Interesting new preprint on #LongCovid. Some take-homes:

- ~14% of people
- can last months
- associated with +symptoms, previous respiratory disease, gender, age
- not associated with metabolic disease (mostly)
medrxiv.org/content/10.110…
To me, this is the most interesting table. You can look through and see what is and isn't associated with PCR-positive Long COVID
Not unsurprising that people who experience worse symptoms in their initial COVID-19 infection are more likely to suffer from #LongCovid
However, some MAJOR limitations to the analysis. The patient group is very selected (people who use and KEEP using an app long term), and this only captures those who had PCR-positive cases of COVID-19
So, interesting, but I'd be very cautious about drawing inferences from this (i.e. you can't say that 2% of people who get COVID-19 will still have symptoms months later, we don't know if that's true from this study)
A good way of thinking about it is, I reckon, to say that #LongCovid does appear to impact a reasonable fraction of people, but exactly who they are is still up in the air and requires much more research
It's also worth noting that we still don't know how much COVID-19 differs from other respiratory diseases in this context, although this study does seem to indicate that those who tested positive for COVID-19 were more likely to experience long-lasting symptoms
Also, I should note that the fact that this data was gathered through an app is definitely an issue. I've actually published research on attrition in app-based interventions, it's a tricky subject jmir.org/2020/9/e20283/

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More from @GidMK

22 Oct
Worth noting that this represents 607,559 COVID-19 tests with 226 positives, giving a positive rate of 0.0372%

Even if EVERY TEST was a false positive, that gives a specificity of ~99.96%
But, because positive people are almost always retested here we can actually examine this question more robustly. Of the 226 positive results, one was later retested and found to be a false positive! Image
To calculate test specificity, we take TN/(TN+FP) = 607333/(607333+1) = 99.99984%

To put it another way, very roughly 1 false positive test per million tests done
Read 5 tweets
21 Oct
This article raises some interesting points. Have death rates from COVID-19 gone done since March?

npr.org/sections/healt…
Now, I think it's reasonable to assume that the proportion of people who die after being infected by COVID-19 will fall over time. It's probably true that being infected today is less deadly than earlier this year
That being said, I'm quite skeptical of the evidence presented. This story seems to claim that death rates have dropped ENORMOUSLY, while I would expect something more in the range of a relative 10-20% drop (say from 25% to 20%)
Read 13 tweets
20 Oct
Calling government action on COVID-19 "Health fascism" - a good start to what I'm sure will be a measured, balanced piece
Hm well I guess if the Human Rights Commission doesn't care about human rights during COVID-19 that would be a proble-oh, wait
Moving on we have...oh, some classic denialist tropes. That's not ideal

We're now numerically above the death toll of any pandemic since 1918, and the "survival rates" give your average 60 year old a 1 in 200 risk of dying
Read 5 tweets
19 Oct
Sweden is set to unveil a set of tough new regulations amid growing COVID-19 cases

businessinsider.com.au/sweden-shifts-…
Depressingly, there is little evidence that the pre-existing immunity from the first wave has substantially dampened viral spread, despite earlier hopes
Worth noting that Tegnell himself predicted that Sweden would reach "herd immunity" by mid-May originally, until serology studies proved that this was wrong
Read 4 tweets
18 Oct
People have been asking me to debunk this thread "proving" that COVID-19 deaths are false positives by correlating things, but instead I thought I'd simply list a few things that are more well correlated than this
US spending on science, and suicides by hanging/strangulation/suffocation

99.97%

"Biology just isn't like that"
Divorce in Maine, consumption of margarine

99.26%

"Biology just isn't like that"
Read 8 tweets
15 Oct
Something that I think is worth explaining:

The term "herd immunity" has a few different meanings, all of which are quite precise. This is an important point
In a very strict mathematical sense, herd immunity is the slowing of disease spread due to sufficient infected people in a population (such that Rt<1)
This leads to the second definition, which is the ability to calculate immunity within a population based on dynamics of disease spread
Read 9 tweets

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