India Achieves Covid Herd Immunity With Mortality of One in Five Thousand

 India, is reported to have achieved Covid herd immunity, with about half the population, or just under seven hundred million people, having Covid19-specific antibodies. That means India is essentially finished with Covid as a national disaster. 

Covid deaths recorded in India total 155,000, indicating a Covid19 infection fatality rate of around one in 5000.  That is around one tenth of the rates reported in Europe and North America. That difference reflects, at least in part, the steep age-dependence of Covid mortality and a difference in population age profile. India has fewer than 6% of its population aged over 60 versus around 26% in Europe and North America. 

In addition, the European and North American infection fatality rates are undoubtedly greatly exaggerated due to underestimation of the infection rate, which is based on reported cases, not population-wide antibody surveys.  

The inference is clear: The Western states have totally mishandled the epidemic. The virus should have been allowed to spread among the young and resilient, while the elderly should have been given every means to isolate themselves — if they so chose. And it should be emphasized that isolation of the elderly should have been entirely voluntary. At the age of 75 plus, why should one not take a 10% risk of dying a year or two prematurely due to Covid, rather than being locked up for much, or perhaps all, of the rest of one's life?

What the response of the Western nations to Covid19 demonstrates is either remarkably poor judgement in government, or a conspiracy to undermine Western economies and crush the spirit of the people. 

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Understanding your risk from Covid19

Out there in the quagmire of the Internet Covid controversy, Ron Unz remains insistent on the deadly peril of covid, asserting that:

... research—examining deaths out of the total number of infections, which includes unreported cases—suggests that Covid-19 kills from around 0.3% to 1.5% of people infected. 

Thus stated, without qualification,  covid mortality rates will be taken to refer to the population as a whole, which is an entirely false inference. 

Covid mortality is hugely age-dependent, so infection fatality rates are meaningless as a basis for assessing personal risk.

If you are under 21, your risk is of death from Covid19 is substantially less than the risk of being killed in a motor vehicle accident. If you are over 75, your risk of death from Covid19 is 10% or more. 

There's another factor that massively distorts understanding of the Covid mortality risk, and that is the prevalence of infection among different groups.

A study conducted in UK care homes revealed that as early as April 2020, 40% of investigated care home residents and 21% of staff were Covid19 antibody positive. These rates, which are vastly higher than national rates at the time (almost certainly less than 5%), mean that  UK care homes were death traps for the most vulnerable, and accounted for a large majority of the UK's total Covid death toll. 

Take these facts into consideration and it is evident that talking of population-wide IFRs is either foolish nonsense or deliberate misdirection. 

In Canada, for example, as of October, 2020, 73% of all Covid 19 deaths were of care home residents.  

Covid is not a world-destroying pandemic, but rather, whether launched deliberately or by chance, a mechanism for saving both the UK's bloated National Health Service from collapse under its own monstrous weight, and the profits of the US Healthcare insurers. This it is doing by ridding the world of the most useless and expensive eaters. 

Young people mostly understand all of this, which is why they don't give a bleep about lockdowns and resent the cowardice of school teachers and university faculty who won't show up and teach. 

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Scared of Covid19: Here's the Risk It'll Kill Ya

 The CDC reports that, in America, the age-dependent infection fatality rates for Covid19 are:

Age             Risk of death

0    - 19       0.00003 or one in 33,333
20  - 49       0.0002, or one in 5,000
50  - 69       0.005, or one in 200
70 +            0.06, or one in 18

Or looking at that in a more positive way, Covid19 survival rates are:

Age                  Survival rate

0   - 19 Years    99.997%
20 - 49 Years    99.98%
50 - 69 Years    99.5%
70 - 80 Years    94.6%

And that's if you're infected. But thus far, probably no more than about one in ten of the world's population has been infected, so if effective vaccines materialize, you'll likely never be infected. 

And for comparison, here are all ages risk of death due to some other causes:

Cancer:                          one in     562

heart disease:                 one in     520

Respiratory disease:      one in    2104

Motor vehicle accident: one in   5243

Source

So what those numbers show is that it would make as much sense to shutter much of the economy to protect under-50's from motor vehicle accidents as to protect them from covid-19. Yet no one in the right mind would suggest doing anything so idiotic. So why do we do something so idiotic because of Covid19? Explanations invited.

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The Cult of the Brave New Normal

Dealing With Covid19: A Conversation with Stanford University Professor, John Ioannidis, America's Most Distinguished Epidemiologist

 By SAURABH JHA, MD

The COVID-19 pandemic has been a testing time for the already testy academic discourse. Decisions have had to be made with partial information. Information has come in drizzles, showers and downpours. The velocity with which new information has arrived has outstripped our ability to make sense of it. On top of that, the science has been politicized in a polarized country with a polarizing president at its helm.

As the country awoke to an unprecedented economic lockdown in the middle of March, John Ioannidis, professor of epidemiology at Stanford University and one of the most cited physician scientists who practically invented “metaresearch”, questioned the lockdown and wondered if we might cause more harm than good in trying to control coronavirus. What would normally pass for skepticism in the midst of uncertainty of a novel virus became tinder in the social media outrage fire.

Ioannidis was likened to the discredited anti-vax doctor, Andrew Wakefield. His colleagues in epidemiology could barely contain their disgust, which ranged from visceral disappointment – the sort one feels when their gifted child has lost their way in college, to deep anger. He was accused of misunderstanding risk, misunderstanding statistics, and cherry picking data to prove his point.

The pushback was partly a testament to the stature of Ioannidis, whose skepticism could have weakened the resoluteness with which people complied with the lockdown. Some academics defended him, or rather defended the need for a contrarian voice like his. The conservative media lauded him.

In this pandemic, where we have learnt as much about ourselves as we have about the virus, understanding the pushback to Ioannidis is critical to understanding how academic discourse shapes public’s perception of public policy.

Saurabh Jha (SJ): On March 17th, at the start of the lockdown, you wrote in STAT News cautioning us against overreacting to COVID-19. You likened our response to an elephant accidentally jumping off a cliff because it was attacked by a house cat. The lockdown had just begun. What motivated you to write that editorial?

John P.A. Ioannidis (JPA): March seems a long time ago. I should explain my thinking in the early days of the COVID-19 pandemic. Like many, I saw a train approaching. Like many, I couldn’t sense the train’s precise size and speed. Many said we should be bracing for a calamity and in many ways I agreed. But I was concerned that we might inflict undue damage, what I’d call “iatrogenic harm”, controlling the pandemic.

To answer your question specifically, I wrote the piece because I felt that the touted fatality rate of COVID-19 of 3.4 % was inflated, but we had so limited data and so much uncertainty that infection fatality rate values as different as 0.05% and 1% were clearly still possible. I was pleading for better data on COVID-19 to make our response more precise and proportionate.

Read More

(With Thanks to Yusef for this link).

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(With Thanks to Anastasia for this link).

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(With Thanks to Peripatetic Commenter for this link).

Covid Lies to Keep You Terrorized

Absent strong public health measures, we would expect it to kill something like 0.5% to 1.0% of a nation’s population, and whether or not that’s a large number is a matter of personal opinion.

So declared Ron Unz, publisher of the Unz Review. 

That claim is far from the truth as the case of Sweden demonstrates. There, in the absence of "strong public health measures" there have been 5,846 reported Covid deaths, or about 0.06% of the population. That must be close to the final toll, as Covid deaths in Sweden peaked in March and are now at or close to zero.

Why would a scientifically literate person such as Ron Unz make such a false claim? Mere confusion, perhaps*.

One way in which Covid death rates have been greatly exaggerated has been to confuse, deliberately or otherwise, two measures of the death rate; namely, the "Case Fatality Rate" and the  "Infection Fatality Rate." 

The Covid19 Case Fatality Rate (CFR) is a measure of deaths among confirmed Covid19 cases, the latter being mainly cases of serious illness, which thus came to the attention of the medical profession and were identified as due to Covid19 by a more or less reliable diagnostic methods.

The Covid19 Infection Fatality Rate (IFR) is a measure of deaths among all those infected with Covid19, whether they were seriously ill or not, or whether they were ill at all. The IFR can only be determined if there is population-wide testing for past or present Covid19 infection, for example by means of a reliable serological test for Covid19 antibodies. 

Evidence currently available suggests that the the IFR is only about one tenth of the CFR. Therefore, to mistake the CFR for the IFR will result in an exaggeration of the actual IFR by a factor of around ten. 

But even a ten-fold error does not explain Ron Unz's claim that "absent strong public health measures" Covid19 will "kill something like 0.5% to 1.0% of a nation’s population." To explain that, assuming it is not a straight lie, one must assume that Ron Unz confuses the Infection Fatality Rate with the Population Fatality Rate (PFR). Such confusion assumes a Covid death rate among the population as a whole equal to the Covid death rate among those made sick by a confirmed Covid19 infection, which is nonsense.

But perhaps Ron Unz's claim is a straight lie, which would be consistent with the fact that, when I pointed out the error on his Unz Review post, my comment was deleted.

______
* Cf. Ronald B. Brown, 2000, Public Health Lessons Learned from Biases in Coronavirus Mortality Overestimation.

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