02/08/2020 / By Mike Adams

Although *The Lancet* published a recent study showing the coronavirus achieving a 15% death rate among those who are infected, the WHO, increasingly siding with communist China’s discredited “official” figures, claims the death rate is only 2%.

The same source, the WHO, also says “82 per cent of cases are mild.”

*(Put on your math hat, because this article contains a lot of math. Fortunately it’s only about 7th grade math, so perhaps even CNN might be able to follow it.)*

This means, of course, that 18% of coronavirus cases are either “serious” or “critical,” since those are the other two designations which are possible.

The percentage of people who survive those two designations is surprisingly low, according to China’s own official sources. The communist Chinese regime is trying to spin the very low survival rates as some sort of “good news,” not surprisingly. Here’s how the SCMP reported the spin:

*Speaking at a press conference in Beijing, Wang Guoqiang, an infectious disease expert at Peking University No 1 Hospital, said that preliminary data about people who had recovered after being infected was promising.*

*Based on a small sample of discharged patients from Wuhan, the city at the centre of the outbreak, Wang said that about 6 per cent had recovered after being in a serious condition, while less than one per cent had recovered after being classed as in critical condition.*

Only in China could a 6% survival rate for “serious” patients be considered good news. Similarly, a 1% survival rate for “critical” patients is also being spun as good news.

“This shows that cases in serious and critical conditions can be treated and discharged from hospital after receiving proactive treatment, and that has given us great confidence,” said Wang Guoqiang. I’m not sure what medical school Mr. Wang graduated from, but a 1% – 6% survival rate among those patients shouldn’t give any doctor “great confidence.”

If you do the math, this means that 94% of patients in “serious” condition *don’t* recover, which means they die. Similarly, 99% of those in “critical” condition also die.

Out of every 100 infected people, we now know that 82 will be classified as “mild,” and we also know that 18 will be either “serious” or “critical,” but we’re not yet sure exactly how many will be “serious” vs. “critical.” For this investigation, we’ll have to estimate that. So we’ll be conservative and estimate that, out of the 100 original patients, 14 end up in serious condition and 4 in critical.

So here are our working numbers so far:

**For every 100 infected people:**

82 = Mild status

14 = Serious status

4 = Critical status

Now, let’s assume that 100% of the “mild” status patients survive. We also know, from Wang Guoqiang, above, the survival rates of those in “serious” or “critical” conditions:

**Survival rates:**

Mild status (82 / 100) = 100% survival

Serious status (14 / 100) = 6% survival

Critical status (4 / 100) = 1% survival

With these data outlined, then, what is the total number of deaths per 100 people who are infected?

To get the answer, we first calculate the number of survivors: (0.82 x 100) + (0.06 x 14) + (0.01 * 4) = 82 + 0.84 + 0.04 = **82.88**

So we know there are **83 survivors** out of every 100 infected patients.

That means there are **17 who do not survive** (i.e. deaths). That’s another way of saying the mortality rate is 17%, by the way.

Note carefully that this is almost entirely based on numbers coming out of China that the Chinese government is trying to spin as “good news.”

It’s also very consistent with the early study out of *The Lancet* that documented a 15% mortality rate among those who are infected. That study is found here:

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30183-5/fulltext

The WHO is trying to tell us that only 2% of infected people die, but the real numbers now look a lot closer to 15% – 17%, at least for anyone who can do math.

On top of all that, remember the “leaked” data set that appeared last week, revealing how China actually has two databases that track infections and deaths? One database is the “real” numbers, while another database contains all the fudged numbers for the public to see.

The leaked numbers showed 154,023 infections and 24,589 deaths.

If you do the math on that, it comes to a **16% mortality rate**.

Go figure.

Chinese propagandists have been flooding the internet and media lately, claiming the coronavirus is “no worse than the seasonal flu.” So let’s take a look at that:

The CDC claims that the seasonal flu infects about 35.5 million people in the United States each year, leading to 16.5 million people going to a doctor. The CDC also claims this leads to 490,600 hospitalizations and 34,200 deaths.

Thus, according to the CDC, the “death rate” of the seasonal flu is 0.0963%, or roughly one person out of every 1,000 who are infected.

We now know, from China’s own press conference, that the coronavirus kills 17 out of every 100 people who are infected. That’s a **177 times higher mortality rate than the seasonal flu**.

Taking the CDC’s claim that 35.5 million people get the flu each year, if that same number of people were to get infected with the coronavirus, what would the number of dead Americans be?

The answer, of course, is 17% of 35.5 million, over **six million dead Americans**.

And that’s using the seasonal flu numbers from the CDC.

Thus, the only reason the coronavirus is “no worse than the flu” is because **it isn’t out of control here yet**. Once it spreads in America at the same rate as the seasonal flu, if the mortality rates that are being reported by the WHO and Chinese doctors hold true in the United States, we would expect to see **6.035 million deaths** in the United States.

But wait, there’s more.

According to the CDC, the flu vaccine prevents anywhere from 40% – 60% of seasonal flu infections “among the overall population,” they claim. Thus, according to the CDC, if there were no flu vaccine, the actual number of flu infections in the USA would be increased by 40% – 60%. Let’s take the mid-point of 50%.

If we increase the 35.5 million infected Americans by 50%, we get **53.25 million Americans infected**.

Why is this important? Because **there is no coronavirus vaccine that’s commercially available to the public**. So even if we believe that vaccines substantially reduce such infections, there is currently no vaccine in play anyway.

This means the number of likely infected, if the coronavirus were to spread uncontained in the United States, is probably closer to 53.25 million, which is still only about one-sixth of the population. With a 17% mortality rate applied, that would result in **over 9 million deaths in the United States.**

But wait, there’s still more.

The ability of infectious diseases to spread is described by the so-called “R0” value (R-naught), which reveals how many additional people are infected by each one person who carries the infection. According to this study published in PubMed.gov, the R0 value for recent influenza strains was between 1.4 and 1.6. That means, on average, every one person who has that strain of influenza will spread it to another 1.5 people.

Estimates for the coronavirus pandemic strain reveal R0 values anywhere from 2.2 to about 3.8. As Business Insider reports, credible research pegs the R0 value as 2.5, or 3.8 or even 5.47.

For the purposes of this thought experiment, let’s say it’s 3.0, which is exactly double the R0 value of the common cold influenza mentioned above.

That means every one person will spread the infection to three people, not just 1.5 people. Thus, you might say, at a simple level, the number of infections would double.

However, that’s not actually accurate. The much higher infectiousness is compounded, since the 3 people who just got it each spread to 3 more people, making 9. Those 9 people spread to 27, then to 81, etc.

After just 10 generations of spreading, a virus with R0 of 1.5 will have infected only **58 people**.

But a virus with R0 of 3.0 will have infected **over 59,000 people**.

Thus, if allowed to spread, a virus with R0 of 3.0 can mathematically infect 1,000 times more people than a virus with an R0 value of 1.5, after just ten generations of infections. This simple fact is completely missed by the scientifically illiterate journalists (talking head puppets) who work at mainstream media outlets, most of whom are also mathematically illiterate to begin with.

In summary, if the seasonal flu typically infects 35.5 million Americans each year, a coronavirus strain with an R0 value of 3.0 (or thereabouts) would obviously infect a far higher number of Americans. Conservatively, we could say 100 million Americans would reasonable be infected (less than one-third of the total population), even though it might actually be far more.

It’s not difficult to see, then, that if 100 million Americans get infected, we’re looking at **17 million fatalities** if the China numbers are accurate.

Now, remember, the WHO says only 2% of people are dying, which would be 2 million deaths, but China’s own press conference just admitted the actual number is closer to 17%. You are free to believe whichever number you want, but the inescapable truth is that if this spreads across the United States, the number of deaths will likely be some number of millions. And that’s far, far worse than any seasonal flue, no matter what the propagandists are trying to claim.

There’s something else to consider, by the way. If 100 million Americans are infected, how many would seek out medical care?

Given the severity of the coronavirus pandemic on a global scale and the awareness among U.S. citizens, we might reasonably conclude that 50 million Americans (half of those infected) would seek out medical care.

According to Statista.com, there were 931,000 hospital beds in America in 2017. Most of those beds are already occupied, of course, by hospital patients who are dealing with other health issues such as heart attacks, cancer, stroke, trauma care, etc. The number of *spare* hospital beds is unknown, but even if we were to be generous and say that 25% of all hospital beds in America are currently available, that’s not even 250,000 hospital beds.

An obvious question now emerges: How do you treat 50 million infected people in a country that has only 250,000 free hospital beds? That’s **one hospital bed for every 200 infected people**, in case you were doing the math.

So then, you begin to see the bigger problem in all this: the **health care infrastructure** and “bandwidth” of treatment during a pandemic.

There’s an even bigger problem that’s now emerging. A leaked photo from the same Chinese press conference mentioned above has accidentally revealed that hundreds of front-line health care workers got infected in their own hospitals, and they are now lying in hospital beds among the patients they once treated. By some estimates, up to **29% of the patients in Wuhan hospitals are doctors and nurses**.

29% — that’s the % of the 138 #coronavirus infected patients who are actually infected medical staff in one Wuhan hospital. Almost 1 in 3 patients being hospital healthcare workers is just insane. New case series report in JAMA: https://t.co/j7HPV8j8dp pic.twitter.com/3Hmu3MaE7m

— Eric Feigl-Ding (@DrEricDing) February 7, 2020

2) In addition to 29% medical staff, 12% of patients had gotten #coronavirus as hospital-acquired🦠. Quote: “Hospital-associated transmission was suspected as the presumed mechanism of infection for affected health professionals (40 [29%]) and hospitalized patients (17 [12.3%]).”

— Eric Feigl-Ding (@DrEricDing) February 7, 2020

*A leaked photo shared on Chinese social media has revealed that hundreds of medical workers in the coronavirus epicenter of Wuhan City have been infected with the virus.*

*Hou Anyang, founder and chairman of a Chinese asset management firm, first posted on Weibo, a Twitter-like social media platform, a photo from a recent coronavirus prevention and control conference in Hubei Province. Wuhan is the capital of Hubei. Hou’s Weibo account is no longer viewable.*

*The photo revealed a presentation slide from the conference, where it lists the Wuhan facilities where there are 15 or more confirmed cases of coronavirus infection among medical staff, along with the dates of the first confirmed infection.*

*The facility with the most infections was the Wuhan Union Hospital. It has 101 confirmed cases and 161 suspected cases, totaling 262. The first infection occurred on January 11.*

*The data reveals that authorities already knew coronavirus patients could transmit the virus to hospital staff—but they lied to the public, only acknowledging that the pathogen was capable of human-to-human transmission on Jan. 20.*

In other words, **hospitals are transmitting the virus to both health care workers and additional patients**. And that means any effort to send millions of people to hospitals will only result in millions of doctors, nurses and health care workers becoming infected themselves.

Hospitals will become “death centers” for the epidemic.

In summary, the real mortality rate from coronavirus infections, according to data released by the Chinese government in a “good news” press conference, is very probably in the range of **17%**.

The Lancet had previously reported a mortality rate of **15%**.

The “leaked” numbers of infections and deaths from China revealed a death rate of **16%**.

We are starting to zero in on the reality of this virus, and it looks like 15% – 17% mortality rate is where this is going to settle. That’s a far cry from the 2% currently claimed by the communist Chinese regime and the clueless WHO bureaucrats who cover for the communists.

It’s easy to claim an artificially low death rate, of course, when you run an authoritarian regime that’s dispatching “cremation vans” on a 24/7 basis to dispose of all the dead bodies before they can be counted.

In any case, if you think communists always tell the truth, then you can believe the 2% number. But if you believe in mathematics, it’s probably more like 15% – 17% mortality.

Plan accordingly.

**Tagged Under:**
China, coronavirus, epidemic, infectious, MATH, mortality, outbreak, pandemic, recovery, Wuhan