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Originally posted by JEWELSTAITEFAN:
It will take me awhile to assemble and compose this thread opening.


I have observed that perhaps the most safe from the virus are men who wear beards. They are not working in meat-packing plants. Mostly not in nursing homes, or hospitals. Often outdoorsy, where the bears are not contagious. And masks don't seal for them, so they are not going places where masks are required.

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Many folk seem to focus on the State which did everything worng, everything to maximize the number of deaths and cases, which is New York, and Governor Fredo Gump.
Why not instead focus on States which did everything right, like Florida - with a greater population than NY, and a tiny fraction of the number of deaths. NY tried to kill off as many old folks as they could, FL did the opposite.

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Originally posted by JEWELSTAITEFAN:
ICU Beds and Hospital Beds.


18 March: the issue of Certificate Of Need is exposed, which curtails number of hospital beds and equipment, preventing adequate supplies from being available. Fake News ignores this, since it was started and championed by New York. Something like 37 States have CON Laws, outlawing adequate medical facilities and supplies.

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Originally posted by SIGNYM:

Quote:

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Originally posted by JEWELSTAITEFAN:
It will take me awhile to assemble and compose this thread opening.


Many folk seem to focus on the State which did everything worng, everything to maximize the number of deaths and cases, which is New York, and Governor Fredo Gump.
Why not instead focus on States which did everything right, like Florida - with a greater population than NY, and a tiny fraction of the number of deaths. NY tried to kill off as many old folks as they could, FL did the opposite.

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Floida is having its own surge of cases right now, 10,000+ in one day. Only time will tell if Florida did the "right thing" or if Florida is going to have a big problem too.

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Originally posted by 1KIKI:
The newest idea of how the virus spreads relates to 2 different scenarios: the vast majority scenario where infected people will spread the virus to no one, or at most 2 people; and the superspreader scenario where one person will spread to virus to many, many people, as many as over 100.

I liken the vast majority scenario to a smouldering fire - conditions are right for it to neither go out nor take off. But the superspreader scenario is like that smouldering fire that finally gets a good gulp of air and explodes into an inferno. And NYC is like a wildland fire that generates its own weather, as conditions were right for superspreader to superspreader transmission.

It's fire in all instances, just under different conditions.

Florida was smouldering for a long time, even after restrictions were put in place. Then restrictions were lifted despite the state not meeting guidelines for reopening -

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Do you think the superspreder episodes are more likely in environs with elevators, subways, Metyro buses (rapid transit)?

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Originally posted by 6IXSTRINGJACK:
I've posted that video in its own thread and in two others now, and not a single person has said anything about it.

I'm pretending real hard to be curious why that is.

Do Right, Be Right. :)

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Originally posted by JEWELSTAITEFAN:
Effects of the Lockdown.



Unemployment by State.
Columns are: State, Governor's Party, date of LockDown, then Month/Year Unemployment percentages. The last 2 columns are the estimated difference between the expected Unemployment rate and the actual rate resultant from LockDown - for April and for May.

ST G Lk/Dn 3/19 4/19 5/19 2/20 3/20 4/20 5/20 4Dif 5Dif
AR R ----- 3.5% 3.0% 3.4% 3.9% 4.9% 10.3 09.4 05.8 04.6
NE R ----- 3.4% 2.9% 3.0% 3.0% 4.2% 08.6 05.1 05.2 02.1
ND R ----- 3.0% 2.5% 2.1% 2.8% 2.7% 09.2 08.6 07.0 06.8
OK R ----- 3.2% 2.8% 3.2% 3.0% 3.0% 14.3 12.6 11.7 09.6
SD R ----- 3.6% 3.3% 3.1% 3.6% 3.4% 11.0 09.2 07.9 06.3
TX R ----- 3.5% 3.0% 3.1% 3.6% 5.1% 13.0 12.7 10.0 09.6
WY R ----- 3.9% 3.5% 3.3% 4.3% 4.3% 9.6% 08.7 05.7 05.0


AL R 4 Apr 3.4% 2.6% 2.5% 2.9% 3.0% 13.3 09.4 11.1 07.3
AK R 26Mar 6.8% 6.3% 6.0% 5.9% 5.9% 13.7 12.5 08.3 07.4
AZ R _ Apr 4.7% 4.5% 4.6% 4.4% 6.1% 12.9 08.7 08.2 04.4
CA D 4 Mar 4.5% 3.8% 3.6% 4.3% 5.8% 16.1 15.9 12.3 12.3
CO D 25Mar 3.1% 2.8% 2.6% 2.9% 4.8% 12.2 10.0 09.4 07.4
CT D 20Mar 4.0% 3.3% 3.6% 4.4% 3.9% 08.0 09.3 04.8 06.8
DE D 20Mar 3.7% 3.5% 3.4% 4.0% 5.0% 14.8 15.5 11.0 11.8
FL R 8 Mar 3.2% 2.9% 3.0% 2.8% 4.3% 13.3 14.3 10.4 11.3
GA R 3 Apr 3.6% 3.1% 3.3% 3.5% 4.5% 12.2 09.5 09.1 06.2
HI D ----- 2.7% 2.6% 2.6% 2.6% 2.3% 23.5 22.5 21.3 20.3
ID R 25Mar 3.5% 3.0% 2.6% 3.1% 2.6% 12.3 08.6 10.2 06.0
IL D 20Mar 4.4% 3.6% 3.5% 3.5% 4.2% 16.9 14.7 14.5 11.4
IN R 20Mar 3.7% 2.9% 3.0% 3.4% 3.4% 17.0 11.9 14.4 09.2
IA R _ Apr 3.2% 2.5% 2.4% 3.1% 3.6% 10.7 09.7 07.8 06.9
KS D 28Mar 3.4% 2.8% 3.0% 3.3% 2.9% 11.6 09.8 09.3 07.3
KY D 6 Mar 4.7% 3.9% 4.2% 4.3% 5.3% 16.1 10.9 12.2 06.7
LA D 20Mar 4.1% 3.8% 4.3% 4.3% 6.3% 14.5 13.1 10.7 08.9
ME D _ Mar 3.9% 3.4% 3.0% 4.3% 3.6% 11.3 09.4 08.2 06.7
MD R 5 Mar 3.7% 3.2% 3.4% 3.6% 3.5% 10.1 09.7 07.1 06.5
MA R _ Mar 3.3% 2.7% 2.9% 3.3% 3.0% 15.9 16.3 13.5 13.7
MI D _ Mar 4.6% 3.7% 3.7% 3.6% 4.0% 23.8 20.7 20.7 17.6
MN D 25Mar 3.9% 3.1% 2.7% 3.6% 3.5% 08.6 09.4 05.9 07.1
MS R 3 Apr 5.1% 4.7% 5.3% 5.1% 4.8% 15.6 10.5 11.2 05.5
MO R 2Citi 3.7% 2.7% 3.0% 3.7% 3.9% 09.8 09.8 06.9 06.6
MT D 26Mar 4.2% 3.3% 2.9% 4.2% 4.2% 11.9 08.5 08.6 05.6
NV D 24Mar 4.1% 3.9% 3.8% 3.8% 6.9% 29.8 25.2 25.9 21.4
NH R 25Mar 2.9% 2.5% 2.4% 3.1% 2.8% 17.2 14.5 14.8 12.2
NJ D 21Mar 3.7% 2.8% 3.0% 4.2% 3.7% 15.9 14.9 13.1 11.9
NM D 24Mar 4.8% 4.4% 4.5% 5.0% 6.2% 11.4 08.8 06.8 04.1
NY D 4 Mar 4.2% 3.6% 3.6% 3.9% 4.2% 15.0 14.2 11.4 10.6
NC D 25Mar 4.0% 3.5% 3.9% 3.7% 4.3% 12.5 12.7 08.7 08.5
OH R 20Mar 4.2% 3.5% 3.7% 4.7% 5.4% 17.4 13.4 13.4 09.2
OR D 8 Mar 4.5% 3.8% 3.4% 3.8% 3.9% 14.8 13.8 11.6 11.2
PA D 7Cnty 4.3% 3.5% 4.0% 5.1% 5.9% 15.5 12.9 11.3 08.1
RI D 26Mar 3.9% 3.2% 3.3% 4.0% 5.0% 17.8 16.0 14.6 12.7
SC R 7 Apr 3.4% 2.6% 2.7% 3.0% 3.0% 12.2 12.2 10.0 09.9
TN R _ Mar 3.5% 2.9% 3.1% 3.8% 3.7% 15.0 11.0 11.9 07.7
UT R 6 Mar 3.0% 2.6% 2.6% 2.8% 4.1% 10.3 08.4 07.7 05.8
VT R _ Mar 2.7% 2.5% 2.2% 2.6% 3.4% 16.8 12.6 14.3 10.4
VA D 24Mar 3.0% 2.4% 2.7% 2.8% 3.3% 10.8 09.2 08.5 06.5
WA D 8 Mar 4.8% 4.1% 4.1% 4.2% 5.4% 15.8 14.8 12.3 11.3
WV D 24Mar 5.2% 4.5% 4.5% 5.5% 6.1% 15.8 12.5 10.4 07.1
WI D 25Mar 3.8% 3.2% 3.1% 4.0% 3.5% 13.6 11.7 10.7 08.9

Color codes: Green for States which allowed their economies to go, did not LockDown - all of which were GOP.
Yellow for States which drastically Locked Down for Wuhan Coronavirus.
Red for GOP led States which limited Employment impact.

I did not highlight NV or HI because they were affected by travel restrictions more than anybody else. VA was helped a lot because D.C. was not really Locked Down, Federal Government was not sent home.

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Quote:

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Originally posted by JEWELSTAITEFAN:
Wisconsin, a microcosm model of America.

I understand that many of you are not familiar with the geography or population of WI.
60% of the Statee's population is in the lower right corner of the state, the southeast corner. This is Milwaukee area, down towards Chicago (essentially across the state border), along the shore of Lake Michigan.
Wisconsin has 72 Counties.
Milwaukee County has consistently supplied half the cases in the State, and more than half the deaths. The next tier of concentration has been the corridor to Chicago, Racine and Kenosha Counties. Next tier has been the counties surrounding Milwaukee County, plus Dane County (Madison). These few counties (suburbs and bedroom Communities) account for the vast majority of cases and deaths in WI. Adding in the counties surrounding Dane Co, and the cast majority of cases and deaths is included.

Since about 60 Counties had no case activity to speak of, Gov Skeletor Evers shut down the entire state. Milwaukee, Racine, and Kenosha remained the leading hotspots. The age groups for cases were dominated by 50-90 year olds. Then the 2 meatpacking plants in Brown County (Green Bay) had positives, and were called outbreaks. Brown County launched up fast enough to surpass all other counties in WI, before leveling off. After a week or so, Milwaukee and Racine retook the lead.
The Gov did not allow any part of the State to reopen, despite any lack of case activity, and even extended the lockdown beyond legal authority, until he was sued and the Supreme Court ordered reopening.

Some data provided here:
www.dhs.wisconsin.gov/covid-19/cases.htm
But really only current, zip for historical.

I see that in WI, there is one group which has absolutely ZERO cases. Those who are of the gender "other" than male or female.


For the following Table of data:
First is Day, Date/Month.
Second column of numbers is the total number of tests with Negative results, as posted by WI website (does not actually include all Negative tests, so this figure is undercounted.)
Third column is total number of persons tested positive so far by this date.
Fourth column is the total number of tests (sum of the prior 2 columns)
Fifth column is the number of Positive results, New since the day before and / number of total test results, New since the day before.
Sixth column is the percent Positive (divided by the total) for the day.
Seventh column is the number of tests stated as the Capacity for that day.
Eighth column is the percent of Positive results, New for today, divided by the Capacity for the day. This helps mitigate the number games played by the delaying and manipulating by the Stats department.
Ninth and Tenth columns are number of cases ever Hospitalized, and that percent of total cases.
Eleventh column is number of cases ever under ICU. Note this figure started out greater than the number of dead, but then number of dead outpaced this figure.
Twelfth and thirteenth columns are number of dead and percent of total cases.
Fourteenth column is Active Cases, either percent (%), or number, or percent-number.

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Quote:

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Originally posted by JEWELSTAITEFAN:
Wisconsin, a microcosm model of America.

I understand that many of you are not familiar with the geography or population of WI.
60% of the Statee's population is in the lower right corner of the state, the southeast corner. This is Milwaukee area, down towards Chicago (essentially across the state border), along the shore of Lake Michigan.
Wisconsin has 72 Counties.
Milwaukee County has consistently supplied half the cases in the State, and more than half the deaths. The next tier of concentration has been the corridor to Chicago, Racine and Kenosha Counties. Next tier has been the counties surrounding Milwaukee County, plus Dane County (Madison). These few counties (suburbs and bedroom Communities) account for the vast majority of cases and deaths in WI. Adding in the counties surrounding Dane Co, and the cast majority of cases and deaths is included.

Since about 60 Counties had no case activity to speak of, Gov Skeletor Evers shut down the entire state. Milwaukee, Racine, and Kenosha remained the leading hotspots. The age groups for cases were dominated by 50-90 year olds. Then the 2 meatpacking plants in Brown County (Green Bay) had positives, and were called outbreaks. Brown County launched up fast enough to surpass all other counties in WI, before leveling off. After a week or so, Milwaukee and Racine retook the lead.
The Gov did not allow any part of the State to reopen, despite any lack of case activity, and even extended the lockdown beyond legal authority, until he was sued and the Supreme Court ordered reopening.

Some data provided here:
www.dhs.wisconsin.gov/covid-19/cases.htm
But really only current, zip for historical.

I see that in WI, there is one group which has absolutely ZERO cases. Those who are of the gender "other" than male or female.


For the following Table of data:
First is Day, Date/Month.
Second column of numbers is the total number of tests with Negative results, as posted by WI website (does not actually include all Negative tests, so this figure is undercounted.)
Third column is total number of persons tested positive so far by this date.
Fourth column is the total number of tests (sum of the prior 2 columns)
Fifth column is the number of Positive results, New since the day before and / number of total test results, New since the day before.
Sixth column is the percent Positive (divided by the total) for the day.
Seventh column is the number of tests stated as the Capacity for that day.
Eighth column is the percent of Positive results, New for today, divided by the Capacity for the day. This helps mitigate the number games played by the delaying and manipulating by the Stats department.
Ninth and Tenth columns are number of cases ever Hospitalized, and that percent of total cases.
Eleventh column is number of cases ever under ICU. Note this figure started out greater than the number of dead, but then number of dead outpaced this figure.
Twelfth and thirteenth columns are number of dead and percent of total cases.
Fourteenth column is Active Cases, either percent (%), or number, or percent-number.

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Originally posted by 6IXSTRINGJACK:
I'm just disappointed that here we are in the middle of August and they still have only managed to attribute less than 20% of the daily US deaths to The Coomph.


Clearly they're not trying hard enough.



C'mon Democrats! You've got an election you're trying to steal here. You can do better than this.

Do Right, Be Right. :)

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Originally posted by Jongsstraw:

Quote:

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Originally posted by 6IXSTRINGJACK:
I'm just disappointed that here we are in the middle of August and they still have only managed to attribute less than 20% of the daily US deaths to The Coomph.

Clearly they're not trying hard enough.

C'mon Democrats! You've got an election you're trying to steal here. You can do better than this.

Do Right, Be Right. :)

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This whole scam has been a libtard wet dream conspiracy from the start.

The CDC released a shocking report Friday that finally told the truth about the absurdly inflated mortality rate attributed to Covid.
https://www.thegatewaypundit.com/2020/08/shock-report-week-cdc-quietly
-updated-covid-19-numbers-9210-americans-died-covid-19-alone-rest-serious-illnesses/

94% of Covid "deaths" were actually due to other, more explainable things, terminal things....things like cancer, heart attacks, and car crashes to name a few. These so-called Covid death patients were going to die soon even without Covid. 180,000 have NOT died from Covid. Only 9,000 in 8 months have. This whole thing has been a total bullshit lie.

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Originally posted by 1KIKI:
"Since about 60 Counties had no case activity to speak of ..." That's not true. If you look at the map, every single county https://www.dhs.wisconsin.gov/covid-19/cases-map.htm has a minimum of 10 - 50 cases (19 out of 72 are at that minimum), and of course 53/72 have significantly more.

I thought maybe the data table confused you. It did me at first until I downloaded it, and realized that their data table added new cases by APPENDING new data to the bottom. So for example, Crawford county's first 2 listings had 0 cases ... but the third listing had 22 (IIRC), and there were roughly 287 listings for the Crawford county in the entire data table to date.

Maybe you didn't realize the newest data that showed the updated information was at the bottom, which might be why you assumed so many counties had no listings.


"Maybe so many of these positives are obtained from autopsy, from like stubbed toe or overdose. "

I'm sorry to see you've taken to posting lies. Or maybe you found a narrative that you agreed with, and couldn't be bothered to check any further? Here's the Wisconsin law about who gets to fill out and sign the death record https://docs.legis.wisconsin.gov/statutes/statutes/69/I/18 . Basically it's the attending physician, another physician who worked with the attending physician in caring for the individual if the attending is unavailable, the chief medical officer of the hospital or nursing home in which the death occurred, or a coroner or ME (if required).

What you're claiming is that these people are willing to lose their medical licenses in order to falsify a cause of death. And not only that, that so many of them are willing to do so in such LARGE numbers that it'll skew the statistics. Do you really want to stick by that claim?

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Since about 60 Counties had no case activity to speak of, Gov Skeletor Evers shut down the entire state.

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Quote:

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Originally posted by JEWELSTAITEFAN:
Wisconsin, a microcosm model of America.


Some data provided here:
www.dhs.wisconsin.gov/covid-19/cases.htm
But really only current, zip for historical.

I see that in WI, there is one group which has absolutely ZERO cases. Those who are of the gender "other" than male or female.


For the following Table of data:
First is Day, Date/Month.
Second column of numbers is the total number of tests with Negative results, as posted by WI website (does not actually include all Negative tests, so this figure is undercounted.)
Third column is total number of persons tested positive so far by this date.
Fourth column is the total number of tests (sum of the prior 2 columns)
Fifth column is the number of Positive results, New since the day before and / number of total test results, New since the day before.
Sixth column is the percent Positive (divided by the total) for the day.
Seventh column is the number of tests stated as the Capacity for that day.
Eighth column is the percent of Positive results, New for today, divided by the Capacity for the day. This helps mitigate the number games played by the delaying and manipulating by the Stats department.
Ninth and Tenth columns are number of cases ever Hospitalized, and that percent of total cases.
Eleventh column is number of cases ever under ICU. Note this figure started out greater than the number of dead, but then number of dead outpaced this figure.
Twelfth and thirteenth columns are number of dead and percent of total cases.
Fourteenth column is Active Cases, either percent (%), or number, or percent-number.

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Quote:

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Originally posted by JEWELSTAITEFAN:
Wisconsin, a microcosm model of America.


For the following Table of data:
First is Day, Date/Month.
Second column of numbers is the total number of tests with Negative results, as posted by WI website (does not actually include all Negative tests, so this figure is undercounted.)
Third column is total number of persons tested positive so far by this date.
Fourth column is the total number of tests (sum of the prior 2 columns)
Fifth column is the number of Positive results, New since the day before and / number of total test results, New since the day before.
Sixth column is the percent Positive (divided by the total) for the day.
Seventh column is the number of tests stated as the Capacity for that day.
Eighth column is the percent of Positive results, New for today, divided by the Capacity for the day. This helps mitigate the number games played by the delaying and manipulating by the Stats department.
Ninth and Tenth columns are number of cases ever Hospitalized, and that percent of total cases.
Eleventh column is number of cases ever under ICU. Note this figure started out greater than the number of dead, but then number of dead outpaced this figure.
Twelfth and thirteenth columns are number of dead and percent of total cases.
Fourteenth column is Active Cases, either percent (%), or number, or percent-number.

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Quote:

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Originally posted by JEWELSTAITEFAN:
Wisconsin, a microcosm model of America.


For the following Table of data:
First is Day, Date/Month.
Second column of numbers is the total number of tests with Negative results, as posted by WI website (does not actually include all Negative tests, so this figure is undercounted.)
Third column is total number of persons tested positive so far by this date.
Fourth column is the total number of tests (sum of the prior 2 columns)
Fifth column is the number of Positive results, New since the day before and / number of total test results, New since the day before.
Sixth column is the percent Positive (divided by the total) for the day.
Seventh column is the number of tests stated as the Capacity for that day.
Eighth column is the percent of Positive results, New for today, divided by the Capacity for the day. This helps mitigate the number games played by the delaying and manipulating by the Stats department.
Ninth and Tenth columns are number of cases ever Hospitalized, and that percent of total cases.
Eleventh column is number of cases ever under ICU. Note this figure started out greater than the number of dead, but then number of dead outpaced this figure.
Twelfth and thirteenth columns are number of dead and percent of total cases.
Fourteenth column is Active Cases, either percent (%), or number, or percent-number.

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Originally posted by JEWELSTAITEFAN:
Effects of the Lockdown.

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North America 12,234,890 - Deaths 725 Per Millions
South America 10,606,820 - Deaths 740
Central America 1,571,442 - Deaths 640 Per Million

East Asia 315,416 - Deaths 4 per Million?

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Quote:

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Originally posted by JEWELSTAITEFAN:
Effects of the Lockdown.

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