2022: ONS Statistical Analysis
Summary: SARS-CoV-2 is a virus that has caused worldwide fear, possibly due to the relentless 24/7 media warnings of the dire risks of death over the last 2 years. However, it is estimated that 80% of infections may be asymptomatic, such that a person may have no symptoms, but may include a mild cold-like infection. The next 15% of infections may exhibit symptoms ranging between a common cold to more severe flu-like symptoms. While the last 5% of cases may be serious enough to require hospitalisation, the fatality figures for Covid in the UK, based on official data from the Office of National Statistics (ONS), is estimated to be 0.11% of the UK’s 67 million people. However, this 0.11% figure also needs to be put into further perspective in terms of a mean age of 80+ at the time of death, where most had multiple comorbidities. It will be shown that the (>80) age group have accounted for 60% of all deaths, while the (>60) age groups have accounted for 93% of all deaths. In the context of different age groups, most healthy children have a greater chance of being struck by lightning than dying of Covid.
While fear of the Covid virus has been understandable, the mainstream media, governments and other powerful institutions have possibly distorted what official statistics actually tells us about the risks. This is not to say that risks do not exist, only that they need to be put in perspective of age and other health factors. Only by coming to a better understanding of the actual risks within different age groups might the public at large come to judge the real necessity and effectiveness of imposed lockdowns, mask-wearing, PCR testing, self-isolation and the mass vaccine rollout. However, at the start of 2022, society as a whole now needs to revaluate the cost of such policies in terms of their negative impact on the lives of ordinary people, socially, economically and politically.
It is now January 2022 and from a UK perspective, there is a growing hope that government restrictions may be coming to an end and that life might start to return to some sense of normalcy. However, people in the UK, like many other countries around the world, have been subject to an almost a relentless 24/7 onslaught of media reporting on the dire risk to life from the Covid virus, which it will be argued has been out of all proportion to the actual statistical risk.
Note: Misinformation about the risk from the Covid virus has not just been confined to the media, as governments have also use psychological techniques to try to engineer a ‘consensus majority’ that would support their lockdown policies. In this context, the role of the World Health Organisation (WHO) and other powerful institutions, all with their own self-interests, needs to be questioned – see Propaganda and the Covid-19 Pandemic for more details. Therefore, ending the pandemic may require many more people to question the legitimacy of any consensus, if only manufactured to serve the interests of a powerful minority with little regard to the impact on the lives of the majority.
We might date the start of the Covid pandemic in the UK back to 31-Jan-2020, when the first case was reported. However, over the following months, public concern would be fuelled by media reporting culminating in the first UK death on 6-March-2020. Of course, such media reporting did not only influence public opinion, but government action, such that the UK government would mandate its lockdown policy on 23-March-2020. By 04-April-2020, statistics being issued by the UK and the Italian governments, as recorded on websites like virusncov.com, were suggesting death rates between 10-12% based on infection.
|Date||Country||Population||% Infected||% Death||% Active||% Recovery|
In retrospect, we now know that these initial statistics were not an accurate assessment of the infection numbers nor the actual cause of death. However, it is understandable that people would have been worried by such statistics, especially when translated into newspaper headlines. As a consequence, there were growing calls for governments to mitigate the threat, which in-turn gave politicians an effective mandate to impose lockdowns, mask-wearing, PCR testing, self-isolation and eventually a mass vaccine rollout. While governments claimed their decisions were backed by a ‘scientific consensus’, how this consensus was created and maintained by censorship was never explained to the public – see Pandemic Addendum for links to alternative views. However, at this early stage, overly-protective measures may have seemed a sensible precaution in the absence of any real information about the potential severity of the Covid virus, especially in light of an influential report by Imperial College published on 16-March-2020. This discussion will only summarise the headline recommendations of this report as follows:
In the absence of any control measures, we would expect a peak in daily deaths to occur after approximately 3 months. In such scenarios, given an estimated R0 of 2.4, we predict 81% of the GB and US populations would be infected over the course of the epidemic. In total, in an unmitigated epidemic, we would predict 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.
As of 22-Jan-2022, we know this did not happen, as the number of deaths officially attributed to Covid in the UK now stands at 153,490 after nearly 2 years. Of course, advocates of the government lockdown policy might claim that it was their action that saved 356,510 lives. However, the accuracy behind this claim needs to be questioned both in terms of the many inaccurate assumptions within the Imperial model and the questionable accuracy of the 153,490 deaths attributed to Covid, which will be addressed later in this discussion based on official statistics subsequently released by the Office of National Statistics (ONS).
Note: While statistical data in the early months was limited, the case of the cruise ship Diamond Princess might still have added weight to an alternative to the social and economic lockdowns to be debated rather than censored. This ship began its voyage on 20-Jan-2020 and was held in Covid quarantine until 1-Mar-2020. Over this time, 567 out of 2666 passengers and 145 of the 1045 crew were infected and 14 died.
If this incident were considered as a study case, then 21.2% of the passengers and 13.8% of the crew were infected. While there were possibly many reasons for the difference in these infection rates, the age demographics of older passengers and a younger crew may have accounted for much of this difference. Overall, 19.1% of the 3711 people onboard were infected, but where 14 deaths only represented 1.96% of those infected and only 0.37% of the ship’s population, which contradicted the alarming death rates being cited in the first table above, dated 04-April-2020.
Note: As early as 22 -March-2020, a day before the UK lockdown, Professor Walter Ricciardi, scientific adviser to Italy’s health minister, stated that only 12% of death certificates issued in Northern Italy showed direct causality to the coronavirus, such that 88% of deaths might have been attributed to age and other pre-existing morbidities. It is now also known that vitamin-D deficiency in many of the older women might also have been a contributory factor.
While the issue of deaths by age and other comorbidities will be discussed further in terms of revised UK statistics recently issued by the ONS, there was already growing statistical data in 2020 that questioned the official narrative. The initial analysis in ‘The Covid-19 Pandemic’, published back in 2020, already questioned the death rates from Covid, as well as the efficacy of most of the prevention policies being mandated by governments around the world.
So, how might we now review the statistical data surrounding Covid in 2022?
Initially, we might simply consider updating the first table below with later figures taken from the website virusncov.com. However, while this website provides statistics for most countries, the next table will simply focus on the UK, such that we might attempt to correlate and explain the figures with official UK-ONS statistics.
Note: Each country has experienced different impacts of the Covid virus, which may be attributed to differences in demographics, both geographic and population. In terms of deaths per million, there is a variance around a global average of <1000 (0.1%), which is also reflected in the UK deaths as a percentage of the population. The UK has a population of 67 million, where approximately 600,000 people die every year from all causes, where numbers are weighted towards age and other comorbidities. Due to its northernly latitude, there is a higher risk of death in the winter months, which some have explained in terms of vitamin-D deficiency due to the reduced levels of UVB.
In the table above, we can see the figures for cases and deaths for both 2020 and 2021. However, it is generally accepted that the percentage figure for UK Covid infections may still be an under-estimation, such that the deaths as a percentage of infections may be essentially meaningless. As such, focus will be directed towards the deaths as a percentage of the population, although we still need to question the number of Covid deaths in terms of age and other comorbidities.
Note: First, we might highlight the reduction in the inferred 9.5% death rate initially projected on 04-April-2020 to the actual figure of 0.11%, when presented as a percentage of the population. Again, advocates of lockdown policies may claim this reduction was the result of government action. However, there is now considerable evidence that other developed countries that did not impose severe lockdown policies all ended up with very similar death rates.
At this point, we shall now consider the cause of death in the UK for both 2020 and 2021 using ONS data, published on 7-Jan-2022, such that we might extend the analysis surrounding the statistical data shown in the previous table. In the charts below, the thicker black curve represents the 5-year average of deaths in the UK against which we might make an assessment of the excess deaths being attributed to Covid.
Clearly, in the 2020 chart above, there is an marked increase in deaths in the April-May timeframe, where the scale of the vertical axis now shows deaths as a percentage of the UK 67 million population. In part, this presentation of lives lost was chosen, not to belittle the fact that many people did die, but simply to put the statistical risk into some better initial perspective. After the peak of deaths occur in April and May, the deaths fall back towards the 5-year average, but then rise in the winter months that links the 2020 and 2021 charts. However, in the 2021 chart, the Covid deaths appear to fall towards the 5-year average by March, where the weekly Covid deaths as a percentage of the UK population equates to (0.001%). However, we possibly need to also analyse the Covid deaths by age, again using official statistics from the UK ONS.
In the chart above, we see the ONS actual number of deaths by age, but where these numbers are then translated into the table as a percentage of the population with an overall assessment of percentage risk by age. In the chart and the table, we can clearly see that the (>80) age group is at the most risk, which if combined into an (>60) age group would represent over 93% of all Covid deaths. The figure in the table column right then shows a weighted %-risk by accounting for the percentage size of the population in each age group. For example, the (>80) age group that accounts for 61% of all Covid death, only represents 8.65% of the population by size, such that the weighted risk is nearly 80%. By comparison, the youngest (0-20) age group have a statistically minimal risk of (0.02%) of dying from Covid, which is 3,796 times smaller than people in the (<80) age group. Of course, this does not mean that nobody in the younger age groups have died from Covid, only that the actual risk is far smaller than for many other causes of death.
Note: While the analysis above is based on the latest official ONS data, a similar analysis done in June-2020 basically came to the same conclusion about the risk of death by age – see All-Cause Mortality for more details. In an interview with Professor Karol Sikova (19-Jan-2022) it was stated that a freedom of information (FOI) request to the ONS suggested that only 17,371 people had died directly of Covid over the last 2 years, where the average age was 82.5.
While the figure of 17,371 might have to be treated as somewhat anecdotal at this stage, it would equate to 8,685 deaths per year, if averaged over 2 years, which is 10.75% of the official ONS figure of 80,830. However, this figure appears comparable to the revised figure of 12% issued by Professor Walter Ricciardi for the deaths in Northern Italy in 2020. While it is unlikely that there will ever be a case-by-case review of the 80,830 Covid deaths in the UK, the idea that all of the deaths, where the average age was 82.5, could be attributed solely to Covid seems questionable to say the least.
Note: We might use an earlier hypothetical example presented in the All-Cause Mortality discussion simply by way of an illustration. A frail 85-year-old man is walking along, when a strong gust of wind causes him to fall, such that he sustains a serious head injury. As a consequence, he is taken to hospital for what is perceived to be a life-threatening injury, where unfortunately he is exposed to an influenza virus. Due to his poor general health, the shock of the head injury and a virus infection, his weaken immune system succumbs to pneumonia, where respiratory complications lead to his subsequent death. So, the question is what was the cause of death?
While we might assume that ‘a gust of wind’ would not be cited as the cause of death in this hypothetical case, it is highlighted that prior to 2020, the presence of an influenza virus was not a mandatory requirement to be noted on the death certificate, unlike Covid in 2020. However, we might try to get some additional perspective on this issue using official ONS data, published in 2020, for influenza + pneumonia, as summarised in the chart below.
As cited in the previous example, separating out causality of death between influenza and pneumonia, as well as other potential causes is often difficult, especially in older age groups. In 2020, there were 111,957 recorded influenza and pneumonia infections present at death, but only 20,523 considered to be the primary cause of death. In 2019, this figure was higher at 26,398 and even higher in 2018 at 29,516. As a ballpark estimate, it appears that only 20% of the influenza and pneumonia infections were considered to be the primary cause of death. It might therefore be suggested that a similar estimate might apply to Covid, especially if some of the excess deaths were caused by lockdown policies that curtailed health services for all other non-Covid illnesses. Within this wider appraisal of all-cause mortality, the following causes of death need to be taken into consideration, where most are weighted towards older age groups, as shown by the red curve in the chart below.
|Non-Covid Death Rates||% Rate||Deaths|
|All Other causes||22.00%||132,000|
|All causes, all ages||100.00%||599,988|
At the start of this discussion, it was claimed that the 24/7 media reporting constantly warning of the dire risk to life from the Covid virus could not be supported by an analysis of the statistical risk. While this was also the conclusion of ‘The Covid-19 Pandemic’ analysis done in 2020, the analysis of the latest official ONS data has not change the conclusion that the UK population, along with its politicians, have been misled in respect to both the risks and the effectiveness of its lockdown policy.
But can this conclusion really be defended?
Let us start by first summarising some of the data outlined in terms of the official 2020 ONS statistics, but now rationalised by age groups as suggested by the previous chart. The table below is colour coded into green (0-49), amber (50-59) and red (>60), where in the columns left, we see the potential risk to these aggregated age groups, while the columns on the right show the population breakdown for each age group.
So, in-line with the previous analysis of the official ONS data, we see that the green age groups only have an aggregated 1.85% risk of death from Covid, while representing 62% of the population. The amber group (50-59) has an increased risk of death of 4.29%, such that this group may require greater protection, if known to have existing health issues that may make them more vulnerable to Covid. However, the population of the green and amber age group are the most representative of the working population on which the UK economy depends, while the age group (<20) reflects the equally important section of the population in full-time education. Finally, the red group reflects the (>60) age groups in which 93% of Covid deaths occurred.
Note: The table above reflects the official number of Covid deaths even though the analysis has suggested that the actual number of deaths directly attributable to Covid might be considerably reduced. Equally, just focusing on Covid deaths ignores any excess deaths caused by the negative impact on health services for all other illnesses. Even the official figure of 80,820 Covid deaths only represents about 13% of the 600,000 people who die in the UK every year, where 61% of the Covid deaths were in the (>80) age group, who statistically may have had only months to live, irrespective of the pandemic or any lockdown measures.
Based on the table above, it might be argued that a more cost-effective protection policy may have allowed most of the population, least at risk, to continue to remain in work and in schools with various degrees of ‘smart-distancing’ where necessary. If so, then all of the money and resources expended on widespread social and economic lockdowns could have been focused on the age groups most at risk. As shown in the table, the age groups between (0-49) that make up 62% of the UK population only had a 1.85% risk, while younger age groups (0-19) still in education only had a 0.025% risk. While many will consider an analysis based on statistics to be cold and impersonal, they undoubtedly provide a more rational basis for government policy than political rhetoric as made by the Governor of New York, Andrew Cuomo.
I want to be able to say to the people of New York, I did everything
we could do.
And if everything we do saves just one life, I’ll be happy.
However, without an understanding of the real risks by age groups, politicians in New York transferred elderly Covid patients back into care homes at the height of the pandemic. As a consequence, New York had one of the highest care home death tolls with more than 6,400 Covid related deaths in its care facilities. Sadly, there were many other similar instances of high death tolls in care homes around the world as politicians thought they had to prevent hospitals being overwhelmed by Covid patients within younger age groups, and contrary to media reports, this rarely materialised.
Note: In the UK, only 3 of the emergency Covid hospitals were ever used to treat Covid patients, despite costing more than £500 million of taxpayer money in 2020. Subsequently, only two of these hospitals were used to treat Covid patients in the secondary 2020/21 winter outbreak, despite governments Covid-19 alert levels being raised to five due to further fears that the NHS being overwhelmed. All of these emergency hospitals only ever had very low occupancy.
So, if politicians did not really understand the real statistical risk to its population by age group, we might also question whether they understood the social and economic costs incurred as a result of the lockdown policies. We might start by first considering the economic impact as reported by the ‘Institute of Government’ in the UK as summarised in the following chart estimating the public sector borrowing for just 2020.
While the Institute for Government is described as an independent research and analysis ‘think tank’, it is unclear whether it is completely unbiased in its political alignment. Therefore, we shall only summarise its assessment of the chart above.
Public borrowing in 2020/21 will be £317.4bn above the government’s plans, such that it is representative of the ‘costs of Covid’ so far to the public finances in the current year. While lockdown and social distancing also caused a huge economic contraction in the UK. Estimates vary, but many forecasters predict that the UK GDP figure will be at least 10% lower in real terms in 2020 than in 2019. The latest projection from the Office for Budget Responsibility (OBR) suggests output will fall by 13.3% over the 2020/21 financial year, equating to a further £336 billion loss of revenue to the UK. If so, this would amount to a £700 billion deficit to the UK economy.
However, while some politicians may be happy to incur such enormous costs to the national economy in order to save just one life, the analysis shows that the risk to 75% of the UK population was 6.1%, where the aggregated deaths of the (0-49) age group was 1,499. While some may still be sadly overwhelmed by this number, statistically it represents only 0.25% of the 600,000 people who die every year in the UK.
But how has the Covid pandemic impacted society at large?
While, this is not a question that can really be address solely in terms of statistics, we might try to summarise some of the impacts that may persist into the future. While statistics might help rationalise the risks of Covid within different age groups and provide some insights to the economic cost, the overall damage to society is more difficult to quantify as a number. Anecdotally, it might be realised that society has been unable to function properly due to lockdown restrictions that have often adversely affected the most vulnerable in society.
Note: As a generalisation, the mental health of a population often depends on social interaction, whether in terms of sports and entertainment events, travelling and holidays or the celebration of cultural, religious and festive events. Stress has also been caused by job losses and social distancing restrictions involving family and friends plus imposed school closures and postponement of important examinations.
Of course, people are not immune to the wider impacts of the lockdown policies that have cause disruption to normal health services as governments put disproportional emphasis on just one illness, Covid, that statistics shows has claim the lives of 0.1% of the UK population.
Note: In terms of health services, priority appears to have been given to detecting, quarantine and treatment of suspected or confirmed cases based on questionable PCR results. This has resulted in reduced services for other essential medical services, such that people with other diseases and health problems have been neglected, which have undoubtedly resulted in excess deaths beyond Covid.
While the financial cost of Covid to the UK economy has been outlined, there are clearly much wider impacts that are affecting the global economy that may take years to resolve with the potential for increased geopolitical tensions around the world.
Note: Over the last 2 years, most societies have experienced the impact of a slowdown of the manufacturing of essential goods and the disruption of the supply chain of products, which has also led to the inflation of prices. Again, it is the most vulnerable in society who are the most affected by rising prices and loss of earnings and savings. The idea of a globalised economy is being challenged in a post-Covid world as many nations now realise the danger of being too dependent on foreign imports and exports. If so, this may dramatically change the world over the coming decades.
Finally, some reference might be made to the impact on our political systems. Recent research by Cambridge University has highlighted the loss of confidence in politicians and governments across the western world. While the link above allows access to the actual report, a general summary might be provided.
Across the globe, democracy is in a state of malaise. We find dissatisfaction with democracy has risen over time, and is reaching an all-time global high, in particular in developed countries. It is also suggested that the younger age groups are more affected by the restrictions of government lockdown policies, such that they have come to have less confidence in political institutions with an increasingly negative attitude towards elections.
In part, politicians themselves must take responsibility for this state of affairs, as so many appear to be prioritizing ideological rhetoric and point-scoring over their political opponents rather than focusing on the growing list of problems in the wider world. Therefore, out of all the issues outlined above, possibly the attitude of the younger generations will have the most far-reaching effect on future socio-political developments. As the optimism and influence of the baby-boomer generation of the 20th century continues to fade into history, those born in the 21st century may come to see the world in a very different way. While my generation can only wish their grandchildren well, it can only be hoped that they may become more critical of those who attempt to engineer a consensus that only serves the self-interest of a minority, who then try to use this consensus to impose a censorship on any wider debate.
One final issue for consideration. In 2020 there were no vaccines, while in 2021 there was mass vaccinations. However, the analysis of the ONS official data appears to suggest that Covid deaths, as a percentage of the UK population, probably never exceeded 0.1% in either year. If so, how might the efficacy of any Covid vaccine be calculated with respect to preventing death?