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A flawed #coronavirus antibody study in Santa Clara California estimates:
1. Infections are under-reported 50 to 85-fold
2. 2.49% to 4.16% of the population is infected
3. The #covid19 death rate is 0.12-0.2%:
Here's why their numbers don't hold up: https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
1. Infections are under-reported 50 to 85-fold
2. 2.49% to 4.16% of the population is infected
3. The #covid19 death rate is 0.12-0.2%:
Here's why their numbers don't hold up: https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1
1. As of 4/17 NY state, population 19,440,469, has reported 226,198 cases.
At 50-fold under reporting implies 11,309,900 NY #coronavirus cases.
At 85-fold under reporting implies 19,226,830 NY #covid19 cases.
Respectively, 58% and 99% of the population.
Neither are likely.
At 50-fold under reporting implies 11,309,900 NY #coronavirus cases.
At 85-fold under reporting implies 19,226,830 NY #covid19 cases.
Respectively, 58% and 99% of the population.
Neither are likely.
2. An infection rate of 2.49% to 4.16% implies between 484,067 and 808,723 NY cases, both plausible.
However, NY currently has 16,736 #covid19 deaths and those counts imply a #coronavirus death rate of between 2.06% and 3.45% which is 10 to 28 times higher than the study.
However, NY currently has 16,736 #covid19 deaths and those counts imply a #coronavirus death rate of between 2.06% and 3.45% which is 10 to 28 times higher than the study.
3. With 16,736 #covid19 deaths and counting a 0.12% death rate implies 13,946,667 infections - 72% of NY's population.
A 0.2% death implies 8,368,000 infections or 43% of NY's population and nearly the entire population of NYC.
Infection rates of 43% to 72% are not plausible.
A 0.2% death implies 8,368,000 infections or 43% of NY's population and nearly the entire population of NYC.
Infection rates of 43% to 72% are not plausible.
4. NYC, population of 8,550,971, has reported 12,941 deaths.
That’s 0.15% of NYC’s total population and rules out the lower bound death rate of .12%.
The upper bound death rate of .2%, with an impossible 100% infection rate, allows for 17,101 deaths which NYC will surpass soon.
That’s 0.15% of NYC’s total population and rules out the lower bound death rate of .12%.
The upper bound death rate of .2%, with an impossible 100% infection rate, allows for 17,101 deaths which NYC will surpass soon.
5. The study itself admits uncertainty about the tests noting the estimate of the population infected could drop to under 1%:
"If new estimates indicate test specificity to be less than 97.9%, our SARS-CoV-2 prevalence estimate would change from 2.8% to less than 1%"
"If new estimates indicate test specificity to be less than 97.9%, our SARS-CoV-2 prevalence estimate would change from 2.8% to less than 1%"
6. The study also noted known issues with false negatives and false positives:
"Among 37 samples of known PCR-positive COVID-19 patients with positive IgG or IgM detected on a locally-developed ELISA test, 25 were kit-positive"
"Among 37 samples of known PCR-positive COVID-19 patients with positive IgG or IgM detected on a locally-developed ELISA test, 25 were kit-positive"
7. More noted issues with false negatives and false positives:
"Among 75 samples of clinically confirmed COVID-19
patients with positive IgG, 75 were kit-positive, and among 85 samples with positive IgM, 78 were kitpositive. Among 371 pre-COVID samples, 369 were negative.
"Among 75 samples of clinically confirmed COVID-19
patients with positive IgG, 75 were kit-positive, and among 85 samples with positive IgM, 78 were kitpositive. Among 371 pre-COVID samples, 369 were negative.
8. The study itself only found 50 positive antibody tests out of 3,330 total people tested, a crude prevalence of 1.5% of subjects infected.
The 1.5% was then "statistically" adjusted to fit racial and geographic demography arriving at the estimated 2.49% and 4.16% infected.
The 1.5% was then "statistically" adjusted to fit racial and geographic demography arriving at the estimated 2.49% and 4.16% infected.
9. NYC currently has 131,263 confirmed cases and if the true infection rate there is 85 times higher, that's 11,157,355 million people.
If the death rate is 0.12%, 10,964,166 would need to be infected.
NYC only has 8.5 million people, so both study bounds are impossible.
If the death rate is 0.12%, 10,964,166 would need to be infected.
NYC only has 8.5 million people, so both study bounds are impossible.
10. The study estimates 2.5%-4.2% of people are infected with #COVID19.
4.2% of NYC's 8,550,971 population is 359,140 and with 13,157 current deaths that's a lower bound death rate of 3.66%.
2.5% is 213,774 infections and a 6.15% death rate.
Both exceed the .12%-.2% bounds.
4.2% of NYC's 8,550,971 population is 359,140 and with 13,157 current deaths that's a lower bound death rate of 3.66%.
2.5% is 213,774 infections and a 6.15% death rate.
Both exceed the .12%-.2% bounds.
11. For New York State:
2.5% of the population infected is 484,067 infections, and and with 13,157 current deaths that's a 2.72% death rate.
4.16% infected is 808,723 infections and a 1.63% death rate.
These infection rates are plausible but the death rates exceed the study.
2.5% of the population infected is 484,067 infections, and and with 13,157 current deaths that's a 2.72% death rate.
4.16% infected is 808,723 infections and a 1.63% death rate.
These infection rates are plausible but the death rates exceed the study.
12. The Santa Clara #coronavirus study is already being criticized in the scientific community. It will not pass peer review.
Nature, the leading international weekly journal of science, notes a large not of positive results may have been false positives. https://www.nature.com/articles/d41586-020-01095-0
Nature, the leading international weekly journal of science, notes a large not of positive results may have been false positives. https://www.nature.com/articles/d41586-020-01095-0
13. Santa Clara's #COVID19 antibody control test had a 0.54% false postive rate (2 of 371 known negative #CoronaVirus samples).
The study tested 3,330 people.
0.54% of the total implies 18 false positives.
50 people in the study were positive.
That's a 36% false postive rate.
The study tested 3,330 people.
0.54% of the total implies 18 false positives.
50 people in the study were positive.
That's a 36% false postive rate.
