I don’t have any big issue with this interview taken as a whole. But it’s representative of the rampant oversimplification even by doctors that leads to a distorted view of COVID-19.
Here, I present a few of the claims and point out how they mislead and fail to provide full context. Select excerpts, emphasis added.
The flu season peaks from December through February in the United States, sickens between 9 million and 49 million people each year, and sends an average of 200,000 to the hospital annually, according to the Centers for Disease Control and Prevention.
Influenze numbers are estimates based on CDC models, These models are not real data, they are guesses not validated by science. Models are for persuasion; models are not science. Models that don’t work well are thrown away and not discussed; models that get lucky are cited until they stop working. In short, models are bullshit.
There also appears to be a greater number of asymptomatic COVID-19 cases than asymptomatic flu cases. And the death rate for COVID-19 appears to be higher than the death rate for flu. There also appears to be more super-spreading events with COVID-19 than with flu: It seems to be transmitted more easily through the air, although both viruses are primarily spread by droplets. Finally, the risk of complications and death in healthy infants and children appears to be higher for flu than for COVID-19.
How would we know about asymptotic influenza cases any more than we know about asymptotic COVID-19 cases? While the statement might be correct, no one really knows for sure: do you go to the doctor if you just feel slightly “off” or think you have a mild cold? I sure don’t. Who reports that? No one. Who tests for influenza? I’ve never been tested for it.
Note the weasel words “appears”; this is doublespeak for “we don’t know; it is unproven”. Ditto for any failure to have real proof—ferquently referred to as a “consensus”—most often when Big Pharma is involved, or there are political considerations.
“Death rate”: no one knows or can know how many people have been infected by either influenza or COVID-19. Without knowing that, it is mathematically impossible to compute a death rate. Yet the term is bandied about as if it is some kind of fact, when it is actually a crude guess influenced by political considerations, financial corruption (hospitals pressuring doctors to presume CV19 for financial gain), etc.
What Dr. Kappagoda is referring to as the “death rate” is unclear, but what is clear that non one knows or can know the death rate versus infection rate, since no one knows the infection rate, and it cannot be known without large-scale randomized testing at frequent intervals! Which no country has done.
Thus it’s misleading to quote an undefined “death rate” for something that cannot even be computed. Death rate for confirmed infections? Death rate based on model estimates? Death rate based on hospitalizations? On guessing? Yep, based on guessing. No, that’s not a joke.
“COVID death” = no credible definition or science
- As defined by the CDC, a COVID-19 death includes virtually any death in which the patient is even suspected of having CV19. It need not be proven that the patient actually had CV19, it need not be shown as the primary cause, it’s hugely unscientific.
- A death in a car crash, by heart attack or stroke and just about anything can be counted as a CV19 death if CV19 is suspected (it need not be proven).
- Doctors are pressured to categorize as CV19 death because hospitals have financial incentives to label the death on COVID (extra payments to them). It used to be illegal for hospitals to employ doctors; now hospitals can fire doctors at will for failing to bow to such pressures (which also includes the medications you are given-beware!).
- Different jurisdictions within the same country or state frequently use different approaches, and other countries may count COVID deaths completely differently!
There is nothing scientific when it comes to the claimed death toll from COVID.