Reposted from Dr. Judith Curry’s Climate Etc.
Posted on January 10, 2021 by niclewis |
By Nic Lewis
Introduction
Many people, myself included, thought that in the many regions where COVID-19 infections were consistently reducing during the summer, indicating that the applicable herd immunity threshold had apparently been crossed, it was unlikely that a major second wave would occur. This thinking has been proved wrong. In this article I give an explanation of why I think major second waves have happened.
Key points
- The herd immunity threshold (HIT) depends positively on the basic reproduction number R0 and negatively on heterogeneity in susceptibility.
- Since neither of the factors on which the HIT depends are fixed, the HIT is not fixed either.
- R0 depends on biological, environmental and sociological factors; colder weather and the evolution of more transmissible strains likely both increase R0; more (less) cautious behaviour and social distancing / restrictions on mixing reduce (increase) R0.
- Second waves were due primarily to changes in these factors increasing R0 and thus the HIT from below to above the existing level of population immunity.
- Heterogeneity in susceptibility is partly biological, but social connectivity differences are key.
- The effect of heterogeneity in susceptibility on the HIT can be represented by a single parameter λ.
- λ will always exceed 1 (its level in a homogeneous population); pre-epidemic λ may be ~4. The higher λ is, the lower the HIT for any given R0.
- The natural infection HIT is hence bound to be below the level of {1 – 1/R0} quoted by ‘experts’.
- Government restrictions reduce λ as well as R0, so the HIT falls less than it would if λ were fixed.
- The final size of an uncontrolled epidemic will substantially exceed the HIT, due to overshoot, so high reported seroprevalence levels can be consistent with a much lower HIT.
The herd immunity threshold (HIT) for a disease epidemic is the proportion of the population needing to have been infected, and thereby no longer susceptible to infection, before the rate of new infections starts to decline. The HIT depends both on the basic reproduction number for infections (R0) – the number of other people that at the start of an epidemic an infected person will on average infect – and the degree of heterogeneity in individuals’ likelihood of being infected (their susceptibility). That likelihood in turn depends on both their social connectivity and biological susceptibility to infection. Neither R0 nor the degree of heterogeneity in susceptibility is fixed in value, so the HIT is not fixed either.
Changes in population behaviour – whether arising from government interventions or in response to increasing disease incidence – affect both R0 and heterogeneity in susceptibility. In addition, R0 (which is proportional to how readily infection is on average transmitted between individuals) may vary seasonally, and change as the virus or other infectious organism mutates.
The resurgence of COVID-19 infections in a second wave after the summer ended is almost certainly due to some combination of the foregoing sociological and biological factors. It has been claimed that the influence of weather on its transmission is relatively minor,[1] and it has so far proved difficult to detect seasonality for COVID-19.[2] However, common colds caused by other coronaviruses are highly seasonal and I now think that it is reasonable to work on the basis that COVID-19 shares that behaviour.
I focus in this article on the mathematical dependence of the HIT to R0 and heterogeneity in susceptibility, and on the factors influencing those controlling variables. I also touch on difference between the HIT and the final size of an uncontrolled epidemic. I discuss in an appendix how, in my view, changes in the factors influencing R0 and heterogeneity in susceptibility likely shaped the evolution of the epidemic in western Europe
How the HIT varies with R0 and population heterogeneity
Table 1 illustrates how the herd immunity threshold varies with R0 and population heterogeneity in susceptibility to infection. The effect of such heterogeneity on transmission of infection and on the HIT can be represented by a single parameter λ, the heterogeneity factor (Tkachenko et al. 2020)[3], which is a function of population variability in both social connectivity and in biological susceptibility.[4] The reproduction number at any time, Rt, and the HIT are related as follows to R0 and λ:
Rt = R0 × Sλ
HIT = 1 – (1/R0)1/λ
where S is the proportion of the population that remains susceptible to infection. For a homogeneous population, these formulae reduce to the classical results Rt = R0 × S and HIT = 1 – 1/R0. With heterogeneity in susceptibility to infection, Rt falls more than pro rata to the susceptible proportion S decreases. Initially, Rt falls λ times as fast with S as in the homogeneous case.
Note that an epidemic takes some time to die out after the HIT is reached, since at that point many people will be infected and will go on to infect others, albeit at a declining rate. Therefore, the final size of the epidemic (FSE) – the attack rate (the ultimate proportion of the population that has been infected) – will exceed the HIT. The columns to the right of each HIT column show (in italics) the FSE if social and biological factors remain unchanged throughout the epidemic.[5] As shown in a previous article,[6] well timed short term restrictions to reduce transmission as the HIT is approached can prevent the FSE from significantly overshooting the HIT.
Table 1. Relationship of each of the herd immunity threshold (HIT) and the final size of the epidemic (FSE) with the basic reproduction number R0, at varying levels of heterogeneity factor λ that arises from heterogeneity in susceptibility (assumed gamma-distributed) across the population, from none (λ = 1) to an estimated normal level (λ = 4). The FSE values assume that the same R0 and λ value applied throughout the epidemic.
Since a person’s social connectivity, which reflects their average rate of contacts with others, equally affects their infectivity, variability in it has a more powerful effect than variability in biological susceptibility.[7] Note that heterogeneity in infectivity that is uncorrelated with susceptibility does not affect the overall progression of an established, large epidemic, although it may affect smaller scale features such as clustering of cases.
For a population that is homogeneous in both biological and social components of susceptibility, λ = 1 (pink columns). In that case, the ‘classical’ formula HIT = 1 – 1/ R0 is valid. This formula also applies to immunity gained through vaccination at random, since such vaccination – unlike natural disease progression – does not preferentially confer immunity on individuals who are more susceptible to infection (and also more likely to infect others).
Analyses of contact networks indicate that, in normal circumstances, the coefficient of variation (standard deviation / mean) for social connectivity in a population is about 1, while biological susceptibility is likely to have a coefficient of variation of about 1/3 or more (Tkachenko et al). Use of those figures implies that λ = 4 (green, rightmost columns).
The effect of government social distancing measures on R0 and the heterogeneity factor
It has been estimated that, prior to significant social distancing taking place, 80% to 90% of all transmission of infection is caused by circa 10% of infected individuals, often at superspreading events where a large number of people are present. When restrictions on gatherings, bars and other venues are introduced, non-household social mixing generally is reduced and superspreading opportunities fall even further, while household mixing will be little affected. The result will be a reduction in R0, but also reduced heterogeneity in social connectivity and hence λ. A further reduction in both these factors can be expected to occur when a lockdown (stay-at-home order) is introduced.
The effects of such government measures, for a range of resulting R0 values, are illustrated by the two middle sets of columns. These both assume the same 1/3 coefficient of variation for biological susceptibility, but a reduction in the coefficient of variation for social connectivity to 0.625, resulting in λ = 3 (yellow columns) or to 0.25, resulting in λ = 2 (salmon columns).
Even in the absence of legal restrictions being imposed, people can be expected to significantly change their behaviour when an epidemic involving severe disease takes hold. The resulting reduction in λ, for any given resulting reduction in R0, might however be less than under an enforced reduction in mixing, since more gregarious people may be less cautious and reduce their high social mixing proportionately less than more cautious, less gregarious people do – the opposite relationship to that arising from restrictions on gatherings, bars and other venues.
How a high seroprevalence level can arise even in the presence of substantial heterogeneity
It might be thought that a high attack rate is incompatible with significant population heterogeneity in susceptibility and hence a moderate HIT. An attack rate of 76% has been claimed for the city of Manaus.[8] However, the weighted measured seroprevalence on which that estimate was based was not from a random sample nor representative of the population,[9] and never exceeded 44%[10]. A random population survey found seroprevalence in Manaus to be only between one-quarter one-third the level claimed in the foregoing study, casting severe doubt on its claim.[11]
The first mentioned study also estimated that in or just after mid-March, near the start of the epidemic in Manaus, Rt – which at that point would not have been far short of R0 – was approximately 2.5, suggesting R0 was in the 2.6 to 2.8 range. The extent of physical distancing that they estimated applied then was moderate, similar to that near the end of the main epidemic. In a relatively poor city like Manaus with household and transport crowding it seems quite likely that in normal circumstances there is lower population heterogeneity in social connectivity than in a high income city, indicating an heterogeneity factor λ perhaps more like 3 than 4 (yellow not green columns). And under moderate social distancing the heterogeneity factor λ might be closer to 2 than 3. For an R0 of 2.6, λ = 2 implies an HIT of 38% but a final epidemic size (FSE) of 64%[12]. Even at λ = 3, the FSE would be 49% (with an HIT of 27%).[13]
To summarize, it seems doubtful that the attack rate in Manaus in fact exceeded 50% – it may have been no more than 20-25% – and an attack rate of 50% is fully compatible with the HIT being below 30%.
Appendix – Changes in R0 and population heterogeneity during the epidemic
The following discussion, which represents my semi-quantitative broad brush analysis of what has occurred, relates primarily to the progress of the epidemic in western Europe. However, it may also be somewhat applicable to the north east United States, where the epidemic took off only slightly later than in western Europe and where the seasonal variation in climate is also large.
In the initial stages of the first wave, which generally started in major cities, in early spring 2020, infections appear to have been doubling every three days or so prior to governments imposing restrictions or people becoming significantly more cautious. Depending on the assumed distribution of the generation interval (from one infection to those it directly leads to), that implies an R0 value of between 2 and 4.[14] I will assume a middle of the range R0 value of 3 for illustrative purposes. That would imply a HIT of 67% for a homogeneous population, reducing to 24% for a population with the highest degree of heterogeneity illustrated in Table 1, which might be expected to apply before people started behaving more cautiously and mixing less.
When people started mixing less, voluntarily or by government fiat, R0 would have reduced, but as discussed above λ will also have fallen. The combined effect of these changes can be visualised as moving diagonally upwards and leftwards in Table 1, from the green columns to the yellow columns and then to the salmon columns. The resulting reduction in the HIT would therefore be somewhat smaller than that implied by the reduction in R0 alone.
By late spring or early summer the first wave had largely faded, and it generally continued to decline after restrictions on mixing were at least partially relaxed. As summer progressed, people’s behaviour unsurprisingly returned closer to pre-epidemic norms. I will assume for illustrative purposes that the yellow columns (λ = 3) were representative of that period. Since by midsummer the epidemic appears to have been declining even where only a minor first wave had occurred, it seems that R0 must generally have declined to 1 or below, so that population immunity levels would everywhere have exceeded the HIT (which is only positive if R0 > 1).
As autumn arrived, infections and then serious illness started to rise again, although where testing was increasing the rise may have been exaggerated. It follows that R0 must have risen again, resulting in the HIT increasing to above the level of population immunity. An obvious explanation for the rise in R0 is seasonally reduced sun and cooler weather, with more contact occurring indoors, where almost all COVID-19 transmission appears to take place. A major increase in mixing among young people as school and, particularly, university terms started likely also boosted R0 and the level of infections in the autumn; young adults have generally had the highest incidence rates during the second wave.[15] In some places the rise in infections appears to have occurred slightly earlier, perhaps as a result of holidaymakers returning infected from areas where COVID-19 was more prevalent.[16]
Initially it seemed that some large cities where a significant proportion of the population had been infected in the first wave might be spared, but in most cases the increase in R0 evidently became sufficiently large to raise the HIT to above the level of population immunity. As a result of increasing infections, government-imposed restrictions were generally increased, which as well as reducing R0 will also have reduced the heterogeneity factor λ. This can be visualised as a move diagonally upwards from the yellow columns to the salmon columns. Those actions appear typically to have pushed Rt down to about 1, or slightly lower, which in the presence of a reasonable degree of existing population immunity implies an R0 level significantly above 1. With reduced heterogeneity, the existing level of population immunity causes a lesser reduction in Rt, relative to R0, but Rt will still be a smaller fraction of R0 than the proportion of the population that remains susceptible to infection.
In the UK, and possibly various other countries, a new lineage (B.1.1.7) of the SARS-CoV-2 virus has now emerged[17] and grown faster than existing ones, as discussed in a previous article[18]. Since writing that article, some further data has provided less indirect evidence that B.1.1.7 is 25–50% more infectious than pre-existing variants.[19] On the other hand, recent data from the regions where B.1.1.7 has become dominant suggests that it may now be growing no faster than other variants.[20] It has been suggested that the fast growth in the regions where B.1.1.7 now dominates may have been at least partly due to it spreading there in schools.[21] However, making for illustrative purposes the assumption that B.1.1.7 is actually 25–50% more infectious, R0 will have been increasing, perhaps typically reaching somewhere in the range1.5 to 2.0 once B.1.1.7 becomes the dominant variant, if R0 was previously in the 1.2 to 1.4 range.
Tougher restrictions that have been introduced in a number of countries in response to infection rates increasing, whether due to the spread of the B.1.1.7 lineage, to cold winter weather or to greater mixing, will have reduced population heterogeneity in social connectivity further. In these circumstances, is unclear whether existing levels of population immunity will suffice to prevent further growth of the B.1.1.7 lineage, or the rather similar one that has emerged in South African, even with severe restrictions being introduced. However, increased population immunity resulting from some combination of further spread of infections and vaccination programmes, the combination varying from one country and region to another, should bring COVID-19 epidemics under control within the next few months.
Nicholas Lewis 10 January 2021
[1] “All pharmaceutical and non-pharmaceutical interventions are currently believed to have a stronger impact on transmission over space and time than any environmental driver.” Carlson CJ, Gomez AC, Bansal S, Ryan SJ. Misconceptions about weather and seasonality must not misguide COVID-19 response. Nature Communications. 2020 Aug 27;11(1):1-4. https://doi.org/10.1038/s41467-020-18150-z
[2] Engelbrecht FA, Scholes RJ. Test for Covid-19 seasonality and the risk of second waves. One Health. 2020 Nov 29:100202. https://doi.org/10.1016/j.onehlt.2020.100202
[3] Tkachenko, A.V. et al.: Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19. medRxiv 29 July 2020 https://doi.org/10.1101/2020.07.26.20162420 They use the term ‘immunity factor’ for λ. Equations [11)], [12] and [13] and intervening paragraph. I adopt their assumption that there is negligible correlation across the population between biological susceptibility to infection and either social connectivity or biological infectivity.
[4] I make from here on the common assumption that a gamma distribution can well represent variation within the population in both social connectivity and biological susceptibility, on which basis λ = (1 + 2 × CVs2) × (1 + CVb2) where CVs and CVb are respectively the social and biological coefficients of variation (standard deviation / mean) for the population.
[5] The FSE (1 – S∞) depends on the sum of the squared coefficients of variation η = CVs2 + CVb2 as well as on λ. It is given by the solution to the equation S∞ = (1 + R0 η [1–S∞λ–η]/[ λ–η])–1/η. See Tkachenko et al. equation [17].
[6] https://www.nicholaslewis.org/when-does-government-intervention-make-sense-for-covid-19/
[7] Variability in infectivity that is uncorrelated with susceptibility in the population has no overall effect in a sizeable epidemic.
[8] Buss, Lewis F., et al. “Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic.” Science (2020).
[9] It was a convenience sample, comprised entirely of blood donors.
[10] That maximum seroprevalence estimate was adjusted upwards to 52% to account for test for sensitivity and specificity. The attack rate estimate further assumed that antibodies would no longer be detectable in a proportion of previously infected individuals.
[11] Hallal, P.C. et al:SARS-CoV-2 antibody prevalence in Brazil: results from two successive nationwide serological household surveys. Lancet, 8(11), e1390-e1398,, September 2020 https://doi.org/10.1016/S2214-109X(20)30387-9
[12] Actually slightly lower, as the stricter social distancing measures in the middle part of the epidemic would have reduced the excess of the FSE over the HIT.
[13] If R0 = 2.0, which is possible if a shorter estimate of the generation interval is used, the corresponding FSE sizes would be 52% or 38%, with the HIT being respectively 29% or 21%.
[14] Assuming a gamma distributed generation interval with a mean in the range 4 to 6.5 and a coefficient of variation between 0.37 and 0.74.
[15] Aleta A, Moreno Y. Age differential analysis of COVID-19 second wave in Europe reveals highest incidence among young adults. medRxiv. 13 November 2020. https://doi.org/10.1101/2020.11.11.20230177
[16] It is also possible that, notwithstanding a published finding to the contrary, the A20.EU1 variant that was brought back from Spain by people infected on holiday there may have been somewhat more infectious than existing variants.
[17] Other evidence that has now become available suggests that a similar variant arose in Italy prior to B.1.1.7 being detected in the UK.
[18] https://www.nicholaslewis.org/the-relative-infectivity-of-the-new-uk-variant-of-sars-cov-2/
[19] The observed 50–70% increase in weekly growth rate corresponds to roughly a 25–50% increase in infectivity (and hence in R0), assuming a generation interval with a 4–6 day mean and a reasonable CV, if R0 was previously not substantially above 1.
[20] https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/adhocs/12722estimatesofcovid19casesto02januaryforenglandregionsofenglandandbycasescompatiblewiththenewvariant
[21] Loftus (2021, Jan. 1). Neurath’s Speedboat: Did the new variant of COVID spread through schools? Retrieved from http://joshualoftus.com/posts/2021-01-01-did-the-new-variant-of-covid-spread-through-schools/
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
As soon as the HIT is reached, the virus will mutate to overcome it.
As long as we do not see many secondary infections, means we are well below HIT and the virus has no pressure to overcome the immunity. We are still naive to the virus.
HIT is somewhere around 70%.
USA has reached just 7% infection level.
There is a looong way to go.
Alex,
I think that’s incorrect logic that ascribes sentience and strategizing to a primitive life form. We may still be far from HIT, but the idea that a virus “feels pressure to mutate” is off base in my opinion. A virus doesn’t have any intelligence allowing it to be aware of whether it is having trouble finding a host. (“pressure to mutate”). It either ends up in a host cell and replicates or it degrades and fails to replicate.
Mutations arise independently of whether hosts are immune to the dominant strain or not. Maybe because they are “survivors” of a mostly effective drug treatment, or just random damage that happens to give some new trait that allows survival. Mutations that render the virus less deadly to its host will replicate more because dead hosts interact far less with naive hosts than do infected living hosts.
When there are “more fit” competitors, mutant strains may be slow to replicate or die out, but later, when there is immunity to the original strain, the mutant may take hold for lack of competition—provided that the mutant form happens to be sufficiently different that hosts immune to the original strain are not immune to the mutant.
Mutations can also supplant strains where hosts still lack immunity to either type. If the mutant has some advantage in surviving the environment to reach a host cell, it will have a higher probability of replicating than the original.
There is never any awareness on the part of a virus. It’s all random chance and the effects of human interventions.
Apart from that, there is the vaccine. So why paint a gloomy picture of a long road ahead? I’d say that’s unnecessarily pessimistic. Unless you’re pushing the “poison jab” theory.
Primitive or not – it is life.
Do not underestimate it.
Whether the jab us “poison” we will see in a couple years.
I guess, yes it is.
I do not trust miracles pushed by politics.
Actually it is questionable that it is life at all. Viruses cannot self-replicate. They require host cells to do that. They may be more like stray bits of genetic garbage that gum up the molecular works in living cells.
You are a male, right?
You also cannot self-replicate.
Are you a life form?
I am a life form but does that mean that my toenail clippings are also an independent life form in their own right? I think you’re trying to argue that apples are oranges.
He can use the machinery of another life-form to replicate. Sounds familiar…
Up-ticked despite the last paragraph. Do any of the ‘vaccines’ on offer actually satisfy the medical definition of a vaccine? Do any offer prophylaxis?
The only containment factor that I’ve seen “proven” to stop the spread of #19 is total isolation. As long as there’s an infected vessel traveling around we’re going to have hosts …. somewhere. Quarantining was successful in “flattening the curve” but you can’t quarantine forever. Vaccines will only be as effective as those willing to take it and because they aren’t 100% effective the disease will always be lingering.
“Isolation” often means driving families inside, where weaker populations are subject to infection from asymptomatic carriers.
As I’ve noted before, Europeans, hit hard, often use the equivalent of whole house fans, which dilutes the virus aerosol. When fall and winter comes, these fans are turned off, the virus accumulates, and cases also rise.
Look at these numbers (reported above…):
“India
New Cases: 18,106
New Deaths: 234
United States
New Cases: 279,154
New Deaths: 4,207”
India uses Ivermectin and HQC liberally, and it works. I took the 1% injectable grade Noromectin, 2 grams liquid in applesauce, and I believe I am protected.
see https://trialsitenews.com/an-unlikely-nation-is-kicking-this-pandemic-guess-which-then-why/
R0 is a myth, there is no such factor in reality.
Every individual has his/her own R0 based on their social behavior and hygiene and immune response. Even for the individual, R0 varies with time. It is near zero when socially isolated and shoots up as soon as you go to work or go into a store to shop or go to a church service.
“Heterogeneity” is just an admission of that fact.
It is not a myth, it is a variable, subject to many factors. You named some of them, yet forgot the virility of the virus itself as one primary factor.
I believe that Luxembourg has realised that mass testing artificially increases the number of ‘cases’ so is now, very sensibly, only testing people with symptoms.
If the false positive rate of the PCR test is as low as 1%, then for every 100000 people tested, 1000 will be incorrrectly reported as positive – even if no disease is present in the population. With positive test rates of around 5%, the false positive error rate inflates the numbers by around 25%.
If you look at excess deaths by state per week you can see that even adjoining states have peaks at different times. See https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
The graph that loads is total US, but you can select individual states from the drop-down list. Look at Illinois vs Wisconsin, for example.
To me, it just looks like God’s Roomba wandering across the country sweeping up the old and infirm. I have my own theories about weather and a/c, density of multigenerational immigrant housing, etc., but I don’t think my guesses are any more or less valid than the epidemiological calculations in the discussion above.
I once watched an animation of cases or deaths shown over time on a map, but I didn’t bookmark it. I wish I could find it again.
History tells us the second wave always kills more than the first.
Statistical squiggles are useless as the virus will not comply.
Epidemics follow the math of Laplacian diffusion systems with time delay, ie- they characteristically exhibit spatio-temporal waves. Imposing social distancing, mask wearing, etc merely effects the details of the pattern…The longer things are delayed, the longer the susceptible remain at risk…. Wishful thinking notwithstanding, the casualty count remains almost unchanged over time unless immunity can be obtained without risk of illness (ie- by vaccination.)
What is interesting about the ‘Second Wave’ in the UK is thatPHE (Public Health England) state in their most recent report: “In week 52 2020 in England, no statistically significant excess mortality by week of death… was seen overall”.
So we have No “statistically significant” change in excess mortality from an average yearDespie claims of a huge 2nd wave ….
Equally informative is the data from NHS England showing that ‘Flu like illnesses are running at about one third of the normal baseline for this time of year, Pneumonia is significantly below the normal baseline and perhaps most significantly Respiratory Illness – which Includes Covid-19 – attendance at A&E is also significantly below the normal baseline for this time of year.
So what we have is policy being made on the basis of unreliable PCR tests – seemingly without taking the other data into account – in the badly implemented rush to get the vaccines out.
But let’s assume, despite the seemingly contradictory PHE and NHS evidence, that there is a ‘second wave’, why could this be? Could it be because every year as people age there are an increasing number of very elderly people with one or multiple morbidities that are going to kill them in the near future and specifically likely to during cold winter weather? Could it be that pneumonia, flu and other seasonal illnesses are all being attributed to Covid-19 ? because that would explain why the NHS and PHE data show these as dramatically lower than in any ‘normal’ year?
Could it be that having politically destroyed the economy and spent billions on vaccines that the narrative has to be maintained at all costs to preserve political and government health advisers reputations ? I suspect that answers most of the questions and explains the incongruities existing between the data and policy.
Nicholas, the weather is the most significant driver of airborne virus spread and potency. This, what you call “second wave” is not, it is the 20/21 seasonal season. Just because it is the same virus plus mutations, doesn’t mean it isn’t seasonal. My forecast is to peak 15/22Jan and then fall as per a Gompertz curve.
Airborne viruses like cold, high humidity and no sunshine (UV). You can see here https://www.weather-research.com/articles/uk-cov-2-update the peak dates for the last 11 years is mostly in January.
The first epi/pandemic was out of season and unique over the last 11 years in the UK.
Kind regards
Neil
Neil,
I agree with your remarks regarding the significance of weather, but you seem to be speaking only of high latitude temperate regions. Lower latitude and tropical regions have vastly different curves than what we see in the the US and Europe.
That being said, it seems that Western societies in general have very poor overall nutritional health; probably pushed along by the symbiotic relationship between government, pharmaceutical corporations and the fast/processed food industry! The refusal to allow cheap and effective treatments like HQC and ivermectin is just as much of a democide as the push for low-fat diets that led to the steep rise in diabetes over the last forty years! When corporations and governments collude together for wealth and power, the citizen’s lives are as much at risk as their freedoms! One would think we would have learned from the tragedy of WWII, but apparently history unlearned must be repeated!
Charles, thank you for an insightful and important post and discussion! We must never forget how this disaster was pushed onto humanity the by the ChiComs and their puppets!
The UK’s Worldometer death chart looks a bit like the one posted above.
Sweden’s second death-wave appears to be almost over – and predictably smaller than the first wave. Sort of what one might have expected. Rather a neat chart.
It rather suggests lockdowns have merely kicked the can down the road and possibly have made things worse – our chart is messy and protracted.
Sweden’s ‘casedemic’ by comparison is odd – hardly any at the first wave, massive second time around. Tends to suggest the over-testing hypothesis is correct.
This is pure BS. It is predicated on a crappy nonspecific PCR test that shows positive if cycled too high (a common practice) and also looks for general coronavirus sequences that include rhinovirus and even human sequences. The PCR test is currently simply picking up the viruses of the current flu season. It has nothing to do with Covid-19, which for all intents and purposes does not exist as the virus has never been isolated, cultured, or shown to cause disease.
The poor specificity of the PCR test and everything related to it, the antibody test and the vaccines, are all false as, without a God Standard virus culture, none of these are specific for anything. This is why the public is being told that, even with a vaccination, you can still contract the virus and transmit it—the virus must replicate to make a person transmissible—which is doublespeak that the vaccines do nothing that is claimed, even with their poor specificity. However, it fits their agenda to keep the public in fear, even with the vaccines, as this is all about manipulating and controlling the people and nothing about disease.
The old flu season is gone, along with the viruses that caused Covid-19 syndrome. Now, we have a new season and they are using the same test and pretending that positives mean the virus is still around. That is NOT how infectious viruses work.
It is wrong to fall for the purposely wrong idea that the PCR test is specific in any way. Acknowledging this fact, completely explains the current peak in “cases.” It’s an epidemic of testing with a purposely bad test. You simply cannot be a “case” if you are not sick as a well, and the CPR test is completely useless in diagnosing anything as, at this point, it is 100% false positives.
Claiming C-19 to be a novel virus, the authorities pretend that all the established rules of how a virus behaves are null and void and that they can make up anything they want. From the false claims that a membrane-bound virus can survive on cardboard up to a week to the idea that you can catch the same virus over and over truly beggars the mind. [Membrane-bound viruses dry up very quickly and cease to function.] Unfortunately, many people do not think deeply enough and delve into the facts. If something does not sound logical, it probably isn’t.
Has anyone got accurate reports from hospitals regarding the number of sick people inside, specifically their age and comorbidities?
Are the ICUs overrun, and if so, where?
How often does PCR test discover flu virus, common cold virus, or dead covid virus?
Does isolating yourself make one more likely to have a bad reaction when ultimately being exposed to covid virus? In other words, does a little exposure all the time help in the long run?
how is it possible that nobody is getting the “flu” this year?
Cures – If you doubt that discuss it with the doctors promoting them
1) Inhaled steroids like Budesonide
The interview with Dr. Richard Bartlett has been BANNED BY YOUTUBE:
But you can still see it here starting around the 4 minute mark:
https://banned.video/watch?id=5f06524a672706002f481047
Cheap and can be used on very sick people with serious existing health conditions.
2) Ivermectin + Doxycycline + Zinc
Professor Thomas Borody developer of the triple therapy treatment for peptic ulcers in 1987.
“It’s easier than treating the flu now”. “You can actually eradicate it”. “We know it’s curable”
http://covexit.com/we-know-its-curable-its-easier-than-treating-the-flu-professor-thomas-borody/
3) Swiss Policy Research HCQ+ Treatment Protocol (5 to 7 day regimen)
https://swprs.org/on-the-treatment-of-covid-19/
Zinc — 50 milligrams [mg] to 100 mg per day
Hydroxychloroquine — 400 mg per day
Quercetin — 500 mg to 1,000 mg per day
Bromhexine — 50 mg to 100 mg per day
Azithromycin — up to 500 mg per day
Heparin — usual dosage
I understand Doxycycline is considered equivalent to Azithromycin but “safer.”
There are two reasons that there is a second wave of covid…
Vitamin D Deficiency. In Canada 25% of the population is Vitamin D deficient in the summer and 40% deficient in the Winter.
And secondly the Chinese have released a new strain of covid that 50% to 70% more contagious that the first version of covid,
Coronavirus: Black African deaths three times higher than white Britons – study
https://www.bbc.com/news/uk-52574931
82% of the US black population, 69% of the US Hispanic, and 42% of the US general population is Vitamin D deficient.
Prevalence and correlates of vitamin D deficiency in US adults.
https://tahomaclinic.com/Private/Articles4/WellMan/Forrest%202011%20-%20Prevalence%20and%20correlates%20of%20vitamin%20D%20deficiency%20in%20US%20adults.pdf
https://emerginnova.com/patterns-of-covid19-mortality-and-vitamin-d-an-indonesian-study/
Patterns of COVID-19 Mortality and Vitamin D: An Indonesian Study
Vitamin D Insufficient Patients 12.55 times more likely to die, blood serum 25(OH)D level from 21 to 29 ng/ml
Vitamin D Deficient Patients 19.12 times more likely to die, Vitamin D blood serum level less than 20 ng/ml
Vitamin D ‘normal’ for this study is 25(0H)D above 30 ng/ml.
William Astley, you are correct, and, as far as I can tell, the only one who gets it. For those of you who want to understand the coronavirus, start here. It is the medical paradigm:
https://virologyj.biomedcentral.com/articles/10.1186/1743-422X-5-29
Thank for the link. Ted. It is amazing. Correcting the Vit D deficiency would reduce all US health care costs by more than 50%.
This is a chart that was prepared the US group that has done all of the higher dosage Vitamin D supplement research. That summarizes the disease that are ‘cured’ as the level of activated Vit D in the bloodstream increases.
https://www.grassrootshealth.net/wp-content/uploads/2017/05/disease-incidence-prev-chart-051317.pdf
https://www.grassrootshealth.net/wp-content/uploads/2018/08/McDonnell-2018-breast-cancer-GRH.pdf
Serum 25-Hydroxyvitamin D Concentrations 40 ng/ml Are Associated with >65% Lower Cancer Risk: Pooled Analysis of Randomized Trial and Prospective Cohort Study
This pandemic has been so politicized that much of the data we do have is questionable. Most of the declarations from the so-called experts is rank speculation. Our leaders don’t want to admit they don’t know either, so they just plow ahead hoping that their “solutions” don’t kill more people than the “problem”. It’s a Charlie-Foxtrot of epic proportions.
“they just plow ahead hoping that their “solutions”
don’taren’t reported to kill more people than the “problem””I think a lot of them don’t really care about the actual results, or how many die.
We hear how Zinc is important.
OK
But your Zinc level depends if you drink alcohol or not. Alcohol flushes Zinc right out of you
e.g. India, with its very low death rate. What’s their per capita consumption compared to the UK or the US?
We hear that Vitamin D is important.
OK
But to actually ustilise the stuff, your metabolism needs to be that of a Fat Burner
i.e. A low carbohydrate diet
Hi-Carb diets causes you to be a sugar-burner and you turn excess sugar into fat.
Being ‘fat soluble’, Vitamin D disappears into that fat and stays there.
Unused
Hi-Carb diets are full of fibre. Almost all the nutrients ## we need are water-soluble.
water sticks to fibre and those nutrients stick to the water – and go down the toilet.
Unused
## Especially Magnesium – vital to the metabolisation of Vitamin D
It gets worse. Copper is needed to help with Magnesium usage
You need Iodine to manage almost everything
Copper and Iodine go down the pan with all that Nutritious (as the haha diet quacks tell us) Fibre
B Vitamins
Have a lot to do with how we use protein Our immune systems are all about proteins – its how they recognise friend from foe
Hi-Carb diets are horribly deficient in Vitamin B
We also use vast amounts of B vitamin to metabolise alcohol. First sign of deficiency is pins & needles in fingers & toes
Also and esp Vitamin B12 – presenting as decline of Executive Function = poor short-term memory – classically progressing to something identical to full-blown Alzheimer’s
Especially in elderly people who need more of all those things yet typically have smaller appetites.
Double Whammy
THEN, they are incarcerated into haha Care Homes where they are fed Government Recommended Hi-Carb Diets – while being assured that there is such a thing as a Safe Level of alcohol.
Sadly it’s just about the Care Home residents’ only source of joy.
While all the rich & clever people race around inside and outsideof computers and Hi-Tech medicine and using those Authorities to impose their Blind Panic and Dysfunctional & Magical Thinking upon everyone else
What A Total Mess
CDC graphs show most areas with early high rates of excess deaths did not see second spikes, e.g. NYC
but infection rates are highly contingent on many factors, including weather
e.g. a level of immunity sufficient to prevent an outbreak in June might do very little in January
If there’s any doubt about the seasonality of covid19, here are the daily death charts from Worldometer for Canada and Australia, superimposed. Two countries that are very similar in size, demographics etc., except that they are in different hemispheres. The Canada chart bars are reddish and the Australia ones are greenish.
The overall lower death rate in Australia could be due to its relative geographic isolation, or to the fact that winters there are not as cold. Too many unknowns to speculate.
More evidence that masks and social distancing are ineffective against the spread of cold and flu viruses.
I think the seasonality exhibited when the first wave diminished was falsely hoped to be as a consequence of either non-clinical interventions, or the onset of (localised) herd immunity. After the first lockdown (UK), I said that I wished they would just open up the nightclubs so that the youngsters could build their immunity in the summer and become a firewall to later spread. By the time universities opened up in the autumn, it was too late for that strategy, even though the exuberance of youth imprisoned in the halls of residence may have inadvertently exhibited some behaviour towards that end. The initial autumn spread was indeed in locations which had largely escaped the first wave, so it was effectively still a novel coronavirus spreading in a naive local population, and peaked early November. That peak coincided with the panic decision to impose the second lockdown (England). That lockdown was only really released in low population density areas not yet hit, and areas previously hit hard, so having scattered immunity. Only as we progressed into the heart of the flu season did the virulence of the virus overwhelm the suppression from that previously developed immunity. Now we continue with another lengthy lockdown until the vaccines can take credit for end of epidemic at the the end of the flu season.
Meanwhile, the NHS continues to infect non-COVID patients, and refuses to use the effective early treatments.
Reports of plans to activate the London Nightingale white elephant just happen to coincide with reports that the most vulnerable will be sent to the same location to be vaccinated. One last chance for the NHS to infect any vulnerable they have missed so far?
Perhaps the Stasi will let us out at Easter.
Well, it has been very interesting reading all the comments here. Some make sense, others do not. My own experience has to do with following the rules (isolate, wear a mask, etc.) which I did do, and literally nothing happened all summer beyond my being annoyed by having to wear that mask to go to the store. However, I have stuck it out, but never had a chance to get my flu shot last fall because around the time I’d have gotten it, my furnace went on the clanker-bound side, and had to be replaced. Immediately, or have no heat all winter.
Called the HVAC company, set up a time to get the blower motor removed, and the guy who showed up said my 30-year-old furnace + AC should be replaced, period. And this conversation went on in the damp, chilly, gray afternoon outside my back door, while I’m wearing a mask and he is, too, and by the 1st week in November, the new HVAC setup is installed and I’m back in business. Meantime, a small ceramic heater kept my cat and me somewhat warm.
HOWEVER — and this does matter — during the time it took for the new HVAC stuff to arrive and be installed (very quickly, too!) I started having the sniffles, which became a cough, sore throat, and eventually by mid-December, the nastiest cold I’ve ever had.
Nothing like waking up and finding that a mix of 1/2 tomato juice & 1/2 V8 was too acidic to swallow, anything hot was too painful to swallow, and coughing violently was the order of the day. That is all gone now, and if I cough, it is once in a while.
No, I did not get my flu shot, because you don’t get the flu vaxx when you have a cold, and this one was THE worstest ever. Period.
I never quit running errands, but I have had little to no contact with other people in person, only online. And that may be what the difference is: followed the rules (masks outside the house for errands, use the card to pay for stuff, make it quick and be GONE!) and yet I had plenty of contact with other people online.
Bored silly at some point by it all, but still followed the rules, and am now waiting for Spring to come along so I can get out with my camera again. All the local forest preserves have been empty of people except for back in the Spring, when the local fishing lake was finally opened up and brought in all the free food people who were elbow-to-elbow there, and in other places.
Over it all now: stuck to milk when my throat was too sore for hot stuff or V8/tomato juice, coughed like a howling banshee and avoided people like the Plague. Sometimes, even bread was too abrasive to swallow, so I stuck with things like mashed potatoes and ice cream. (Yeah, eat your hearts out on that one, but it is far better than the B&R brand, made with eggs as part of the recipe, and I survived quite well.)
Whatever, I never got the flu shot for this past flu season and will wait patiently for it next fall. I went out as much as I liked and kept myself busy and had plenty of online contact with other people so did not feel isolated – just BORED out of my mind at times, so I pulled out favorite books to read and kept myself busy with other things besides that.
Now this confounded “cold” (if it was that, it didn’t act like a cold) is nearly gone, my coughing spells no longer scare my cat because they are gone, the sore throat is gone – ALL those things are gone and I have the occasional need for Kleenex for a runny nose – and THAT is IT. Tomato/V8 juice combo is back on my menu, as is my favorite soup, and dill pickles – food items that were too abrasive for me to eat them for about 2 weeks.
All this nattering on about this treatment and that medication, etc., is fine but it ignores the stuff about “stay away from other people” part. Did I ever get tested? No, and I won’t, because the paranoia about it, as well as the miserable crap involved in some stranger sticking something right up your nose is not my idea of testing for anything. Get a blood test or a spit test developed, or shut up. The obsession with this disease by the media is a huge part of the problem. If this virus can mutate and jump to another bug to acquire its RNA and become a new strain, then it is nothing more than another nasty virus like the flu.
The Stephen King novel “The Stand” was based on an aggressive shifting antigen flu virus that changed RNA at will, but it was fiction. So far, this one hasn’t killed off horses, cows, or cats. The Brit TV show “Survivors” was about someone developing a vaccine that would address “every flu virus ever”, which ended in killing off massively large portions of the population, and spread like wildfire worldwide – and that was just a TV show.
Since the seasonal flu vaccine has to be redeveloped EVERY YEAR, because the influenza viruses constantly exchange their RNA with each other, just HOW is this CV19 virus any different?
It has already changed to a new strain by combining RNA from other Covid viruses and changing its properties. No one is even addressing this issue. And it isn’t any different, and no, it won’t go away any more than the flu and the common cold will go away.
I am looking forward to Spring and the arrival of geese coming back from the South, and the wildflowers springing up out of the ground again.
I’m not dead yet and frankly, I will be glad to see less asinine crap about this bug. Yes, it is bad news if you’re one of those that get sick constantly, but if your immune system is strong (and mine appears to be), you’ll likely outlive the whole thing.
Sara,
Sorry you weren’t feeling well! In the future you might want to try chamomile tea with honey and lemon for soothing a raw throat! Honey was considered a medicine for centuries so I always have some raw honey on hand to add to my daily green tea.
There seems to be some connection between cold weather and respiratory viruses. Perhaps the lower humidity of air from furnaces and heaters makes our mucous membranes more susceptible to viral infections. Lots of healthy teas, soups and stews will not only warm you up; but will also help keep your indoor humidity level a little higher. I think I’m going to make some beef barley stew soon and test my hypothesis!
If a virus is challenged by a lockdown is it more likely to mutate into a more easily transmissable form just like evolution works? If I wear a mask and have the virus in a non-symptomatic state does it mean I breathe exhaled virus back in and increase the load in my lungs and so increase my risk of symptomatic infection? Since wearing a mask causes my spectacles to mist, I take them off. Does that make me more susceptible to Covid infection through my eyes? Does anyone know?
Well it turned out to be easier to manipulate Worldometer graphics than I thought. So I tried something else. Here are the daily death charts for Canada (red) and no-lockdown Sweden (blue) adjusted for population. Covid deaths are probably a better measure than number of cases, because they are not quite so dependent on the number of tests.
The two charts are strikingly similar, except that Sweden got about twice the deaths per unit population as Canada did.
But look at the right hand end of the chart. <b>Since mid-December, Sweden’s covid deaths have dropped to almost nothing</b>, while deaths in Canada appear to be still rising.
Sweden has just recently adopted what appears to be a semi-voluntary semi-lockdown, and it seems to be working, while strict lockdowns in Canada are apparently not working at all. The only conclusion I get from this is that Sweden benefits from its initial tactic of letting the disease rip to try and build as much immunity as possible among the young and healthy.
It looks as though Sweden exposed itself to short-term pain, with a long-term gain.
In Canada, police are breaking into homes and arresting people where the neighbour has ratted out a family for having guests over. So far, that’s only in Québec, but who knows? The strident scolding of people who go to visit their sister in the next town (or whatever) by politicians, health-care workers, journalists (and let’s not forget the ubiquitous karens) has increased in volume to the point that I expect the unpleasantness to be nation-wide before winter is over.
Who’d have thought it? Peaceful, polite, prosperous, progressive Canada, where nothing really bad ever happens, is turning into a f—ing police state. And half the population seems to think that’s a good thing!
World gone crazy! Thank heavens I’m getting old; I won’t have to listen to it much longer.
“turning into a f—ing police state. And half the population seems to think that’s a good thing!”
Ditto in the U.S.
Amazing how something that does not exist gests around.
Where is that purified isolate Gold Sample of the SARS-CoV-2 virus?
If that does not exist a year after the virus was said to have existed and has infected supposedly tens of millions and killed hundreds of thousands, how can you possibly believe that the virus is real?
No virus to study. It is not isolated to study.
Create a test to identify people infected. Infected with what? You have no idea what you are looking for. The test requires high cycle thresholds, making the test about 65,000 times too sensitive to make any sense.
Create a “vaccine” that is not a vaccine in order to cause you to supposedly not get sick when you do get infected, but if you get infected you can still pass on the non existent virus. But this is going to create herd immunity, HOW? Supposedly, once “vaccinated” you will test positive for the virus, so the sensitivity of the “test” has to be lowered, and unsurprisingly, lower cycles means that you do not test positive. The “Vaccine” that is not a vaccine is working! We could have done this by lowering the test cycles and gotten the same results.
This is so confusing, I can understand why people with an I.Q. lower than 125 might not get the problems with this. But for the rest of you. Seriously?