The @CDCgov page currently claims 11M people have initiated COVID-19 vaccination, but the underlying data suggests that it's actually 11M *doses*.
This is quite misleading, and I hope this error is corrected ASAP.
I took some time to correct for this myself. Our vaccination page now breaks down administered doses into 1st & 2nd doses: covid19-projections.com/path-to-herd-i…
According to our estimates, 10M people (not 11.1M) have received at least one dose. Out of those 9M, 1.1M have received both doses.
After this adjustment, the current pace of new vaccinations is ~4M people per week. Even if we double that pace, it would take 9 months to vaccinate everyone.
As of now, ~15% of the daily doses given are used as a 2nd dose (114k / 747k). I expect this fraction to grow over time.
So to summarize, 34 days after the vaccine was first approved for emergency use, approximately 1.1 million people in the US, or 0.3% of the population, have received the two doses required for maximum efficacy.
We have a long way to go.
Update: The error has been fixed!
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For example, states like Florida and New York are quickly vaccinating more people than new infections, while states like California and Georgia are still lagging behind.
See my short thread from yesterday for more vaccination data + projections.
Are high levels of existing COVID-19 population immunity in US counties associated with a lower infection rate in this current wave?
This thread contains my latest findings to this question.
Initial conclusion: No, there is practically no correlation.
The plot above shows the the percentage of the population infected before Sep 1 & after Sep 1 in each county (based on covid19-projections.com estimates).
The question is: can knowing the % infected before Sep 1 in a county predict the relative severity of this current wave?
When looking at all 3,000+ counties, the answer is no. There is practically no correlation (R^2 = 0.002) between the % infected before Sep 1 and after Sep 1.
So given a county, the COVID-19 prevalence before Sep 1 has no predictive value in determining the severity since Sep 1.
A lot of people have asked why the CDC estimates close to 100M total US COVID-19 infections (28%) by Dec 1, while covid19-projections.com only estimates 58M (17%).
I believe there are major flaws in the CDC estimates, which I will explain in this thread.
To begin, the covid19-projections.com model is tuned on serology surveys, while the CDC model is not.
While CDC estimates 7x more COVID-19 infections than reported, covid19-projections.com estimates this ratio to currently be ~3x, down from 10x in April and 4x in the summer.
Using the CDC claim that "1 in 7 total infections were reported", this would imply that 70% of North & South Dakota were infected, which doesn't pass a common sense test.
While a 7x multiplier is believable in the spring, the paper still claims this is the case in September.
Many people are unaware that the COVID-19 vaccine has significantly more side effects than the flu vaccine. I hope to see more honest discussions regarding this.
Props to @Cat_Ho for her realistic, data-centric reporting of this issue. It's much needed.