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>Surgical masks with particle collection efficiencies around ~50% cannot prevent the release of millions of particles per person and their inhalation by others (green dots in Fig. 1, B and D). In other words, the human-emitted respiratory particle number is so high that we cannot avoid inhaling particles generated by another person even when wearing a surgical mask

So the entire premise of the modeling in the paper rests on the assumption that surgical masks can filter some percentage of viral particles. It's my understanding that viral particles are around 3 orders of magnitude smaller than the pores in surgical masks. So is there any evidence that surgical masks can filter aerosolized viral particles?




Virus particles do not travel naked in the air, instead they are colloidally suspended in liquid, both droplets and aerosols.

So, if your filter catches the droplets and aerosols, which are much larger in size than the actual virus, the filter works.


Realization that somebody's droplets are getting into your mouth and nose makes one want to wear mask even after pandemic is over :)


You may want to check how much of your body weight is bacterial and how easy it is to exchange samples with others. Just own the things that make us human.


You're of course free to do whatever you think makes sense, but please don't expect other people to follow. The world is full of risks, but everything is a tradeoff - it's really bad if we start thinking random people are a danger to us.

And for what it's worth, I'm not anti-mask in the context of the pandemic - I've been wearing masks indoors since the whole thing started and I'll continue to do this until most people around me are vaccinated, for their sake.


assuming: 1) 100% capture of air flow 2) no fatigue (ie capture is same at t=0, and t=later)

anyone with glasses will tell you 1 isn't a very good assumption. As masks saturate in moisture, back pressure causes (1) to be more false.


Except that field data shows they don’t because they are not used precisely as required - which means the filter doesn’t work effectively if at all and then it becomes infectious waste that isn’t treated and disposed of correctly.

Human system effects dominate - as the field data shows. It’s like HCQ - works in a lab, not in the real world.

Might be useful in tightly controlled medical settings with adequate filtered ventilation. But there’s no hard evidence beyond that at this stage.

Feynman’s rule still applies.


Science is based a lot on assumptions and beliefs. A scientist who does not consciously say: „We have observed that… which makes us believe that…“ still ultimately becomes a victim of his unconsciously formed belief system, a pseudo-religion.

I’m a software engineer, I work scientifically, but I don’t own the truth. I own the thought process which works on top of assumptions. But I don’t want my own work to feel like magic, and to avoid that, I observe and try to understand it. But at the end of the day I have to say: „I assume that my program is bug free because I have observed many test runs in which the program behaved correctly. I belief it will work well at the customer.

Same has to be said for above study. Otherwise we wouldn’t find studies which even claim the opposite. These other studies are just based on different assumptions and belief systems.


Here’s a nice interactive graphic showing how masks block particles:

https://www.nytimes.com/interactive/2020/10/30/science/wear-...


That's a very cool visualization and I wish I'd seen it before. I am curious though as to what makes some viruses have higher R values than others. These masks more effectively stopped influenza and I still don't understand why.


Google cross-protection and competition in respiratory viruses. Lots of pre-2019 literature.


Viral particles are concentrated in droplets and aerosols, which are significantly blocked by surgical masks.




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