Covid $$$ Income Hospitals - Big Pharma

What will be the total hospital payouts for all the combined Covid cases?  

  No Wonder Big Pharma pushed this bioweapon on the people. 

 

I'm rechecking these numbers. If this is how much Hospitals earned from Covid I see why the push used to get everyone inoculated with the bioweapon:
[All States] Total Per Covid Patient $2,631,471,568.63
Average [State] per Covid Patient $171,431.37 #BigPharma https://t.co/ZhMbo84bnZ

— Scotty (@StLHandyMan) April 3, 2022

HHS recently began distributing the first $30 billion of emergency funding designated for hospitals in the Coronavirus Aid, Relief, and Economic Security Act. Some of the states hit hardest by the COVID-19 pandemic will receive less funding than states touched relatively lightly, according to an analysis by Kaiser Health News. 

Missouri $175,000 received by the Government for each covid case reported State-by-state breakdown of federal aid per COVID-19 case

What sort of care did the victims of the bioweapon receive in West Virginia compared to New York? pic.twitter.com/0u1QBh9thm

— Scotty (@StLHandyMan) April 3, 2022

What sort of Car was provided to the different states?  

The first round of grants will be distributed based on historical share Medicare revenue, not based on COVID-19 burden. Therefore, hard-hit states like New York will receive far less per COVID-19 case than most other states.  

HHS said it doled out the first slice of funding based on Medicare revenue to get support to hospitals as quickly as possible. The agency said the next round of grants "will focus on providers in areas particularly impacted by the COVID-19 outbreak," rural hospitals and other healthcare providers that receive much of their revenues from Medicaid.

Below is a breakdown of how much funding per COVID-19 case each state will receive from the first $30 billion in aid. Kaiser Health News used a state breakdown provided to the House Ways and Means Committee by HHS along with COVID-19 cases tabulated by The New York Times for its analysis. 

Missouri $175,000 received by the Government for each covid case reported State-by-state breakdown of federal aid per COVID-19 case https://t.co/KPaU6ZdScr?

— Scotty (@StLHandyMan) April 3, 2022

per COVID-19 case 

Alabama
$158,000 

Alaska
$306,000 

Arizona
$23,000

Arkansas
$285,000

California
$145,000 

Colorado
$58,000 

Connecticut
$38,000

Delaware
$127,000

District of Columbia
$56,000

Florida
$132,000

Georgia
$73,000

Hawaii
$301,000

Idaho
$100,000 

Illinois
$73,000

Indiana
$105,000

Iowa
$235,000

Kansas
$291,000

Kentucky
$297,000

Louisiana
$26,000

Maine
$260,000

Maryland
$120,000

Massachusetts
$44,000

Michigan
$44,000

Minnesota
$380,000

Mississippi
$166,000

Missouri
$175,000

Montana
$315,000

Nebraska
$379,000

Nevada
$98,000

New Hampshire
$201,000

New Jersey
$18,000

New Mexico
$171,000

New York
$12,000

North Carolina
$252,000

North Dakota
$339,000

Ohio
$180,000

Oklahoma
$291,000

Oregon
$220,000

Pennsylvania
$68,000

Rhode Island
$52,000

South Carolina
$186,000

South Dakota
$241,000

Tennessee
$166,000

Texas
$184,000

Utah
$94,000

Vermont
$87,000

Virginia
$201,000

Washington
$58,000

West Virginia
$471,000

Wisconsin
$163,000

Wyoming
$278,000

What will be the total hospital payouts for all the combined Covid cases? This number is going to be huge. No Wonder Big Pharma pushed this bioweapon on the people. Greedy B'stards.

— Scotty (@StLHandyMan) April 3, 2022

Covid19 Case Graphs with Reports MO

An interactive visualization of the exponential spread of COVID-19 in the MidWestern States, with additional  Missouri and St.Louis highlights

Missouri Highlighted Covid-19 Cases per day 

https://tidbitsbyscotty.blogspot.com/2021/12/covid19-case-graphs-with-reports-mo.html

Detailed Data Report: New Confirmed COVID-19 Cases per Day Midwest States only

Largest percent increases since one week ago:

1. Wisconsin: +57.52% change
2. Illinois: +0.1% change
3. Iowa: -0.86% change
4. Ohio: -2.57% change
5. Indiana: -6.03% change
Kansas: -8.01% change
Missouri: -9.97% change
Nebraska: -15.27% change
Michigan: -16.55% change
Minnesota: -17.68% change
North Dakota: -26.74% change
South Dakota: -27.62% change

Largest percent decrease since one week ago:

1. South Dakota: -27.62% change
2. North Dakota: -26.74% change
3. Minnesota: -17.68% change
4. Michigan: -16.55% change
5. Nebraska: -15.27% change
Missouri: -9.97% change
Kansas: -8.01% change
Indiana: -6.03% change
Ohio: -2.57% change
Iowa: -0.86% change
Illinois: +0.1% change
Wisconsin: +57.52% change

Comparing the Total Vaccine vs Deaths for Missouri link

Missouri Vaccination Stats vs Deaths for Dec 2020 to Dec 2021 Link 

Detailed Data Report: Total COVID-19 vaccines allocated by States/Territories

This report is generated based entirely on the visualization options you have selected and includes only the data displayed above. As you change the chart options, you can regenerate the report with your new data selection. (Click on any country in this report to add it as an additional highlight.)

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Largest percent increases since one week ago:

1. Missouri: +0% change

Largest raw increases since one week ago:

1. Missouri: +0 vaccines allocated

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Largest percent decrease since one week ago:

1. Missouri: +0% change

Largest raw decrease since one week ago:

1. Missouri: +0 vaccines allocated

Try the Interactive Map to Track the Covid-19 Fiasco for your state or Territory. 91-DIVOC

 

Detailed Data Report: New People fully vaccinated from COVID-19 per Day link

This report is generated based entirely on the visualization options you have selected and includes only the data displayed above. As you change the chart options, you can regenerate the report with your new data selection. 

 

Guide to the 91-DIVOC Visualizations

Data Sources

All of the data presented on this visualization comes from a trusted, high-quality data source: either Johns Hopkins University, Oxford University (Our World in Data), or The Atlantic (COVID Tracking Project). You can switch between the data sources by using the "Data Source" control at the top of the visualization. By default, Johns Hopkins University is displayed by default but your data selection can be stored by bookmarking a "Direct Link" that is displayed below each of the visualizations. All data sets are updated multiple times each day.

In the visualization controls, the "Data" selection allows you view various different data about COVID-19, including cases, deaths, tests, hospitalizations, test positivity rates, case fatality rates, and more. If a data selection is not available for a selected source, you will be prompted to switch to a data source where the data is available.

The specific data source used will always be displayed in the lower-right corner of the graph.

Regions

In addition to the country and state data provided by the data sources, several regions are added for additional context. These regions include:

1. All World Health Organization (WHO) regions, which includes:
   • African Region (WHO-AFRO)
   • Region of the Americas (WHO-PAHO)
   • South-East Asia Region (WHO-SEARO)
   • European Region (WHO-EURO)
   • Eastern Mediterranean Region (WHO-EMRO)
   • Western Pacific Region (WHO-WPRO)
2. The European Union, based off the current union of 27 members states ("EU-27"). Note that the EU-27 does not include the United Kingdom.
3. The four United States' US Census Bureau-designated regions:
   • Northeast, which includes New Jersey and Pennsylvania and states further to the northeast
   • South, which includes Delaware, Maryland, West Virginia, Kentucky, Arkansas, Oklahoma, Texas, and all states south
   • Midwest, which includes the Dakotas, Nebraska and Kansas
   • West, which includes Hawaii and Alaska

Each region can be selected as a "Highlight" option in the controls below each graph. Additionally, by choosing "+Add Additional Highlight", multiple selections can be highlighted on each graph.

Normalized Data by Population

The first two visualizations displays the raw case data (ex: number of cases, deaths, tests, etc). The last two visualizations displays the same data normalized by the official population displayed in cases per 100,000 people. This normalized view provides a more equatable comparison between regions of different sizes (ex: California, Texas, Illinois, and New York will have more cases if the distribution of cases were uniform simply because they have more residents). The formula used is:

(data value) / (population) * 100,000

The population of each country is sourced from the following Wikipedia pages:

• For populations of countries, "List of countries and dependencies by population"
• For populations of US states and territories, "List of states and territories of the United States by population"

Additionally, the use of data per 100,000 people provides an easy translation to a percentage since 1,000 is 1% of 100,000. Therefore, the thousands-digit comma can be thought of as the decimal point for viewing the data as a percentage of the population. For example, on Oct. 14, 2020, Johns Hopkins' data shows the United States to have a cumulative total of 2,403 confirmed cases / 100,000 people -- or 2.403% of the population of the United States.

Direct Link

Finally, every change you make to the visualization will generate a "Direct Link" that will link to the specific visualization you have created. You can bookmark this link to view it later or share it with friends/family to share the exact graph you are exploring.

More Information

There are many more options to explore in the visualization controls, including the ability to save an image or video/GIF of your graph. This 91-DIVOC project is a side-project of mine while I'm not working on teaching the next generation of students about Computer Science at The University of Illinois. You can read about my motivation for creating this project, and some of the uses it has received, on the "Overview and Motivations " page.

Finally, if you have any questions or feedback, you can write to me (faculty website, and additional contact information at the bottom of this page) -- I read all of the e-mails, reply to as many as I'm able to, and I'd love to hear from you! :)