pepperberg

Here's a good summary by Cochrane from 2020:

"There is uncertainty about the effects of face masks. The low‐moderate certainty of the evidence means our confidence in the effect estimate is limited, and that the true effect may be different from the observed estimate of the effect. The pooled results of randomised trials did not show a clear reduction in respiratory viral infection with the use of medical/surgical masks during seasonal influenza. There were no clear differences between the use of medical/surgical masks compared with N95/P2 respirators in healthcare workers when used in routine care to reduce respiratory viral infection. Hand hygiene is likely to modestly reduce the burden of respiratory illness. Harms associated with physical interventions were under‐investigated."

https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD...

Source? A RCT from 2019 found "no significant difference in the incidence of laboratory-confirmed influenza" between N95 and medical masks.

https://pubmed.ncbi.nlm.nih.gov/31479137/

"The COVID-19 pandemic is estimated to push an additional 88 million to 115 million people into extreme poverty this year [2020], with the total rising to as many as 150 million by 2021"

https://www.worldbank.org/en/news/press-release/2020/10/07/c...

YouTube's definition of COVID-19 misinformation: "Medical misinformation that contradicts local health authorities’ or the World Health Organization’s (WHO)" [1]

January 2020: WHO claims that there's "no clear evidence of human-to-human transmission" for SARS-CoV-2 [2]. Should YT have removed all videos discussing an alternative hypothesis?

June 2020: WHO claims asymptomatic spread is "very rare"[3]. Should YT have deleted all videos claiming that asymptomatic spread causes the majority of infections?

October 2020: WHO does "not advocate lockdowns as the primary means of control of this virus"[4]. Should YT have banned all lockdown advocates?

[1] https://support.google.com/youtube/answer/9891785?hl=en

[2] https://archive.vn/LS9kW

[3] https://www.cnbc.com/2020/06/08/asymptomatic-coronavirus-pat...

[4] https://www.abc.net.au/news/2020-10-12/world-health-organiza...

Could you share a few authors that offer worthwhile analyses on this subject?

Those are really valuable resources, thank you!

Although France's electricity mix is exceptionally low, I'm surprised to see that the EU average (438gCO₂eq/kWh) is even higher than in Germany ([2], page 74).

In the US, it's over 600gCO₂eq/kWh, in China even 1,000gCO₂eq/kWh (1.3 million EVs were sold in China in 2020).

"The disabled community doesn’t want to drive gas-burning cars while everyone else zips around in zero-emission vehicles"

I do not understand this craze for EVs. The German Fraunhofer ISI found evidence [1] that it might take up to 93,000 miles / 150,000km until you hit a break even point with regards to emissions (58 kWh; compared to Diesel).

Is that also a factor in most buyer's decisions or is it just about the feeling of "zipping around" in a EV?

[1] https://www.isi.fraunhofer.de/content/dam/isi/dokumente/sust...

Did you read my comment?

Have a look at Google Cloud Platform's ToS:

"Benchmarking. Customer may conduct benchmark tests of the Services (each a "Test"). Customer may only publicly disclose the results of such Tests if it (a) obtains Google's prior written consent, (b) provides Google all necessary information to replicate the Tests, and (c) allows Google to conduct benchmark tests of Customer's publicly available products or services and publicly disclose the results of such tests."

https://cloud.google.com/terms/service-terms

The author's argument is based on the assumption that taking aspirin results "in around one death per 10,000 people".

The cited study [1] does not say that. Those results are specifically for "a fifty-year-old male" (see p. 638), not the general population.

Additionally, the results are from an "aspirin therapy simulation", not real world data [2]. How the researchers ended up with their model parameters, is unknown.

Did the author even read the studies?

[1] https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.26.3.6...

[2] https://pubmed.ncbi.nlm.nih.gov/15590881/

Again, your argumentation is problematic and therefore hard to argue with.

Your first point depicts a fictional anecdote that tries to prove that terminally-ill patients with a positive COVID-19 test could have lived longer. It's like saying "If someone has stage IV cancer and tests positive for COVID-19, that does not mean he died due to COVID-19. Heck, he could have even died due to multidrug-resistant bacteria"

What's your source? What's mine? What does it add to the discussion to bring up fictional scenarios?

Regarding your second point: Source? How closely does excess mortality correlate with COVID-19? Could there be other causes? We are talking about highly complex situations that need to be thoroughly analyzed.

Please have a look at your argumentation:

- "I don't think this is true" - "And AFAIK most countries do actually [...]" - "In other words, this is a common myth [...]"

You present your thoughts, a theoretical anecdote and things you might have read. And based on that you conclude that it is a "common myth"?

You're right, it is the same flawed assumption. Both approaches lead to problematic conclusions, both should face scrutiny.

Unfortunately, we mostly see one-sided criticism.

Edit: Thank you for downvoting without commenting!

You're right, they should have written a short summary of the content and not make us research it ourselves.

I wouldn't use "there's no Wikipedia on him" as an argument. Karikó's entry is only 1 year old [1].

Additionally, it seems that Karikó's work acknowledges contributions from Malone [2].

Whether he's the original inventor or not, whether his claims are true or false, should be up for debate. But isn't that enough to at least tolerate his opinion on YouTube?

[1] https://en.wikipedia.org/w/index.php?title=Katalin_Karikó&of...

[2] https://www.sciencedirect.com/science/article/pii/S000527369...

Where do you see the "crackpot claims" in this situation? He/she just stated that "inclusive discussion is being suppressed", showing a recently removed YT video.

For anyone who can't take 30s to look it up: It is a discussion between 3 individuals (2 of them already fully vaccinated with Moderna) regarding the pandemic:

https://www.youtube.com/watch?v=6XkRq4PaHqo

Instead of looking up the original video (e.g. by using the watch id), you immediately write it off as "crackpot claims" because some unknown authority at YouTube removed it, citing broad community guidelines.

Maybe we should stick to your words from 4 days ago:

"Science reporting is terrible and the general education system doesn't teach rational skepticism, it teaches unconditional trust of intellectual authority."

Is this really a skeptical, discussion-friendly behaviour or an unconditional trust in some kind of authority?

" all the nuclear waste generated by the world since the invention of nuclear energy can fit into a single Highschool auditorium"

Source?

You’re right, they completely differ from each other (regarding their relevance) and should therefore face an adjusted amount of scrutiny.

If you’re one of the top pharmaceutical companies in the world, some press releases and study protocols are simply not enough [1] and should be (imo) discarded.

If you’re a new player (Vaxxas) claiming “complete protection” by testing your product on mice, it’s simply not enough and should be (imo) discarded.

[1] https://blogs.bmj.com/bmj/2020/11/26/peter-doshi-pfizer-and-...

BioNTech/Pfizer published a press release regarding 94% efficacy in November 2020 (1 month before publishing any study) and it too landed on the front page:

https://news.ycombinator.com/item?id=25135984

Thank you for your explanation!

I have one question regarding the current Pfizer data (it would be great if anyone with experience in statistics could help out):

UK healthcare professionals received this information called "REG 174 INFORMATION FOR UK HEALTHCARE PROFESSIONALS" [1] It states that the "efficacy of COVID-19 mRNA Vaccine BNT162b2 [for 75 years of age and older] was [...] 100% (two-sided 95% confidence interval of -13.1% to 100.0%)"

What does this mean? With my very minimal university statistics knowledge I would say that they are 95% sure that the efficacy lies between -13.1% and 100.0% for age >=75. And that means: We simply do not know (probably due to lack of data in this cohort). Where am I making an error?

Thank you in advance!

[1] https://assets.publishing.service.gov.uk/government/uploads/...

I have one question regarding the current data (it would be great if anyone with experience in statistics could help out):

The FDA document (p. 26, table 8) states that the vaccine efficacy (age group >=75) is 100.0% (95% confidence interval of -12.1 to 100.0).

What does this mean? With my limited university statistics class knowledge I would say they are 95% sure that the efficacy lies between -12.1% and 100.0% for age >=75.

Is this the correct interpretation? If yes, doesn’t it show that we simply do not know about its efficacy in this age group yet (due to lack of data)? If not, could you please explain it?

Thank you in advance!