I get it that San Francisco got extra credit for saving the whales and a gold star for Nancy Pelosi's beautiful hairdo, so the
actual scientific transmission rate of 2.5 was graded on a curve and given a San Francisco score of 1.5
But that doesn't explain how they turned the revised
1.5 score into a
0.9 score that is required for the
Yellow Tier.
The Yellow Tier was always stated as needing to be "Less Than One", and that language is still clearly stated on the state website that San Francisco was graded by. 1.5 is more than 1.0
0.9 is less than 1.0, what am I missing there? Besides saving the whales, of course.
covid19.ca.gov
Let me take a stab at it because the underlying documentation is truly dense and their spreadsheet only shows values and no formulas:
A) Take the Positivity Rate and the number of COVID Cases per 100,000 people from two weeks ago.
- stats from from two weeks ago because of delays of reporting... the past week's numbers are constantly changing and are usually under-reported
- this applies to a city or county... which I'll call a 'district' from here on out.
So, let's walk through the situation of these three districts whose numbers this week are...
District (County/City) | Positivity % | Cases per 100,00 |
---|
Los Angeles | 3.4 "orange" | 10.1 "purple" |
Orange | 3.2 "orange" | 4.6 "red" |
San Francisco | 0.8 "yellow" | 2.5 "orange" |
B) Now, apply a modifier to the Cases/100k People (last column). Here's how...
This modifier depends on total number of tests that the district administers per 100k people.
- Don't get this number confused with Cases/100k people, which is the absolute number of those who've tested positive. We're talking instead about the total number of tests administered whether positive or negative.
The number of tests is a "median" (i.e., an "average") of the previous week. So, going back two weeks, you average out the number of tests per day administered that week and divide by 100k people. This is the district's "median testing" stat.
You take the district's median number of tests/100k and compare it to California State's median number of tests/100k.
If your district has been doing more testing than the state median, then your "Cases of COVID per 100,000" number can get adjusted down.
An adjustment reduction is given for having a district median anywhere up to two times the state median of testing. Within that range, the higher your testing, the more your Cases per 100k gets reduced to a maximum of 60% of the unadjusted figure.
So, let's look at the current stats: The California state median of testing for COVID is about 240 tests per 100,000 people for the whole state over the prior week.
- Los Angeles has a testing rate per 100k of 386 which reduces its Cases/100k [which is 10.1] to 75% of its unadjusted value [which becomes 7.6].
- San Francisco has a testing rate of 596 and its Cases/100k [which is 2.5] is adjusted down to 60% of its value [which becomes 1.5]
- Orange has a testing rate of 218. Uh oh... that's *less* than the median. That could mean its testing rate [of 4.6] can be adjusted *up*!!
However, if a district has a Positivity Rate that is under 3.5% [Orange County's positivity is 3.2%], then it gets off on good behavior and it doesn't get its Cases/100k inflated. And thus, no adjustment to Orange's Cases [stays at 4.6].
The new standings after adjustments:
County | Positivity % | Cases per 100,00 |
---|
Los Angeles | 3.4 "orange" | 7.6 "purple" |
Orange | 3.2 "orange" | 4.6 "red" |
San Francisco | 0.8 "yellow" | 1.5 "orange" |
C) Next comes the "Equity Adjustment."
The state doesn't want counties to avoid providing testing and caring for its poorest or disenfranchised members. And so, there is a really complicated way to determine what parts of the district are in the 'lowest quartile' (lowest 25% bracket) and to make sure these two things happen:
- The most depressed parts of the district have Positivity Rates that are close to that of the rest of the county.
- The most depressed parts of the district have targeted health care plans.
In order to progress to a better tier the difference between the the lowest quartile and the rest of the district needs to be minimized.
So, not caring for the lowest quartile can hold you back, however, caring for the lowest quartile can have rewards!! For even though your district's case rate (per 100k) may not qualify for the next lower tier, if both the district as a whole, and it's lowest quartile's *positivity* qualify for the next tier then the district can move into the next tier.
And this kinda makes sense because if you let the virus run rampant in depressed areas (where all your minimum wage employees live), it won't just stay there when they go to work in the wealthier part of the district.
Conclusion: And that's why San Francisco is in the Yellow Tier even though their Cases/100k is still in Orange. That's because both the whole district's Positivity and their lowest quartile's Positivity are in Yellow (plus all the work they did to show they have targeted health care plans for the lowest quartile).
County | Positivity % | Equity Positivity % | Cases per 100,00 |
---|
Los Angeles | 3.4 "orange" | 5.9 "red" | 7.6 "purple" |
Orange | 3.2 "orange" | 5.6 "red" | 4.6 "red" |
San Francisco | 0.8 "yellow" | 1.5 "yellow" | 1.5 "orange" |