A wise man doesn’t run blindly with the crowd, he observes carefully and thinks for himself.
An astute and careful examination of the science and data, current and historical, nationally and internationally, helps us to put the current and past coronavirus situation into real perspective. Statistics and charts can be tricky and they are often used to push a certain point-of-view. However, with some critical thinking and basic school-level mathematics, we are all capable of understanding what the data means. We do not need to be scientists, mathematicians or subject-matter experts to come to sensible and informed conclusions.
“It is the right and duty of every citizen to see what the scientists have said and to analyse it for themselves.” - Lord Sumption, former Justice of The Supreme Court.
All images and graphs will expand if dabbed.
Notice that the government continues to record any death as a COVID19 fatality providing there was a history of a positive PCR test result. They have narrowed this down now to “Deaths for any reason within 28 days of a positive test”, whereas before there was no time restraint to this unprecedented method of recording.
Before going into detail, we need to be honest and concede that an accurate determination of the statistical facts for the 2020 coronavirus epidemic is almost impossible to achieve, primarily due to the very unusual way in which this situation has been recorded and reported. Currently, under new UK legislation, rushed in by the current government, a person only has to test positive for the Sars-Cov-2 virus at any point in the 28 days prior to their death for “COVID-19” to be recorded as the cause of passing on their death certificate, a policy which totally ignores the fact the majority of SARS-CoV-2 infections are completely asymptomatic. This has already resulted in hugely inflated numbers, which had to be re-estimated and revised down by thousands following cross examination by Oxford University’s Centre for Evidence Based Medicine.
Due to recording bias in favour of higher numbers, the officially recognised COVID-19 numbers are likely to be significantly higher than the actual reality.
Unfortunately, we are unable to change the past and must do our best to use the government figures to try and gain some proper perspective, which is probably still possible, especially if we remain mindful of these facts.
At the time
of writing this piece in early October, the UK COVID death toll, including all
the sad losses which weren't actually directly "from COVID" but
"with COVID", such as those who died of cancer, other infections, accidents and other serious co-morbidities but still got recorded as COVID deaths, is now
sadly 42,592 for the entire United Kingdom, or 38,395 for England and
Wales (necessary for better comparisons, as seen in the first bar chart below).
This number stands despite the fact that “Covid19 deaths” are incredibly vaguely defined.
Now that millions of people are being tested, anyone of those that dies within the 28 days following a positive PCR test, regardless of whether its a genuine or a false-positive result, can potentially be recorded as a COVID death, making it even more difficult to make real sense of the situation.
However, for context, in an average year in the UK we lose 620,000 people to all causes, which averages out at 51,700 per month. During the months that we’ve been focussed on COVID, those 8 months would normally, on average, see the passing of nearly 500,000 people to all causes, which equates to 1700 per day.
To start putting the England and Wales COVID-19 tally of 38,395 into perspective, just two years ago in the 2017/18 winter period, according to the Government's Office for National Statistics (ONS), there were 50,100 excess winter deaths (EWD) in England and Wales alone; which totalled around 64 thousand in the whole of the UK. The ONS report blamed "circulating influenza" for the spike in deaths.
If we look
back a little further to the winters of 1999/00 and 2014/15, there were 48,000 and 44,000
excess deaths respectively in England and Wales. In 2018 the ONS reported that, "The number of EWD observed in 2017 to 2018 was higher than all years
since the 1975 to 1976 winter period when there were 58,100 EWD." (Ref)
The EWD for England and Wales in 1950/51 totalled 106,400; in 1962/63 they totalled 89,600; in 1967/68 they totalled 70,260; and in 1975/76 they totalled 58,100. For the fifteen years between 1950 and 1965 we lost on average 62,000 people per year to respiratory illnesses like flu in England and Wales alone, with a population 25% smaller than today’s. According to the ONS - "Respiratory disease caused most excess winter deaths".
Please note the following bar chart is for England & Wales, as this is the most common format of statistical records on the ONS website.
These illustrations hopefully help to provide context of scale. The following graph is available on the ONS site and allows more detailed analysis interactively.
Source: UK GOV, ONS interactive graph
The following graph, from Inproportion2, illustrates how the levels of cumulative deaths in 2019/20 are slightly lower than those suffered in 1999/00, which was a nasty flu season.
The following shows the proportion of weekly deaths that were due to Covid-19 in the context of total deaths in the same time period during 1999/00. This year’s April peak is actually lower than the January 2000 peak (totals adjusted to reflect 14% growth in population).
The dark blue bars show the 2020 lockdown deaths not attributed to COVID-19.
Interestingly, fewer people died during the April 2020 peak than in January 2000.
By the tail end of the Spring COVID outbreak, compared to the 5-year average, an excess of 15,000 deaths occurred not attributed to COVID-19, the dark blue bars in the chart.
The next chart, compiled using data from the European Centre for Disease Prevention and Control and Our World In Data, illustrates how “cases” have no relationship to deaths. As the worldwide cumulative case totals increase (shown in red), the COVID-19 deaths (shown in blue) remain flat. As can be seen, deaths from all causes worldwide far exceed deaths from COVID-19.
Regarding the overall lethality of the virus, the World Health Organisation (WHO) has quietly stated in the release of a peer review paper "Infection
fatality rate of COVID-19 inferred from seroprevalence data", by Professor John Ioannidis:
"For people < 70 years old, the infection fatality rate of COVId-19 across 40 locations with available data ranged from 0.00% to 0.31% (median 0.05%); the corrected values were similar."
Its important to note that this IFR is based only upon seroprevalence data (antibodies), and does not take into account T-cell markers of immunity. As we increase our understanding of the global range of spread of the virus, the degree of natural resistance to infection that many have, and the development of community immunity (antibody and T-cell); the IFR has fallen, and is continuing to do so.
Overall infection fatality rate is 0.23%
Under 70’s infection fatality rate is 0.05%
The infection fatality rate for influenza is 0.1%
The above comes only a week after the WHO's , 'Head of Health Emergencies Programme' also confirmed that COVID-19 is on par with flu according to their latest "best estimates", which put the Infection Fatality Rate (IFR) at 0.14%
The following clip of the conference goes into detail:
Ivor Cummins, a biochemical engineer and complex problem solver, has produced an amazing analysis of COVID-19's numbers and patterns. If you want to improve your understanding of how we got here and where we might go next, I would urge you to watch it. It’s the best presentation on the epidemiological science and data that I’ve seen since this scandal started.
He explains the possible reasons for variable annual flu fatalities, including the impact of varying degrees of severity of prior respiratory illness seasons, and considers the pattern of virus behaviour in relation to geographical and latitudinal factors.
Please find the original at https://youtu.be/8UvFhIFzaac
For a better understanding of how and why we are amidst a suging epidemic of new "cases", without a noticable clinical impact, I'd recommend an analysis of the dubious choice of test protocol which has been used to measure and report on the pandemic - How accurate is the COVID-19 test system?
