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Figures Lie and Liars Figure: Facemask Edition

Updated: Mar 20, 2021


Look, funny lines that appear to support my view!
Proof that face masks help prevent the spread of COVID-19 in Arizona.

Figures lie, and liars figure. It's an old phrase that, sadly, still has much relevance today. It's a caution, a warning, to be careful of simply accepting data handed to you. Sadly, so many people these days are in such a need to justify the correctness of their chosen political party that all analytical thought gets thrown out of the window the minute something supports/attacks their party's position. News Flash: Both of the major super parties will lie to you. I know a lot of you are nodding your heads in agreement, even as you think to yourself 'but not my party'. Because its just the other side that are mindlessly following along with whatever they're told, right? Wrong.


BOTH. WILL. LIE.


They differ in what they lie about (and how often) only. But both lie. Which means that it's you're job as concerned citizens to test what you are told, not to accept/reject it along party lines. It is your job to question the standard position. It is your job to ask yourself if the data presented is solid, anecdotal, or even unrelated. Because yes, they will tell you cows produced more milk this year, which proves climate change, if they think the majority of their followers will believe it.


Case in point: the above picture. It is deliberately mislabeled. I'm sure some of you noted the fact that the y axis is labeled in thousands while the x axis is labeled in days, suggesting a thousands of cases per day bar chart. Which is ridiculous. Even the most pessimistic follower of the current pandemic would have to admit as much.

Those that noted this discrepancy are most likely people against wearing face masks. It didn't support their position, so they paid attention. Those that failed are most likely people who will accept anything that looks like it supports their side of the argument.


But this isn't actually a graph of the number of confirmed cases of Covid-19 per day. It's a graph of the number of Covid-19 tests given per day. Note how it looks much like this graph:



The resemblance is uncanny; are you two brothers?

Note: Both of these graphs were taken from the Arizona Department of Health and Services Dashboard.


This graph has been passed about a lot by pro-maskers as proof that face masks help stop the spread of Covid-19. The problem is, even if testing were uniform over every day, this would only be what's known as anecdotal evidence. It does not prove that face masks help. It does support that concept, but it ignores many other factors that could affect the spread of the virus.

And, from the graph previous, we know that testing was not uniform. While this graph is more scrunched up than the above to make room for a map of Arizona, you can still see a very similar peak and fall centering on July. In other words, as testing went up the number of cases found went up. As testing fell, the number of tests fell.


What's that? Is it a one to one ratio? Now that's the question you should be asking. And the answer is no. The graph you should have been shown was this one:



Note: Click on this chart to be diverted to the interactive HTML version.


Now, this graph presents the number of infected as a function of the amount of testing being conducted in all of Arizona. I built it using the data from the above two graphs with the help of the kind folks over at Flourish.Studio.

You can already see some data that did not show in the previous two graphs, namely that this graph shows a spike starting in late march. That would be the spike caused by the mid march rush to ensure everyone had up to two months of supplies at home, or as I like to call it 'The Great TP Shortage of 2020'. Also, note that even here we see the same peak in July. So why wasn't this the graph you were presented with? Two reasons that boil down to: it's not nearly as definitive.


1) Both curves appear very similar, with the main difference being their starting point. If anything, the drop-off seems to take longer during the second. Taking the average of values from the peak of the first lockdown gets a 14.47 percent positive rate. It took only (roughly) 20 days to reach an average of 4.55 percent. Yet, despite a nice leveling out of the curve in the second lockdown from 7/17-7/28 that equals 14.89 percent positive, we still have not seen that large a drop in percent confirmed cases one month later.


2) This graph shows that, even after face masks were instituted in Az the numbers continued to climb. It was not until 9 days after another lockdown was put into effect that the percentage of positive tests began to fall again.


In other words, the relevant data does not show one way or another whether masks help. Some could even argue that they have slowed the drop in positive cases (though I wouldn't). And the funny thing is that this is still just anecdotal data! This attempts to boil a complex system into two data points: date and percent positive tests. It ignores a plethora of other affects. For instance:

Weather: The virus is vulnerable to UV radiation; Arizona was just reaching its highest sun, highest temperature months as we entered the second lockdown, which should have made infection harder. Gatherings: We've been blessed with only a few riots in the wake of George Floyd's murder, but there were several peaceful protests which could have helped spread the disease. Testing Policy: During the first lockdown, only suspected persons were being tested, which would artificially raise the percentage of positive tests. By the second lockdown, Arizona had embarked upon what it called 'Testing Blitzes' where they tested anyone that would let the testers near enough to have a swab jammed up their nose. This has the effect of lowering the percent positive testing compared to testing during the first lockdown.


Area of Testing: High population areas yield more opportunity for close contact as opposed to low areas.


And lastly, type of mask being used: Few are actually helpful at all. A single wrap of cloth will barely impede moisture from leaving your mouth which is, after all, the goal. The virus rides upon the water molecules in your breath.

Worse, many have gone towards using 'moisture wicking' materials to cover their mouths. Just where do you think the moisture wicks too? Yep, to the external air. The whole purpose of these is to ensure maximum evaporation from the skin. In other words, you've just created an aura of Covid (assuming you have it) around you.

Many are using allergen masks with a filter to stop incoming pathogens, but a valve that helps with easy exhale. This helps those concerned with getting sick, but does nothing for those you come into contact with.


Nearly every mask I see out there is what's called a comfort mask. It does nothing to slow the spread disease. It makes the people around you feel more secure. That's all. The best that can be said for them is that they stop people from licking/coughing on, each other. Personally, a good jab does just fine at stopping that nonsense.


The bottom line is, if your goal is to protect others there's a simple test for your mask: How hard is it to breath through? If its not hard to breath through, its not stopping anything.


But, that still begs the question: do they help at all? Some figurers say yes. Others say no. I don't claim to know, but the data doesn't seem to support it. On top of that, allow me to add my own bit of anecdotal data.


I live in a house with four roommates, all of whom work. Four of us work directly with customers. One works online from an office. All of our jobs required anyone inside to wear a mask. 2 of us were using neoprene masks with N97 filters in them. We all got Covid-19. And, strangely enough, we all became symptomatic within about 12 hours of each other. Those symptoms did not last for more than two and a half days for all but one of us. It took him nearly a week to get over it. And honestly, I've worked through worse colds.


My girlfriend, whom I spent the evening with just prior to becoming symptomatic, and who insisted on seeing me during, did not get sick. (And she insisted I take the mask off during because she said it felt like a BDSM thing.) Two friends that come to the house at least once a week did not get sick.


Of course, that's just anecdotal data.


But here's more : The CDC State and National Provisional Death Counts. Now, only the first three months of 2020 have been tallied on this so far, but a check shows actual lower death rates with a stable 12 month ending death rate, than the previous year. Keeping in mind that mid March rush on toilet paper that started a big surge in infections of Covid-19, one would think we would have seen some spike by the end of March. After all, it does take much longer to recover from a disease than to die from it.

But, maybe that spike didn't happen until April. I'll have to wait and see on that.


But, if face masks don't work (and that's a legitimate if) the question becomes 'why is someone trying to convince others it does, even if the data is inconclusive at best?' What's the goal? What do they really want?


And that's exactly why we have to be on the lookout for lies even when we think they support our position. Because there has to be a motive. Few people would expend the kind of effort it takes to create such hysteria without some motive, even if its just for their own amusement. Maybe they just have a hard time adapting to new data as it comes in. Maybe they feel a 'better safe than sorry' approach should be enforced on everyone. Maybe they get kickbacks from the mask makers.


Or maybe its because that person/group knows people think via precedent and analogy. They think in terms of 'my child got a vaccine and then got diagnosed with autism, so it must be the vaccine's fault'. They think in terms of 'Someone I respect said the Earth was flat, so it must be so' or, 'My parents said there's a funny man in the sky, so it must be so'. They think in terms of 'we did something similar before and it was good, so this must be so'.


This sort of generalized logic can be dangerous, mainly because it creates nasty little precedents. In this case it creates a precedent granting governmental power over the populous to be used in the event of unrest.


In other words, if it becomes okay to mandate the way a person lives their lives because it makes other people 'feel secure' then the door is thrown wide open for what can and can't be allowed. Get rid of those guns: it makes people feel secure. Stop all abortion: it makes people feel secure. Don't mention Tienanmen Square: it makes people feel secure. P.S. Masks may indeed help, but don't expect intelligent people to conclude as such because you through together a chart that only looks at infections per day with no thought given to the amount of testing being done. #Masks #PossibleGovernmentalOverreach #IncompleteData #LiarsFigure

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