Propaganda and the Covid-19 Pandemic

Note: Originally, this discussion was preceded by another discussion entitled 'The Scope of Propaganda' that has now been returned to the Essay section. While this preceding discussion is not necessary in the context of the Covid-19 discussion, it might still be useful.

The first problem is that truth can quickly be lost or hidden in claim and counter-claim, such that we may only infer probability, not certainty, over any facts. However, we might proceed on the basis of what was initially assumed to be true, i.e. the Covid-19 virus first infected humans in a wet market in the city of Wutan. However, some now claim that the virus ‘escaped’ from a virology laboratory located in Wutan, not far from the cited wet-market. At this time, this is still an unproven claim – see videos Source of the Coronavirus and Origin of the CCP virus for more details. Irrespective of the source, evidence suggests that this initial infection may have occurred as early as 17-Nov-2019. Subsequent evidence has also emerged that doctors in Wuhan tried to report an outbreak of an unknown illness in December 2019, but were censored by the Chinese government, although possibly a decision taken at a local level. However, what is known is that China did not put the city of Wutan into lockdown until 23-Jan-2020 by which time it is estimated that possibly up to 5 million people had left Wutan for the Chinese New Year, many on international flights. The first case of the virus outside China was reported on 13-Jan-2020 in Thailand, followed two days later by Japan and within 10 days infections had appeared in over 20 countries. Analysis shows that most of the countries initially infected had international flights from Chinese cities known to have been infected at that time.

So, who knew what and when?

Taiwanese health officials claim to have alerted the World Health Organisation of a coronavirus on 31-Dec-2019 and that the WHO failed to pass on the warning to other countries. On 14-Jan-2020, the WHO supported China’s claim that the coronavirus was not contagious to human. However, subsequent event suggest that the WHO simply accepted the Chinese claim as the reality of human-to-human transmission became increasingly obvious. Finally, on 11-Mar-2020, the WHO declare the Covid-19 virus to be a pandemic, by which time it had already infected over 118,000 people in 110 countries around the world.

Note: Dr. Tedros Adhanom Ghebreyesus was elected to become the WHO Director-Genera in 2017. In light of some of the events outline above, some have claimed he was unduly biased towards the narrative of the Chinese government. Evidence used in support of this claim is based on a campaign speech at China’s Peking University, where he discussed ways China could expand its influence in Africa, which first helped him secure support of the Chinese in his WHO campaign. Later, after he was elected, he apparently promised to exclude Taiwan from the WHO and held meetings to discuss how the WHO could support China’s Belt and Road initiative. On 14-Apr-2020, President Trump announced he was halting WHO funding while a review was being conducted.

 While an impartial review might rightly question some of these statements, probability along with growing circumstantial evidence suggests that some events along the timeline of the pandemic were intended to mislead the public. In this context, ‘the public’ are all the people of the world, including the Chinese people, who have also suffered, and are still suffering, from the consequence of this pandemic.

What other sources of misinformation might be considered?

In the previous discussion of the Covid-19 pandemic, it was highlighted that there appears to be a considerable discrepancy between the number of reported infections and deaths, which cannot be reconciled with any of the basic SIR models produced. While it was recognised that these models were not sophisticated or authoritative, they still highlighted that the current virus statistics, see virusncov.com, show that the number of people still ‘susceptible’ is over 99% in both the global population as a whole or any national population. If so, the current lockdown policies to suppress the basic reproduction number [R0] to below unity and, in so doing, mitigate the peak number of infections may only last while the various lockdown policies are maintained or until an effective vaccine is available for the 99% susceptible population. However, most estimates for any sort of effective vaccine being available for mass use on an entire population are in the 1-2 year timescale, which then leads to the next question.

Can a developed economy remain in lockdown for this length of time?

While it appears that many governments do not want to discuss this question in open public debate, we might speculate that some revised second-phase strategy may be required after the first-phase infections, and deaths, start to fall. As the Covid-19 pandemic discussion has already provided some outline of a potential phase-2 approach, this discussion will not speculate further on this issue, other than to reiterate the question about how long any developed economy can afford to remain in lockdown. However, in the context of this discussion, we might continue to consider the potential scope of propaganda that may already surround the Covid-19 pandemic.

Note: One initial issue of misinformation might be highlighted in terms of the naming of the Covid-19 virus, which some have called either the ‘China virus’ or the ‘Wutan virus’ due to its geographical origins. Others have politicised the name by calling it the ‘CCP virus’ as they consider the Chinese government responsible due to a lack of transparency, which allow the outbreak in Wutan to become a global pandemic. This website has used the name Covid-19 in the belief that the name used will not necessarily determine the results of the investigations needed to understand what went wrong and who might be to blame for its global spread.

 The next issue of misinformation might be considered in terms of a 24/7 mainstream media, which often appears to want to sensationalise the ‘drama’ surrounding the pandemic crisis. For example, little may be presented that informs the public about detailed analysis, but rather gives preference to a myriad of ‘human-interest’ stories, which often help undermine a political ideology they may oppose. In many cases, it seems that the covert ‘mission statement’ of many mainstream media outlets is not to ‘report’ the news, but to present it in a form that best supports their editorial goals. If so, they are propagating misinformation that may be hard to differentiate from propaganda. Under the onslaught of this type of 24/7 news, many governments were basically forced to adopt a suppression policy driven by the idea of ‘political correctness’, where every single life must be saved irrespective of the costs to society as a whole.

Note: While we might all perceive the moral or political reasoning behind this form of political correctness, we still need to question its wisdom as the basis of public policy. For while statistics can be perceived as cold and impersonal, they possibly highlight a wider reality, where 1-billion people go to bed hungry with 25,000 dying, every day, as a result of malnutrition and hunger-related diseases. Possibly more tragic in human terms is that 18,000 of this number is estimated to be children under 5 years old. While these people are not immune to the virus, they are also often the worst affected by any downturn in the global economy.

Of course, misinformation may seek to differentiate itself from propaganda by simply failing to provide accurate information. For example, as indicated, there appears to be little general information about the spread of infection as a percentage of the population or the number of deaths directly attributable to the virus as a percentage of deaths, which normally occur in any population. In addition, even if a death was known to be directly attributable to the Covid-19 virus, little information is provided about the age and underlying health of those who have died. The table below summarises some basic analysis of the UK population, where the low-risk groups represents under 50, while the correspondingly high-risk groups are over 50. The generally accepted %-death rates have then been aggregated for all ages in each of these two groups and shows a 27-fold difference in the death rate for those at high risk.

Risk Groups % Pop % Death
Low-Risk 53.40% 35,778,000 1.00%
High-Risk 46.90% 31,423,000 27.70%

However, it needs to be highlighted that these two groups, based only on age, does not properly reflect potential health risks. Without this type of information, the public will not necessarily understand the nature of the risk that they, as individuals, might be taking, if and when they are exposed to the virus. Equally, it might be argued that without this sort of information, the public will not really understand the effectiveness and implications of the suppression policies being adopted by their government, especially in terms of any secondary phase infections, especially in populations with a 99% susceptibility.  

Note: At this point, a clear distinction has to be made about the necessity to limit the spread of the pandemic and the wider implications of social and economic problems associated with these containment policies. As a first-phase pandemic strategy, the actions of the Taiwan and South Korean governments might be seen as the ‘gold standard’ that few other governments, especially in the West, even came close to meeting. In reality, this gold standard should have been taken by all governments as their first-phase strategy, which may have then prevented or mitigated the subsequent need for a total lockdown with its obvious risks to the social and economic health of the population.

In hindsight, the inability to meet the gold standard outlined has led to a situation, where each government has attempted to justify its version of lockdown on the basis of the advice of medical science. Why so many Western democracies were unprepared to deal with the Covid-19 pandemic, despite plans having been ‘discussed’ for years is beyond the scope of this summary, but clearly needs to be reviewed, if this failure is not to be repeated. However, in terms of the current pandemic, it is not clear whether the scientific medical advice was really in a position to consider the wider issues of the ‘wellbeing’ of a society and its economy, which appear to have been placed on the ‘back-burner’ until the pandemic is ‘under control’. Again, whether the lockdown suppression of [R0] below unity really aligns to the definition of ‘under control’ might be question, if 99% of the population remains susceptible. At this time, one of the major sources of misinformation appears to be the statistics being attributed to the Covid-19 pandemic in different populations, if they have been potentially corrupted for political and economic reasons. While this discussion does not pretend to be authoritative on these statistics, it appears that the number of infections has been under-estimated, grossly in some cases, while the number of deaths has been over-estimated. In the case of the reported infection numbers, the under-estimation may be attributed to the fact that the means to test even a representative sample of the population simply did not exist, although statistical analysis might have been used to provide, at least, a more realistic estimate. Of course, if this is the case, the number of deaths as a percentage of the infected will have been over-estimated, a trend which seems apparent in the following statistics, dated 20-Apr-2020.

Rank Country Population Infections % Deaths %
0 Global 7,700,000,000 2,217,006 0.03% 118,392 5.34%
1 USA 329,227,746 764,265 0.23% 40,565 5.31%
2 Spain 50,800,000 200,210 0.39% 20,852 10.42%
3 Italy 60,500,000 178,972 0.30% 23,660 13.22%
4 France 67,000,000 152,894 0.23% 19,718 12.90%
5 Germany 82,800,000 145,743 0.18% 4,642 3.19%
6 UK 67,772,000 120,067 0.18% 16,060 13.38%
7 Turkey 84,106,165 86,306 0.10% 2,017 2.34%
8 China 1,400,000,000 82,747 0.01% 4,632 5.60%
9 Iran 79,900,000 82,211 0.10% 5,118 6.23%
10 Russia 144,438,554 47,121 0.03% 405 0.86%

In the table above, we see a wide disparity between the %-deaths in the UK and Germany for a comparable infection rate of (0.18%). While we will not speculate too far into the reasons for this disparity, earlier analysis in the Covid-19 pandemic suggested that the UK infection numbers were being grossly under-estimated, such that this alone may explain the four-fold discrepancy between two similar countries. However, as previously suggested, the number of deaths being attributed to the Covid-19 virus without necessarily proving this was the actual cause of death might also have been over-estimated. If so, statistics surrounding both infections and deaths, especially in percentage terms may be almost meaningless, such that they deceive the public about actual risks. Of course, others might question whether some governments might see some short-term advantage in manipulating the risks associated with the Covid-19 pandemic, if it helps public compliance of the lockdown policies. While it is recognised that this sort of speculation does not necessarily change the current situation in which most of us find ourselves, it raises a question that needs to be considered by the public and government alike.

Why are we in this situation and how will we get out of it?

Clearly, this is a question that does not necessarily have a single answer as it may depend on where you live in the world and the strategy being adopted by your government. However, we might attempt to outline a conceptual 3-stage approach to mitigate the pandemic. Ideally, stage-1 requires the ability to quickly ‘detect and monitor’ the spread of the virus, similar in scope to that adopted by Taiwan and South Korea.

Note: We might try to quantify the effectiveness of stage-1 by referencing the Covid-19 statistics as of 22-Apr-2020. Taiwan has a population of 23.6 million, but has only 426 infections and 6 deaths (1.4%). South Korea has a population of 50.8 million with 10,694 infections and 238 deaths (2.2%). In contrast, a country like Italy with a not dissimilar population of 60.3 million has 183,957 infections and 24,648 deaths (13.4%).

The failure, or possibly non-existence, of stage-1 in the worst hit countries has apparently required a stage-2 response in the form of a range of lockdown policies in the hope that the spread of the virus can be contained by suppressing [R0] below unity. However, as indicated, this stage-2 approach appears to leave 99% of the population still susceptible to the virus. If so, the final option, stage-3, is now assumed by some to rest solely on the hope of a vaccine, although it is unclear whether a developed economy can remain in lockdown for the time it might take to develop an effective vaccine.

Note: At this point, the issue of public information about the risks to health along with the social and economic implications of the stage-2 lockdown policies needs to be discussed. This will be especially true, if it is argued that the lockdown policy will need to remain in force until a vaccine is developed, e.g. 1-2 years. However, while many governments are still insisting that maintaining ‘lockdown’ is the only viable approach to protect its population, there is growing evidence that statistics related to infections and deaths are misinforming the public of the actual risk, where the average age of those most seriously affected by the Covid-19 virus may well be over 70 with pre-existing health conditions – see video A Data Centric Perspective for a rational appraisal of the situation and an outline of an alternative prevention strategy being called ‘Smart Distancing’.

This discussion possibly needs to pause for a moment, because it is recognised that the original focus concerning the ‘scope of propaganda' is now only being discussed in terms of the Covid-19 pandemic. However, there may be some justification in continuing to focus on this one issue, if it has become the key topic of public concern now subject to both misinformation and disinformation. If so, a clearer distinction possibly needs to be made between misinformation and disinformation.

Note: We might initially describe misinformation as false information given without malice, if propagated in error. Today, this is possibly the exception rather than the rule, where rumours, half-truths and fake-news are deliberately spread to deceive the public, such that it rarely acts as a positive contribution to society. In contrast, disinformation will be described as the fabrication of knowingly false information, especially when propagated as government propaganda, and used to influence and deceive entire populations.

It is not unreasonable to suggest that the Covid-19 virus has been subject to both misinformation and disinformation, such that it has become almost impossible for the general public to rationalise what is true or false. It might also be argued that this situation has been compounded by the fact that most ‘authoritative’ sources are now being questioned at almost every level. As already indicated, increasing numbers have come to distrust the mainstream media to report the news without political or ideological bias. Such bias has led to a polarisation of ‘opinions’ along political or ideological divides, which is also leading to people to question the nature and effectiveness of their political systems. Of course, this distrust of governments, even democratic ones, will also be compounded if the public suspects that transparency is being subverted by the opaqueness of powerful interests. In such situations, we might recognise why the world has turned to a multitude of social media platforms and applications, too numerous to detail, for information. However, it is naïve to assume that the companies behind these social media platforms do not have their own commercial or ideological bias. If this outline even partially reflects the evolving nature of the modern world in which we now find ourselves, we need to consider a basic question.

How can we determine what is true?

First, we possibly need to accept that the idea of ‘absolute truth’ may be too much of an idealised concept, such that we should aim at a more realistic objective. In this respect, it is going to be suggested that we might proceed by considering the words of Voltaire, not as a rigid axiom, but rather as a guide by which we might judge any information.

“Doubt is not a pleasant condition, but certainty is absurd.”

These words suggest a degree of caution is necessary before simply believing anybody, especially somebody who asserts complete certainty in what they are telling you. Likewise, suspicion might also be raised, if this person or group is advocating the need for a consensus and a suppression of the freedom of others to question their narrative. As argued, these may be the tell-tale signs of propaganda, such that caution is necessary, even if being propagated by what might be assumed to be an ‘authoritative’ source. So, having gone off on a somewhat tangential issue, it will be reiterated that this discussion does not assume itself to be an authoritative source, but will now continue to discuss some further speculative issues surrounding the Covid-19 virus, where no ‘certainty’ should be assumed.

 Note: Lets table some of the statistical information believed to be known about the effects of the Covid-19. These statistics suggest that 80% of those infected may only have mild symptoms, while another 15% will have more severe symptoms, possibly requiring some medical treatment, with the final 5% experiencing life threatening symptoms. Statistics also suggest that the worst effects of the virus are biased towards increasing age, but where even these statistics need to be rationalised in terms of any pre-existing health conditions.

In addition to the note above, those at greatest risk to any disease, including viral infections, invariably have weakened immune systems. This weakness may also be problematic when considering the risks of any future Covid-19 vaccine, especially one that may have only been subject to limited human trials. However, this is an issue that is bound to invite conspiracy theories, fake-news and controversy, especially if proved to be based on rumours, half-truths and falsehood, intended to influence and deceive public opinion. While this discussion makes no apology for being openly critical of the Chinese governments for its excessive use of propaganda, it is also naïve to assume that we necessarily have full access to the ‘truth’ within the borders of our own country. Of course, as indicated, the public has become increasingly suspicious of mainstream media, such that many seek alternative sources of information via search engines and social media platforms, such as Facebook and Google, which also owns YouTube. However, whether these companies are actually the champions of freedom of speech is possibly worthy of some further consideration.

Note: As of 16-Apr-2020, Facebook announced that they will begin alerting users who have interacted with ‘misinformation’ about the coronavirus and refer them to information from the World Health Organization (WHO), as an authoritative source. Similar policies are also being adopted by most other major social media platforms.

While this position might initially be seen as a responsible decision to help prevent their users, and the wider public, from being the victims of misinformation, we possibly need to understand their exact status, as either private or public corporations. Without necessarily pursuing the details, it might be accepted that many decisions taken by these, essentially private companies, will be based on financial or political considerations that may affect their share price, while other policies may reflect an ideological preference of the company founder(s). In this context, the criteria by which these companies determine policy regarding what constitutes fake-news or is considered an authoritative source of information is far from clear. For the reasons already cited, this discussion has already questioned the track-record of the World Health Organisation (WHO) on the issue of the Covid-19 pandemic, especially when guided by its director-general. This authority has also been questioned by President Trump’s announcement, on 14-Apr-2020, that the WHO funding would be halted, while a review was conducted. Two days later, Facebook announces its decision to endorse the WHO as an authoritative source.

Note: Interested readers might wish to reflect on the following summary of WHO statements concerning the Covid-19 virus issued some two weeks after Taiwan wrote to the WHO expressing their concerns of a coronavirus spreading in Wutan. On 09-Jan-2020: WHO states that novel coronaviruses emerge periodically, e.g. SARS in 2002, MERS in 2010. Later 11-Jan-2020: WHO advises against any travel or trade restrictions on China related to the virus outbreak. Also, on 11-Jan-2020: WHO recommends against any specific health measures for travellers to and from Wutan. On 14-Jan-2020, the WHO supports China’s claim that coronavirus was not contagious to humans. Only on 11-Mar-2020, does the WHO finally declare the Covid-19 virus to be a pandemic, by which time it had already infected over 118,000 people in 110 countries around the world.

While certainty about this timeline cannot be made within this discussion, there does appear to be sufficient supportive evidence that the advice of the WHO was far from authoritative. Of course, if this is the case, then we might need to question why social media platforms are endorsing the WHO as the preferred source of authoritative information.

So, where should the public turn for authoritative information about the Covid-19 pandemic?

Clearly, at this point, some further clarification may be required as it would appear that this discussion has cast doubt on all normal sources of information, i.e. world health organisation and governments along with most sources of mainstream and social media. First, this discussion is not suggesting all information from these sources should be rejected, only that we should question the ‘certainty’ of any information. Second, the question about certainty is only being discussed in terms of the Covid-19 pandemic at this point. In this context, much of the public information is being based on provisional statistics from website such as virusncov.com or worldmeters.info, but where the accuracy of the number of reported infections and deaths in each country is questionable. This assertion is based on increasing evidence that the Covid-19 infection spread far more widely long before most national lockdown policies were enforced, where the infected numbers were limited by the capacity to test the wider population. Likewise, there is growing evidence that the number of reported deaths being directly linked to the Covid-19 virus may need to be reviewed in terms of both age and pre-existing health conditions. Again, the video entitled A Data Centric Perspective, dated 24-Apr-2020, might be reviewed for more technical details. Of course, such questioning may be seen to undermined the lockdown policies adopted by most national governments, which leads to a far more contentious question.

Are these lockdown policies a long-term solution?

By way of an extreme and hypothetical example, let us assume that a government could isolate most, but not all, people within a hermetically sealed box, such that they were guaranteed to be protected from the virus. In this respect, this form of lockdown policy would undoubtedly reduce the basic [R0] reproduction number, such that infections and deaths might quickly reduce. Of course, the public might reasonably want to know how long they would have to remain sealed up in this way and what would happen when they were released. As previously discussed, basic SIR models suggest that 99% of the population would still be susceptible to the virus should it be re-introduced in any number of ways. While this is an extreme and hypothetical example of lockdown, it still raises a valid concern.

How long must lockdown last and what happens when it ends?

While this discussion has questioned the accuracy of numbers of reported infections, which suggest that 99% of most national populations are still susceptible to the virus, the idea of herd immunity requires a much larger percentage of the population to have been infected. The actual percentage required for herd immunity to be effective may range between 40-80% depending on the virus. It has been estimated that the Covid-19 virus would require an infection rate of 60-70% in order that [R0] might fall below unity.

Note: Many argue against the idea of herd immunity for a variety of reasons. First, it is often assumed that vaccines will be the most effective way to achieve herd immunity in a population. Of course, if such a vaccine is still 1-2 years away for the general public, this approach may not be realistic in terms of social isolation and economic impacts, which are also known to be detrimental to health. It is also highlighted that ongoing research into antivirals and other medications may also prove to be a treatment for the Covid-19 virus, although it is unclear how effective they might be or that they would negate the need for lockdown to continue. Of course, there is also the underlying worry that hospitals and healthcare systems will become overburdened without the lockdown policy remaining in force.

As also pointed out in the A Data Centric Perspective video, consideration of increasing herd immunity does not have to be polarised in terms of ‘lockdown’ versus ‘doing nothing’, if a revised policy of ‘smart distancing’ might prove to be equally affective. In this context, ‘smart distancing’ might mitigate the worst effects of social isolation and the economic impact on younger and healthier generations, while still maintaining social distancing restrictions on the most at-risk groups, as  determined by age and health risks.

Note: Some reference might also be made to two further videos. The first video entitled ‘The Role of Diet’ discusses the role of the human immune system to fight viral infections based on the dietary effects on a condition known as metabolic syndrome. The second video entitled Vitamin D and Human Health may also provide some further information about ways that the human immune system might be improved and thus be more effective in fighting viral infections.

An argument might reasonably be made that both these videos would not only be informative to the general public, but also reflect authoritative expertise in the topics discussed. It might also be highlighted that the information associated with the levels of obesity, type-2 diabetes and vitamin-D deficiency in northern latitude populations like the UK and New York may also explain the wide variance in Covid-19 deaths now being reported. Therefore, it might be questioned as to why this information is rarely, if ever, presented to the public by the mainstream media, or as government health advice.

Note: The interested reader might wish to consider the discussion of Prevention versus Cure for one possible explanation of the censorship of information. This discussion outlines some of the interests that seek to create a consensus and then restricts any opinion that challenges the narrative of this consensus. Again, such issues question the scope of what constitutes an ‘authoritative source’

Returning to the issue of the lockdown policies, as previously discussed under the heading ‘The Covid-19 Pandemic’, one of the authoritative sources that influenced the lockdown policies in the UK was a report written by the Imperial College. The lead author on this report was Neil Ferguson, who is an epidemiologist and professor of mathematical biology plus a member of  the Scientific Advisory Group for Emergencies (SAGE), a UK governmental body that advises the UK government in emergencies. This group is headed up by Sir Patrick Vallance, Chief Scientific Adviser and Professor Chris Whitty, Chief Medical Adviser. As such, these people were the authoritative sources of information that continue to advise the UK government on its ongoing Covid-19 lockdown strategy. However, the report written by the Imperial College team was then questioned by an Oxford team of epidemiologists based on its assessment that the Covid-19 had already spread through a much larger percentage of the UK before lockdown started.

Note: At this point, other conflicting expert opinions might be highlighted in terms of Professor Johan Giesecke, who is a Swedish expert, who has advised the Swedish government and the WHO and appears in a video interview entitled ‘Why lockdowns are the wrong policy’. However, the same YouTube channel has also published another video with Professor Neil Ferguson, where he defends the UK Coronavirus lockdown strategy.

Again, at this point, it needs to be highlighted that misinformation may be differentiated from propaganda, if it simply fails to provide accurate information. Of course, it might still be recognised that this form of information may still influence and deceive public opinion. So, while this discussion is not in a position to challenge the conclusions of either expert, it might still raise questions and issues surrounding these different conclusions. However, before continuing, it will be stated that the previous discussion entitled ‘The Covid-19 Pandemic’ broadly supported the lockdown policy forwarded by Professor Ferguson as a phase-1 approach, as per the slightly paraphrased extract below:

The longer-term hope appears to be that suppression of the virus might eventually lead to a figure of [R0] below unity, where new infections are outnumbered by the number of recoveries and, in so doing, buy the necessary time, e.g. 1-2 years, for the development of a vaccine. This said, the Cambridge report highlights that if these policies are relaxed, presumably before the general availability of the vaccine, then ‘transmission could quickly rebound’. However, while this discussion will make no direct criticism of any attempts to both understand or minimise the impact of the pandemic, this does not mean that alternative perspectives have to be suppressed provided that the source carries a sufficient weight of authority.

So, in respect to the last sentence, the issue of concern surrounds what happens next and when. As pointed out by Professor Ferguson, the impact, and therefore the response, to the Covid-19 pandemic has to be seen in the context of the demographics of any specific population. Simply as examples, we might consider the latest figures from South Korea and the UK, dated 26-Apr-2020, which appears to show an enormous disparity in both infections and deaths for not dissimilar population sizes.

Country Population Infections % Deaths %
South Korea 50,800,000 10,178 0.02% 240 2.36%
UK 67,772,000 148,377 0.22% 20319 13.69%

First, we might highlight the 10-fold difference in the numbers of infections, which we might initially attribute to the success of the stage-1 approach adopted by South Korea, which included extensive testing and contact tracing backed up by quarantine and isolation protocols plus various degrees of social distancing. In comparison, this was not achieved in the UK, which only imposed a lockdown policy some 52 days after the first infection was detected. It might also be highlighted that South Korea has a younger population, median (41.8) compared to the UK, median (50). This type of demographic difference may undoubtedly change the profile of health conditions, such that one population may be more susceptible to the Covid-19 virus. However, it is not clear that any, or all, of the reasons suggested can account for the deaths shown in the table above being 5.81 times higher in the UK compared to South Korea.

Note: As previously highlighted, the number of infections in both populations corresponds to over 99% still being susceptible. However, there is evidence that the infection numbers in the UK have been grossly under-estimated, which might then lower the high %-deaths in the UK to be more comparable to South Korea. Likewise, it has also been suggested that the number of deaths in the UK attributed to the Covid-19 virus has been over reported by including anybody who has died with the symptoms of the Covid-19 virus without proof that it was the actual cause of death.

Despite the suggestions of the daily statistical reports from website like virusncov.com or worldmeters.info that infection rates are less than 1% of all national populations, Professor Ferguson makes reference to studies suggesting much higher rates of infection, possibly as high as 10-30%, while also alluding to the demographic differences between populations, such as New York and London, being younger and therefore statistically more resilient to the Covid-19 virus. However, if this was the case, we might speculate that the virus could have quickly spread through these younger populations, where a high percentage (80%) may have experienced few obvious symptoms. Likewise, in the absence of any extensive testing to verify the actual spread of the virus in a given population, the percentage of the population now infected with the Covid-19 virus has to remain speculative. This said, it is not unreasonable to assume that infections are much higher than the reported statistics, but below the level required by herd immunity, i.e. 60-70%. However, this issue might still be important to the debate surrounding any future suppression policy, even without having made any reference to other health or economic impacts.

Note: Reference will be made to a YouTube video, Connecting the Dots Part 2, which the reader is advised to question, but not necessarily dismiss. The initial reference is the ‘Computing Forever’ channel run by Dave Cullen and while this channel clearly reflects the bias of its producer, it appears open about this bias and therefore might be said to reflect an opinion, not a conspiracy, that would not otherwise get aired on mainstream media. However, this video also makes reference to another video produced by UK Column News, where the link provides some background information by which to judge the motivation of this channel. Again, while this channel may have a bias, it does not necessarily invalidate the analysis in its news report, dated 15-Apr-2020. However, the reason for referencing these videos is that they suggest that the actual number of UK Covid-19 deaths in week-14 was 475, which might be compared to the number of normal deaths per week being in the region of 10,500, i.e. just 4.5%. However, the real issue of concern is the suggestion that the number of unexplained deaths per week-14 being 5,665 and caused by the unintended consequence of prioritising the Covid-19 virus above all other health conditions.

While these videos are not being propagated as authoritative sources, and accepting that some of the figures need to be questioned, they suggest a possible ‘side-effect’ of the lockdown that has not necessarily been openly discussed by mainstream media. As far as it is known, the figure of 10,500 death per week is compatible with an official figure of 600,000 UK deaths in 2018, where some 78% were caused by medical conditions listed below left, rather than the death rates due to the Covid-19 virus right.

Non-Covid Death Rates % Rate Deaths Age % Death Overall % Risk
Cardiovacular 28.62% 171,702 10-19 0.20% 0.20% 1.00%
Cancers 25.61% 153,630 20-29 0.20% 0.40%
Respiratory 12.18% 73,074 30-39 0.20% 0.60%
Digestive diseases 4.65% 27,876 40-49 0.40% 1.00%
Mental disorders 3.61% 21,630 50-59 1.30% 2.30% 27.70%
Nervous system 3.35% 20,076 60-69 3.60% 5.90%
All Other causes 22.00% 132,000 70-79 8.00% 13.90%
All causes, all ages 100.00% 599,988 80+ 14.80% 28.70%

Again, while there is no certainty in the suggestion, there is some evidence that people who might have normally been treated for the conditions, shown left, within the UK health service may have been ‘overlooked’ by the priority being given to the Covid-19 pandemic. Also, as a consequence of the Covid-19 risk factors, shown right, we might better understand the high mortality rates in some care homes for the elderly, as accepted by both Professors Giesecke and Ferguson. While this outline has only highlighted a few of the issues raised in the videos, we might now consider a series of basic questions.

What was required of the lockdown policy?

As a generalisation, it might be said that the lockdown was attempting to minimise the loss of life, especially in light of the fear that health services might have been overwhelmed by the numbers of Covid-19 cases requiring medical treatment. As stated by Professor Ferguson, the UK health system did avoid being overwhelm, presumably because of the lockdown policy, with only a few hospitals coming close to full capacity. However, there are reports that only 19 patients were treated at the 4,000-bed NHS Nightingale hospital in London over the Easter weekend, while the intensive care capacity at existing London hospitals never went above 80%. However, at the same time, there have been many reported cancellations of elective surgery and cancer treatments as well as a general reduction in the workloads in accident and emergency (A&E) units. As a consequence, concern has been raised that the focus on the Covid-19 virus might have led to additional deaths, not related to the Covid-19 virus, but possibly still contributing to the number of Covid-19 deaths being reported. For example, while the previous figures from the UK Column news report might have to be questioned, the idea that an additional 5,665 people may have died in excess of the normal 10,500 weekly figure might suggest that more people have died as a result of the lockdown than possibly saved by it.

Why did so many governments adopt the lockdown approach?

Of course, this discussion cannot be authoritative on this issue, although it might table some speculative issues that may need to be addressed in the future. For some reason, despite years of apparent planning, many developed nations turned out to be almost totally unprepared for the pandemic, when it hit their populations in comparison to Taiwan or South Korea. We might question why this was so, as it is not unreasonable to assume that ‘intelligence services’ must have had some knowledge of what was really going on in China, especially as the Taiwanese had raised a warning back in December 2019 following the first suspect case in November 2019. Likewise, we possibly have to accept that while some of the misinformation released by the WHO probably did not help, it is not clear that this explains what followed. Irrespective as to why, few governments were in a position to adopt the preventive measures taken by Taiwan and South Korea, we might also recognise that many populations were increasingly being ‘bombarded’ by 24/7 news coverage of the spread of the pandemic and the apparent success of the lockdowns in and round Wutan in China. Again, we may have to wait for clarity on what was information, misinformation or disinformation in order to determine the scope of the propaganda being propagated by different governments and news sources, which the public might have initially perceived as authoritative. Therefore, all that might be surmised at this point is that many governments were coming under increased pressure to prioritise the safety of their populations, irrespective of the economic cost. So, in the face of this onslaught from mainstream media plus the advice of medical science and the possible lobbying by powerful interest groups, governments may have perceived any alternative to lockdown as political suicide. This said, many governments are now having to count the economic cost to the nation, while many sections of the population, especially younger generations, are experiencing the negative effects of both financial loss and loss of their social liberty.

So, what might be the next step after lockdown?

Professor Ferguson makes several references to some form of lockdown being required until a vaccine is developed, which by his own estimates may take 1-2 years before being generally available. However, in the context of this timescale, he also appears to accept that there may be other practical issues to be considered, beyond the remit of medical science. As illustrated in the previous table right, people in the age groups over 50 are much more likely to be seriously affected by the Covid-19 virus, i.e. by a factor of 27. If so, then lifting the restrictions on younger generations may be a viable way to getting the economy back to work, while recognising that younger generations have often been the hardest hit by the phase-1 lockdown policy, both socially and financially. Of course, it has to be recognised that, statistically, these groups still have a 1% risk of death, which might translate into 1000 lives in an infected population of 100,000. Therefore, any phase-2 strategy would still need to mitigate this risk by recommending younger people with known health issue to maintain stricter social distancing and wear face masks. In addition, it would be hoped that many more governments may now be better prepare to adopt the strategy of Taiwan and South Korea, especially if virus and antibody tests become more widely available. Likewise, it might be suggested that some costs associated with the Phase-1 lockdown policy might then be diverted to better protect the most vulnerable, i.e. those elderly people in care homes with a history of many of the health conditions cited in the previous table.

 But, what about the vaccine option?

While the cartoon might be seen to have an obvious bias, it reflects a concern about the role of pharmaceutical companies in the various organisation seeking to develop vaccines, as will be outlined below. It will also be flagged from the outset that this section of the discussion will be the most controversial, because the authority of some sources needs to be seriously questioned. However, again, while highlighting this concern and recognising the risk of propagating misinformation, the cost of retaining a freedom of speech requires us all to make informed judgements rather than just imposing censorship on anything to which we might disagree. So, let us start by returning to the problem of ‘authoritative sources’ given some of the concerns previously outlined. On the issue of vaccines, most might recognise that our politicians will, in general, have no authoritative knowledge of the issues surrounding the development and effectiveness of vaccines. Likewise, any information received from mainstream media may be based on the opinions of a variety of ‘experts’, who may have been selected because they support the narrative being propagated by the news channels. So, let us try to establish some reasonable baseline of information about vaccines and the history of their development, which will be summarised in terms of the references to the generally ‘acceptable’ sources in the note below.

Note: A goal of a vaccine is to help the human immune system to better recognise and fight specific infectious diseases. The historical timeline of vaccine development provides a powerful argument to their benefit, while the introduction possibly indicates some limitations. However, in the context of the current discussion, the focus is on the future development of a Covid-19 vaccine, where most estimates appear to range between 1-2 years.

However, we possibly need to recognise that vaccine development is not just an altruistic endeavour, but one also driven by commercial ‘return on investment’. A report from Statista in 2019 suggested that the global vaccine market was expected to reach revenues of nearly $60 billion by 2020. Of course, this was before the current Covid-19 crisis, such that we might reasonably assume this earlier projection might now be inflated to a much higher figure.

Note: We might make a very speculative estimate of the value of the Covid-19 vaccine market, if we assume that the pharmaceutical companies might charge $500 per vaccine. Any analysis of what pharmaceutical companies charge for other life saving drugs might question this estimate as being overly optimistic. However, if we proceed on this estimate plus the assumption that half the global population might be a buyer of this vaccine, it would lead to a potential market value of about $2 trillion. If required every year, like the flu vaccine, we might perceive why so many companies are now trying to develop a vaccine and why the share price of many leading pharmaceutical companies is rising. Of course, not all will be winners in this development race, but the winners will surely be a position to guarantee a very lucrative ROI.

So far, the information surrounding vaccine development has not really been that controversial, even in terms of its assessment of some of the profit motives behind the pharmaceutical companies. However, reference will now be made to some more controversial information that many need to question, but not necessarily dismissed.

Note: While previous reference has already been made to a YouTube video, Connecting the Dots Part 2, comments were initially limited to the issue of potentially additional deaths in the UK resulting from the lockdown policy. However, this video makes reference to information about vaccine development in another UK-Column video, dated 15-Apr-2020. This video introduces Vanessa Beeley, who might either be described as an activist, who promotes conspiracy theories or simply an investigative journalist. Either way, some caution is advised in assuming this to be an authoritative source. 

At this point, this discussion is not making any direct comments on the claims made within the UK-column video, but will reference other information about the various institutions mentioned. The Vaccine Impact Modelling Consortium lists its key partners as Imperial College London, but where the Bill & Melinda Gates Foundation and the Gavi Vaccine Alliance are the primary funders. While Professor Neil Ferguson is listed as the Acting Consortium Director, he is also a professor at the Imperial College, which the video claims has received a total of $400 million from the Wellcome Trust and $185 million from the Gates Foundation, since 2014. The video also highlights some of the strategic partnerships that both support and finance the Gavi Vaccine Alliance, as outlined in the following charts.

The video also goes on to mention a link between the Gavi Alliance and the ID-2020 alliance, where the goal or mission statement of this organisation may be subject to some very different interpretations, although we will start with the ID-2020’s own statement shown below.

Identity is vital for political, economic, and social opportunity. But systems of identification are archaic, insecure, lack adequate privacy protection, and for over a billion people, inaccessible. Digital identity is being defined now and we need to get it right.

While this appears to be an admirable goal, it is not surprising that some might seriously question this goal in terms of the right to privacy, such that we might wish to know a little bit more about this organisation and its objectives. The ID-2020 Alliance was apparently started in 2017 with founder members Accenture, GAVI, Microsoft, Rockefeller Foundation and IDEO.org with the goal of tagging every global citizen by the year 2030. GAVI along with vaccine manufacturers also support the ID-2020 program in support of their own goals for global vaccination. Now, this discussion is not in a position to judge these developments, but the idea that some people, like Vanessa Beeley, might be worried about where all this may lead is not necessarily conspiracy. However, we might highlight yet one more organisation, founded in 2015, called the Coalition for Epidemic Preparedness Innovations (CEPI) with another laudable goal to finance independent research projects to develop vaccines against emerging infectious diseases, where its funding also links back to various governments and the Gates Foundation ($100 million) and the Wellcome Trust ($100 million). In March 2020, the British government pledged £210 million to CEPI to focus on a vaccine for the Covid-19 virus, making it the largest individual donor to CEPI and GAVI.

Note: At this point, this discussion will not pursue any further claims in the UK-Column video, but it will be suggested that some of the claims outlined do not appear to be without some foundation. However, it must be highlighted that while some might be rightly concerned about some, or all, of these developments, especially if lacking public transparency, it does not constitute a proven conspiracy against public interests.

However, the information above, which was first reference through the Connecting the Dots Part 2 video also links to another video where Stefan Molyneux interviews Dr. Shiva Ayyadurai. However, having simply provided the links to this information, this discussion will not comment further on the ideas presented, because at this time the information appears questionable and beyond the ability of this discussion to verify the statements of concern being made.

So, how might the public judge all the information outlined in terms of the Covid-19 pandemic?

In truth, it may be possible that the majority, within any national population, will not come to any judgement about the information outlined, not only because they will never read it, but because they probably have other priorities in their lives and may simply hope their government will make the right decisions. However, for those few, that wish to hold their governments and powerful institutions to account, then transparency of information, both misinformation and disinformation, is important. At the outset of the discussion the following statement was made.

This discussion wants to consider the scope of propaganda, both in terms of its nature and use to influence what people may come to believe about ‘their world’. The phrase ‘their world’ is used to highlight that propaganda has often been used to fundamentally change how many people come to view the world, i.e. it can propagate a new worldview.

So, while the historical use of propaganda may become increasingly obvious with hindsight, as might its overt and covert usage in the present-day by certain national governments, its use in our daily lives is not only more pervasive, but also more insidious and increasingly sophisticated. Therefore, as suggested, any claim of consensus might be seen as a warning sign of the propagation of propaganda, not just information, especially if it seeks to suppress any arguments against the consensus narrative. Finally, the claim of certainty in any worldview should not only be considered absurd, but dangerous. So, with these thoughts in mind, we might table one final question.

How might we personally judge the risks of the Covid-19 virus?

As has been pointed out, your risk to the Covid-19 virus will depend on your age and health conditions. Broadly, if you are under 50 and healthy, statistics suggest that you are considerably less likely to succumb to the virus than somebody over 50, who has health conditions, although this is not guaranteed. However, to-date, the statistics collected about the Covid-19 virus, by websites like virusncov.com, appear questionable, both in terms of the number of reported infections and death. In this context, an initial discussion of the Covid-19 Pandemic attempted to provide some level of wider analysis based on relatively simple SIR model, although the results were equally problematic in the sense that infection rates still suggested that 99% of all populations had to remain susceptible to the virus. If so, then secondary outbreaks of the virus appear highly probable, should the phase-1 lockdown policy be relaxed. However, there is now an increasing recognition that an entire population cannot remain in this level of lockdown without inflicting far-reaching damage on the economy and the quality of life. However, as pointed out in the A Data Centric Perspective video, this is not a binary choice between lockdown or no-lockdown, but rather the relaxing of the lockdown policy towards ‘smart distancing’, where the risks are evaluated for each age group and health condition. Therefore, as argued,  people need to take more responsibility for managing their own risk, depending on age and health, but where the video entitled Vitamin D Status and Viral Interactions might provide some valuable advice.

Note: See The Efficacy of Lockdown for further and wider discussion of the implications.