So a quick š§µ with the new @CDCgov county measures. Unsurprisingly, not great news.
61% of the country lives in a high-level county, based on the hospitalization risk measure.
1/
Here's your updated map.
I'm used to saying whoa...Florida.
This week I said whoa...California.
2/
You can really see the rapid rise in the % of people living in high-risk areas in places like California, Illinois, Kentucky, West Virginia...and even a resurgence in NY and NJ. Other places have remained high.
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Compared to last week, 13% of people lived in counties that worsened in their level, compared to 6% of people who lived in a county that improved.
81% of people lived in a county whose risk level did not change.
4/
10 states now have 80% or more of their population living in high-risk counties, led by California (99%), Florida (98%), Hawaii (95%), New Jersey (91%), and Illinois (88%).
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More later when the transmission levels are updated for today.
I'll also update my dashboard then.
Thanks for the well-wishes. Fever of 100.9 at its highest, cough, fatigue, and typical man-complaining. Toddler is great, wife improving! #Blessed
1. Here's the more complete š§µ after the CDC update
My how things have changed in just weeks
On May 19, 17% of the US population lived in a "high" level, mostly in the northeast.
On June 30, 33% of the US population lived in a "high" level, almost everywhere but the northeast.
2. In my home state, during that 6 week time period, we went from "high" levels, based on CDC's hospitalization-based measure, in our 3 largest counties in the south
...to 99% of the population living in a county classified as a "high" level
3. Here's the current county-level snapshot of where we are today on the hospitalization-based measure with the less intimidating color scheme (left) to the original transmission-based measure (right)
1. It's been a while, but I finally added state-level #COVID19 vaccination data to my dashboard.
For a date you select, it allows you to query various milestones (primary series, 1st booster, 2nd booster) & age groups.
I also allow various denominators to be used.
Quick š§µ
2. Let's say you want the most current data on everyone 18 years and older in terms of receipt of their first booster.
Well, we can calculate the vax rate using the entire population 18+ š to get overall scope of getting first boosters in arms.
3. Or we can calculate the vax rate using the population 18+ WHO COMPLETED A PRIMARY SERIES š to assess how well we are doing in getting first boosters to those who at least came in to get that initial series.
Obviously this will be a higher rate that using the entire pop.
1. I'm still waiting for an update of the Community Transmission levels needed to run my typical risk levels analysis, but here's where we'll be with the hospital-based measures.
2. Here's how things have changed from last week.
Blue is improvement
Red is worsening
Gray is no change
3. Another way of looking at the change in levels from last week