Whoooooaa....why was my post deleted?

[5-time state chump]

I posted in 2 topics...that in my opinion....if they keep testing kids...that seasons won't happen and that we need to stop testing kids. DOCTORS have said it. You want names? Are you part of the Covid-19 Response Team?

Deleted for that? THAT's the kind of censorship you have? LOL. You decide on people's opinions? What a crock of crap.

Please explain.

[NDPREP]

If your opinion is really bad and can cause damage to someone I see why they deleted it. The solution to things is not to bury your head in the sand, ND has done that for too long in other regards.

One thing worrying is the increase in athletes who post covid recovery are being discovered with heart swelling

https://www.espn.com/college-football/story/_/id/29633697/heart-condition-linked-covid-19-fuels-power-5-concern-season-viability

[5-time state chump]

If your opinion is really bad and can cause damage to someone I see why they deleted it. The solution to things is not to bury your head in the sand, ND has done that for too long in other regards.

One thing worrying is the increase in athletes who post covid recovery are being discovered with heart swelling

https://www.espn.com/college-football/story/_/id/29633697/heart-condition-linked-covid-19-fuels-power-5-concern-season-viability

So you posted a link? So you're saying links count. I mean you used one to show a viewpoint.

So what if I post a link of the doctors saying the whole thing is poo-poo? I will have then posted a link showing a viewpoint.

Who's link is correct? Yours or mine?

[JackofDiamonds]

Why can't content stay on message boards when someone states their opinion? Right, wrong, or other it gives High School fans something to debate and keeps message boards alive. Only way it should come off is when it gets abusive. IDK Just my take.

[Run4Fun2009]

Why can't content stay on message boards when someone states their opinion? Right, wrong, or other it gives High School fans something to debate and keeps message boards alive. Only way it should come off is when it gets abusive. IDK Just my take.

Things got personal and way off topic after his original post. Those posts were deleted...the site preceded to take his original post with the deleted replies (which was stated in a PM to original poster which has not been opened yet)

Let’s talk sports while we have them.

[hoophoophoop]

I'm with Chump, this covid thing is blown way out control, until someone shows me a spike in deaths in 2020 then i will get concerned, same deaths in 2020 than any other year, check it out for yourselves. Poor kids get screwed out of what was supposed to be the best times of their lives for a cold. The heart thing is for guys over 50 by the way.

[NDPREP]

I'm with Chump, this covid thing is blown way out control, until someone shows me a spike in deaths in 2020 then i will get concerned, same deaths in 2020 than any other year, check it out for yourselves. Poor kids get screwed out of what was supposed to be the best times of their lives for a cold. The heart thing is for guys over 50 by the way.

28% more deaths than what they expected there should have been March to May

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2767980

[Bison-Vikes #1]

I'm with Chump, this covid thing is blown way out control, until someone shows me a spike in deaths in 2020 then i will get concerned, same deaths in 2020 than any other year, check it out for yourselves. Poor kids get screwed out of what was supposed to be the best times of their lives for a cold. The heart thing is for guys over 50 by the way.

28% more deaths than what they expected there should have been March to May

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2767980

Interesting article. Read through the entire article. Understand what model (Poisson regression) and variables they use in their regression model and also read through all supplied appendices. Remember that the function of using the Poisson regression is to "forecast" by using some known data, using a number of variables and also a function f(x) to fit the observed data. Once they feel they have a fit, in other words feel their regression model replicates some known data, they use this model to predict going forward.

What's most interesting is seeing the results and which states (remember they supply their state's deaths) bring the "overall death rate" up and which are relatively unchanged from any other year. Here is the report's findings copied from the link you gave:

"The changes in mortality that occurred during the pandemic varied by state and region. In New York City, all-cause mortality rose 7-fold above baseline at the peak of the pandemic, for a total of 25 100 (95%prediction interval, 24 800-25 400) excess deaths, of which 26% were unattributed to COVID-19 (Table and Figure 2). In contrast, in the rest of New York State, the increase was more moderate, rising 2-fold above baseline and resulting in 12 300 (95% prediction interval, 11 900-12 700) excess deaths. There were notable per capita increases in rates of death due to any cause in many other states, including New Jersey, Massachusetts, Louisiana, Illinois, and Michigan, where the number of deaths greatly exceeded the expected levels (Table, Figure 2, and Figure 3; eFigure 2 in the Supplement for additional states). Other states, particularly smaller states in the central United States and northern New England, had some COVID-19 deaths reported in official tallies but small or no detectable increases in all-cause deaths above expected levels (Table).

The gap between the reported COVID-19 deaths and the estimated all-cause excess deaths varied among states (Table; eFigure 3 in the Supplement). For instance, California had 4046 reported deaths due to COVID-19 and 6800 (95% prediction interval, 6100-7500) excess all-cause deaths, leaving 41% of the excess deaths unattributed to COVID-19 (Table). Texas and Arizona had even wider gaps, with approximately 55% and 53% of the excess deaths unattributed to COVID-19, respectively. In contrast, there was better agreement between the reported COVID-19 deaths and the excess all-cause deaths in Minnesota, with 12% unattributed to COVID-19 (Table)."

Look at the states involved that were well over the predicted results, followed the study's results and look at the states that were basically unchanged from any other year's deaths and draw your own conclusion. Science is a wonderful thing but remember that the input data is key and the results can be interpreted many different ways. Last but not least, ask yourself who paid for the study and who will benefit most from the perceived outcome of the study.