serious cases.
With influenza, infection with one strain of virus can provide partial protection against another similar strain. This is why, even if the flu shot does not prevent you from getting the flu, your illness will be less severe than if you had not been vaccinated.
But with some other diseases, like dengue, a recent infection with one strain can make an infection with a second strain of dengue extremely serious and even fatal, due to the way the antibodies, the virus, and the immune system interact. This is why vaccine development for dengue has been such a challenge. (Protect yourself from mosquitoes if you travel overseas.)
Yes, that may very well be the case. The study authors included no controls of people who have had the common cold (preferably confirmed to be caused by a coronavirus), which are needed to show that positive results are, indeed, Covid-19. Given the cross-reactivity that most antibodies exhibit and the similarity of all coronaviruses, I am not at all convinced that they were specifically measuring Covid-19 antibodies.
Several years ago, I took a cat to an emergency hospital and the attending vet ordered an FIP test for the cat. FIP is a coronavirus that causes fatal disease in cats. The test came back positive, but based on the clinical symptoms, the vet said that she was "not impressed" and did not diagnose the cat with FIP. (The cat had a severe immune disease that caused massive blood clotting and low blood cell counts. Miraculously, she recovered and lived another 9 years.) The FIP test was, in fact, approved by the FDA for clinical use, meaning that it met certain standards of specificity and sensitivity. Given that the FDA approved test can give false positives, I am not at all convinced that a research grade kit that has not been validated is accurate.
I can’t get into this article on this computer. But, I see some misinterpretation here. “On the order of about 5%” is a VERY hazy estimate, ie., a 10:1 range. And even that’s prefaced with “may”. The tweet is next to meaningless.
The sampling itself is supposed to reflect the entire population. How does the tweeter get from actual data(!) in a hotspot(!) of 2.49-4.16% infected to 5% nationally? When a hotspot is surely going to be considerably higher than the general population? By being very sloppy, that’s how. Then the article author confuses the number of diagnosed, which is not taken from the general population.
OTOH, COVID-19 is clearly contagious enough that eventually much of the population will be infected, barring a good vaccine. Whether lasting immunity is conferred is uncertain. I have serious doubts about it for mild and asymptomatic cases.
In truth, the number of infections is at this point less important than the rate of hospitalizations. Even for “just the flu”, getting hospitalized gets one into fairly grim CFR (HCFR) numbers. It’s pretty clear that had NYC locked down a week later, it would have had a healthcare system disaster, even with all the Federal help that could be brought to bear.
as 8 understand it all the detection kits key on a spike that is specific to covid 19. if this had wide crossreactivity to other corona viruses I would expect the positive rate to be near 100%. We have all had colds
TY
As far as I can tell from the paper, the immunoassay detects both IgG and IgM antibodies. The first immune response after infection is the IgM, which spikes quickly and soon falls off. So any test that picks up IgM is only detecting recent infection. The IgG response is slower, with a longer delay until it spikes and a longer drop off. I do not know specifically how long the antibody titer remains elevated after a cold infection, but seriously doubt that the titer a year or more after is going to be even close to the convalescent titer. So, depending on the reaction conditions, the kit they used might not pick up antibodies to a coronavirus infection from previous cold seasons. So, the “pre-COVID” sera might very well fall below the limit of detection (or whatever cut-off the study authors selected). The bottom line is that the kit is suited to detecting recent infections.
Yes, we have all had colds. But the ones caused by coronavirus are a small subset of those colds, and not everyone gets a cold every year. (I get one about every 5-10 years.)
Another piece of evidence that the test may be detecting recent infection with coronavirus, not specifically Covid-19, is the infection rate. To believe that the real number of Covid-19 infections is 85 fold greater than the actual case count is to believe that Covid-19 is orders of magnitude more infectious than any other respiratory virus. I am highly skeptical of such findings.
I think the Stanford paper has a high chance of being published because of the subject matter, but if I were one of its peer-reviewers, I’d send it back with recommendations for major revision and further study. Study, as in including controls who have recently had common colds caused by ordinary coronaviruses. I want to see the data on cross-reactivity of the test.
I am well aware of the difference between IgM and IgG.
I think the data matches with what we all expect. You can dive into the specifics of their assays and that might answer your question The real problem has been false negatives which are running 20-30% not false positives. You could ask for the cross reaction studies later but I think it is important people understand this illness is far more prevalent than most think.
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