thelibertybeacon--2020-09-28--Covid-19: How Likely Is a Second Wave?

Covid-19: How Likely Is a Second Wave?

ER Editor : On the same subject , we recommend this – Chief Science Officer for Pfizer Says “ Second Wave ” Faked on False-Positive COVID Tests , “ Pandemic Is Over .
” The former Chief Science Officer for Pfizer is Dr. Mike Yeadon , one of the co-authors of the article below .
Evidence presented in this paper indicates that the severe acute respiratory syndrome coronavirus 2 pandemic as an event in the UK is essentially complete , with ongoing and anticipated challenges well within the capacity of a normalised NHS to cope .
The virus infection has @ @ @ @ @ @ @ as a result of wholly natural processes and evidence indicates that in the UK and other heavily infected European countries , the spread of the virus has been all but halted by a substantial reduction in the susceptible population .
This has occurred because the level of infection required to introduce enough immunity into the population to reduce the reproduction number ( R ) permanently below 1 occurred at markedly lower infection rates and loss of life than had been initially anticipated .
The evidence presented in this paper indicates that there should @ @ @ @ @ @ @ ‘ second wave , ’ with smaller localised outbreaks when the virus contacts pockets of previously uninfected populations .
Current mass testing using the PCR test is inappropriate in its current form .
If it is to continue , then results and reporting should be refined to meet the gold standard of testing methodology to give clinicians improved information so that they are able to make appropriate clinical decisions .
Positive tests should be confirmed by testing a second sample , and all positive tests should be reported along with the Cycle Threshold @ @ @ @ @ @ @ to aid assessment of a patient ’ s viral load .
It is recommended that a greater focus be placed on evidence-based medicine rather than highly sensitive theoretical modelling based on assumptions and unknowns .
Current evidence allows for a greatly improved understanding of positive infectious patients ; and using the evidence to improve measurements and understanding can lead to sensitive measurements of active cases to give a more accurate warning of escalating cases and potential issues and outbreaks .
Based upon guidance from NHS England , our primary and secondary care service @ @ @ @ @ @ @ to limit access to care due to the dangers of the severe acute respiratory syndrome coronavirus 2 ( SARS-CoV-2 or COVID-19 ) pandemic .
Whilst work has begun to restore NHS services ( the “ restoration ” ) , there remains a strong focus on preparing for a second wave as implied by the Imperial College epidemiological model designed by Professor Neil Ferguson and his team .
While this model may have had some limited value when we were faced with a novel virus outbreak , the evidence that has emerged over recent @ @ @ @ @ @ @ previous outbreaks , implies that the model that is still being followed is unreliable and not consistent with both previously measured systems and current evidence .
This paper outlines the evidence and data we have gathered to support a change in focus to further expedite the return of both primary and secondary care to full capacity .
The COVID-19 pandemic has undoubtedly allowed for some very positive and rapid changes within NHS pathways , protocols and services which should be maintained .
However , the current reduction in delivered primary care activity , @ @ @ @ @ @ @ to the degree of ‘ collateral damage ’ being caused in patients not receiving the diagnostic and ensuing care they should be receiving at the earliest possible stage of intervention .
While there has been a very specific focus on the cancer and cardiology services , similar negative impacts can be seen across most services with , for example , neurological , dermatological and renal patients all presenting with more severe disease due to delays in receiving both diagnosis and treatment .
National weekly mortality data is useful for looking at the effect @ @ @ @ @ @ @ four years data were used for comparison purposes and to calculate upper and lower control limits ( based on two standard deviations ) .
This shows that in the pandemic peak ( April 17th to 30th ) , more than twice the number of seasonal average deaths occurred , with the number of deaths above the upper control limit from March 27th through to June 12th , totalling 44,895 excess deaths .
Since June 26th , the number of weekly deaths has now fallen so it is not only below the weekly average @ @ @ @ @ @ @ control limit , showing that we are now at the lowest number of weekly deaths recorded in many years .
Over the last three months since lockdown measures started easing on the May 10th , there has been no increase in weekly deaths .
On the contrary , these have continued to fall .
Another useful measure of disease impact is the Adult Critical Care Bed Occupancy , which showed a peak in bed demand between April 7th and 23rd with the number of patients occupying critical care beds significantly higher than our @ @ @ @ @ @ @ the end of May the occupancy had dropped back to pre-COVID-19 levels , well below the national baseline capacity and has shown no statistical change since .
Restrictions have been progressively eased across the country for over three months .
A continuation of the virus would be expected to manifest itself as an increase in both Critical Care bed occupancy and national All-Causes Mortality statistics .
This has not been the case in either critical indicator .
There are very good reasons to believe that the population of the UK and of many @ @ @ @ @ @ @ position where the prevalence of the virus is low and probably falling further because the reproduction number ( R ) has been below 1 for several months .
We understand the term ‘ herd immunity ’ can raise hackles in some quarters of the media .
However , it might be more acceptably expressed by stating that the proportion remaining of the population who are susceptible to the virus has fallen sufficiently far that a sustained and growing outbreak of disease is no longer supported .
This end state is not at all @ @ @ @ @ @ @ controversial .
It is how mammals – specifically jawed vertebrates – learned to live with the thousands of viruses that infect every living organism on the planet , not just us , but even plants , fungi and bacteria .
We are of the view that a continued focus primarily on the virus flows from responding to what we are concerned is a seriously flawed transmission model .
We are told that only seven per cent of the population have antibodies to the virus , and it is implied that this represents the @ @ @ @ @ @ @ far been infected .
The model assumes that we started with 100 % susceptibility , because the virus is new , therefore the virus hasn ’ t gone away and must sooner or later return .
This is the basis of all the second wave fears we hear about .
However , we do not believe the model is correct , and our assertions and inferences are based upon recently published science , some in highly eminent journals and some by researchers in pre-review online servers which have this year become crucial in @ @ @ @ @ @ @ published data on deaths ‘ with ’ COVID-19 is dependent on testing regimes and therefore liable to inaccuracy due to missing information – for example undetected asymptomatic patients – the data does allow a sound approximation of the flow of the outbreak .
Inspecting the daily COVID-19 deaths vs. time curve for the UK , we see a Gompertz-type curve ( Rypdal and Rypdal , 2020 ) which are typical of natural , biological phenomena , well documented in biomedical scientific papers over the last 40 years .
Note the lack of discontinuities @ @ @ @ @ @ @ interventions have interrupted its development .
The Gompertz-type plot seen above , which is formed by a single surge in activity , often followed by smaller minor upturns as the disease reaches new populations , is typical of previous virus outbreaks that have been well documented , none of which have demonstrated a significant second wave even though control methods were used to prevent the spread of disease in each case .
For example , below we see in the MERS CoV outbreak of 2015 what appears to be a significant double wave @ @ @ @ @ @ @ single waves affecting geographically distinct populations at different times as the disease spreads .
In this case the first major peak was seen in Saudi Arabia with a second peak some months later in the Republic of Korea .
Analysed individually , each area followed a typical single event Gompertz curve .
Similarly , when we look at the SARS outbreak of 2003 , the initial identification of an apparent double wave when looking at world wide data is actually multiple single events or waves in disparate locations each following the typical Gompertz-type @ @ @ @ @ @ @ at least 30 % of our population already had immunological recognition of this new virus , before it even arrived ( Le Bert et al , 2020 ; Braun et al , 2020 ; Grifoni et al , 2020 ) .
COVID-19 is new , but coronaviruses are not .
There are at least four well characterised family members ( 229E , NL63 , OC43 and HKU1 ) which are endemic and cause some of the common colds we experience , especially in winter .
They all have striking sequence similarity to the @ @ @ @ @ @ @ immune systems is the group of white blood cells called T-cells , whose job it is to memorise a short piece of whatever virus we were infected with so the right cell types can multiply rapidly and protect us if we get a related infection .
Responses to COVID-19 have been shown in dozens of blood samples taken from donors before the new virus arrived .
The most recent paper by Mateus et al ( 2020 ) was published in the journal Science in August and supports the previous findings of Le Bert @ @ @ @ @ @ @ , only Mateus performed detailed epitope mapping and found that epitopes present in each of the known endemic coronaviruses share sequence homology or close similarity to those in the new virus .
Prior to this , three other groups including immunologists in Germany , Sweden and the USA each independently published similar findings ( refs as above and discussed in Sewell , 2020 ) .
These papers showed this pre-immunity is geographically widespread and prevalent within each population studied , but it was only the Mateus paper that gave us the understanding as @ @ @ @ @ @ @ previously been suggested that pre-pandemic immune responses in circulating T-cells might have occurred following exposure to one or more of the endemic coronaviruses .
Mateus , by using parts of these endemic coronaviruses which also exist within COVID-19 confirmed this .
We understand that objections might be raised about the clinical correlates of this T-cell recognition .
While that is a fair challenge , it would be unreasonable to dismiss it and assume is has no relevance .
This is because this is how T-cell memory works ( for example , Ling et @ @ @ @ @ @ @ patients analogously display exactly these T-cell responses ) and more importantly because we have solid evidence in the case of SARS that those expressing T-cell recognition of that coronavirus were resistant to it .
In a study of 23 people who survived SARS in 2003 , every single one had memory T-cells that recognised the SARS virus 17 years later ( Le Bert et al , 2020 ) .
The T-cell response was consistent with measurements taken after vaccination with approved vaccines for other viruses .
As important , these T-cell responses also @ @ @ @ @ @ @ the new virus but who were asymptomatic ( Sekine et al , 2020 ) .
In conclusion , we believe it is reasonable to take from this body of work that those displaying vigorous T-cell responses to this family of coronaviruses are resistant to , or immune from , infection .
They are distinct from the others in the population who do not have these T-cell responses and are therefore susceptible to a new virus .
Transmission models , such as the one used by the Imperial team , are highly sensitive to @ @ @ @ @ @ @ , and we argue that a modification of the current model should be applied with , at most , 70 % initial population susceptibility .
This is a conservative value since current literature finds that between 20 % and 50 % of the population display this pre-pandemic T-cell responsiveness , meaning we could adopt an initially susceptible population value from 80 % to 50 % .
The lower the real initial susceptibility , the more secure we are in our contention that a herd immunity threshold ( HIT ) has been reached .
@ @ @ @ @ @ @ model are not limited solely to T-cell memory mediated reduction in initial susceptibility .
This is because there are factors other than T-cell mechanisms which alter a person ’ s susceptibility to the virus .
We now know that children , especially young children , appear harder to infect and/or they are less affected by the virus .
To do us harm , viruses need to get inside our cells .
To do that , they exploit as ‘ grappling hooks ’ receptors on the outside of those cells – in the case @ @ @ @ @ @ @ high speed , scientists determined it is an enzyme called ACE2 .
It turns out that the levels of ACE2 are highest in adults and much lower in children , becoming progressively lower the younger they are ( Lingappan et al , 2020 ) .
That is a fortunate finding indeed , and goes some way in explaining why children have been relatively spared .
In addition , other groups have shown that infectivity is significantly reduced in individuals with the O-blood group ( Wu et al , 2020 ; Ellinghaus et al @ @ @ @ @ @ @ eight million children aged 0-10 in the UK and 12.7 million aged 0-15 .
These cohorts represent approximately 11.9 % and 19 % of the UK population , respectively .
Taking this into account it is , in total , at least 35 % , and likely to be significantly more of the population who are resistant or immune to the virus , meaning that they will neither get ill nor participate significantly in viral transmission ( Lee , 2020 ) .
This is crucial to understanding where we are with respect to @ @ @ @ @ @ @ potential for a second wave of infections .
The proportion of the population that needs to be resistant to an infection in order to stop it spreading depends on the proportion who were originally susceptible and the initial reproduction number , or R0 .
If 100 % truly were susceptible , then epidemiology suggests that 65 % would have to be infected for the herd immunity threshold to be reached , given the initial estimates of R0 .
That would have resulted in very many more deaths than have been measured .
But @ @ @ @ @ @ @ sure , a much lower initial percentage was susceptible , it takes far fewer people to catch the virus before there are too few susceptible people remaining within the population for the virus to be able to find the next person to infect .
Recent seroprevalence studies , which measure the proportion of the population displaying antibodies to the novel virus , are widely assumed to show the proportion of the population which has been infected .
However , the observation that , for example , only 17 % of Londoners have antibodies @ @ @ @ @ @ @ 17 % have been infected ( though the media often wrongly assumes it does ) .
It is important to appreciate that much of the early serological studies were conducted on hospitalised patients who , by definition , are the most ill cohort .
In such patients the majority do seroconvert ( eg Theel et al , 2020 ) .
In mildly symptomatic and asymptomatic patients , a lower proportion seroconvert ( Long et al , 2020 ) .
This is because the antibody system is but one of several tools our immunology @ @ @ @ @ @ @ been a number of papers illustrating this important principle .
Long et al ( 2020 ) find that almost half of previously infected individuals are no longer seropositive a few months later .
Gallais ( 2020 ) shows that none of the familial contacts of those testing positive to SARS-CoV-2 went onto to develop antibodies .
A reasonable hypothesis is that the lower intensity of immunological challenges tends to rely less on the generation of antibodies and more on innate and cellular responses .
This means that a factor of two-fold and possibly @ @ @ @ @ @ @ population serology data in order to better approximate the infected population .
If 7 % is the mean for UK , then perhaps 14-21 % of the population has actually been infected ( which would imply , very approximately , 9-14 million people infected ) .
The authors recognise that the exact number in this example is speculative , but conversations with immunologists indicate that this principle is widely accepted as reasonable for community infection where viral load varies widely and contrasts markedly with seroconversion after vaccination , where the goal is close @ @ @ @ @ @ @ question of what percentage of the population has been infected can be approached using a different methodology .
Numerous estimates have been made of the infection fatality ratio ( IFR ) for this new virus .
Naturally , it varies depending on the population under study as well as the methodology used and , accordingly , researchers have arrived at a wide range of estimates for IFR .
The Centre for Evidence-Based Medicine has done much work in this area and their current estimate is 0.1-0.4 % ( Oke and Heneghan , 2020 @ @ @ @ @ @ @ value , especially as for months the US CDC displayed a value for IFR of 0.26 % on their website .
This implies that for every death from COVID-19 , there were a preceding 100/0.26 or ~400 infections .
The UK has suffered approximately 42,000 such deaths which , to a first approximation using IFR , implies 16.8million infections , or 25 % of the population having been infected .
Consequently , two different and independent analytical approaches provide estimates that are at least in the same range for total population having been @ @ @ @ @ @ @ ) , and this is crucial in the argument put forward here .
Other , theoretical epidemiological studies show that , with the extent of prior immunity that we can now reasonably assume to be the case , only 15-25 % of the population being infected is sufficient to bring the spread of the virus to a halt ( Lourenco , 2020 ; Gomez et al , 2020 ) .
Importantly , we emphasise there are additional schools of epidemiological work which show that variation in likelihood of becoming infected itself can greatly @ @ @ @ @ @ @ and that this can be reached at even lower proportions of the population having been infected ( e.g .
Aguas , 2020 ) .
We saw early on in the pandemic that the number of daily deaths rapidly soar and at that time did we not know where and when it would stop rising .
It has been evidenced previously that the most easily infected people got infected earliest ( see Gomez et al , 2020 ) .
Humans vary hugely , not only in our responses to viruses , but also in @ @ @ @ @ @ @ as it tries to invade us .
The most susceptible were those already elderly and/or ill , some very ill , and so we saw very high death rates initially .
Once that super-susceptible group were removed from the pool of susceptible individuals by the virus , it began a slower march through everyone else , slowing all the time , as the remaining population ’ s susceptibility fell continually towards the herd immunity threshold .
That is where our evidence indicates we are now and why the virus is disappearing from the @ @ @ @ @ @ @ this document in light of information available elsewhere in the world .
It has widely been observed that in all heavily infected countries in Europe and several of the US states likewise , that the shape of the daily deaths vs. time curves is similar to ours in the UK .
Many of these curves are not just similar , but almost super imposable .
Italy , France , Spain , Sweden and the UK , for example ( OWID , 2020 ) .
The shape of the deaths vs. time curve implies @ @ @ @ @ @ @ mainly from human interventions , given the widely varying non-pharmaceutical interventions in those countries .
Taking this and applying it more widely , the very strong similarities of UK data with that of nearby countries which employed different responses yields another conclusion – that none of the interventions altered the broad course of the pandemic event .
Further , it is reasonable to conclude that the pandemic event has ended in those countries , too .
Famously , Sweden has adopted an almost laissez faire approach , with qualified advice given , but @ @ @ @ @ @ @ and that of the UK ’ s is very similar .
The officials in Sweden appear to be of the view that their population has closely approached or in some places reached what they term herd immunity , with R persistently lower than 1 .
The PCR test for the virus is good enough to confirm infection in someone with symptoms .
“ Is it flu or is it COVID-19 ?
” is a question easily answered .
What it is very poor at , however , is what is being asked of @ @ @ @ @ @ @ of people who are currently infectious in the community .
We do not know exactly what the false positive rate is , but it is widely believed to be greater than the actual , remaining prevalence of the virus ( Heneghan , 2020 ) , which is around 1:2000 , or 0.05 % .
( ONS prevalence survey Aug 14th 2020 ) .
The result of continuing to use this test alone on a massive widescale screening program is inevitably to generate a high proportion of false positives .
The problem of using @ @ @ @ @ @ @ low prevalence virus with a PCR test has been widely discussed ( Heneghan , 2020 ) .
Under present parameters , even accepting an unlikely 0.1 % False Positive rate and a prevalence of 0.1 % , more than half of the positives are likely to be false , potentially all of them .
It is the opinion of the authors that the false positive rate is higher and the prevalence lower than this .
Consequently , it is impossible for the positives to be much other than false .
A recent letter @ @ @ @ @ @ @ , 2020 ) exemplifies the extent of harm that actually arose in a setting in which all but one of the positives ended up being false positives .
This resulted not only in considerable time and money wasted by surgeries , but also other medical issues being delayed .
It is not rational and may even be dangerous to use these results to drive policy .
Note that recent so-called ’ spikes ’ were never accompanied or followed by people getting ill , going to hospital and dying in elevated numbers .
Consequently @ @ @ @ @ @ @ the positives from mass testing are either false positives or ‘ cold positives ’ ( fragments of real virus which are not intact and incapable of replication or of causing disease or infecting others ) and therefore begs the question of whether mass testing of patients without symptoms is in fact helpful or misleading ?
It may be of relevance to note that , on August 24th , the US CDC changed its guidance on when PCR testing is appropriate .
They now recommend not testing people with no symptoms who are not @ @ @ @ @ @ @ are practical alternatives to mass testing .
For example , calls to the NHS111 service captures all reports of what is termed ‘ influenza-like illness ’ .
Change in this parameter is likely to be a much more sensitive measure of the presence of increasing prevalence of SARS-CoV-2 infection than flawed PCR testing without modifications .
Obviously , and perhaps it has already happened , there is the potential for emerging influenza to complicate the picture .
A modification to the strategy involving PCR testing which would easily resolve any uncertainty is this @ @ @ @ @ @ @ up as quickly as possible , ideally within 24 hours of the positive result , and every one is retested .
If this is done , almost all the false positives will be removed .
We predict there would be few genuine positive results remaining .
But even here , it is important to recall what it is that the PCR test measures , and it is simply the presence of partial RNA sequences present in the intact virus .
This means that even a true positive does not necessarily indicate the presence @ @ @ @ @ @ @ to date , many researchers have shown that some subjects remain PCR-positive long after the ability to culture virus from swabs has disappeared .
We term this a ‘ cold positive ’ ( to distinguish it from a ‘ hot positive ’ , someone actually infected with intact virus ) .
The key point about ‘ cold positives ’ is that they are not ill , not symptomatic , not going to become symptomatic and , furthermore , are unable to infect others .
As each PCR test that is carried out returns @ @ @ @ @ @ @ to obtain a positive result , it is important that this Ct is reported with every positive result .
The Ct gives strong evidence of the viral load and aids clinicians in determining if a patient has a “ hot ” infectious positive result or a “ cold ” non-infectious positive result .
Gniazdowski et al ( 2020 ) studied 161 positive PCR test samples with a Ct value below 23 that yielded 91.5 % of virus isolates , and the study showed a strong correlation between recovery of SARS-CoV-2 infectious virus on @ @ @ @ @ @ @ values above 30 returned negative cultures in all except one case .
Daily deaths from and with COVID-19 have almost ceased , having fallen over 99 % from peak .
All the numbers monitored carefully fall like this , too : the numbers being hospitalised , numbers in hospital , number in intensive care – all are falling in synchrony from the April peak .
Viral evidence historically tells us that you don ’ t generally get infected by the exact same virus twice , certainly not within a short period of time @ @ @ @ @ @ @ immune system which lets that happen , and we ’ d probably not have made it as a species into the 21st century if that ’ s how it worked .
So there ’ s an expectation of some duration of immunity .
It needs studying , but our experience and evidence for coronaviruses ( Le Bert et al , 2020 ) suggests that if you have memory T-cells , durability can be very long lasting .
This study showed that people still had robust T-cell responses in 2020 , 17 years after @ @ @ @ @ @ @ .
The concerns people have expressed about falling antibody levels underscores a lack of knowledge about acquired immunity .
It is not efficient nor required for immunity to maintain high levels of antibodies to everything to which you are immune .
Instead , cellular memory enables very rapid re-generation of antibodies upon re-encounter with the antigen , if that is required to defend the host .
Alternatively , innate and cellular memory responses can be sufficient .
The NHS currently remains ‘ COVID-19 ready ’ in preparation for an expected second wave , @ @ @ @ @ @ @ initial model with highly sensitive input variables that we already know to be inaccurate .
The evidence we ’ ve presented leads us to believe there is unlikely to be a second wave , and that while there have been apparent multi- ‘ wave ’ respiratory viruses in the past , notably 1918-20 , in many cases it became clear that this was either different populations being infected at different times or in some cases multiple different organisms involved .
There is no biological principle that leads us to expect a second wave @ @ @ @ @ @ @ the past six months .
Instead , it is likely there will be local , small and self-limiting mini-outbreaks as areas previously unexposed come into contact with the virus .
So what is happening in terms of second wave concerns in France and Spain ?
As the rate of hospitalisations , ICU utilisation and the daily death rate from COVID-19 all decayed steadily , it appears that several but not all countries have greatly expanded their testing capacity in the broader population of people who are not showing any symptoms of infection .
@ @ @ @ @ @ @ the media for outbreaks , spikes and second waves are all artefacts of amplified rates of testing .
It should be noted that illness , hospitalisations and deaths have not reversed in any clear and sustained manner .
Specifically , careful examination of the weekly all-causes mortality data in France is completely clear .
Six weeks into an apparent surge of cases , the number of deaths remain completely flat and normal , in all age bands ( as of mid-August when this document was written ) .
Paul Kirkham , Professor of @ @ @ @ @ @ @ Research Group at Wolverhampton University Dr Mike Yeadon , former CSO and VP , Allergy and Respiratory Research Head with Pfizer Global R & D and co-Founder of Ziarco Pharma Ltd Aguas , et al ( 2020 ) .
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ER Editor: On the same subject, we recommend this – Chief Science Officer for Pfizer Says “Second Wave” Faked on False-Positive COVID Tests, “Pandemic Is Over. ” The former Chief Science Officer for Pfizer is Dr. Mike Yeadon, one of the co-authors of the article below.
Executive Summary
Evidence presented in this paper indicates that the severe acute respiratory syndrome coronavirus 2 pandemic as an event in the UK is essentially complete, with ongoing and anticipated challenges well within the capacity of a normalised NHS to cope. The virus infection has passed through the bulk of the population as a result of wholly natural processes and evidence indicates that in the UK and other heavily infected European countries, the spread of the virus has been all but halted by a substantial reduction in the susceptible population. This has occurred because the level of infection required to introduce enough immunity into the population to reduce the reproduction number (R) permanently below 1 occurred at markedly lower infection rates and loss of life than had been initially anticipated. The evidence presented in this paper indicates that there should be no expectation of a large scale ‘second wave,’ with smaller localised outbreaks when the virus contacts pockets of previously uninfected populations.
Current mass testing using the PCR test is inappropriate in its current form. If it is to continue, then results and reporting should be refined to meet the gold standard of testing methodology to give clinicians improved information so that they are able to make appropriate clinical decisions. Positive tests should be confirmed by testing a second sample, and all positive tests should be reported along with the Cycle Threshold (Ct) obtained during the test to aid assessment of a patient’s viral load.
It is recommended that a greater focus be placed on evidence-based medicine rather than highly sensitive theoretical modelling based on assumptions and unknowns. Current evidence allows for a greatly improved understanding of positive infectious patients; and using the evidence to improve measurements and understanding can lead to sensitive measurements of active cases to give a more accurate warning of escalating cases and potential issues and outbreaks.
Background
Based upon guidance from NHS England, our primary and secondary care service across the country are currently following protocols to limit access to care due to the dangers of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) pandemic. Whilst work has begun to restore NHS services (the “restoration”), there remains a strong focus on preparing for a second wave as implied by the Imperial College epidemiological model designed by Professor Neil Ferguson and his team. While this model may have had some limited value when we were faced with a novel virus outbreak, the evidence that has emerged over recent months, along with detailed analysis of previous outbreaks, implies that the model that is still being followed is unreliable and not consistent with both previously measured systems and current evidence. This paper outlines the evidence and data we have gathered to support a change in focus to further expedite the return of both primary and secondary care to full capacity.
The COVID-19 pandemic has undoubtedly allowed for some very positive and rapid changes within NHS pathways, protocols and services which should be maintained. However, the current reduction in delivered primary care activity, referrals and elective care gives concern as to the degree of ‘collateral damage’ being caused in patients not receiving the diagnostic and ensuing care they should be receiving at the earliest possible stage of intervention. While there has been a very specific focus on the cancer and cardiology services, similar negative impacts can be seen across most services with, for example, neurological, dermatological and renal patients all presenting with more severe disease due to delays in receiving both diagnosis and treatment.
Mortality and Critical Care
National weekly mortality data is useful for looking at the effect of the COVID-19 pandemic. The past four years data were used for comparison purposes and to calculate upper and lower control limits (based on two standard deviations).
This shows that in the pandemic peak (April 17th to 30th), more than twice the number of seasonal average deaths occurred, with the number of deaths above the upper control limit from March 27th through to June 12th, totalling 44,895 excess deaths. Since June 26th, the number of weekly deaths has now fallen so it is not only below the weekly average but has regularly dropped below the lower control limit, showing that we are now at the lowest number of weekly deaths recorded in many years.
Over the last three months since lockdown measures started easing on the May 10th, there has been no increase in weekly deaths. On the contrary, these have continued to fall.
Another useful measure of disease impact is the Adult Critical Care Bed Occupancy, which showed a peak in bed demand between April 7th and 23rd with the number of patients occupying critical care beds significantly higher than our national baseline capacity. However, by the end of May the occupancy had dropped back to pre-COVID-19 levels, well below the national baseline capacity and has shown no statistical change since.
Restrictions have been progressively eased across the country for over three months. A continuation of the virus would be expected to manifest itself as an increase in both Critical Care bed occupancy and national All-Causes Mortality statistics. This has not been the case in either critical indicator.
A Complete Event of the Pandemic
There are very good reasons to believe that the population of the UK and of many heavily infected countries have arrived at a position where the prevalence of the virus is low and probably falling further because the reproduction number (R) has been below 1 for several months. We understand the term ‘herd immunity’ can raise hackles in some quarters of the media. However, it might be more acceptably expressed by stating that the proportion remaining of the population who are susceptible to the virus has fallen sufficiently far that a sustained and growing outbreak of disease is no longer supported. This end state is not at all new or, in our view, controversial. It is how mammals – specifically jawed vertebrates – learned to live with the thousands of viruses that infect every living organism on the planet, not just us, but even plants, fungi and bacteria.
We are of the view that a continued focus primarily on the virus flows from responding to what we are concerned is a seriously flawed transmission model. We are told that only seven per cent of the population have antibodies to the virus, and it is implied that this represents the proportion of the population who have so far been infected. The model assumes that we started with 100% susceptibility, because the virus is new, therefore the virus hasn’t gone away and must sooner or later return. This is the basis of all the second wave fears we hear about.
However, we do not believe the model is correct, and our assertions and inferences are based upon recently published science, some in highly eminent journals and some by researchers in pre-review online servers which have this year become crucial in keeping pace with emerging science.
While published data on deaths ‘with’ COVID-19 is dependent on testing regimes and therefore liable to inaccuracy due to missing information – for example undetected asymptomatic patients – the data does allow a sound approximation of the flow of the outbreak. Inspecting the daily COVID-19 deaths vs. time curve for the UK, we see a Gompertz-type curve (Rypdal and Rypdal, 2020) which are typical of natural, biological phenomena, well documented in biomedical scientific papers over the last 40 years. Note the lack of discontinuities in the curve, suggesting no effective interventions have interrupted its development.
Epidemic Outbreaks
The Gompertz-type plot seen above, which is formed by a single surge in activity, often followed by smaller minor upturns as the disease reaches new populations, is typical of previous virus outbreaks that have been well documented, none of which have demonstrated a significant second wave even though control methods were used to prevent the spread of disease in each case.
For example, below we see in the MERS CoV outbreak of 2015 what appears to be a significant double wave. However, it is actually multiple single waves affecting geographically distinct populations at different times as the disease spreads. In this case the first major peak was seen in Saudi Arabia with a second peak some months later in the Republic of Korea. Analysed individually, each area followed a typical single event Gompertz curve.
Similarly, when we look at the SARS outbreak of 2003, the initial identification of an apparent double wave when looking at world wide data is actually multiple single events or waves in disparate locations each following the typical Gompertz-type curve.
Population Susceptibility
It is now established that at least 30% of our population already had immunological recognition of this new virus, before it even arrived (Le Bert et al, 2020; Braun et al, 2020; Grifoni et al, 2020). COVID-19 is new, but coronaviruses are not. There are at least four well characterised family members (229E, NL63, OC43 and HKU1) which are endemic and cause some of the common colds we experience, especially in winter.
They all have striking sequence similarity to the new coronavirus. A major component our immune systems is the group of white blood cells called T-cells, whose job it is to memorise a short piece of whatever virus we were infected with so the right cell types can multiply rapidly and protect us if we get a related infection. Responses to COVID-19 have been shown in dozens of blood samples taken from donors before the new virus arrived. The most recent paper by Mateus et al (2020) was published in the journal Science in August and supports the previous findings of Le Bert et al (2020).
Importantly, only Mateus performed detailed epitope mapping and found that epitopes present in each of the known endemic coronaviruses share sequence homology or close similarity to those in the new virus. Prior to this, three other groups including immunologists in Germany, Sweden and the USA each independently published similar findings (refs as above and discussed in Sewell, 2020). These papers showed this pre-immunity is geographically widespread and prevalent within each population studied, but it was only the Mateus paper that gave us the understanding as to why and how. It had previously been suggested that pre-pandemic immune responses in circulating T-cells might have occurred following exposure to one or more of the endemic coronaviruses. Mateus, by using parts of these endemic coronaviruses which also exist within COVID-19 confirmed this.
We understand that objections might be raised about the clinical correlates of this T-cell recognition. While that is a fair challenge, it would be unreasonable to dismiss it and assume is has no relevance. This is because this is how T-cell memory works (for example, Ling et al, 2020 show that convalescent COVID-19 patients analogously display exactly these T-cell responses) and more importantly because we have solid evidence in the case of SARS that those expressing T-cell recognition of that coronavirus were resistant to it. In a study of 23 people who survived SARS in 2003, every single one had memory T-cells that recognised the SARS virus 17 years later (Le Bert et al, 2020). The T-cell response was consistent with measurements taken after vaccination with approved vaccines for other viruses. As important, these T-cell responses also develop even in recovering patients infected with the new virus but who were asymptomatic (Sekine et al, 2020).
In conclusion, we believe it is reasonable to take from this body of work that those displaying vigorous T-cell responses to this family of coronaviruses are resistant to, or immune from, infection. They are distinct from the others in the population who do not have these T-cell responses and are therefore susceptible to a new virus.
Immunity Threshold
Transmission models, such as the one used by the Imperial team, are highly sensitive to the input parameters they are based on, and we argue that a modification of the current model should be applied with, at most, 70% initial population susceptibility. This is a conservative value since current literature finds that between 20% and 50% of the population display this pre-pandemic T-cell responsiveness, meaning we could adopt an initially susceptible population value from 80% to 50%. The lower the real initial susceptibility, the more secure we are in our contention that a herd immunity threshold (HIT) has been reached.
However, our concerns with the Imperial model are not limited solely to T-cell memory mediated reduction in initial susceptibility. This is because there are factors other than T-cell mechanisms which alter a person’s susceptibility to the virus. We now know that children, especially young children, appear harder to infect and/or they are less affected by the virus. To do us harm, viruses need to get inside our cells. To do that, they exploit as ‘grappling hooks’ receptors on the outside of those cells – in the case of the new virus, and at high speed, scientists determined it is an enzyme called ACE2. It turns out that the levels of ACE2 are highest in adults and much lower in children, becoming progressively lower the younger they are (Lingappan et al, 2020). That is a fortunate finding indeed, and goes some way in explaining why children have been relatively spared. In addition, other groups have shown that infectivity is significantly reduced in individuals with the O-blood group (Wu et al, 2020; Ellinghaus et al, 2020). There are approximately eight million children aged 0-10 in the UK and 12.7 million aged 0-15. These cohorts represent approximately 11.9% and 19% of the UK population, respectively.
Taking this into account it is, in total, at least 35%, and likely to be significantly more of the population who are resistant or immune to the virus, meaning that they will neither get ill nor participate significantly in viral transmission (Lee, 2020). This is crucial to understanding where we are with respect to the epidemic in the UK and the potential for a second wave of infections.
The proportion of the population that needs to be resistant to an infection in order to stop it spreading depends on the proportion who were originally susceptible and the initial reproduction number, or R0. If 100% truly were susceptible, then epidemiology suggests that 65% would have to be infected for the herd immunity threshold to be reached, given the initial estimates of R0. That would have resulted in very many more deaths than have been measured. But if, as we are now reasonably sure, a much lower initial percentage was susceptible, it takes far fewer people to catch the virus before there are too few susceptible people remaining within the population for the virus to be able to find the next person to infect.
Recent seroprevalence studies, which measure the proportion of the population displaying antibodies to the novel virus, are widely assumed to show the proportion of the population which has been infected. However, the observation that, for example, only 17% of Londoners have antibodies is not the same as saying only 17% have been infected (though the media often wrongly assumes it does). It is important to appreciate that much of the early serological studies were conducted on hospitalised patients who, by definition, are the most ill cohort. In such patients the majority do seroconvert (eg Theel et al, 2020). In mildly symptomatic and asymptomatic patients, a lower proportion seroconvert (Long et al, 2020). This is because the antibody system is but one of several tools our immunology has to defend us. There have been a number of papers illustrating this important principle. Long et al (2020) find that almost half of previously infected individuals are no longer seropositive a few months later. Gallais (2020) shows that none of the familial contacts of those testing positive to SARS-CoV-2 went onto to develop antibodies.
A reasonable hypothesis is that the lower intensity of immunological challenges tends to rely less on the generation of antibodies and more on innate and cellular responses. This means that a factor of two-fold and possibly higher would need to be applied to population serology data in order to better approximate the infected population. If 7% is the mean for UK, then perhaps 14-21% of the population has actually been infected (which would imply, very approximately, 9-14 million people infected). The authors recognise that the exact number in this example is speculative, but conversations with immunologists indicate that this principle is widely accepted as reasonable for community infection where viral load varies widely and contrasts markedly with seroconversion after vaccination, where the goal is close to 100%.
Interestingly, this question of what percentage of the population has been infected can be approached using a different methodology. Numerous estimates have been made of the infection fatality ratio (IFR) for this new virus. Naturally, it varies depending on the population under study as well as the methodology used and, accordingly, researchers have arrived at a wide range of estimates for IFR. The Centre for Evidence-Based Medicine has done much work in this area and their current estimate is 0.1-0.4% (Oke and Heneghan, 2020). Let us take a midpoint value, especially as for months the US CDC displayed a value for IFR of 0.26% on their website. This implies that for every death from COVID-19, there were a preceding 100/0.26 or ~400 infections. The UK has suffered approximately 42,000 such deaths which, to a first approximation using IFR, implies 16.8million infections, or 25% of the population having been infected.
Consequently, two different and independent analytical approaches provide estimates that are at least in the same range for total population having been infected (overlapping at approximately 20%), and this is crucial in the argument put forward here. Other, theoretical epidemiological studies show that, with the extent of prior immunity that we can now reasonably assume to be the case, only 15-25% of the population being infected is sufficient to bring the spread of the virus to a halt (Lourenco, 2020; Gomez et al, 2020). Importantly, we emphasise there are additional schools of epidemiological work which show that variation in likelihood of becoming infected itself can greatly reduce the so-called herd immunity threshold, and that this can be reached at even lower proportions of the population having been infected (e.g. Aguas, 2020).
We saw early on in the pandemic that the number of daily deaths rapidly soar and at that time did we not know where and when it would stop rising. It has been evidenced previously that the most easily infected people got infected earliest (see Gomez et al, 2020). Humans vary hugely, not only in our responses to viruses, but also in the ease or difficulty the virus experiences as it tries to invade us. The most susceptible were those already elderly and/or ill, some very ill, and so we saw very high death rates initially. Once that super-susceptible group were removed from the pool of susceptible individuals by the virus, it began a slower march through everyone else, slowing all the time, as the remaining population’s susceptibility fell continually towards the herd immunity threshold. That is where our evidence indicates we are now and why the virus is disappearing from the environment.
It is important to see this document in light of information available elsewhere in the world. It has widely been observed that in all heavily infected countries in Europe and several of the US states likewise, that the shape of the daily deaths vs. time curves is similar to ours in the UK. Many of these curves are not just similar, but almost super imposable. Italy, France, Spain, Sweden and the UK, for example (OWID, 2020). The shape of the deaths vs. time curve implies a natural process and not one resulting mainly from human interventions, given the widely varying non-pharmaceutical interventions in those countries. Taking this and applying it more widely, the very strong similarities of UK data with that of nearby countries which employed different responses yields another conclusion – that none of the interventions altered the broad course of the pandemic event. Further, it is reasonable to conclude that the pandemic event has ended in those countries, too. Famously, Sweden has adopted an almost laissez faire approach, with qualified advice given, but no generalised lockdowns. Yet its profile and that of the UK’s is very similar. The officials in Sweden appear to be of the view that their population has closely approached or in some places reached what they term herd immunity, with R persistently lower than 1.
The PCR Test
The PCR test for the virus is good enough to confirm infection in someone with symptoms. “Is it flu or is it COVID-19?” is a question easily answered. What it is very poor at, however, is what is being asked of it now, namely estimating the percentage of people who are currently infectious in the community. We do not know exactly what the false positive rate is, but it is widely believed to be greater than the actual, remaining prevalence of the virus (Heneghan, 2020), which is around 1:2000, or 0.05%. (ONS prevalence survey Aug 14th 2020). The result of continuing to use this test alone on a massive widescale screening program is inevitably to generate a high proportion of false positives. The problem of using any assay to conduct surveillance on a low prevalence virus with a PCR test has been widely discussed (Heneghan, 2020). Under present parameters, even accepting an unlikely 0.1% False Positive rate and a prevalence of 0.1%, more than half of the positives are likely to be false, potentially all of them. It is the opinion of the authors that the false positive rate is higher and the prevalence lower than this. Consequently, it is impossible for the positives to be much other than false. A recent letter to the British Medical Journal (Healy, 2020) exemplifies the extent of harm that actually arose in a setting in which all but one of the positives ended up being false positives. This resulted not only in considerable time and money wasted by surgeries, but also other medical issues being delayed. It is not rational and may even be dangerous to use these results to drive policy. Note that recent so-called ’spikes’ were never accompanied or followed by people getting ill, going to hospital and dying in elevated numbers. Consequently, it is possible that most of the positives from mass testing are either false positives or ‘cold positives’ (fragments of real virus which are not intact and incapable of replication or of causing disease or infecting others) and therefore begs the question of whether mass testing of patients without symptoms is in fact helpful or misleading? It may be of relevance to note that, on August 24th, the US CDC changed its guidance on when PCR testing is appropriate. They now recommend not testing people with no symptoms who are not contacts in a contact-tracing activity.
There are practical alternatives to mass testing. For example, calls to the NHS111 service captures all reports of what is termed ‘influenza-like illness’. Change in this parameter is likely to be a much more sensitive measure of the presence of increasing prevalence of SARS-CoV-2 infection than flawed PCR testing without modifications. Obviously, and perhaps it has already happened, there is the potential for emerging influenza to complicate the picture. A modification to the strategy involving PCR testing which would easily resolve any uncertainty is this: every positive test result is followed up as quickly as possible, ideally within 24 hours of the positive result, and every one is retested. If this is done, almost all the false positives will be removed. We predict there would be few genuine positive results remaining. But even here, it is important to recall what it is that the PCR test measures, and it is simply the presence of partial RNA sequences present in the intact virus. This means that even a true positive does not necessarily indicate the presence of viable virus. In limited studies to date, many researchers have shown that some subjects remain PCR-positive long after the ability to culture virus from swabs has disappeared. We term this a ‘cold positive’ (to distinguish it from a ‘hot positive’, someone actually infected with intact virus). The key point about ‘cold positives’ is that they are not ill, not symptomatic, not going to become symptomatic and, furthermore, are unable to infect others. As each PCR test that is carried out returns the Cycle Threshold (Ct) used to obtain a positive result, it is important that this Ct is reported with every positive result. The Ct gives strong evidence of the viral load and aids clinicians in determining if a patient has a “hot” infectious positive result or a “cold” non-infectious positive result. Gniazdowski et al (2020) studied 161 positive PCR test samples with a Ct value below 23 that yielded 91.5% of virus isolates, and the study showed a strong correlation between recovery of SARS-CoV-2 infectious virus on cell culture and Ct values. Ct values above 30 returned negative cultures in all except one case.
Expectations of a Second Wave
Daily deaths from and with COVID-19 have almost ceased, having fallen over 99% from peak. All the numbers monitored carefully fall like this, too: the numbers being hospitalised, numbers in hospital, number in intensive care – all are falling in synchrony from the April peak. Viral evidence historically tells us that you don’t generally get infected by the exact same virus twice, certainly not within a short period of time. It’d be a poor immune system which lets that happen, and we’d probably not have made it as a species into the 21st century if that’s how it worked. So there’s an expectation of some duration of immunity. It needs studying, but our experience and evidence for coronaviruses (Le Bert et al, 2020) suggests that if you have memory T-cells, durability can be very long lasting. This study showed that people still had robust T-cell responses in 2020, 17 years after the first SARS outbreak back in 2003. The concerns people have expressed about falling antibody levels underscores a lack of knowledge about acquired immunity. It is not efficient nor required for immunity to maintain high levels of antibodies to everything to which you are immune. Instead, cellular memory enables very rapid re-generation of antibodies upon re-encounter with the antigen, if that is required to defend the host. Alternatively, innate and cellular memory responses can be sufficient.
The NHS currently remains ‘COVID-19 ready’ in preparation for an expected second wave, a highly unlikely scenario based upon an initial model with highly sensitive input variables that we already know to be inaccurate. The evidence we’ve presented leads us to believe there is unlikely to be a second wave, and that while there have been apparent multi-‘wave’ respiratory viruses in the past, notably 1918-20, in many cases it became clear that this was either different populations being infected at different times or in some cases multiple different organisms involved. There is no biological principle that leads us to expect a second wave based on the accumulation of data over the past six months. Instead, it is likely there will be local, small and self-limiting mini-outbreaks as areas previously unexposed come into contact with the virus.
Spain and France
So what is happening in terms of second wave concerns in France and Spain? As the rate of hospitalisations, ICU utilisation and the daily death rate from COVID-19 all decayed steadily, it appears that several but not all countries have greatly expanded their testing capacity in the broader population of people who are not showing any symptoms of infection. We contend that the many claims in the media for outbreaks, spikes and second waves are all artefacts of amplified rates of testing. It should be noted that illness, hospitalisations and deaths have not reversed in any clear and sustained manner. Specifically, careful examination of the weekly all-causes mortality data in France is completely clear. Six weeks into an apparent surge of cases, the number of deaths remain completely flat and normal, in all age bands (as of mid-August when this document was written).
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Paul Kirkham, Professor of cell Biology and Head of Respiratory Disease Research Group at Wolverhampton University
Dr Mike Yeadon, former CSO and VP, Allergy and Respiratory Research Head with Pfizer Global R&D and co-Founder of Ziarco Pharma Ltd
Barry Thomas, Epidemiologist
Sources
Aguas, et al (2020). Herd immunity thresholds for SARS-CoV-2 estimated from unfolding epidemics. medRxIV https://doi.org/10.1101/2020.07.23.20160762.
Braun, et al. (2020). Presence of SARS-CoV-2 reactive T cells in COVID-19 patients and healthy donors. medRxIV https://doi.org/10.1101/2020.04.17.20061440
Ellinghaus et al. (2020) Genomewide Association Study of Severe Covid-19 with Respiratory Failure. New Eng. J Med. DOI: 10.1056/NEJMoa2020283
Gallais, (2020). Intrafamilial exposure to SARS-CoV-2 induces cellular responses without seroconversion. medRxIV https://doi.org/10.1101/2020.06.21.20132449.
Gomez et al. (2020). Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold. MedRxIV https://doi.org/10.1101/2020.04.27.20081893
Grifoni et al. (2020. Targets of T Cell Responses to SARS-CoV-2Coronavirus in Humans with COVID-19Disease and Unexposed Individuals. Cell 181, 1489–1501. https://doi.org/10.1016/j.cell.2020.05.015ll
Healy, B (2020). Covid-19 testing, low prevalence and the impact of false positives. Brit Med J. 2020;369:m1808.
Long, et al. (2020). Clinical and immunological assessments of asymptomatic SARS-CoV-2 infections. Nature Med 26, 1200-04.
Heneghan (2020). How many Covid diagnoses are false positives? The Spectator, July 20 2020.
Le Bert et al (2020) SARS-Cov-2 specific T cell immunity in cases of Covid19 and SARS and uninfected controls. Nature. Doi 10.1038/s41586-020-2550-z
Lee & Raszka (2020). COVID-19 transmission and children: the child is not to blame. Pediatrics, e2020004879 DOI: 10.1542/peds.2020-004879.
Ling, et al (2020). Detection of SARS-CoV-2-Specific Humoral and Cellular Immunity in COVID-19 Convalescent Individuals. Immunity 52(6), 971-77.
Lingappan et al (2020). Understanding the age divide in COVID-19: why are children overwhelmingly spared? Am. J. Physiol (Lung Cell Molec. Physiol) https://doi.org/10.1152/ajplung.00183.2020
Lourenco et al (2020). The impact of host resistance on cumulative mortality and the threshold of herd immunity for SARS-CoV-2. MedRxIV https://doi.org/10.1101/2020.07.15.20154294
Mateus et al (2020) Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans. Science. DOI: 10.1126/science.abd3871
Oke& Heneghan (2020). Global Covid-19 Case Fatality Rates. https://www.cebm.net/covid-19/global-covid-19-case-fatality-rates/
June 9 2020 update.
ONS coronavirus survey (Aug 14 2020). https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/latest
OWID (our world in data: display UK, Sweden & France, confirmed daily deaths, log plot per million) https://ourworldindata.org/coronavirus-data-explorer?yScale=log&zoomToSelection=true&time=2020-03-02..latest&deathsMetric=true&interval=smoothed&aligned=true&perCapita=true&smoothing=7&country=TWN~GBR~SWE~FRA&pickerMetric=location&pickerSort=asc
Rypdal & Rypdal (2020) A parsimonious description and cross-country analysis of COVID-19 epidemic curves. https://arxiv.org/pdf/2008.02475.pdf
Sekine et al. (2020). bioRxiv preprint doi: https://doi.org/10.1101/2020.06.29.174888.
Sewell, H. (2020). BMJ 2020;370:m3018.
Theel et al (2020). The Role of Antibody Testing for SARS-CoV-2: Is There One? J. Clin Microbiol, 28(8), 1-7.
Wu et al (2020) Association between ABO blood groups and COVID-19 infection, severity and demise: A systematic review and meta-analysis. Infection , Genetics and Evolution. Doi 10.1016/j.meegid.2020.104485
Wood (2020). Did COVID-19 infections decline before UK lockdown? https://arxiv.org/pdf/2005.02090.pdf
Gniazdowski V, Morris P, Wohl S et al. Repeat COVID-19 molecular testing: correlation with recovery of infectious virus, molecular assay cycle thresholds, and analytical sensitivity. medRxiv 2020.08.05.20168963; doi: https://doi.org/10.1101/2020.08.05.20168963
Other Data sources and Reference
https://github.com/owid/covid-19-data/find/master
https://www.ecdc.europa.eu/en/news-events/epidemiological-update-middle-east-respiratory-syndrome-coronavirus-mers-cov-4
https://en.wikipedia.org/wiki/2012_Middle_East_respiratory_syndrome_coronavirus_outbreak
https://en.wikipedia.org/wiki/2002%E2%80%932004_SARS_outbreak
https://www.researchgate.net/figure/Severe-acute-respiratory-syndrome-epidemic-curve-in-Hong-Kong-2003-by-infection-cluster_fig1_8200905
https://www.researchgate.net/figure/Epidemic-curve-of-cases-of-severe-acute-respiratory-syndrome-by-date-of-onset-November_fig1_8501177
https://science.sciencemag.org/content/303/5664/1666
https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
https://www.worldometers.info/coronavirus/country/spain/
https://www.worldometers.info/coronavirus/country/france/
https://www.gov.uk/guidance/coronavirus-covid-19-information-for-the-public#number-of-tests
https://www.cebm.net/study/covid-19-testing-and-correlation-with-infectious-virus-cycle-thresholds-and-analytical-sensitivity/
Featured image is from LS


thelibertybeacon--2020-09-28--German Doctor Heiko Schoning Arrested After Speaking At “We Do Not Consent” Rally In London [VIDEOS]

The Liberty Beacon Project is now expanding at a near exponential rate , and for this we are grateful and excited !
But we must also be practical .
For 7 years we have not asked for any donations , and have built this project with our own funds as we grew .
We are now experiencing ever increasing growing pains due to the large number of websites and projects we represent .
So we have just installed donation buttons on our websites and ask that you consider this when you visit them .
Nothing is too small .
We @ @ @ @ @ @ @ your considerations … ( TLB ) Comment Policy : As a privately owned web site , we reserve the right to remove comments that contain spam , advertising , vulgarity , threats of violence , racism , or personal/abusive attacks on other users .
This also applies to trolling , the use of more than one alias , or just intentional mischief .
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Repeat offenders may be blocked or permanently banned without prior warning .
Disclaimer : TLB websites contain @ @ @ @ @ @ @ not always been specifically authorized by the copyright owner .
We are making such material available to our readers under the provisions of “ fair use ” in an effort to advance a better understanding of political , health , economic and social issues .
The material on this site is distributed without profit to those who have expressed a prior interest in receiving it for research and educational purposes .
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Nothing mentioned is intended to be a substitute for professional medical advice , diagnosis or treatment .

ER Editor: We remind readers that Dr. Heiko Schoning (pictured below beside Robert F. Kennedy Jr.), doctor, father and former soldier, is one of the founding members of Germany’s ACU2020 group, along with Dr. Bobo Schiffmann and Dr. Martin Haditsch, which is calling for an investigation into the WHO’s actions over the virus crisis, and for free and open debate on the whole debacle. See Germany’s Extra-parliamentary Inquiry on COVID-19 [VIDEO] and Spanish and German Doctor Groups Team Up for International Investigation of CV ‘Scam’ [VIDEO]. You’ll also find Dr. Schoning at the press conference with Robert F. Kennedy Jr. in Berlin recently (see Robert F. Kennedy, Jr. Holds a Press Conference in Berlin After Launching CHD’s Europe Chapter).
Schoning was indeed arrested, then released on Sunday within 24 hours without charge. He was let out the police station door quietly, with a small group of people waiting outside who charmingly apologized for his arrest on British soil. Here are some relevant tweets from the weekend. (Please note that TLB and ER are in no way related to Anna Brees at Brees Media.)
TWEET – Schoning speaking to reporter on Saturday at Trafalgar Square
TWEET – Schoning being taken away by police
TWEET – general view of Trafalgar Square protestors on Saturday
TWEET – Schoning emerging from the door of the police station
TWEET – Schoning speaking after his release from police custody
We’re also throwing this in, which has been doing the rounds on social media, showing a lady of senior years get violently pushed around by police.
TWEET
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thelibertybeacon--2020-09-28--Your chances of dying have been greatly exaggerated

One thing we tend to be denied amid the turmoil is perspective .
Perspective requires a point from which to view things .
So let ’ s adopt one .
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I have not verified the authenticity of this but the % figures in this meme from March when the “ pandemic ” was at its height and the scaremongeing and inflating of the death stats were rampant , appear more or less right for today .
Good enough for purposes of illustration I think It gives you the approximate likelihood , by age group , of dying from @ @ @ @ @ @ @ The COVID19 deaths stat for the whole UK yesterday was 17 .
A COVID19 “ death ” is counted whenever someone dies after having tested positive for COVID19 within 28 days of their death .
This does not necessarily mean the virus killecd them .
It means some trace of it was present in their body when they died .
So of those 17 people who died we do not know if the virus killed all 17 , or 5 or 3 or none at all .
And of course the “ deaths @ @ @ @ @ @ @ small to scare the populace so the government and media have dropped mentioning it much and have focussed instead on a stat that is , superficially , still scary enough to fit the bill .
This stat is extremely unfreliable .
The Health Secretary has admitted that it returns about 1 % false positives .
This does not sound much but it is crucial and so blows the entire government con out of the water , we should be having enquiries and bringing criminal charges .
See the video below for a full @ @ @ @ @ @ @ when , say , 1000 tests are done and , say , there are 150 positives , which the government then touts as “ new cases ” .
But , per Hancock , there are 1 % false positives , so of those 1000 tests , 100 of them are false positives , yet they are counted as “ new cases ” .
So deduct the false “ new cases ” from the declared number of 150 and you get 5o .
Try this out on any one day : take the number @ @ @ @ @ @ @ % of those , which will give you the number of false positives one can expect .
The government , although it knows a large proportion of “ new cases ” are false , does not deduct the false positives from the overall figure so do their job for them and deduct those false positives from the number of “ new cases ” and you get a more reliable number – a number that is FAR less scary .
Of course , the 1 % false positives is what Hancock says , so @ @ @ @ @ @ @ likely worse than that .
This was recently confirmed by Raab the Foreign Secretary who said that the “ challenge ” with testing for # COVID19 in airports is ‘ the very high false positive rate ’ and adds ‘ only 7 % of tests will be successful in identifying those who have the virus ’ .
In other words , the unreliability of the tests means that 97 % ( not 1 % ) of the reported cases can not be relied upon .
So for example on a day when , @ @ @ @ @ @ @ by the government , the true figure could be as low as 21 .
And the government is basing its whole scaremongeing operation and ruinous strategy -including threats of further lockdown – on these knowingly false numbers !
The odds are extremely low and for it to kill you even if you do have it , you usually need to be in pretty bad shape from some pre-existing condition .
Pre-existing conditions include recognised illnesses such as cancer or heart disease but what is seldom mentioned is that there is also obesity , @ @ @ @ @ @ @ smoking probably that also lower your chances .
I quit smoking at the start of this flu outbreak and recommend you do the same just so you take the matter of your own survival into hour own hands .
So for some or perhaps even many there are things you can do to help lower even these low percentages .
And of course these low percentages tell us that this “ pandemic ” has been talked up and misrepresented to make is appear worse than it is .
This is not to say @ @ @ @ @ @ @ Just that it is nowhere near AS BAD as we are told .
YOUR CHANCES OF GETTING SICK On the matter of your chances of catching the disease in the first place , these are already statistically low .
I recommend this article in of all things The Sun .
I never thought I would be recommending The Sun but it is a good and simply put article .
https : //www.thesun.co.uk/…/chance-catching-covid-44-in…/ So your chances of catching it are LOW .
Bear in mind as you read the Sun article what is now @ @ @ @ @ @ @ number for “ new cases ” ( see above and the video below ) .
You can do a great deal OF YOUR OWN FREE WILL and ON YOUR OWN INITIATIVE to control that and lower the chances even more – for yourself and others .
These include SENSIBLE precautions you would use in any flu outbreak to avoid getting infected or infecting others .
They also include getting lots of vitamin C and vitamin D , fresh air , exercise , wholesome food , avoiding drugs , meds , alcohol , tobacco @ @ @ @ @ @ @ avoiding Fear ( such as what the government and media hit you with daily ) and also staying productive .
Switching off the TV and not listening to your brain-dead government will help too .
The point here is that there is a LOT you can do to raise even further your already statistically VERY high chances of survival .
You can be far more CAUSE and far less EFFECT .
This is the type of message and type of advice , education and PERSPECTIVE the government SHOULD be providing and would be @ @ @ @ @ @ @ agenda smokes-screened by the turbulence it puts out , as opposed to the fear mongering and YOU MUSTs in which it is speciallising in an effort to put you at EFFECT .
And of course the educational approach would get more cooperation and good will than the dictatorial approach that is riling people up .
Now here ’ s a very important video that blows the whole government con job out of the water and makes a very strong case for bringing criminal charges agnainst the people responsible for scamming the nation .
@ @ @ @ @ @ @ Reloaded

by Kieron McFadden
A BIT OF PERSPECTIVE
One thing we tend to be denied amid the turmoil is perspective. Perspective requires a point from which to view things. So let’s adopt one . . .
YOUR CHANCES OF DYING
I have not verified the authenticity of this but the % figures in this meme from March when the “pandemic” was at its height and the scaremongeing and inflating of the death stats were rampant, appear more or less right for today. Good enough for purposes of illustration I think
It gives you the approximate likelihood, by age group, of dying from COVID 19 IF YOU CATCH IT.
The COVID19 deaths stat for the whole UK yesterday was 17.
A COVID19 “death” is counted whenever someone dies after having tested positive for COVID19 within 28 days of their death. This does not necessarily mean the virus killecd them. It means some trace of it was present in their body when they died. So of those 17 people who died we do not know if the virus killed all 17, or 5 or 3 or none at all.
And of course the “deaths” stats is in any case too small to scare the populace so the government and media have dropped mentioning it much and have focussed instead on a stat that is, superficially, still scary enough to fit the bill.
This stat is extremely unfreliable. The Health Secretary has admitted that it returns about 1% false positives. This does not sound much but it is crucial and so blows the entire government con out of the water, we should be having enquiries and bringing criminal charges. See the video below for a full explanation but briefly:
Imagine a day when, say, 1000 tests are done and, say, there are 150 positives, which the government then touts as “new cases”. But, per Hancock, there are 1% false positives, so of those 1000 tests, 100 of them are false positives, yet they are counted as “new cases”. So deduct the false “new cases” from the declared number of 150 and you get 5o. Try this out on any one day: take the number of tests done, then calculate 1% of those, which will give you the number of false positives one can expect. The government, although it knows a large proportion of “new cases” are false, does not deduct the false positives from the overall figure so do their job for them and deduct those false positives from the number of “new cases” and you get a more reliable number – a number that is FAR less scary.
Of course, the 1% false positives is what Hancock says, so we can safely assume it is more likely worse than that.
This was recently confirmed by Raab the Foreign Secretary who said that the “challenge” with testing for #COVID19 in airports is ‘the very high false positive rate’ and adds ‘only 7% of tests will be successful in identifying those who have the virus’.
In other words, the unreliability of the tests means that 97% (not 1%) of the reported cases cannot be relied upon. So for example on a day when, say, 300 new cases are reported by the government, the true figure could be as low as 21.
And the government is basing its whole scaremongeing operation and ruinous strategy -including threats of further lockdown – on these knowingly false numbers!
The odds are extremely low and for it to kill you even if you do have it, you usually need to be in pretty bad shape from some pre-existing condition.
Pre-existing conditions include recognised illnesses such as cancer or heart disease but what is seldom mentioned is that there is also obesity, drugs, meds and alcohol and heavy smoking probably that also lower your chances. I quit smoking at the start of this flu outbreak and recommend you do the same just so you take the matter of your own survival into hour own hands.
So for some or perhaps even many there are things you can do to help lower even these low percentages.
And of course these low percentages tell us that this “pandemic” has been talked up and misrepresented to make is appear worse than it is. This is not to say it is not a Bad Thing. Just that it is nowhere near AS BAD as we are told.
YOUR CHANCES OF GETTING SICK
On the matter of your chances of catching the disease in the first place, these are already statistically low. I recommend this article in of all things The Sun. I never thought I would be recommending The Sun but it is a good and simply put article. https://www.thesun.co.uk/…/chance-catching-covid-44-in…/
So your chances of catching it are LOW. Bear in mind as you read the Sun article what is now known to be a highly inflated false number for “new cases” (see above and the video below).
You can do a great deal OF YOUR OWN FREE WILL and ON YOUR OWN INITIATIVE to control that and lower the chances even more – for yourself and others.
These include SENSIBLE precautions you would use in any flu outbreak to avoid getting infected or infecting others. They also include getting lots of vitamin C and vitamin D, fresh air, exercise, wholesome food, avoiding drugs, meds, alcohol, tobacco, mental turbulence, familial turbulence, avoiding Fear (such as what the government and media hit you with daily) and also staying productive. Switching off the TV and not listening to your brain-dead government will help too.
The point here is that there is a LOT you can do to raise even further your already statistically VERY high chances of survival.
You can be far more CAUSE and far less EFFECT.
This is the type of message and type of advice, education and PERSPECTIVE the government SHOULD be providing and would be providing if it were working on some agenda smokes-screened by the turbulence it puts out, as opposed to the fear mongering and YOU MUSTs in which it is speciallising in an effort to put you at EFFECT. And of course the educational approach would get more cooperation and good will than the dictatorial approach that is riling people up.
Be CAUSE.
LIVE
Make your government behave itself.
Now here’s a very important video that blows the whole government con job out of the water and makes a very strong case for bringing criminal charges agnainst the people responsible for scamming the nation.
this article was first published on UK Reloaded
••••
The Liberty Beacon Project is now expanding at a near exponential rate, and for this we are grateful and excited! But we must also be practical. For 7 years we have not asked for any donations, and have built this project with our own funds as we grew. We are now experiencing ever increasing growing pains due to the large number of websites and projects we represent. So we have just installed donation buttons on our websites and ask that you consider this when you visit them. Nothing is too small. We thank you for all your support and your considerations … (TLB)
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thelibertybeacon--2020-09-28--Irish health official denounced, cites U.S. studies to support COVID views

Irish health official , denounced for criticizing COVID policy , cites US studies to support views A top Irish medical official who resigned amid a furor over his comments challenging “ draconian ” COVID-19 restrictions has doubled down on his position , citing U.S. statistics to support his views .
The official , Dr. Martin Feeley , on Sept. 12 said that his government could not justify continued lockdowns in light of what has emerged about COVID-19 infections and morbidity .
The virus has turned out to be “ much less severe ” than the average annual flu , and @ @ @ @ @ @ @ national economy , Feeley told the Irish Times .
When Dublin health officers denounced those comments , Feeley resigned his post as clinical director of Ireland ’ s Midland Fields Hospital Group , a division of the government-run Health Service Executive .
( Picture credit of Dr. Feeley- Broadsheet.ie ) Feeley last week reiterated his views , and expanded on them , bolstering his position with American studies and statistics .
“ It is not for want of good reason that deaths are now referred to as Covid-19-associated deaths , ” Feeley wrote @ @ @ @ @ @ @ “ Of 5,700 patients admitted to New York hospitals , 88 per cent had more than one underlying condition ( co-morbidity ) and the US Centres for Disease Control and Prevention reported that from January to May , 19.5 per cent of Covid-19 patients with co-morbidity died compared to 1.6 per cent with no other illness.
” Noting that the Irish experience mirrors that of New York , Feeley also cited a study out of California .
“ A Stanford-led group analysed over 100,000 Covid-19-related deaths in Europe , including Ireland , and @ @ @ @ @ @ @ for people under 65 without predisposing conditions were remarkably uncommon , ’ ” Feeley wrote .
Infections aboard two American ships – one civilian , one military – showed that many cases of Covid-19 are so mild as to show no symptoms , Feeley wrote .
“ In extremely well-defined scenarios such as the Diamond Princess cruise liner and the Theodore Roosevelt aircraft carrier almost 66 per cent of the positive tests were completely asymptomatic , while a report from China suggests 78 per cent of cases were asymptomatic , ” he wrote @ @ @ @ @ @ @ Ireland for supporting the herd immunity approach to managing the coronavirus .
He has said that young people are the least vulnerable members of society , and should be allowed to live their lives without being locked down .
The initial response to Covid-19 was appropriate at first , when it was suspected of being as contagious as the Spanish flu of 1917 , Feeley wrote .
“ However , after nine months of intensive scientific scrutiny of the virus ’ behaviour globally concludes this is no longer the case.
” Neither Feeley @ @ @ @ @ @ @ Executive immediately could be reached for comment .
( TLB ) published this article with permission of John Solomon at Just the News Some emphasis and pictorial content added by ( TLB ) Click Here to read about the staff at Just the News The Liberty Beacon Project is now expanding at a near exponential rate , and for this we are grateful and excited !
But we must also be practical .
For 7 years we have not asked for any donations , and have built this project with our own funds @ @ @ @ @ @ @ experiencing ever increasing growing pains due to the large number of websites and projects we represent .
So we have just installed donation buttons on our websites and ask that you consider this when you visit them .
Nothing is too small .
We thank you for all your support and your considerations … ( TLB ) Disclaimer : TLB websites contain copyrighted material the use of which has not always been specifically authorized by the copyright owner .
We are making such material available to our readers under the provisions of “ @ @ @ @ @ @ @ advance a better understanding of political , health , economic and social issues .
The material on this site is distributed without profit to those who have expressed a prior interest in receiving it for research and educational purposes .
If you wish to use copyrighted material for purposes other than “ fair use ” you must request permission from the copyright owner .

Irish health official, denounced for criticizing COVID policy, cites US studies to support views
Ireland’s experience with COVID-19 mirrors that of New York, wrote Dr. Martin Feeley, who resigned from his government health post amid a furor over his comments.
By Susan Katz Keating
A top Irish medical official who resigned amid a furor over his comments challenging “draconian” COVID-19 restrictions has doubled down on his position, citing U.S. statistics to support his views.
The official, Dr. Martin Feeley, on Sept. 12 said that his government could not justify continued lockdowns in light of what has emerged about COVID-19 infections and morbidity. The virus has turned out to be “much less severe” than the average annual flu, and lockdowns are hurting young people and the national economy, Feeley told the Irish Times. When Dublin health officers denounced those comments, Feeley resigned his post as clinical director of Ireland’s Midland Fields Hospital Group, a division of the government-run Health Service Executive. (Picture credit of Dr. Feeley- Broadsheet.ie)
Feeley last week reiterated his views, and expanded on them, bolstering his position with American studies and statistics.
“It is not for want of good reason that deaths are now referred to as Covid-19-associated deaths,” Feeley wrote on Thursday in the Irish Times. “Of 5,700 patients admitted to New York hospitals, 88 per cent had more than one underlying condition (co-morbidity) and the US Centres for Disease Control and Prevention reported that from January to May, 19.5 per cent of Covid-19 patients with co-morbidity died compared to 1.6 per cent with no other illness.”
Noting that the Irish experience mirrors that of New York, Feeley also cited a study out of California.
“A Stanford-led group analysed over 100,000 Covid-19-related deaths in Europe, including Ireland, and the US and concluded that ‘deaths for people under 65 without predisposing conditions were remarkably uncommon,’ ” Feeley wrote.
Infections aboard two American ships – one civilian, one military – showed that many cases of Covid-19 are so mild as to show no symptoms, Feeley wrote.
“In extremely well-defined scenarios such as the Diamond Princess cruise liner and the Theodore Roosevelt aircraft carrier almost 66 per cent of the positive tests were completely asymptomatic, while a report from China suggests 78 per cent of cases were asymptomatic,” he wrote.
The 70-year-old Feeley is known within Ireland for supporting the herd immunity approach to managing the coronavirus. He has said that young people are the least vulnerable members of society, and should be allowed to live their lives without being locked down.
The initial response to Covid-19 was appropriate at first, when it was suspected of being as contagious as the Spanish flu of 1917, Feeley wrote.
“However, after nine months of intensive scientific scrutiny of the virus’ behaviour globally concludes this is no longer the case.”
Neither Feeley nor a representative of the Health Service Executive immediately could be reached for comment.
_________
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(TLB) published this article with permission of John Solomon at Just the News
Some emphasis and pictorial content added by (TLB)
Click Here to read about the staff at Just the News
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Stay tuned to …
••••
The Liberty Beacon Project is now expanding at a near exponential rate, and for this we are grateful and excited! But we must also be practical. For 7 years we have not asked for any donations, and have built this project with our own funds as we grew. We are now experiencing ever increasing growing pains due to the large number of websites and projects we represent. So we have just installed donation buttons on our websites and ask that you consider this when you visit them. Nothing is too small. We thank you for all your support and your considerations … (TLB)
••••
Comment Policy: As a privately owned web site, we reserve the right to remove comments that contain spam, advertising, vulgarity, threats of violence, racism, or personal/abusive attacks on other users. This also applies to trolling, the use of more than one alias, or just intentional mischief. Enforcement of this policy is at the discretion of this websites administrators. Repeat offenders may be blocked or permanently banned without prior warning.
••••
Disclaimer: TLB websites contain copyrighted material the use of which has not always been specifically authorized by the copyright owner. We are making such material available to our readers under the provisions of “fair use” in an effort to advance a better understanding of political, health, economic and social issues. The material on this site is distributed without profit to those who have expressed a prior interest in receiving it for research and educational purposes. If you wish to use copyrighted material for purposes other than “fair use” you must request permission from the copyright owner.
••••
Disclaimer: The information and opinions shared are for informational purposes only including, but not limited to, text, graphics, images and other material are not intended as medical advice or instruction. Nothing mentioned is intended to be a substitute for professional medical advice, diagnosis or treatment.