Coronavirus Study Confirms Overall Mortality Not Much Different Than a Bad Flu Season

With Exception of New York and New Jersey,

By Joe Hoft, GATEWAY PUNDIT July 15, 2020

On March 17, 2020, we were the first to identify that the WHO and the WHO’s Director General Tedros were pushing fraudulent numbers regarding the expected mortality of the coronavirus. The WHO over-stated the mortality rate of the virus by at least 30 times.

We then followed up with multiple posts on the subject. We reported on June 7, 2020, a study showed that when looking at the mortality rates for all causes this flu season, things aren’t much worse than a bad flu.

We followed up on this study on June 18th with more current data supporting these results.

Today we have more information based on more current data that supports our initial observations – that current mortality rates from the China coronavirus are within expectations for an above-average flu season with the exception of NYC.

Dr. Richard Cross, PhD, provided us the following information related to the China coronavirus. We have updated the following as of June 6, 2020, through week 36:

The Week 36 P-Score (0.041) for the US is could be leveling off, showing an above average flu-level mortality for the year of about 4%. – -Excess deaths have climbed by from 67.9k to 84.5k for the nation through 36 weeks. This updated level remains below the estimated 114.5k COVID-19 mortality on Worldometers (on June 06).

This study is brilliant because it takes out the CDC’s confusing directive that stated that all deaths should be counted as coronavirus deaths, even if the cause may have been another condition. By counting all deaths, no matter the cause, we can clearly see the impact of the coronavirus on the nation is ‘not much worse than a bad seasonal flu’.

The study previously reported on the New York situation:

The relative impact on total mortality of the COVID-19 event in the New York City region was in a class by itself. Figure 2 shows the increased cumulative total mortality increase as measured by the P-Score compared to previous 6-year mortality trends for each state; this is a more sensitive indicator of mortality change for each state since each state’s current mortality is based upon the previous six years mortality trend for that state. In Figure 2, New York City (NYC) mortality excess is 68% and is the highest across all locales with the current data. By week 34 in the current season, NYC is so far outside the mortality space of the other regions that it inhabited a different mortality universe altogether. It was widely reported as well that New Jersey experienced a high level of COVID-19 deaths, which translated into a seasonal excess mortality of 28 percent greater than its own expected increase, but yet this is still far below NYC.

Here is a picture showing today’s results for total mortality in the US – not the results show mortality is approximately as expected and comparable to prior years:

Today’s results are consistent with the prior results on a state by state basis as well:

  • NYC Total Mortality remains at Spanish Flu Levels for the  season – New Jersey and Massachusetts remain high.
  • Michigan and Illinois have increased marginally from week 35.
  • Georgia and Texas are holding steady.
  • California excess mortality is holding steady at less than 1%, and is marginally higher than Florida; both states are well within normal levels for flu season mortality. Florida remains open, although Calf. is locking back down.
  • Some jurisdictions are still under-reporting mortality, in these tables, such as CT, PA, and NC and DC.

The Mainstream Media

As we reported previously, the media was responsible for the fear caused during this time period:

Much of the COVID-19 fear was sustained by media repetition and focus on daily and weekly COVID-19 infection rates and putative COVID-19 mortality that spiked in April. Daily and weekly mortality changes are quite variable, and the COVID-19 mortality estimates are partially confounded with total mortality, whereas cumulative weekly estimates of total mortality are highly regular. The growth pattern for COVID-19 mortality was shown day after day, but it was never placed within the context of the total cumulative mortality, and this gave rise to the impression that all the COVID-19 deaths were in fact directly caused by the disease, along with an additional false impression that the COVID-19 mortality was pushing the total mortality well above average for the year. These impressions turn out to be false.

Overall, these numbers are not surprising. The China coronavirus impact on the US was not as severe as predicted by the so-called experts.

Social distancing doesn’t appear to have much of an impact on overall mortality.

Finally, the actions of the governor and health officials in New York City caused that area to explode with cases and death, especially when compared to the rest of the country.

(Richard Cross PhD is a retired university professor, consulting psychologist, and research director in test development.)

July 19, 2020 | 6 Comments »

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6 Comments / 6 Comments

  1. But it cost $trillions and economic DISLOCATION for millions! The flu Doesn’t do THAT!
    And the “Socialist party of America” may be here for ever! “A thousand year Nazi empire” Hitler proclaimed!

  2. @ Adam Dalgliesh:
    Isn’t there a consensus that Covid only kills people with underlying conditions? Who is to say that even the gunshot and drug overdose victims wouldn’t have lived but for the virus.

  3. @ Adam Dalgliesh:
    Who is to say that even the gunshot and drug overdose victims wouldn’t have lived but for the virus. [it wouldn’t allow me to edit the previous comment

  4. @ Adam Dalgliesh:
    Isn’t there a consensus that Covid only kills people with underlying conditions? Who is to say that even the gunshot and drug overdose victims wouldn’t have lived but for the virus.

  5. There is accumulating evidence that the Johns Hopkins figures for COVID-19 are false. Peope who have done the laborious task of counting the total number of deaths so far this year from all causes (the CDC makes it very difficult to compile these estatistics without a great deal of number-crunching) have discovered that the number of deaths from coronavirus by Johns Hopkins has substantially exceeded the total death toll for the weeks since the first cv-2 cases were diagnosed in the U.S. The only way that could have happened is if there was a substantial drop in deaths from other causes during this period–which is very unlikely. There is also evidence from a variety of other sources that the death date has been inflated–instructions from the CDC to physicians count any deaths from people who may have been in contact with someone who had COVID-19 as COVID-19 deaths, counting deaths as caused by COVID-19 even when the physician who recorded the cause of death listed another disease (such as a heart attack) was the primary cause of death, and COVID-19 only as secondary cause; bonuses paid to hospitals for each patient that they report to the CDC as a coronavirus death; listing any death of a person who had coronavirus at the time of his/her death as having died of cCV-2, even when there was obviously a more likely cause of death (such as COVID19-positive peple who died of gunshot wounds, drug overdoses, etc.

    Someone has got to do a thorough statisitical analysis, “targeted” to the relevant dates for a full comparison of over-all deaths with alleged COVID-19 deaths since the virus was first declared a pandemic. So far, no one has done this.

  6. Becker’s Hospital Review
    COVID-19 Coverage

    States ranked by COVID-19 test positivity rates: July 17
    Molly Gamble (Twitter) – Tuesday, July 14th, 2020

    https://www.beckershospitalreview.com/public-health/states-ranked-by-covid-19-test-positivity-rates-july-14.html?fbclid=IwAR0I5nhazIUkj_LmzoKhk5SFbbF7UzEEdxrtR2s5n9GS57W-e9ikuBzAby0

    Here are the rates of positive COVID-19 tests in each state, along with the number of new cases most recently reported and number of tests conducted per 1,000 people.

    Data points for rates, cases and tests were last updated July 16 and are seven-day moving averages. This information cited is from Johns Hopkins’ Coronavirus Resource Center. States are arranged in descending order of test positivity rates.

    Arizona: 22.8 percent positive

    New daily cases: 3,259

    Tests per 1,000: 1.9

    Florida: 18.1

    New daily cases: 13,965

    Tests per 1,000: 3.0

    South Carolina: 17.6

    New daily cases: 1,838

    Tests per 1,000: 2.1

    Nevada: 17.1

    New daily cases: 1,447

    Tests per 1,000: 1.9

    Texas: 16.1

    New daily cases: 14,962

    Tests per 1,000: 1.9

    Mississippi: 15.9

    New daily cases: 1,230

    Tests per 1,000: 1.9

    Idaho: 15.6

    New daily cases: 685

    Tests per 1,000: 1.8

    Georgia: 15.5

    New daily cases: 3,449

    Tests per 1,000: 2.1

    Alabama: 14.8

    New daily cases: 2,021

    Tests per 1,000: 2.3

    Arkansas: 13.9

    New daily cases: 817

    Tests per 1,000: 1.7

    Kansas: 10.7

    New daily cases: 468

    Tests per 1,000: 1.5

    Louisiana: 10

    New daily cases: 2,280

    Tests per 1,000: 4.4

    Iowa: 9.3

    New daily cases: 814

    Tests per 1,000: 1.9

    Tennessee: 9.2

    New daily cases: 2,479

    Tests per 1,000: 3.2

    Oklahoma: 9.0

    New daily cases: 626

    Tests per 1,000: 2.0

    Utah: 8.8

    New daily cases: 640

    Tests per 1,000: 2.3

    Indiana: 8.5

    New daily cases: 710

    Tests per 1,000: 1.1

    North Carolina: 7.4

    New daily cases: 1,871

    Tests per 1,000: 2.6

    Wisconsin: 7.2

    New daily cases: 900

    Tests per 1,000: 2.0

    California: 7.1

    New daily cases: 9,821

    Tests per 1,000: 3.0

    Colorado: 6.7

    New daily cases: 571

    Tests per 1,000: 1.1

    Kentucky: 6.5

    New daily cases: 406

    Tests per 1,000: 1.4

    Oregon: 6.3

    New daily cases: 428

    Tests per 1,000: 1.2

    Nebraska: 6.1

    New daily cases: 155

    Tests per 1,000: 1.9

    Virginia: 6.0

    New daily cases: 904

    Tests per 1,000: 1.8

    Missouri: 5.9

    New daily cases: 816

    Tests per 1,000: 1.7

    North Dakota: 5.9

    New daily cases: 103

    Tests per 1,000: 1.9

    Washington: 5.7

    New daily cases: 1,267

    Tests per 1,000: 1.7

    Wyoming: 5.7

    New daily cases: 41

    Tests per 1,000: 1.1

    Pennsylvania: 5.4

    New daily cases: 806

    Tests per 1,000: 1.2

    Ohio: 5.4

    New daily cases: 1,290

    Tests per 1,000: 2.1

    South Dakota: 5.3

    New daily cases: 42

    Tests per 1,000: 1.1

    Maryland: 5.3

    New daily cases: 648

    Tests per 1,000: 1.9

    Minnesota: 4.2

    New daily cases: 605

    Tests per 1,000: 2.5

    Montana: 4.0

    New daily cases: 135

    Tests per 1,000: 2.5

    Delaware: 4.0

    New daily cases: 64

    Tests per 1,000: 2.2

    New Mexico: 3.9

    New daily cases: 297

    Tests per 1,000: 3.2

    Rhode Island: 3.8

    New daily cases: 71

    Tests per 1,000: 1.7

    West Virginia: 3.8

    New daily cases: 100

    Tests per 1,000: 1.8

    Illinois: 3.1

    New daily cases: 1,257

    Tests per 1,000: 2.7

    Alaska: 2.8

    New daily cases: 62

    Tests per 1,000: 5.3

    Michigan: 2.8

    New daily cases: 922

    Tests per 1,000: 2.5

    Massachusetts: 2.2

    New daily cases: 234

    Tests per 1,000: 1.6

    Hawaii: 1.9

    New daily cases: 19

    Tests per 1,000: 1.0

    New Hampshire: 1.9

    New daily cases: 26

    Tests per 1,000: 0.9

    Washington, D.C.: 1.6

    New daily cases: 50

    Tests per 1,000: 4.9

    New Jersey: 1.4

    New daily cases: 223

    Tests per 1,000: 2.6

    New York: 1.2

    New daily cases: 780

    Tests per 1,000: 3.3

    Vermont: 0.8

    New daily cases: 7

    Tests per 1,000: 1.4

    Connecticut: 0.8

    New daily cases: 114

    Tests per 1,000: 2.8

    Maine: 0.8

    New daily cases: 20

    Tests per 1,000: 1.6