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Coronavirus (Stay on Topic)

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Seems like it's worse if you get it a second time. I've seen a few stories of people catching it twice, and it seems like most have a more difficult time the second time. That's not good if that turns out to be the general rule.
 
smast16 said:
You say tomato, I say tomato...

You say


But that's not what the study says. The study says
Community exposure 14 days before illness onset¶​
Shopping​
131 (85.6)​
141 (88.1)​
0.51​
Home, ≤10 persons​
79 (51.3)​
84 (52.5)​
0.83​
Restaurant​
63 (40.9)​
44 (27.7)​
0.01​

that Shopping was by far the largest group... 85% of people who tested positive for Covid went shopping in the 14 days prior to symptoms compared to the 40% who went to a restaurant.

Where in The left column is persons who performed 'X' 14 days prior to testing positive, and the middle column is number of persons who performed 'X' 14 days prior to being sick and having a negative Covid-19 result. The main number is persons reported for each group and the number in parenthesis is percentage of their respective groupings.

Also, of the 107 people who reported going a restaurant only 19 more went to a restaurant and tested positive for covid vs those that went to a restaurant and didn't test positive covid.

That's a barely a 17% increase... but lets shutter a whole industry over a less than 1 in 5 chance.



Just to point out, they did break this down further in the study 81% in the Positive group, and over 97% in the negative group reported that 50% or more of the patrons in the restaurant wore masks ...

Restaurant: others following recommendations such as wearing a face covering or mask of any kind or social distancing (n = 107)​
None/A few​
12 (19.0)​
1 (2.3)​
0.03​
About half/Most​
25 (39.7)​
21 (47.7)​
Almost all​
26 (41.3)​
22 (50.0)​

(Left column and middle column are the same as above. Pos. Covid on left, and Negative Covid middle with the number of responses as the main number and the percentage of the total in percentage)

Keep in mind this is also limited in scope of the seating in the restaurant per it's own words " Of note, the question assessing dining at a restaurant did not distinguish between indoor and outdoor options."

The problem with studies like these is that people do take them out of context and push them for more than they are. What's not being added here is there are Governors and local government officials using studies like this to make policy about restaurants, Bars, and other forms of employment. You have people reading a single line and taking to twitter for Gotcha liners, when even the studies own numbers don't support its own proclamations.

Like This...


but per their own numbers a few scrolls of the scroll wheel....

Restaurant: others following recommendations such as wearing a face covering or mask of any kind or social distancing (n = 107)​
None/A few​
12 (19.0)​
1 (2.3)​
0.03​
About half/Most​
25 (39.7)​
21 (47.7)​
Almost all​
26 (41.3)​
22 (50.0)​

Again, as I stated above, that's 81% and 97% reported greater than 50% usage of Masks and social distancing in Restaurants

and of Bars... (Keep in mind, Bars is lumped up with Coffeeshops...
Bar/Coffee shop​
13 (8.5)​
8 (5.0)​
0.22​

but later on, the word "Coffee shop" is dropped, but the numbers stay the same
Bar: others following recommendations such as wearing a face covering or mask of any kind or social distancing (n = 21)​
None/A few​
4 (31.8)​
2 (25.0)​
0.01​
About half/Most​
7 (53.8)​
0 (0.0)​
Almost all​
2 (15.4)​
6 (75.0)​

Nice wave of the wand to keep the heat of Starbucks... But yea, 6 people reported the bars / coffee shops didn't have masks on, but 15 did... That surely equates to more likely to see masks at a bar / coffee shop than not seeing masks at a bar / coffee shop.


/Rant
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No, I say tomato you say potato. I again recommend by professor's book if you're interested in evaluating medical literature, it appears you are. If you want the link, DM me. Also I’m just trying to be informative here, don’t take it personally...Anywho, you can't take unrelated percentages and compare them to draw your own conclusions. In your charts, you have a third column that is unlabeled. This is p-value. Notice how the p-value for restaurant is 0.01, while the p-values for home (0.81) and shopping (0.51) are much higher. This is because it is not statistically significant, which means a conclusion cannot be made that a difference in infection exists in that group.

"A p-value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p-value, the greater the statistical significance of the observed difference."

Note the p-values of ALL the locations but restaurants are all very high, except restaurants, which is <0.02 and therefore, significant.

Therefore,
that Shopping was by far the largest group... 85% of people who tested positive for Covid went shopping in the 14 days prior to symptoms compared to the 40% who went to a restaurant.
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is an incorrect conclusion to make. There's no statistically increased risk between case and control groups where shopping increased risk, because well, it didn't. Other factors MUST be contributing to those high infection rates between both case and control and people who happened to go shopping. It doesn't mean you're more likely to get covid from shopping than dining at a restaurant. This is why the CDC didn't make a statement about shopping. They are not cherry picking data or choosing what to infer, it's how you read medical literature.

Also, of the 107 people who reported going a restaurant only 19 more went to a restaurant and tested positive for covid vs those that went to a restaurant and didn't test positive covid.

That's a barely a 17% increase... but lets shutter a whole industry over a less than 1 in 5 chance.
Click to expand...
That's a wrong conclusion. Again, the trial demonstrated by the p-value that it was clinically significant. Simply counting the numbers of people out of context with the study design and statistical findings is worthless.

This is what the study found.
"Patients with symptomatic COVID-19 were more likely than uninfected controls to report some form of restaurant dining -- including indoor, patio and outdoor seating -- in the 2 weeks prior to symptom onset, CDC researchers found.

Compared to controls without COVID-19, case patients were more than twice as likely to have reported dining at a restaurant (adjusted OR 2.4, 95% CI 1.5-3.8), reported Kiva Fisher, PhD, of the CDC, and colleagues."

OR is what's called an Odds Ratio. So they're not simply looking at percent values of populations and blindly drawing conclusions, they're evaluating the data using statistics. An OR of 2.4 means the exposure group (restaurant goers) are 2.4x likely to get diagnosed with COVID-19 than the control group. This means that the CDC is justified saying 2 times likely, even though at a glance at the data tries to tell you otherwise.

1602718350738.png
 
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Jon said:
No, I say tomato you say potato. I again recommend by professor's book if you're interested in evaluating medical literature, it appears you are. If you want the link, DM me. Also I’m just trying to be informative here, don’t take it personally...Anywho, you can't take unrelated percentages and compare them to draw your own conclusions. In your charts, you have a third column that is unlabeled. This is p-value. Notice how the p-value for restaurant is 0.01, while the p-values for home (0.81) and shopping (0.51) are much higher. This is because it is not statistically significant, which means a conclusion cannot be made that a difference in infection exists in that group.

"A p-value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p-value, the greater the statistical significance of the observed difference."

Note the p-values of ALL the locations but restaurants are all very high, except restaurants, which is <0.02 and therefore, significant.

Therefore, is an incorrect conclusion to make. There's no statistically increased risk between case and control groups where shopping increased risk, because well, it didn't. Other factors MUST be contributing to those high infection rates between both case and control and people who happened to go shopping. It doesn't mean you're more likely to get covid from shopping than dining at a restaurant. This is why the CDC didn't make a statement about shopping. They are not cherry picking data or choosing what to infer, it's how you read medical literature.


That's a wrong conclusion. Again, the trial demonstrated by the p-value that it was clinically significant. Simply counting the numbers of people out of context with the study design and statistical findings is worthless.

This is what the study found.
"Patients with symptomatic COVID-19 were more likely than uninfected controls to report some form of restaurant dining -- including indoor, patio and outdoor seating -- in the 2 weeks prior to symptom onset, CDC researchers found.

Compared to controls without COVID-19, case patients were more than twice as likely to have reported dining at a restaurant (adjusted OR 2.4, 95% CI 1.5-3.8), reported Kiva Fisher, PhD, of the CDC, and colleagues."

OR is what's called an Odds Ratio. So they're not simply looking at percent values of populations and blindly drawing conclusions, they're evaluating the data using statistics. An OR of 2.4 means the exposure group (restaurant goers) are 2.4x likely to get diagnosed with COVID-19 than the control group. This means that the CDC is justified saying 2 times likely, even though at a glance at the data tries to tell you otherwise.

View attachment 50415
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Damn. Was that a good game no rematch?
 
superjames1992 said:
The restrictions on socializing outside your family might be one of the more draconian things I've ever seen. And the UK isn't the only country that's done this, to say the least.
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Probably coming to a town near you soon... not that I support that idea at all.
 
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