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Atomsk's Sanakan Profile picture
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25 Nov, 4 tweets, 5 min read
It's almost 2021.
And I don't forget, even years later. 🙂



For analyzing global warming trends:
ysbl.york.ac.uk/~cowtan/applet…
psl.noaa.gov/cgi-bin/data/t…
climexp.knmi.nl/start.cgi

Judith Curry (@curryja), in 2016:
judithcurry.com/2016/03/06/end…
Someone will have a lot to answer for in 2021...

"I do receive some funding from the fossil fuel industry"
scientificamerican.com/article/climat…

"Politically I am independent, with libertarian leanings."
culturalcognition.net/blog/2014/8/19…



judithcurry.com/2011/10/27/can…
And for those wondering which dataset to use in assessing Curry's claims.



On the predicted warming trend Curry rejected:



"This [2001/2002] shift and the subsequent slight cooling trend provides a rationale for inferring a slight cooling trend over the next decade or so"
judithcurry.com/2013/06/14/wee…

archive.is/Gea0O#selectio…

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More from @AtomsksSanakan

Atomsk's Sanakan Profile picture
20 Nov
PaperOfTheDay

@GidMK @BillHanage

Gangelt, with:
- an IFR of ~0.4%
- 13.6% IgG+ (which they test-corrected to 14.1%)

"Infection fatality rate of SARS-CoV2 in a super-spreading event in Germany"
nature.com/articles/s4146…

However:

finddx.org/covid-19/dx-da…

medrxiv.org/content/10.110… Image
So the test correction based on FINDDx increases the Gangelt IFR by ~4, and/or renders Gangelt less relevant since corrected seroprevalence overlaps with 0%.

There are other cases in which using FINDDx decreases IFR. For example:



medrxiv.org/content/10.110… Image
Based on the above paper's FINDDx-based analysis, some of the worse offenders in terms of sensitivity (i.e. false negatives) at particular times post-infection are:

- 41%: Abbott Architect IgG
- 42%: Euroimmun IgG
- 57%: CTK Biotech IgG/IgM rapid test

Read 5 tweets
Atomsk's Sanakan Profile picture
8 Nov
1/S

Sweden did not lockdown in response to COVID-19. Many politically-motivated COVID-19 contrarians try to support Sweden's policy by making misleading comparisons between Sweden + other countries. This thread will address that.



2/S

On average, it takes a virus less time to spread thru + kill 50% of a population of 10 people vs. 50% of a population of 10,000 people.

So smaller populations have less time for public health changes, behavior changes, etc. to limit their COVID-19 deaths per capita.
3/S

Also, on average, it takes less time for a virus to spread thru a smaller geographical area.

So microstates' combination of smaller geographical area and smaller population make them a poor, apples-to-oranges comparison to Sweden.

ourworldindata.org/coronavirus-da…
Read 14 tweets
Atomsk's Sanakan Profile picture
4 Oct
1/C

A lot of COVID-19 contrarians abuse the idea of "cross-reactivity" to make SARS-CoV-2 (the virus that causes COVID-19) look less dangerous than it really is. Many of them do this to avoid policies they dislike, like lockdowns.

So let's get into that

2/C

Some basics:

Immune cells known as T cells and B cells have receptors that recognize viruses.

Think of the receptors as a lock, + portions of the virus as a key; i.e. the lock (receptor) binds to a specific key (virus region), + not to other keys

3/C

Even if you've never been infected with a virus, bacteria, etc., you almost certainly have T + B cells that recognize it.

When you're first infected, those cells (especially B cells) take a few days to increase in number (and activity) + generate their full immune response.
Read 20 tweets
Atomsk's Sanakan Profile picture
4 Oct
1/G

Interesting method from @GidMK and co-authors for calculating IFR from PCR-based cases.

(IFR is the proportion of SARS-CoV-2-infected people who die COVID-19;
PCR measures viral genetic material in people;
Cases are people who were infected)

medrxiv.org/content/medrxi…
2/G

The basic idea is that some countries had relatively few infected, and tested with PCR so thoroughly, that their PCR testing got a relatively large proportion of infected people.

Iceland is used a baseline example:

medrxiv.org/content/medrxi…
3/G

Their method yields a range of IFR values consistent with those from serology [i.e. antibody testing], which provides independent validation for their method.

green: their PCR-based methods
blue: Serology-based estimates

medrxiv.org/content/10.110…
Read 9 tweets
Atomsk's Sanakan Profile picture
27 Sep
1/C

The infection fatality rate (IFR) states what proportion of people infected with the virus SARS-CoV-2 die of the disease COVID-19.

Many COVID-19 contrarians abuse IFR estimates from the USA's Centers for Disease Control and Prevention.

So let's discuss those estimates. Image
2/C

For context:

Seasonal flu's IFR is <0.1%:


If 100 million people (less than 1/3 of the USA's pop.) get infected at an average IFR of 1%, that means 1 million COVID-19 deaths.

medrxiv.org/content/10.110…


medrxiv.org/content/10.110… Image
3/C

Round 1:

The CDC initially gave an IFR of 0.26%.

They gave no evidence for this, and their estimate was below that of published research.

So experts were annoyed:




usatoday.com/story/news/fac…

npr.org/sections/healt… Image
Read 8 tweets
Atomsk's Sanakan Profile picture
25 Sep
1/M

For months, COVID-19 contrarians spread misinformation about the immune system and COVID-19.
So I'll combine some rebuttal points I've made elsewhere, with a focus on T cells.





Image
2/M

An important concept here is 'herd immunity'.

In simplified terms:

The 'herd immunity threshold' is the number of people who need to be immune to infection, in order for 'infections per unit time' to stop increasing, at baseline.

medium.com/@silentn2040/t… Image
3/M

So for the graph below:
y-axis = # of new infections per day
x-axis = time

This is under 'baseline' conditions; i.e. people don't change their behavior in response to infection, + no further public health interventions (ex: lockdown).

At x = 10, the threshold was reached. Image
Read 15 tweets

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