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26 Feb, 7 tweets, 1 min read
There's been a lot of discussion recently about preprints and how we should interpret them as evidence

A few thoughts from my perspective as an epidemiologist and science communicator 1/7
2/7 The basic idea of preprints was originally twofold:

1. Put your research in the public domain, get feedback before publication
2. Get research up while it works its way through months/years of peer review
3/7 During the pandemic, given the absurd reality of months+ for studies to be peer-reviewed, preprints have become one of the primary ways for us to see new science

Imo there are pros and cons here
4/7 Peer review isn't perfect. Often, it's not even very good. It is at best an enormously flawed method of ensuring that bad-quality research doesn't get published

In case you've forgotten, the fraudulent Surgisphere papers were peer reviewed!
5/7 On the other hand, peer review is still FAR better than NO peer review. Having 3-4 colleagues check over your work doesn't make it perfect, but it makes it better than you just blindly posting it online
6/7 Ultimately, my advice to anyone is to basically treat preprints almost exactly as you would any scientific study, with maybe a touch more skepticism. They aren't necessarily worse than a published paper, but they almost certainly won't be better than one
7/7 For science journalists, while it's important to note that a study is a preprint, I would otherwise approach it exactly as you would any other study

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More from @GidMK

25 Feb
Some fascinating new data on 2020 deaths in Australia from @ABSStats:

- no excess mortality
- a modest (-0.8%) DECREASE in deaths
- biggest driver of the decrease is the massive (-37%) reduction in flu deaths

abs.gov.au/statistics/hea…
Pretty amazing that, despite the spike in COVID-19 deaths from the Victorian outbreak, there was ~no~ excess mortality during winter because the number of deaths directly attributable to influenza fell from a yearly average of ~900 to 42
Also interesting - despite lockdowns and restrictions, at worst only very minor increases in deaths due to diabetes, cancer, or CVD, and a modest reduction in deaths due to COPD (probably flu related)
Read 5 tweets
23 Feb
As an interesting note on this, the last time I contacted an author/editor to point out a study had mathematical errors, I was dismissed by the editor and insulted by the author
Conversely, I've had some really excellent discussions on Twitter about research, people are often happy to engage. Is this unprofessional?
Another important point to think about @apsmunro is that formal channels to critique research take at least months, and can easily stretch to years. The challenge with the status quo is that it often results in no action even for obvious mistakes
Read 4 tweets
23 Feb
The United States recently reached 500,000 COVID-19 deaths

That means the POPULATION fatality rate (i.e. deaths/population) for the US is 0.15%

With an estimated ~25% infection rate, the INFECTION fatality rate is ~.6%
Really puts into perspective how wildly off the earlier estimates of very low IFRs in the US were. An IFR of 0.1% is numerically impossible at this point
Another important piece of perspective is that, in the 12 months from March 2020-March 2021, COVID-19 will likely be the leading cause of death in the US
Read 4 tweets
22 Feb
A new study has hit the headlines claiming that eyeglasses can reduce your risk of catching COVID-19 by "2-3 times:

Unfortunately the science is...not good

Some peer-review on twitter 1/n
2/n The study is preprinted on medrxiv here. It is a single-author study on a survey done in India during COVID-19 medrxiv.org/content/10.110…

This will be a short thread, because...wow. Issues
3/n Some background here - traditionally, in epidemiology, to work out whether something is protective against disease, you need to know two basic things:

1. Likelihood of disease if exposed
2. Likelihood of disease if not exposed
Read 14 tweets
21 Feb
It's not like the CDC has detailed information easily available online about how influenza disease burden is calculated and obtained

Oh wait

cdc.gov/flu/weekly/ove…
The basic issue with influenza surveillance is that, JUST LIKE COVID-19, influenza can cause mild illness similar to a cold

Most people who have an infection don't get tested!
This raises a conundrum. We want to know how much influenza is around, but (based on research) only about 10-20% of people with infections get a test to see if it's influenza or something else
Read 5 tweets
21 Feb
Headline: "COVID-19 pandemic impacts rich people less"

Epidemiologists everywhere: yes, this is true of ALL HUMAN DISEASE. WE'VE BEEN TRYING TO TELL YOU FOR YEARS
It'd be nice if from this global tragedy came a better understanding of the nightmarish social aspects of disease, but my guess is as soon as COVID-19 is gone most people will go back to not caring very much about it
If you want a quick introduction to the topic at a global scale, the @WHO produced this report in 2008 that is still very applicable today

who.int/publications/i…
Read 4 tweets

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