8 ms·

That is a weird graph. Am I missing something, or does it say that the counties with a mask mandate began to have substantially lower cases than those without s

by makomk 5y ago

That is a weird graph. Am I missing something, or does it say that the counties with a mask mandate began to have substantially lower cases than those without starting two months before the first mask mandates were reimposed?

diognesofsinope 5y ago
Same thought -- makes you think it has less do you with masks/mandates and more with city-folk being cautious as delta surges. Maybe the mandates encourage this behavior shift? Top points if politicians noticed this difference off the bat and create the mask mandate to engineer the illusion that it was their policy that worked, even though it would've happened anyways -- aka action bias. In any case, I think we can all agree people need to stop (1) using different random X-day moving averages and (2) give us the data. edit: there's an entire literature on methodologies (1) Regression Discontinuity Design (RDD) and (2) Difference-in-Difference (DiD) that's designed to address this problem in analysis.
- mjevans 5y ago
  The reason for a 7 day running average is because there is a great deal of noise in the source data, that is how you clarify the picture to remove short term trends in numbers. Confounding trends might exist for various reasons like: labs want people to have a day or two off, so process less on the weekends or some days of the week in spreading that weekend out. People might interact in different risk settings over the course of a week. (E.G. For some higher risk on the job and shut in on the weekends. For others time to go out clubbing on the weekends and shut in jobs during the week). So the 7 day running average just says: we can't disentangle to get at the true raw numbers, this is the best we can do to get useful data out of the data-feed. PS: The only way to get truly useful data would be sufficient testing capacity to issue fully randomized tests on everyone, in a mandatory way, on a regular basis. A 'well designed survey' would probably still have biases but might approach that. To the best of my knowledge (public news media), currently most tests are probably focused on populations perceived to be at higher risk, who show visible possible symptoms, or who are obviously ill.
  - diognesofsinope 5y ago
    I get why it's used, but I strongly believe people are better off seeing the raw data. Exactly as you said, we can probably infer if there is variation in testing (weekends). Or at the very least show the 7-period SD so we can see if the confidence intervals overlap. You can absolutely use averages to hide data points and data quality. PS: I disagree with your PS -- if we're being wildly theoretical and impractical about this we should just create a second Earth where everyone wears mask and a third Earth where no-one wears masks and compare all the Earths.... And none of what you're saying addresses the core problem I mentioned, which is that the divergence in the series starts before the policy date.
weezin 5y ago
Yes, this headline is really misleading. You could argue the gap widened a bit after the mandate, but that is probably more a factor of behavior/vaccination rate compounding than masking. This is anything but conclusive about mask.
belorn 5y ago
If I wanted to create a graph that disproved the effectiveness of mask I would use cities near the coast during the summer, one with mask mandates and one without. I would look at all those people that are outdoor in the warm and humid climate. If I wanted to do the opposite I would pick cities that are inland with temperate climate during that fall, with the air dry and most people inside poorly ventilated buildings.
- eesmith 5y ago
  How is that relevant given these are all in MO, during the same time period?
  - belorn 5y ago
    Sorry, I should have developed the comment a bit more. Transmitting and date rates are determined by multiple factors, many that are known. Risk groups, ability and convenience to do social distancing, population density, ventilation, weather, population movement patterns and more. In this case we got Kansas city vs St. Louis, through the article is trying to making an argument about the world in general. Graphs like this are basically pointless except for one thing. They imply that there might be a benefit of masks, and thus while its not evidence of effectiveness its is not evidence of the opposite. It is what researcher use as support for doing further studies that later accounts for known factors. If however one uses it to jump ahead, someone else can create a similar graph in a different locations and time to create the opposite conclusion. (Small note about the time period). It is worth looking at the period between April and August. The two lines swap places which each other. St. Louis started out with a higher rate than Kansas city, and end up with a lower rate afterward. This is a pretty common pattern and follow the old "even out the curve" concept.
gumby 5y ago
Note that this graph was created by the reporters and was not generated by the health department. The labeling is weird. The reinstatement arrow should point SSW not NW. That says that during the surge, those counties* had a lower death rate. Presumably the counties that ever had a mask mandate had higher compliance even during periods when the mandate was lifted, but the article doesn’t discuss any of that, and it’s only a presumption. * I think the blue line should be labeled “death rate in the four counties”.
- contravariant 5y ago
  How does changing the arrow change the fact that they had significantly lower case rates at the end of June while the mask mandate came into effect on July 26?
- throwawaylinux 5y ago
  > The reinstatement arrow should point SSW not NW. It points to the the point on the blue line at July 26. Why should it point SSW? Does SSW even intersect with the blue line at any point?
jtbayly 5y ago
Even if the change started the day after the mask mandates we would know that the drop wasn’t caused by the mask mandates. Why? Because of incubation times.
- Retric 5y ago
  You are assuming people would wait until the mandate was in effect to change behavior rather than for example buying masks in preparation for a mandate.
  - jtbayly 5y ago
    So your contention would be that people will wear masks even when they are not mandated? I would agree that could happen. But then, that’s not a result of masks being mandated, is it?
    - Retric 5y ago
      No. I am saying if you create a mandate on date X, people will prepare for it before it comes into effect.
      - jtbayly 5y ago
        Yes, lots of things happen before and after lots of other things. But figuring out causes is a lot harder than saying something happened after something else. Regardless, if people are willing to voluntarily wear masks before they are required, like you claim, then one thing is clear: Masks do not need to be mandatory for people to wear them. Imagine if they dropped the speed limit from 70 to 50. How many people would start driving 50 a week early to "prepare"? Not many. If people are so resistant to an idea that it has to be mandated for them to do it, then they aren't going to suddenly do it before it is mandatory. And if they aren't resistant to it, then it won't take a mandate.
        Retric 5y ago
        In theory you might be right, but we don’t have to guess people have collected actually evidence. Also, you can’t fake the response from an impending mandate without a mandate. Most people fill out their taxes early, but if taxes were optional then nobody would be filling them out. The test would simply be to look up when a mandate was announced and then when it took effect.
cm2187 5y ago
In fact, the way I read the chart, it rather proves that mask mandate were ineffective as there was no inflection point following the introduction of the mandate. Instead the two curves remained pretty much parallel, suggesting the evolution wasn't related to masks.
- LongTimeAnon 5y ago
  Excuse me, racist, but those masks were made by minorities, and since math and science are clear signals of white supremacy, I think it's important we raise awareness about what you're really trying to say here.
- onion2k 5y ago
  it rather proves that mask mandate were ineffective as there was no inflection point following the introduction of the mandate That might indicate that the mask mandate was ineffective and the evolution was due to something else, or it might indicate people didn't abide by the mandate as soon as it came in.
tinus_hn 5y ago
When you look at the world through mask tinted glasses, all the mask flags just look like flags.
gnramires 5y ago
It depends on interpretation and I think conclusions are unclear from that graph. Try this: shift the blue curve about 15 days to the left. We may then interpret masks acted in lowering the infection peak, since masks were introduced at an earlier infection stage. In other words, if St Louis reinstated masks at the same infection count as Missouri it might have seen a higher infection peak.
refurb 5y ago
This is what makes me laugh about everyone trying to figure out which country did it “right”. One country is on the down slope of a wave and get kudos for an effective strategy. Some country on an upslope get trashed. And it changes every few months. We won’t know which countries handled it well for another 5-7 years once analyses can be done that take into account the full impact of strategies. Then add on top their stats aren’t even comparable due to different levels of testing, different categorization, etc. Just looking at raw stats says Africa did really well with Covid even without the vaccine. But if you don’t test, you can’t find cases. No cases, no covid deaths.
- SideburnsOfDoom 5y ago
  > Just looking at raw stats says Africa did really well with Covid even without the vaccine. Africa is doing surprising well with COVID-19, considering expectations. Reasons may include: * Not kidding themselves like UK and US did that they were "world leaders", and had this in the bag. (1) * Recent and ongoing experience of combatting other diseases, e.g. HIV, TB, Ebola. 1) "In October 2019, an extensive report two years in the making placed the US and the UK first and second respectively in a global ranking of countries’ pandemic preparedness." https://www.huffingtonpost.co.uk/entry/uk-coronavirus-pandemic-preparedness-what-went-wrong_uk_5f105b86c5b6d14c3363e8d2 https://www.huffingtonpost.co.uk/entry/uk-coronavirus-pandem...
  - ceejayoz 5y ago
    Another reason may be better ventilation.
    - SideburnsOfDoom 5y ago
      The last time I was in an African city there wasn't air-conditioning as standard in houses. Sure, windows were open in summer, but closed up in winter. Office buildings had the usual levels of ventilation. I can't really describe this as "better" - how about you?
    - thoughtstheseus 5y ago
shinydevops 5y ago
As someone who lives in one of the areas in this study that instituted a mask mandate, I think the clearest explanation of the lower case rates preceding the mandates is the general willingness of the population to mask prior to the dates noted on the graph. Yes, the most recent mask mandates weren't instituted until July 26th, but, for whatever my anecdata is worth, masking use in the more urban areas was already substantially higher than it was in the areas without the mandates. There's also the small matter of the more populous areas having higher vaccination rates than the state's more rural areas. To me, the story here is not the data itself; it's another example of elected officials hiding data that doesn't agree with their position. Is the headline the best interpretation of the data? Not at all. But it's one more data set showing that the areas that are most closely following relevant recommendations are seeing better outcomes than areas that aren't.
obelos 5y ago
I think it may ultimately be more useful to think of mask mandates as an effect rather than a cause of reduced disease spread. Communities that are culturally predisposed toward prosociality don't actually need mandates to produce collective behaviors that reduce spread. It's politically viable to impose a mask mandate in those places, even though it's unnecessary for producing a public health impact. The converse, in areas where it's politically infeasible for public officials to impose a mandate, appears in a population where individuals are not predisposed to adopting public health measures on their own.
- Pxtl 5y ago
  Yep. There's a very strong correlation simply by political affiliation. This Washington Post columnist has some very telling graphs: https://twitter.com/pbump/status/1466261627074920452 https://twitter.com/pbump/status/1466261627074920452 Basically, the more urban and politically blue the county is, the more success they had against COVID, despite the fact that urban locations with higher density and more shared spaces have an intrinsic disadvantage in stopping the spread of disease. By politicizing public health measures, they got outcomes split by political culture.
orangecat 5y ago
Exactly. If you remove the labels from the two lines and then ask which set of counties imposed mask mandates in July, there would be no way to tell. If anything, you might think it was the higher line; "see, their cases were spiraling out of control, then they required masks and their cases peaked and declined at the same time as the less hard hit counties". Unless that chart is a horribly misleading presentation of the data (quite possible!), it's evidence against mask mandates having any discernible impact.

by makomk 5y ago

diognesofsinope 5y ago

Same thought -- makes you think it has less do you with masks/mandates and more with city-folk being cautious as delta surges. Maybe the mandates encourage this behavior shift? Top points if politicians noticed this difference off the bat and create the mask mandate to engineer the illusion that it was their policy that worked, even though it would've happened anyways -- aka action bias. In any case, I think we can all agree people need to stop (1) using different random X-day moving averages and (2) give us the data. edit: there's an entire literature on methodologies (1) Regression Discontinuity Design (RDD) and (2) Difference-in-Difference (DiD) that's designed to address this problem in analysis.

mjevans 5y ago
The reason for a 7 day running average is because there is a great deal of noise in the source data, that is how you clarify the picture to remove short term trends in numbers. Confounding trends might exist for various reasons like: labs want people to have a day or two off, so process less on the weekends or some days of the week in spreading that weekend out. People might interact in different risk settings over the course of a week. (E.G. For some higher risk on the job and shut in on the weekends. For others time to go out clubbing on the weekends and shut in jobs during the week). So the 7 day running average just says: we can't disentangle to get at the true raw numbers, this is the best we can do to get useful data out of the data-feed. PS: The only way to get truly useful data would be sufficient testing capacity to issue fully randomized tests on everyone, in a mandatory way, on a regular basis. A 'well designed survey' would probably still have biases but might approach that. To the best of my knowledge (public news media), currently most tests are probably focused on populations perceived to be at higher risk, who show visible possible symptoms, or who are obviously ill.
- diognesofsinope 5y ago
  I get why it's used, but I strongly believe people are better off seeing the raw data. Exactly as you said, we can probably infer if there is variation in testing (weekends). Or at the very least show the 7-period SD so we can see if the confidence intervals overlap. You can absolutely use averages to hide data points and data quality. PS: I disagree with your PS -- if we're being wildly theoretical and impractical about this we should just create a second Earth where everyone wears mask and a third Earth where no-one wears masks and compare all the Earths.... And none of what you're saying addresses the core problem I mentioned, which is that the divergence in the series starts before the policy date.

weezin 5y ago

Yes, this headline is really misleading. You could argue the gap widened a bit after the mandate, but that is probably more a factor of behavior/vaccination rate compounding than masking. This is anything but conclusive about mask.

belorn 5y ago

If I wanted to create a graph that disproved the effectiveness of mask I would use cities near the coast during the summer, one with mask mandates and one without. I would look at all those people that are outdoor in the warm and humid climate. If I wanted to do the opposite I would pick cities that are inland with temperate climate during that fall, with the air dry and most people inside poorly ventilated buildings.

eesmith 5y ago
How is that relevant given these are all in MO, during the same time period?
- belorn 5y ago
  Sorry, I should have developed the comment a bit more. Transmitting and date rates are determined by multiple factors, many that are known. Risk groups, ability and convenience to do social distancing, population density, ventilation, weather, population movement patterns and more. In this case we got Kansas city vs St. Louis, through the article is trying to making an argument about the world in general. Graphs like this are basically pointless except for one thing. They imply that there might be a benefit of masks, and thus while its not evidence of effectiveness its is not evidence of the opposite. It is what researcher use as support for doing further studies that later accounts for known factors. If however one uses it to jump ahead, someone else can create a similar graph in a different locations and time to create the opposite conclusion. (Small note about the time period). It is worth looking at the period between April and August. The two lines swap places which each other. St. Louis started out with a higher rate than Kansas city, and end up with a lower rate afterward. This is a pretty common pattern and follow the old "even out the curve" concept.

gumby 5y ago

Note that this graph was created by the reporters and was not generated by the health department. The labeling is weird. The reinstatement arrow should point SSW not NW. That says that during the surge, those counties* had a lower death rate. Presumably the counties that ever had a mask mandate had higher compliance even during periods when the mandate was lifted, but the article doesn’t discuss any of that, and it’s only a presumption. * I think the blue line should be labeled “death rate in the four counties”.

contravariant 5y ago
How does changing the arrow change the fact that they had significantly lower case rates at the end of June while the mask mandate came into effect on July 26?
throwawaylinux 5y ago
> The reinstatement arrow should point SSW not NW. It points to the the point on the blue line at July 26. Why should it point SSW? Does SSW even intersect with the blue line at any point?

jtbayly 5y ago

Even if the change started the day after the mask mandates we would know that the drop wasn’t caused by the mask mandates. Why? Because of incubation times.

Retric 5y ago
You are assuming people would wait until the mandate was in effect to change behavior rather than for example buying masks in preparation for a mandate.
- jtbayly 5y ago
  So your contention would be that people will wear masks even when they are not mandated? I would agree that could happen. But then, that’s not a result of masks being mandated, is it?
  - Retric 5y ago
    No. I am saying if you create a mandate on date X, people will prepare for it before it comes into effect.
    - jtbayly 5y ago
      Yes, lots of things happen before and after lots of other things. But figuring out causes is a lot harder than saying something happened after something else. Regardless, if people are willing to voluntarily wear masks before they are required, like you claim, then one thing is clear: Masks do not need to be mandatory for people to wear them. Imagine if they dropped the speed limit from 70 to 50. How many people would start driving 50 a week early to "prepare"? Not many. If people are so resistant to an idea that it has to be mandated for them to do it, then they aren't going to suddenly do it before it is mandatory. And if they aren't resistant to it, then it won't take a mandate.
      - Retric 5y ago
        In theory you might be right, but we don’t have to guess people have collected actually evidence. Also, you can’t fake the response from an impending mandate without a mandate. Most people fill out their taxes early, but if taxes were optional then nobody would be filling them out. The test would simply be to look up when a mandate was announced and then when it took effect.

cm2187 5y ago

In fact, the way I read the chart, it rather proves that mask mandate were ineffective as there was no inflection point following the introduction of the mandate. Instead the two curves remained pretty much parallel, suggesting the evolution wasn't related to masks.

LongTimeAnon 5y ago
Excuse me, racist, but those masks were made by minorities, and since math and science are clear signals of white supremacy, I think it's important we raise awareness about what you're really trying to say here.
onion2k 5y ago
it rather proves that mask mandate were ineffective as there was no inflection point following the introduction of the mandate That might indicate that the mask mandate was ineffective and the evolution was due to something else, or it might indicate people didn't abide by the mandate as soon as it came in.

tinus_hn 5y ago

When you look at the world through mask tinted glasses, all the mask flags just look like flags.

gnramires 5y ago

It depends on interpretation and I think conclusions are unclear from that graph. Try this: shift the blue curve about 15 days to the left. We may then interpret masks acted in lowering the infection peak, since masks were introduced at an earlier infection stage. In other words, if St Louis reinstated masks at the same infection count as Missouri it might have seen a higher infection peak.

refurb 5y ago

This is what makes me laugh about everyone trying to figure out which country did it “right”. One country is on the down slope of a wave and get kudos for an effective strategy. Some country on an upslope get trashed. And it changes every few months. We won’t know which countries handled it well for another 5-7 years once analyses can be done that take into account the full impact of strategies. Then add on top their stats aren’t even comparable due to different levels of testing, different categorization, etc. Just looking at raw stats says Africa did really well with Covid even without the vaccine. But if you don’t test, you can’t find cases. No cases, no covid deaths.

SideburnsOfDoom 5y ago
> Just looking at raw stats says Africa did really well with Covid even without the vaccine. Africa is doing surprising well with COVID-19, considering expectations. Reasons may include: * Not kidding themselves like UK and US did that they were "world leaders", and had this in the bag. (1) * Recent and ongoing experience of combatting other diseases, e.g. HIV, TB, Ebola. 1) "In October 2019, an extensive report two years in the making placed the US and the UK first and second respectively in a global ranking of countries’ pandemic preparedness." https://www.huffingtonpost.co.uk/entry/uk-coronavirus-pandemic-preparedness-what-went-wrong_uk_5f105b86c5b6d14c3363e8d2 https://www.huffingtonpost.co.uk/entry/uk-coronavirus-pandem...
- ceejayoz 5y ago
  Another reason may be better ventilation.
  - SideburnsOfDoom 5y ago
    The last time I was in an African city there wasn't air-conditioning as standard in houses. Sure, windows were open in summer, but closed up in winter. Office buildings had the usual levels of ventilation. I can't really describe this as "better" - how about you?
  - thoughtstheseus 5y ago

shinydevops 5y ago

As someone who lives in one of the areas in this study that instituted a mask mandate, I think the clearest explanation of the lower case rates preceding the mandates is the general willingness of the population to mask prior to the dates noted on the graph. Yes, the most recent mask mandates weren't instituted until July 26th, but, for whatever my anecdata is worth, masking use in the more urban areas was already substantially higher than it was in the areas without the mandates. There's also the small matter of the more populous areas having higher vaccination rates than the state's more rural areas. To me, the story here is not the data itself; it's another example of elected officials hiding data that doesn't agree with their position. Is the headline the best interpretation of the data? Not at all. But it's one more data set showing that the areas that are most closely following relevant recommendations are seeing better outcomes than areas that aren't.

obelos 5y ago

I think it may ultimately be more useful to think of mask mandates as an effect rather than a cause of reduced disease spread. Communities that are culturally predisposed toward prosociality don't actually need mandates to produce collective behaviors that reduce spread. It's politically viable to impose a mask mandate in those places, even though it's unnecessary for producing a public health impact. The converse, in areas where it's politically infeasible for public officials to impose a mandate, appears in a population where individuals are not predisposed to adopting public health measures on their own.

Pxtl 5y ago
Yep. There's a very strong correlation simply by political affiliation. This Washington Post columnist has some very telling graphs: https://twitter.com/pbump/status/1466261627074920452 https://twitter.com/pbump/status/1466261627074920452 Basically, the more urban and politically blue the county is, the more success they had against COVID, despite the fact that urban locations with higher density and more shared spaces have an intrinsic disadvantage in stopping the spread of disease. By politicizing public health measures, they got outcomes split by political culture.

orangecat 5y ago

Exactly. If you remove the labels from the two lines and then ask which set of counties imposed mask mandates in July, there would be no way to tell. If anything, you might think it was the higher line; "see, their cases were spiraling out of control, then they required masks and their cases peaked and declined at the same time as the less hard hit counties". Unless that chart is a horribly misleading presentation of the data (quite possible!), it's evidence against mask mandates having any discernible impact.