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28 Mar, 4 tweets, 1 min read
CALIFORNIA UPDATE.

Counties.

Covid deaths per million residents; minimum 100 covid deaths:

Imperial 3,916
Los Angeles 2,284
San Bernardino 1,815
Stanislaus 1,804
Tulare 1,745
Riverside 1,733
San Joaquin 1,661
Fresno 1,610
Kings 1,592
Merced 1,580

continues...
California counties, covid deaths per million population

continued:

Orange 1,479
Madera 1,465
Kern 1,350
Ventura 1,139
Shasta 1,122
Sutter 1,074
San Diego 1,059
Sacramento 1,038
Santa Clara 998
Santa Barbara 983

continues...
California counties, covid deaths per million population

continued:

San Luis Obispo 898
Yolo 889
Marin 851
Alameda 837
Butte 826
Monterey 781
Santa Cruz 733
San Mateo 711
Placer 669
Contra Costa 662
Sonoma 620
El Dorado 561
San Francisco 534
Solano 428.
Notes for this update:

— These 34 counties account for 98% of all covid deaths in California;

— New this update (surpassing 100 deaths for the first time): Sutter County;

— Exceeding 1,000/million for the first time in this update: Shasta, San Diego, Sacramento counties.

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More from @AndrewNoymer

Andrew Noymer Profile picture
28 Mar
Regional covid epidemiology in the US of A.

A short 🧵.

Living in California, I have been increasingly optimisitc of late. Pic related.

But... Image
... continued

But, New York and New Jersey, OTOH, are giving me the heeby jeebies...

... my thinking *before* this pandemic was that the next pandemic would see rapid spread, leading to regions being in phase with one another. Ex., there has not been a ground-stop of aviation. ImageImage
continued...

And it's not just the northeast. Here's Michigan:

Clearly, the US of A remains a country with epidemics, plural, playing out at least with different timing in different regions.

continues... Image
Read 5 tweets
Andrew Noymer Profile picture
10 Feb
CALIFORNIA. Update.

Counties. Covid-19 deaths per M population (minimum 100 deaths):

Imperial 3,151
Los Angeles 1,817
Stanislaus 1,590
Tulare 1,419
Riverside 1,393
Merced 1,336
Fresno 1,265
San Joaquin 1,234
Madera 1,199
Kings 1,169
Orange 1,072

continues...
California. Counties, cont'd

San Bernardino 1,006
Shasta 911
Sacramento 877
San Diego 853
Santa Clara 813
Ventura 803
Santa Barbara 779
Yolo 771
Kern 740
Marin 697
Monterey 668
Butte 640
Alameda 631
San Luis Obispo 627
Santa Cruz 583
San Mateo 581

continues...
California. Counties, cont'd

Sonoma 554
Placer 549
Contra Costa 499
San Francisco 392
Solano 313.

These 32 counties, with at least 100 deaths per county, account for 98% of recorded Covid-19 mortality in the pandemic to date.

Continues...
Read 4 tweets
Andrew Noymer Profile picture
13 Dec 20
Remember this 👇🏻 chart?

I received request for a breakdown by age groups.

I forget who it was; sorry.

Well, ask and ye shall (sometimes) receive.

*THREAD*: All-cause mortality, weeks 1 thru 35 (early Sept). 2015–20, BY AGE, w/trend-line and 95% prediction interval.
Here is ages 0–24 (L) and 25–44 (R).

Deaths and 95% prediction interval. Input data from @NCHStats.
Here is ages 45–64 (L) and 65–74 (R).

Deaths and 95% prediction interval. Input data from @NCHStats.
Read 5 tweets
Andrew Noymer Profile picture
19 Oct 20
#minimodel (👇🏻) guesstimate of Covid-19 infection fatality rate is less than 0.3%, which is in the same ballpark as IFR of flu (0.1%, also an estimate).

In this THREAD, I will explain how this fact has been misconstrued/misused to mean Covid-19 pandemic is a nothingburger.
I'm thinking here of crowd jumping up+down "see! the IFR is same as flu!!!".

Covid-19 IFR is indeed around that of flu. I don't say "low", since everything relative. IFRs are in the same ballpark.

But C-19 will kill far more people in the same time period than flu.

continues
We already see Covid-19 has killed 225,000 in USA, far more than flu. Comparing IFRs is not the right move here (and has never been — see the breakdown of the #minimodel).

Despite similar IFRs, C-19 will kill far more people than flu, because it will infect far more.

continues
Read 9 tweets
Andrew Noymer Profile picture
19 Oct 20
Friends, as you know I've advocated #masks for long time. Certainly longer thn @CDCgov & people at my... place of employment.

Qualitatively, I believe they work. How much they protect is hard to quantify, however.

Today, saw something thought provoking in this vein.

continues:
Anti-masker in inbox wondered what we say in a year, when (in his words/imagination of future), consensus changes against masks.

If can't quantify good masks do, how we know benefit isn't marginal?

Valid question, but #PrecautionaryPrinciple says not to play no-mask roulette.
I was here when they said it was nothing.

~ when... it was no worse than flu.

~ when... it would "only" kill 100,000.

The latest is that "masks won't stop it". It *is* hard to quantify #mask effect — but, I'm sorry but I can't endorse that.

I'm just not that kind of asshole.
Read 4 tweets
Andrew Noymer Profile picture
25 Sep 20
Let's talk about emerging C-19 narrative of "shield sensitive groups". Thread will be USA-centric; I live in US of A, so.

This is C-19 strategy emphasizing nursing homes/elderly, & a euphemism for everyone else to "[keep calm and] carry on".

It won't work. Especially in USA.
Why won't it work?

Where I live, Calif, 26% of C-19 mortality has been in people younger than 65, and 7% has been in people 18–49.

C-19 mortality in CA has been disproportionately felt by the Latinx population and elsewhere in the USA, Blacks have been in a similar position.
continued

The C-19 pandemic is overlaid on the United States' dilapidated public health infrastructure and its major health inequalities, particularly by race.

We can't just take the Swedish experience (which, on Twitter, is more fantasy than reality anyways), and copy+paste.
Read 4 tweets

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