Masks work against COVID

I want to share an observation that’s been on my mind for a while. I was visiting a Zoo with my family before the vaccine was available for regular people, around early Spring 2021. A big Zoo. All the enclosures where animals were indoors (penguins, monkeys and so on) had a big sticker on the door asking to “Please wear a mask for our animals’ sake. They too can get COVID19”. An overwhelming majority were putting on their masks upon reading this sign. Really, close to 99% of people, adults and children alike. At the same zoo, the same people were entering maskless in the Gift Shop and other indoor facilities like toilets and so on. I eyeballed less than 10% were wearing masks in “human enclosures”. I spent a lot of time at this Zoo watching for this behavior instead of looking at the other animals to make sure I’m not imagining things.

My lesson: humans are not deemed worthy the masking trouble, but zoo animals are… Now please explain to me how no mask-wearing is about “freedom”, “COVID is a scam/flu/doesn’t exist”, “masks don’t work” and so on and not about a conscious moral choice to knowingly endanger other people and their kids?

By Neuronicus, 17 August 2021

EDIT: Mrs. Clinton’s first name is Hillary, not Hilary.

REFERENCES:

Howard J, Huang A, Li Z, Tufekci Z, Zdimal V, van der Westhuizen HM, von Delft A, Price A, Fridman L, Tang LH, Tang V, Watson GL, Bax CE, Shaikh R, Questier F, Hernandez D, Chu LF, Ramirez CM, Rimoin AW. (26 Jan 2021). An evidence review of face masks against COVID-19. Proceeding of the National Academy of Sciences of the USA, 118(4):e2014564118. doi: 10.1073/pnas.2014564118. PMID: 33431650. ARTICLE | FREE FULLTEXT PDF P.S. Since this paper was published, dozens of others have been published that say the same thing: wear a mask for all our sakes.

Kahane LH (5 Jan 2021). Politicizing the Mask: Political, Economic and Demographic Factors Affecting Mask Wearing Behavior in the USA. Eastern economic journal, 1-21. doi: 10.1057/s41302-020-00186-0, PMCID: PMC7783295, PMID: 33424048. ARTICLE | FREE FULLTEXT PDF

Air pollution and mortality

The authors used a chemical transport model called GEOS-Chem to estimate the global exposure levels to airborne particulate matter derived from fossil fuel combustion. It’s a worldwide used model for estimating dispersion, for example the simulation of surface pollination. The model has been validated, meaning its predictions were compared with the reality and they matched. Levels of fossil fuels emission were inputted from publicly available data “from multiple sectors (power generation, industry, ships, aircraft, ground transportation, backup generators, kerosene, oil/gas extraction), detailed oxidant-aerosol chemistry, and reanalysis meteorology from the NASA Global Modeling and Assimilation Office” (page 5 of the manuscript). The mortality due to air pollution was computed by starting with the classical risk assessment analysis from epidemiological research and then adjusting for other variables like in-door particulate exposure (smoking) and so on. It sounds straightforward enough but the math and stats involved are very complicated. You have to take into consideration concentration, exposure time, and other factors that affect the outcome.

In addition, the authors calculated the mortality caused by fossil-fuel air pollution in children between 0 and 4 years of age, which was 876 in North America, 747 in South America, and 605 in Europe, annually. Pollution data is from 2012, mortality from 2015. The authors are hopeful that aggressive regulation designed to curb emissions in the last few years may have already lowered these numbers. Policy-makers, take note!

REFERENCE: Vohra K, Vodonos A, Schwartz J, Marais EA, Sulprizio MP, & Mickley LJ (Apr 2021, Epub 9 Feb 2021). Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: Results from GEOS-Chem. Environmental Research, Volume 195, 110754. PMID: 33577774, DOI: 10.1016/j.envres.2021.110754, ARTICLE.

By Neuronicus, 11 March 2021

Social groups are not random

I re-blog other people’s posts extremely rarely. But this one is worth it. It’s about how groups form based on the amount of information given. And, crucially, how amount of information can change individual behavior and group splits. It relates to political polarization and echo-chambers. Read it.

https://scienceblog.com/521229/understanding-how-a-group-of-people-splits/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+scienceblogrssfeed+%28ScienceBlog.com%29

After you read it, you will understand my following question: I wonder by how much the k would increase in a non-binary environment, say the participants are given 3 colors instead of 2. The authors argue that there is a k threshold after which the amount of information makes no difference any more. But that is because the groups already completed the binary task, therefore more information is useless due to the ceiling effect. Basically, my question is: at which point more information stops making a difference in behavior if there were more choices? Is it a log scale, linear, exponential? Good paper, good cover by CNRS, at scienceblog.

By Neuronicus, 24 February 2021

P.S. I haven’t written in a while due to many reasons, one of which is this pesky WordPress changed the post Editor and frankly I don’t have the time and patience to figure it out right now. But I’ll be back :).