Another 'expert' that hopes you don't realize surgical masks are not respiratory protection. Yes, they are meant to keep patients protected against coughs, sneezes, large droplets, bacteria, etc. They are absolutely not nor have they ever been respiratory protection vs. viruses.
Just to keep reminding people, below is a graph from the CDC in early 2020, which I believe can still be found on their site.
"Does NOT provide the wearer with a reliable level of protection from inhaling smaller airborne particles and is not considered respiratory protection."
SARS-CoV-2, the virus that causes COVID-19, is a "small airborne particle."
The average particle, 0.1 microns, is 97% smaller than the standard surgical mask pore (3 microns).
The good doctor @eliowa apparently doesn't like my calling him out on the truth, so he blocked me. Sorry the truth hurts.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
The idea that omicron is much more mild is no longer in question. The evidence has been overwhelming showing 70-90% reduction in severe illness and mortality.
Through Dec. 31, UKHSA had recorded just 75 deaths among 212,019 omicron cases (0.04% fatality rate). They have since discontinued omicron surveillance.
A tale of two groups of cities: the ones people are flying to visit and the ones they're not.
Rate of change in destination enplanements for airports of at least 100,000 enplanements in 2019 in Florida, Texas, California, and New York for Jan-Oct 2021 vs. same months 2019.
What you're seeing is that 7 of these 60 airports are higher in the first 10 months of 2021 than they were in the same months in 2019... all 7 of which were in Florida. Florida (red) and Texas (orange) make up most of the upper half.
Collectively, Florida airports are 10.6% lower in 2021 through October than they were in 2019. Texas -21.3%, California -41.3% and New York -46.3%. The national total is down 28.2%.
Best kickers in the NFL this year with ≥10 makes by net expected probability ratio. Expected accuracy is 3YD rolling averages for all NFL attempts from 2010-19. Formula is total makes / net probability * 100.
1) J. Tucker 2) D. Carlson 3) R. Patterson
4 E. McPherson 5) Y. Koo
This is regular season only. If I add in playoff kicks, McPherson is up to No. 3.
COVID-19 mortality rates are very much in line with overall, all-cause mortality rates by state with only a few major outliers, which appear to be seasonal and regional.
Here is a ratio of COVID-19 per capita deaths to 2019 all-cause per capita mortality grouped by BEA regions.
The formula is COVID-19 mortality, as measured by COVID-19 deaths in the Jan. 26 CDC update of provisional COVID-19 deaths by sex and age, divided by 2020 population estimates, multiplied by a factor of 3.3 to match 2019 all-cause mortality, divided by 2019 all-cause death rates.
In this chart, the ratio is multiplied by 100. So a 1.00 (or 100) means the ratio of COVID-19 deaths is perfectly in line with the rate of mortality for all causes in 2019.
Extreme geographic locations in the NE/NW are clear outliers, as are ones in the SW/border states.
If you are someone that is dealing with COVID-19 mortality and you are not adjusting for age, you should not be in the business of COVID analysis.
Age-adjustments are expected when comparing rates across different jurisdictions. It's standard practice for mortality analysis.
Case in point: in 2019, California (682.9 deaths per 1 million) had a per capita all-cause mortality rate that was 29% lower than Florida did (963.8). This is due to age, mostly, and a few other confounding variables.
But people treat unadjusted COVID death rates as a level comp
Bottom line is even before COVID, there are vast differences in death rates among states due to age and other risk factors.
People that use unadjusted mortality because of political narratives are dishonest analysts.
Today, 6,164 hospitals reported inpatient data to HHS. Yesterday, a total of 6,172 hospitals reported inpatient data. There was a difference in only eight (8) total hospitals.
Something else to know about HHS reporting: if HHS does not receive a report from a facility, they use the most recent data reported within the past four days. So if a facility has 10 patients and doesn't report the next day, HHS doesn't count that as 0, they count it as 10.
So what the 'doctor' is saying is blatantly wrong anyhow. Even if a facility didn't report, it would default to the most recent report rather than zero. So you're not going to see a drop unless they actually report a lower number.