@qaz
One of the problems of posting links to articles from supposedly reputable organisations such as the
CDC article on masks is that it assumes the research is robust.
I would take any mask study with a very large grain of salt - even from the CDC. The CDC have put out studies that support their policy conclusions.
There have been problem with this CDC paper and also the CDC paper on Kansas county by county mask mandate comparison
The Kansas study compared counties with mask mandates with counties without mask mandates. CDC said in August (red circle) masks mandated counties saw a drop in cases while non mask mandates counties did not. However if the data is continued way past August it becomes very unclear whether mask mandates actually work at all.
On the face of it it does appear that mask mandates seem to have a difference. However, anyone doing real science would not be able to come to the conclusion that it was the masks. One problem with masks is that those who wear masks also tend to be more covid averse than those who dont. Was it the masks per se, was it the other rules that are often associated with masks mandates, was it other Covid averse behaviours?. How much time did mask wearers wear masks, did they wear it properly, etc etc etc
Basically it is very difficult to standardise two study groups - those who wear masks and those who dose.
Then there was a CDC study saying kids who get covid have increased risk of diabetes. But if you read the study carefully, they did not standardise for BMI. Subsequent UK studies have debunked the CDC conclusions.
But back to the California study:
Its a test negative case control design with data collection over the phone
- did you wear a mask
- what type of mask
- where did you go
- vaccination status
- age and sex
But are the differences in the test negative and test positive groups really controlled?
The problem is the assumption that the 2 groups are the same:
- did the study control for differences in age, sex, socioeconomic status, type of work., income inequality,
- are they testing for the same reason?. Test negatives could be those who are testing for travel, testing for work, routine screening, also "just coz", or worried, This is different to "I got tested because I had symptoms".
- Is the mask wearing a symbol of other types of Covid mitigating behaviours
- What was the % of case participants who participated in the phone interview? 13.4% = Abysmally low.
- Are the people who participated behaviourally different to the ones who didnt participate?
- did the people who reported mask wearing actually wear a mask?. (Remember this is the CDC - an arm of government who now knows their phone number).
- was there an expectation bias within the study participants that mask wearing was good?
CDC said in this study (a non randomised) study surgical masks have a 66% reduction in risk? The randomised study in Bangladesh (which also had problems) said 11%. Also this result is way different than the
Dan Mask 19 study which was a randomised controlled study which showed a zero difference for surgical masks.
When a non randomised test neg case control study returns a result which is completely different to randomised studies, which one would you give greater weight to?
There are too many study biases in this study, and unfortunately it came from a supposedly reputable agency.
BTW did you see the asterisk next to cloth masks in the diagram comparing cloth, surgical and N95?
What did the asterisk say.
Then ask yourself - why put NON statistically significant data into a large diagram with a very tiny disclaimer?
And then ask yourself - if a NON statistically significant method shows a large reduction in risk what does that say about the conclusions re the other masks.