A month ago, I reported on @CDCgov's overestimate of true infections in the US.
It appears that last week, the CDC significantly lowered their estimates. It now closely matches covid19-projections.com's latest estimate of ~83M infected (~25% of the population).
My thread from last month is below, where I highlight the flaws in the CDC's original estimates (91M infections through November 2020 and a 7:1 infections to case ratio).
"Since the previous update, CDC has received additional data about the proportion of persons with symptomatic illness who seek [..] testing services. The higher values of health-seeking behavior result in lower estimates of infections"
Jan 20 Weekly Update: New vaccinations (750k/day) are still increasing, but at a slower pace. 1st doses saw a 30% increase over last week, compared to 76% increase the week before.
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.
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.