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EXCLUSIVE: Update on China Coronavirus Study – Current Mortality is Within Expectations for an Above-Average Flu Season
By Joe Hoft
Published July 6, 2020 at 5:56pm
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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 20 times the actual number.
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.
Next 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 is within expectations for an above-average flu season.

Dr. Richard Cross, PhD, provided us the following information related to the China coronavirus. We have updated the following as of July 3rd:

US Total Mortality reported by the Center for Disease Control’s “Pneumonia and Influenza Mortality Surveillance from the National Center for Health Statistics Mortality Surveillance System” for the current year are within expectations for the marginally above average flu season. The excess mortality in a state-by-state analysis indicates total mortality within the expected range of mortality increase across most states, but excess mortality in the New York City area has been at levels comparable to the 1918 Spanish Flu, and the adjacent New Jersey/New England regions experienced mortality well above predicted levels. Media focus on the most affected areas, and on narrow time frames with the COVID-19 effect peaked, concealed both the generally high-normal levels of mortality for the current CDC Season in other regions.

We compute the cumulative Total Mortality for each year by week across the last six seasons beginning on the week ending on Oct. 5, 2013 and ending on May 30, 2020. In this report are the cumulative sums of Total Mortality across both 30 and 35 weeks. This approach places the total impact of COVID-19 within the context of the entire season relative to the previous six seasons which begin in the first week of October each year. It also expands the COVID-19 impact range beyond the 8 to 12 week window in early Spring 2020 where the COVID-19 impact peaked in the Northeast. This approach also allows for updating of the total COVID-19 impact throughout the remainder of the current summer and into the fall as additional CDC data updates become available, thus placing the COVID-19 effect within the context of the entire 12 month season.

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 goes on to report 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.

Dr. Cross’s study goes on to suggest that the mortality rates across the nation are not much different in normal years because “the vast majority of COVID-19-related deaths occur in people who from an actuarial perspective would have died this year or soon thereafter from a pre-existing morbidity.” This makes sense because the elderly by a large percent were the ones who died from the coronavirus. If the elderly are proportionally expected to die anyways, the fact that they died from the coronavirus rather than another cause, kept the overall mortality rates similar to other years.
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.

See the entire report here:

How Big is COVID-19? Current Mortality is Within Expectations for an Above-Average Flu Season by Jim Hoft on Scribd

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 caused that area to explode with cases and death, especially when compared to the rest of the country.

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

Can someone explain to me why you would use October to May mortality rates when the first reported deaths from Covid-19 were not reported until February and didn't start hitting serious #s until April? Am I missing something - wouldn't that massively dilute the overall averages per month? Maybe it's just me, but this looks like one of those deals were you ask your account what the #s are and they say "What do you want them to be?"