Governments around the world justify lockdowns and mass vaccinations with the argument, that Covid-19 is extremely deadly and therefore poses an existential threat to society and even mankind. We do not contend that Covid is harmless, but such a claim is hardly corroborated by facts.
Doomsday scenarios have not come true
When the virus emerged, citizens were bombarded with nightmarish scenarios about what would happen, if nothing was done.
In March 2020, Imperial College London’s “Covid-19 Response Team” under the leadership of Prof. Neil Ferguson, issued a paper claiming, that without intervention, by the end of October 2020 or earlier, there would be “approximately 510,000 deaths in GB and 2.2 million in the US, not accounting for the potential negative effects of health systems being overwhelmed on mortality.” This paper had a big influence on the British and other governments in implementing tough lockdowns.
The official number of deaths at the end of October was 47,526 in the UK and 237,062 in the U.S., or 9.3% and 10.8% respectively of what had been forecasted. In hindsight it is surprising that anyone believed those forecasts, as Mr. Ferguson had a sound track record of inflating potential deaths and his models were criticized for being severely flawed.
There were also intimidating projections for other countries. In Germany a research paper predicted in March 2020, that in a worst-case scenario over 1.16 million people would die by the end of May 2020. The Daily Situations Report of the Robert Koch Institut (RKI) of 31.05.20 states 8,500 deaths, which is 0.7% of the forecast.
It later turned out, that the German Ministry of Interior commissioned the report, in order to justify a lockdown. The paper was obviously drafted to create fear, as it openly mentions a desired shock effect (“gewünschte Schockwirkung”).
Lockdown proponents argue, that the forecasted death numbers would have been reached, if governments had not implemented harsh containment measures. However, countries without draconian lockdowns did not suffer the forecasted huge death tolls.
In early April 2020, a research group of Uppsala University applied the work of Mr. Ferguson to Sweden and predicted, that “without mitigation” 96,000 people would die from Covid by July 1. The actual death toll was 5,490 or 5.8% of what had been forecasted. As Sweden implemented far less Covid measures than other countries, a tough lockdown can hardly be credited for saving over 90,500 lives. You can find more on this topic in our blog “Lockdowns don’t work and cause huge collateral damage”.
The highly controversial PCR test
The main method used around the globe to identify Covid-19 is the polymerase-chain-reaction test, or PCR test. As early as January 2020, German virologist Prof. Christian Drosten and others published an article describing an RT-PCR method to detect the novel Corona virus. This article provided the justification for politicians and bureaucrats around the world, to decree broad PCR-testing.
Since then, many scientists have come forward questioning the paper. In November 2020 an external peer review of the paper was published claiming “10 major scientific flaws” and asking for retraction.
It needs to be noted, that one co-author of the January 2020 Drosten et al. paper was Olfert Landt, CEO of Tib-Molbiol, a medium-sized German biotech company, that according to its website has delivered over 60 million COVID-19 PCR test kits in the last 12 months. This not unessential fact was fully ignored in the original paper and only added on 29.07.20 under “conflict of interest”.
A key issue with the PCR test is the number of PCR cycles, or Ct value, after which a sample is deemed either positive or negative. The Drosten paper mentions that 45 cycles were conducted, but is unclear about what that means. The higher the number of cycles, the higher the risk that there is barely any virus, or that it is even a false positive (check here and here).
Many doctors recommend a cut-off at 30 or at most 35 cycles. To investigate Covid infections among those, who have been fully vaccinated, the U.S. Centers for Disease Control and Prevention (CDC) only consider specimens with a Ct value ≤ 28. Notwithstanding, according to the New York Times, most tests in the USA use 40 cycles, or at least 37. Consequently, it is not surprising, that 90% of people, who tested positive in Massachusetts, New York and Nevada, carried barely any virus.
That the application of the PCR test is not unproblematic was emphasized by the deceased Dr. Karry Mullis, who received a Nobel Prize in chemistry in 1993 for the invention of the test. In a panel discussion he stated: “I don’t think you can misuse PCR. It’s the results; the interpretation of it … with PCR, if you do it well, you can find almost anything in anybody …. PCR.. doesn’t tell you that you are sick, or that the thing that you ended up with was going to hurt you.”
Even the WHO had to admit in January “that careful interpretation of weak positive results is needed. The cycle threshold (Ct) needed to detect virus is inversely proportional to the patient’s viral load. Where test results do not correspond with the clinical presentation, a new specimen should be taken and retested using the same or different NAT technology.” It also recommended to “provide the Ct value in the report to the requesting health care provider”, as this had obviously been omitted in many cases.
People with a positive PCR-test are forced to quarantine for up to two weeks or are not allowed to work, even if they don’t feel sick at all. In addition, a negative PCR-Test is often needed to fly and enter other countries. However, there is no clear global standard on what constitutes a positive test. The number of PRC cycles performed is up to the discretion of the laboratory. Nobody seems to care, that private laboratories have a strong financial incentive to set the Ct value very high, as more positive cases generate more tests and therefore more profit. It’s one of the few businesses, where you can easily generate demand.
We are not aware of cancer patients or stroke victims that show no symptoms at all, and are therefore considered to be asymptomatic. But for Covid there are plenty of asymptomatic cases. This is important to understand, in order to properly evaluate Covid infection numbers.
In the scientific community there is a lot of discussion about the share of asymptomatic cases. According to various researches, it can be as low as 1.6% and as high as 57%. Mrs. Van Kerkhove from the WHO mentioned in June 2020, that published and unpublished studies discussed in WHO briefings suggest that between 6% and 41% of people who, test positive for the virus, are asymptomatic.
Many asymptomatic cases are probably the result of false positives. Additional confusion is created by the novel testing procedure for Covid. In disease management, a test normally supports clinical diagnosis, but is not a substitute for it. However, in the eyes of the authorities a positive Covid test makes you automatically a sick person, irrespective of whether you feel ill or not. As most health authorities don’t properly follow up on how the ‘patient’ develops, we know very little about the proportion of people who are truly asymptomatic, are pre-symptomatic (go on to develop symptoms later), or are post-infectious (have viral RNA fragments still detectable from an earlier infection).
There is still uncertainty on whether asymptomatic “cases” can transmit the virus to others. One research paper finds, that “many infections are nonsymptomatic but contribute substantially to community transmission in the aggregate”. In contrast, a meta-analysis concluded, that even within households, asymptomatic individuals passed on the disease to other household members in only 0.7 % of cases (compared to 18% for symptomatic individuals). A study of nearly 10 million citizens of Wuhan states, that “there were no positive tests amongst 1,174 close contacts of asymptomatic cases.”
The WHO stated in December 2020, that “current evidence suggests that people infected with SARS-CoV-2 can transmit the virus whether they have symptoms or not. However, data from viral shedding studies suggests that infected individuals have highest viral loads just before or around the time they develop symptoms and during the first 5-7 days of illness”
The majority of scientists seems to assume, that asymptomatic transmission is low. This has important implications on the lockdown discussion. If people without symptoms can’t transmit the virus or will do it only on very rare occasions, the rationale for lockdowns breaks down. In this case we only have to identify and isolate people with symptoms.
Not every ‘Covid death’ is a Covid death
WHO’s “International Guidelines for Certification and Classification (Coding) of Covid-19 as Cause of Death” issued on 16 April 2020 states that “A death due to COVID-19 is defined for surveillance purposes as a death resulting from a clinically compatible illness, in a probable or confirmed COVID-19 case ….. A death due to COVID-19 may not be attributed to another disease (e.g. cancer) and should be counted independently of preexisting conditions that are suspected of triggering a severe course of COVID-19.” In addition, it stipulates that “COVID-19 should be recorded on the medical certificate of cause of death for ALL decedents where the disease caused, or is assumed to have caused, or contributed to death.”
Even though Covid symptoms overlap with those of other respiratory diseases, this rather vague definition allows everyone who exhibited some symptoms similar to Covid, to be counted as a Covid death. Existing comorbidities, that might have led to a fast death even without the presence of Covid, can be mentioned in the death certificate, but only in another section that is not considered in the official Covid death count calculation.
Despite the WHO guideline, each country uses different rules to count Covid deaths. Some require an autopsy to prove that Covid was the main cause. Others count basically everyone who dies with a positive PCR test within a certain period, even if the person was the victim of a traffic accident or committed suicide. In a few countries, a positive test might not even be required, instead “Covid-like symptoms” suffice. As there is no global guideline, local politicians and bureaucrats possess many options to ‘massage’ the numbers to fit their political agendas.
In the absence of a common standard and considering the questionable reliability of the PCR test, an ‘official’ Covid death can mean that the patient i) died from Covid, ii) died accelerated by Covid, i.e. Covid contributed to a faster death, for instance if a terminal cancer patient is already so weak, that the body can’t build up any resistance against Covid), iii) died with Covid, i.e.: had Covid but died of another cause, for instance a road accident, or iv) died without Covid, i.e.: was a false positive and died of whatever cause, but certainly not Covid. Without an unbiased and comprehensive investigation, that no government wants, we will never find out.
Admittedly, there is not just over- but also underreporting. This is the case, if people die of Covid without ever being tested, or if doctors write another cause of death to avoid additional Covid-related paperwork.
Whether over- or underreporting prevails, depends on the specific circumstances. In countries where most patients are tested for Covid upon admission to hospital and a high Ct value applies, overreporting is almost assured.
Due to the over-/underreporting issue, it has been suggested to use excess deaths as an estimate. They can be defined as the number of actual deaths minus the number of expected deaths.
Our World in Data (OWID), Karlinsky & Kobak, and Parildar, Perara, Oke (PPO) provide respective overviews. To calculate expected deaths, all three models only use the death count of the five previous years (2015 – 2019), which is too short. They arrive at the number of expected deaths by using the average (OWID and PPO) or via regression model (Karlinsky & Kobak). Standard deviation, previous maximums and minimums, as well as population growth and demographic changes are not or not sufficiently included. Therefore, the results have to be interpreted with caution.
All models come to the conclusion, that many countries have experienced substantial excess deaths. For countries like Peru, Ecuador, Bolivia, Spain, and Italy this seems plausible, at least with regard to the years 2015 – 2019. For other countries excess mortality is questionable. For instance, whereas Karlinsky & Kobak claim a 3% excess mortality for Germany in 2020, the country’s death toll in March 2018, at the height of a severe influenza wave, was higher than in December 2020, when Covid deaths peaked. In a detailed analysis, Prof. Kauermann, Chair of Applied Statistics at Munich University, came to the conclusion, that there has hardly been any excess mortality in Germany in 2020.
Even if we assume, that up till now Western countries have indeed experienced high excess mortality rates of up to 21% (calculated by Karlinsky & Kobak for Spain) and many developing countries have suffered even worse excess death tolls of up to 124% (calculated for Peru), this does not mean, that all excess deaths can be attributed to Covid. Other unrelated reasons might have had the same or an even bigger impact on excess deaths. In addition, instead of saving lives, lockdowns are likely to have caused additional deaths, if Covid-related measures were responsible for the insufficient treatment of other illnesses, or have caused additional victims from suicide, domestic violence, or even starvation.
In summary, quite a few countries are alleged to have experienced excess mortality in 2020. However, it is not clear what percentage of excess deaths stems directly from Covid-19 and what percentage is the result of lockdowns and other causes. Only unbiased, detailed and country-specific research can answer this. We don’t expect this to be carried out for most countries.
Death toll in perspective
From the above it is obvious, that the quality of the reported Covid death numbers is highly disputable. But in the absence of a broad and unbiased recount and the implementation of universal testing and counting standards, which will never happen, the reported numbers are all we have got.
According to worldometers, by April 20, 2021 a total of 142.7 million people had tested positive for Covid-19, and 2.9 million had died. This means that 1.8% of the world population got infected and 0.039% died. Though this is certainly deplorable, after more than 15 months, an alleged “killer virus” should have caused a considerably higher death toll.
Compared to previous pandemics, Covid-19 appears to be somewhat similar or slightly worse than the Hong Kong Flu (1968-70) and the Asian Flu (1957-58). To match the Spanish Flu (1918-20), another 68 – 407 million people will have to die from Covid-19. This number soars to 0.5 – 2.2 billion, if we also consider the Bubonic Plague or Black death (1346-51), though population and mortality data from that period is more guesswork than based on hard facts.
Even today, Covid-19 is far from being the deadliest disease. According to ‘Our World in Data’, in 2017 cardio vascular diseases killed 17.8 million and cancer another 9.6 million. For Covid to become the main source of death, it needs to become much deadlier.
The WHO reports that roughly 10 million fall sick with tuberculosis and 1.4 million die. This compares to 1.8 million Covid deaths in 2020. Tuberculosis is another infectious disease, and as about 5% of patients fall ill with drug-resistant tuberculosis, it is not easy to cure. Despite of this, we can’t recount anyone calling for a global lockdown and far-reaching restrictions on personal and economic freedom to reach ‘zero tuberculosis’.
Mortality risk is low, except for the elderly and those with comorbidities
The mortality of Covid is much lower than originally feared. The Case Fatality Rate (= number of deaths divided by confirmed closed cases) CFR is 2.45% according to Worldometers. This compares to a CFR of 50% for Ebola, 34% for MERS, 10% for SARS and about 0.15% for seasonal flu.
As not all people with Covid get tested (at least not yet), the Infection Fatality Rate (= number of deaths divided by the estimated number of infected individuals) IFR is lower.
According to a meta-analysis by renowned scientist Prof. Ioannidis of Stanford University, which has been published by the WHO in October 2020, median IFR estimate is 0.23% for the population as a whole. This means that out of 1,000,000 people who fall sick with Covid, 2,300 are expected to die.
Recently Prof. Ioannidis has released an updated, peer-reviewed study stating that “the available evidence suggests average global IFR of ~0.15% and ~1.5‐2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries, and locations”.
One main reason for the large differences in deaths across countries is age distribution. In his October 2020 meta study Prof. Ioannidis came to the conclusion, that for those under 70 years of age, the IFR is 0,05% or 500 in 1 million. This means that older people have a much higher risk of dying from Covid than younger people. According to other studies (here and here), IFR for children and young adults can be as low as 0.001% or 10 in one million.
That age matters, is acknowledged by the U.S. Centers for Disease Control and Prevention (CDC), which has published the following infographic.
It does not come as a surprise, that the median age of Covid deaths in most countries is above 80 and that in more than two dozen nations with significant elder-care facilities, such institutions are tied to more than a third of Covid-19 deaths, though they typically house less than 2% of the population.
Some people of working age with underlying conditions also have an increased risk of dying from Covid. Especially hypertension, diabetes with chronic compilations and obesity seem to be relevant mortality risk factors. An overview of studies on underlying conditions can be found here.
Covid does not justify far-reaching political oppression
Covid is causing or expediting many deaths. Some of the survivors have to endure excruciating pain and might experience ‘long Covid’ symptoms. This is tragic and we feel deep compassion for the individuals affected and their families.
However, on any given day more people die of other diseases or accidents, and many are also subjected to agonizing pain. Some even suffer, because Covid measures implemented by the authorities prevent them from getting proper treatment. In view of a high survival rate of 99.85%, a sole focus on Covid measures at the detriment of many other urgent issues is unjustified. Furthermore, instead of protecting the vulnerable, implementing far-reaching restrictions for everyone in society is a great injustice to healthy young people with a negligible risk from Covid.
Proponents of harsh government measures defend their position by warning of the devastating impact of more deadly mutants of the virus. Especially those, whose doomsday scenarios have proven wrong on multiple occasions in the past, continue to predict exponential increases in deaths and the total collapse of our health care system.
Even if new mutants increased the infection fatality rate by a factor of 2 or 3, this would not mean the end of the world as we know it. Of course, there is always the ‘tail risk’, that a new killer mutant will send the IFR soaring to 10%, 20% or even higher. But this would create a completely new situation, for which we must prepare, but that should not completely determine our current lives. We should not live, as if the worst-case scenario had already arrived.
In the absence of a vastly more lethal mutant, for which there is currently no broadly accepted scientific evidence, Covid-19 does not pose the existential threat, that many politicians want us to believe. It certainly does not justify far-reaching political oppression and the repeal of many personal and economic freedoms.
As a delicate side note it needs to be pointed out, that we are not supposed to call SARS-CoV-2, the virus that causes Covid-19, the ‘Wuhan virus’. But politicians and the media find it perfectly acceptable, to refer to B.1.1.7 as the ‘UK variant’, B.1.351 as the ‘South African strain’ and P.1 as the ‘Brazilian mutant’.
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