Let's talk Junes. Short thread.

June 2020. Pandemic was still new and chaotic. Here in California, our first big wave was brewing (would peak in July). We didn't have the devastaion in March/April that NY etc. had had.

We were hoping for seasonality, but no... summer wave.
cont'd

So, in June 2020, we didn't know that much. There were diverging opinions about whether the fall would bring more and when the wave(s) would peak.



June 2021. California has low community transmission; very low. Statewide color-coded tier system is scrapped.
cont'd

This past June, we ditched masks, "opened up the economy". Etc., etc.

Well, good vibes didn't last long. Here we are.



June 2022. I think by then we'll have sense of where we stand.Boosters, winter waves, variants, natural immunity, we will have better persepective.
cont'd

William Westmoreland famously kept asking for just a few more thousand troops to win the Vietnam War.

Perhaps similarly, epidemiologists probably overpromise that with a little more data, we can perfect the models. With a little more perspective, we'll understand better.
cont'd

I do think, however, that by June 2022 we'll have a sense of whats-what. Some new variant won't blindside us like Delta did in June 2021 (albeit should not have).

On the other hand: Between now and June 2022, TBPH, there are a lot of questions.
to clarify: "Some new variant won't blindside us like Delta did in June 2021"...

... I mean, we should now steel for variant roulette. We have no excuses anymore.

Fool us twice, shame on us...



Will we actually be alloyed and ready for the next variant? Sigh, probably not.

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More from @AndrewNoymer

29 Apr
Thread on why mRNA vaccines may be giving better immunity vs. SARS-CoV-2 than surviving natural infection.

disclaimer: we still don't understand the long-term correctness of the claim that vaccines are better protection than natural infection.

TL;DR: it's different kind of vax
In this thread I will offer some speculation as to why it's scientifically plausible that the vaccines offer better protection than surviving natural infection.

This is what it is, speculation.

As I said in the parent tweet, it remains to be seen how true this phenomenon is.
cont'd

But if it is true, I don't think it defies logic. And here I will explain why.
Read 15 tweets
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...
... 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.
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...
Read 6 tweets
28 Mar
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.
Read 4 tweets
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
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
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

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