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Common Anti-Mask Arguments Addressed

“Masks can harbour bacteria and fungi and give you pneumonia”

This is most likely referring to the study by Park et al., 2022 doi: 10.1038/s41598-022-15409-x 

However, reading the paper we find that:

  • Most fungi found were on the outside of the mask. Most fungi were opportunistic pathogens (only a danger if immunocompromised), rather than pathogenic.

  • Most bacteria were non-pathogenic in humans. Of the bacteria that were potentially pathogenic, most were commensal (normally found within the body) or opportunistic (don’t cause harm unless immunocompromised).

  • The article does not recommend against mask use, only repeated use of the same mask in immunocompromised individuals.

  • The paper points out that masks reduce transmission of Covid-19.

  • The paper points out that pathogenic bacteria and fungi are detectable on many materials we use in daily life.

And if you’re really worried about what’s on your mask:

Masks can be sterilized with steam or hot water without compromising their efficacy.

(Rahman et al., 2022 doi: 10.3390/polym14071296)

“Studies show that masks don’t work”

The most commonly cited evidence of this is a Danish study on the effectiveness of adding a mask mandate.

(Bundgaard et al., 2021 doi: 10.7326/M20-6817)

This study found that there was no significant difference in infection rates in 4000 Danes, between those recommended masks and those not recommended masks.

However, the study has many limitations which may explain why results differ from the majority of mask studies:

  • Infection rates reported in the study were not comparable with rates reported in the Danish population at the time.

  • Fewer people were infected in the masked group, but not to a level of statistical significance. The authors state that results are inconclusive, as opposed to concluding that masks provide no protection.

  • Only surgical masks were given to participants, which have a limited ability to protect the wearer from airborne viruses vs aerosolised viruses due to their loose fit.

  • The study only assessed how effectively the masks protected the wearer, not how well it reduced transmission to others.

  • In the group where masks were recommended, only 46% reported wearing their masks completely as recommended. I.e. more than half of this group did not always wear a mask.

  • The authors themselves state that the findings should not be used to conclude that mask recommendations in the community would not be effective in controlling Covid-19 spread.

“Masks make it hard to communicate!”

Data is mixed on expression recognition, but some studies show masks have no detrimental effect. Also, context and additional non-verbal cues are often not considered in studies.

A study of children aged 7-13 found that face masks did not impair ability to infer emotions.

(Ruba and Pollack, 2020 doi: 10.1371/journal.pone.0243708)

Also, clear face masks are available, including clear respirators so that lips are visible

“Masks reduce oxygenation”

Molecules of oxygen and carbon dioxide are much smaller than virus particles, so can pass through the mask whilst viruses are filtered out

Wearing a face mask does not cause low O2 nor high CO2 at rest or during activity.

(Shein et al., 2021 doi: 10.1371/journal.pone.0247414)

Gas exchange is not significantly affected by the use of surgical mask, even in subjects with severe lung impairment.

(Samannan et al., 2020 doi: 10.1513/AnnalsATS.202007-812RL)                               

A graph that is often shown


“Fig. 3. Correlation between Infection Rate and Annual Mask Usage generated from discarded face masks. (USA: United States of America; UK: United Kingdom)”
Shukla et al., 2022 doi: 10.1016/j.chemosphere.2022.134805

This graph actually comes from a paper on microplastics from face mask disposal, as opposed to anything epidemiological.

  • This graph does not accurately show the Annual Mask Usage (AMU) of each country to an accuracy that could ever be used in a paper with an epidemiological focus.

  • The authors did not account for variable mask usage in different countries and they use no real world data used on this. Instead, variation in Annual Mask Usage (AMU) is estimated by considering the population of each country in rural vs urban areas, and the presumed acceptance of masks in each area, which is constant for each country (10% in rural areas vs 80% in urban). Basically, this graph shows no accurate data on mask wearing in each country.

  • The authors also state that there is a correlation between AMU and infection rate. However, the country with the greatest population in the world, China, counters this trend. Equally, the data for India and Brazil, which also have a large proportion of the global population, also contradict this conclusion. This would explain why the authors never attempted to provide statistical tests to prove the correlation that they have supposedly found.

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