Britain could have been hit harder by Covid-19 than other European nations because the past two winter flu outbreaks have only been mild, according to a study.
Researchers say influenza kills the same groups of people as the coronavirus, with both illnesses posing the greatest danger to the elderly and those with underlying conditions.
Public Health England statistics show around 20,000 excess deaths – those of any cause that happen above average – occur from influenza each year.
But only 1,700 extra fatalities were recorded during the 2018/19 outbreak, said lead author Dr Chris Hope who claimed data showed the 2019/20 season was also ‘very mild’.
It means more than 30,000 people in England alone were alive at the start of the Covid-19 pandemic who would have been expected to die in the previous two flu seasons.
Novelist Hector Drummond decided to look at the annual death figures for England and Wales from the Office for National Statistics. This is what he found after graphing the numbers all the way back to the turn of the twentieth century.
The 2020 death figures on the right cannot even be considered a spike over the course of the century.
He explained his methodology in this post:
Deaths decreasing as cases surge because of testing.
Testing is going nuts. Testing is out of control. Testing is rampant. Testing is at insane levels and only growing.
Notice anything? You might not have reached the apex of probability like I, the Statistician to the Stars! have, but surely you can see the most salient point. DEATHS ARE DECREASING, EVEN AS NEW “CASES” “SURGE” “SPIKE” “SOAR” “SET RECORDS”.
This is why we must continue to look to all-cause deaths are the best indicator. It’s just too easy to cheat, fudge, shade, tweak, adjust, or whatever word you like, with COVID deaths.
The UK operational false positive rate is unknown. There are no published studies on the operational false positive rate of any national COVID-19 testing programme.
An attempt has been made to estimate the likely false-positive rate of national COVID-19 testing programmes by examining data from published external quality assessments (EQAs) for RT-PCR assays for other RNA viruses carried out between 2004-2019 . Results of 43 EQAs were examined, giving a median false positive rate of 2.3% (interquartile range 0.8-4.0%).
Alistair Haimes interpreted these results in this way:
2.3% false positive rate with 0.04% virus prevalence rate (ONS) means that if you test positive you have only a 4/234= 1.7% chance of being infected. We’re flying blind.@AlistairHaimes. 3 July 2020
if the false positive rate is that high, surely they just know that it is ‘about nothing’; 0.04% must be false precision?
HIQA found that the officially-reported COVID-19 deaths likely overestimates the true burden of excess deaths caused by the virus. This could be due to the inclusion within official figures of people who were infected with SARS-CoV-2 (coronavirus) at the time of death whose cause of death may have been predominantly due to other factors.
- 2.4% of all tests were positive (9,674 out of 397,197)
- 3.9% of residents tested positive (6,747 out of 172,066)
- 3.3% of asymptomatic residents tested positive (5,455 out of 163,945)
- 80.9% of residents who tested positive were asymptomatic (5,455 out of 6,747)
- 1.2% of asymptomatic staff tested positive (2,567 out of 210,620)
Antibody tests on random samples of the population have so far shown much lower levels of general infection than the government’s scientific advisers claimed would be necessary to attain ‘herd immunity’. In London, for example, tests have shown that 17 per cent of the population have antibodies to Sars-CoV-2, the virus that causes Covid-19. In New York, the figure is 21 per cent. At the beginning of this crisis, on the other hand, Sir Patrick Vallance, the chief scientific adviser, suggested that at least 60 per cent of the population would have to be infected in order to achieve herd immunity.
The really concerning thing is that if all the deaths taking place during lockdown are put down as Covid-19 deaths, we are going to miss the fact that the lockdown policies have caused an increase in deaths from many other things. There has been a 50 per cent reduction in people turning up to A&E. It is clear that people just do not want to bother the doctors. And a number of these people will be dying. If we muddle the Covid-19 statistics in with the other statistics, we might think the lockdown has prevented a certain number of deaths, when it has actually caused a large number of deaths.
You hear this idea that all NHS staff have been working 20 times as hard as they have ever done. This is complete nonsense. An awful lot of people have been standing around wondering what the hell to do with themselves. A&E has never been so quiet.
The chances of children dying from COVID-19:
How many people aged 15 or under have died of Covid-19? Four. The chance of dying from a lightning strike is one in 700,000. The chance of dying of Covid-19 in that age group is one in 3.5million. And we locked them all down. Even among the 15- to 44-year-olds, the death rate is very low and the vast majority of deaths have been people who had significant underlying health conditions. We locked them down as well. We locked down the population that had virtually zero risk of getting any serious problems from the disease, and then spread it wildly among the highly vulnerable age group.
It is not clear that getting the virus actually makes you immune to it in the future, and it is not clear a vaccine would either.
Stockholm is the best population to test Covid theory whereby it was hit hard early and did not have lockdowns. Nobel Prize winner Dr Michael Levitt postulated that the virus burns out when it has infected 15-20% of the population. According to this, he’s right.
So what does this mean? Lockdowns were a waste of time and resources. Minimizing deaths just delays the inevitable. Those countries which were not hit are most likely to see continued spikes and outbreaks. Maybe less during the summer but a second wave later this year.
Seeking medical help too late during pandemic was contributory factor in the deaths of nine children, Royal College research finds
The Gompertz function describes global dynamics of many natural processes including growth of normal and malignant tissues. On one hand, the Gompertz function defines a fractal. The fractal structure of time-space is a prerequisite condition for the coupling and Gompertzian growth. On the other hand, the Gompertz function is a probability function. Its derivative is a probability density function. Gompertzian dynamics emerges as a result of the co-existence of at least two antagonistic processes with the complex coupling of their probabilities. This dynamics implicates a coupling between time and space through a linear function of their logarithms. The spatial fractal dimension is a function of both scalar time and the temporal fractal dimension. The Gompertz function reflects the equilibrium between regular states with predictable dynamics and chaotic states with unpredictable dynamics; a fact important for cancer chemoprevention. We conclude that the fractal-stochastic dualism is a universal natural law of biological complexity.
Interview notes and charts
- The difference between what the government was telling us and what their information was telling us was so extreme and outrageous.
- Exponential means a “constant rate of growth.” The government data in March was clearly showing that the COVID-19 was declining, not growing exponentially. This was the same in all countries you could see the data. [See chart 1]
- A constantly declining growth rate will make a bell curve. The government were standing in front of bell curve graphs during their briefings yet they were telling us we were in the middle of the epidemic.
- It was very clear that we were heading to a peak sometime around early to mid-April.
- You don’t have to be complicated mathematics to see that COVID-19 was running out of steam almost from day one.
- The conclusion from the Centre for Evidence-Based Medicine seems to be that it’s impossible to predict if there will be a second wave.
- Sweden’s epidemic looks identical to the UK’s but they did not lockdown. Their datapoint indicates there won’t be a second wave. There has been no spike in Denmark either. [See chart 2]
- Unknowns: has summer affected COVID-19 and will there be a mutation?
- Will illnesses during the autumn and winter be mis-attributed to COVID-19? Poor media coverage means that we can’t be sure.
- Symptoms of COVID-19 are very similar to the flu. Something could look like a second wave but will we really know?
- The lockdown is costing a Brexit bill a week.
- The government response seems to have been skewed by Neil Ferguson’s modelling data. The make-up of government advisors seems to be a recipe for groupthink, which is very dangerous.
- Epidemiology (the way a disease spreads through the population) is not complicated science. The government could have had lots of people who were very good at this but they didn’t.
- We should have cocooned the vulnerable, make sure the NHS has capacity and “let it rip” through the population.
- We should never have had an open-ended lockdown.
- The ‘R number’ is just the difference of in the number of people infected after each generation of a disease. Britain crossed the ‘magical R of 1’ line a few days before lockdown and the same day as Sweden. Whatever interventions have been done doesn’t seem to have had any effect. [See chart 3]
- COVID-19 is mostly a care home and hospital disease. This was obvious very early on. Old people should not have been moved from hospitals into care homes. It seems as if we knowingly seeded the most vulnerable environment with the disease.
- 37% of our deaths are care home residents but they are only 0.5% of our population. Of them are dementia sufferers.
- Over 20% of the infections were picked up in the hospitals. COVID-19 seems more like MRSA than influenza in that it’s an infection control problem.
- COVID-19 is much more comparable to flu for the rest of the population.
- 1968 flu killed 80,000 people in the UK.
- This last winter was a low flu winter. It’s quite possible that the people who died of COVID-19 are those who didn’t die.
- If you overlay COVID-19 deaths with the 2000 flu season, they look very similar. [See chart 4]
- 95% of deaths have had another serious disease. Most people have almost no chance of dying from COVID-19.
- If you are under 40, you have more chance of being struck by lightning that dying of COVID-19.
- If you are under 60, you have more chance of drowning.
- At any age, you have more chance of dying on the roads than dying of COVID-19.
- Lead indicators of 111 and 999 calls with COVID-19 symptoms show there was no spike after VE Day celebrations or BLM protests. In fact, it was even coming down at lockdown. That lockdown was big change for COVID-19 is invisible in the data. [See chart 5]
Chart 1: COVID-19 was declining in Europe as of march. It was not growing exponentially
Chart 2: Sweden’s epidemic looks similar to the UK’s but they did not lock down.
Chart 3: Britain crossed the ‘magical R of 1’ line a few days before lockdown
Chart 4: COVID-19 deaths overlayed with the 2000 flu season
Chart 5: No spike after BLM protests
- Far from following the science, the government turned its back on all available data.
- Until mid-April, with the escalating deaths in care homes agonisingly clear across Europe, government policy was still for patients to be discharged to care homes from hospitals without requiring negative tests. And so the toll: around half of UK Covid-19 deaths are care home residents, despite them accounting for only 0.6 per cent of our population.
- Germany, whose population is roughly 25 per cent bigger than ours, has suffered approximately a quarter of our Covid deaths.
- Ministers have deferred to scientists who themselves deferred to the projections of models, even when data on the ground told a completely different story.
- Statisticians on social media had a field day pointing out the chasm between modelled outcomes and reality, but it is not clear that the models on which SAGE relied (both their input parameters and mechanical dynamics) were continually refined with on-the-ground data (or simply discarded as wrong).
- Why weren’t Oxford’s team, who specialise in zoonotic viruses and who looked at the same data as Neil Ferguson’s modelling-led team but came to wildly different conclusions, on SAGE’s panel to provide an alternative view?
- Why were there no economists on SAGE? Economics is not the bloodless pursuit of money but the science of decision-making under uncertainty where resources are finite; could they really have brought nothing to the party?
- In mid-March, Stanford’s Nobel laureate Michael Levitt (biophysicist and professor of structural biology) discussed the “natural experiment” of the Diamond Princess cruise ship, a petridish disproportionately filled with the most susceptible age and health groups. Even here, despite the virus spreading uncontrolled onboard for at least two weeks, infection only reached a minority of passengers and crew.
- The data towards the end of March clearly showed we were already near the tipping point of the bell-curve (meaning the disease is on the wane). We were already past the point where lockdown could have made much difference.
- Knut Wittkowski: “respiratory diseases [including Covid-19] . . . remain only about two months in any given population”.
Scientists at Institut Pasteur studied 1,340 people in Crepy-en-Valois, a town northeast of Paris that suffered an outbreak in February and March, including 510 students from six primary schools. They found three probable cases among kids that didn’t lead to more infections among other pupils or teachers.
The study confirms that children appear to show fewer telltale symptoms than adults and be less contagious, providing a justification for school reopenings in countries from Denmark to Switzerland. The researchers found that 61% of the parents of infected kids had the coronavirus, compared with about 7% of parents of healthy ones, suggesting it was the parents who had infected their offspring rather than the other way around.
After years of a near jobs miracle that saw record numbers in employment, Covid-19 is taking a brutal toll.
Figures from the ONS today show that the number of staff on UK payrolls fell by 612,000 between March and May.
Claimant unemployment is already up by 1.6 million since March to 2.8 million. In the whole year after the 1929 Wall Street Crash it rose by 1.0 million.
The sad but unavoidable fact, that the disease is little danger to most young and healthy people but is especially deadly to the old and ill, is also now beyond dispute…
The ceaseless assumption of the Government and the BBC that the shutdown ‘protected’ the NHS is simply not borne out by any facts. The NHS was never going to be overwhelmed. Covid deaths in this country peaked on April 8 – an event far too soon to have been caused by the shutdown announced on March 23 and begun the following day.
In fact, the country with the highest number of deaths per head is Belgium (843 per million). Yet Belgium introduced one of the tightest and most severe shutdowns on the planet. Sweden, without a shutdown at all, has suffered 472 deaths per million.
The UK figure of 620 per million may be inflated by our lax recording methods but hardly suggests that we did better than Sweden by throttling our economy and grossly interfering in personal liberty. Japan, which also did not shut down, suffered just over seven (yes, seven) deaths per million…
I believe that forces hostile to our country, its history and nature, have seen this as an opportunity. Probably incredulous to begin with, they realised the British people really had gone soft, accepting absurd and humiliating diktats, believing the most ridiculous claims.
By simply separating out weekly reporting variability, the long-term death rate profile becomes clear, and its peak can be located with confidence. Using the distribution of times from disease onset to death, it is possible to extend the model to infer the time course of fatal infections required to produce the later deaths. Because of the wide variability in onset to death times, a quite sharply peaked infection curve produces a death curve that declines only slowly. The inferred infection curve peaks a few days before lockdown, with fatal infections now likely to be occurring at a much-reduced rate.
If social distancing made things better, we would expect a positive correlation on both of these graphs – in other words, earlier social distancing would lead to both earlier flattening of the curve and lower total deaths, meaning these points would all sit close to a diagonal line sloping up from left to right. Instead what we see is very little correlation at all, and what there is is negative. So early social distancing is either doing nothing or making things worse. This is likely because the virus spreads mainly in hospitals, care homes and private homes rather than in the community, so social distancing of the wider population beyond a basic minimum (washing hands, self-isolating when ill, not getting too close, and so on) has little impact.
Professor Carl Heneghan, an Oxford University epidemiologist, expects no ‘excess deaths’ by the second week of June, for which the data will not become available until mid-June.
The weekly death toll in England and Wales dropped to its lowest levels since the lockdown began, an Office for National Statistics (ONS) report said today. A total of 1,983 people in England and Wales died with Covid-19 in the week ending May 22, down almost 30 per cent in a week and the lowest figure for two months.