australiannationalreview--2020-05-05--CDC Public Health Data Fudging 1: COVID-19 Rates Explained

THIS IS A COMPANION ARTICLE TO AN UPCOMING EPISODE OF THE PODCAST “ UNBREAKING SCIENCE ” IN WHICH DR. JACK EXPLAINS 1 .
WHICH RATES YOU NEED TO UNDERSTANDING TO DISCUSS THE COVID-19 PANDMIC , 2 .
WHY ESTIMATING DEATH RATES DURING AN OUTBREAK IS HAZARDOUS , 3 .
HOW TO NOT CONFUSE CASE FATALITY RATES AND POPULATION MORTALITY RATES , AND 4 .
HOW YOU CAN THINK ABOUT HOW YOU ARE THINKING ABOUT COVID-19 AND CONTRIBUTE TO THE CONVERSATION .
On 5/2/2020 , CDC published the number of deaths from COVID as under 34,000 .
Surprised ?
You should @ @ @ @ @ @ @ US has reported over 67,000 deaths – depending on who you read , confirmed deaths ( e.g.
, The Weekly ) .
The point being , of course that when the public – and public health officials see “ Number of Deaths ” – they believe they are seeing confirmed deaths .
Johns Hopkins reports – without caveat = that the “ Number of Deaths ” in the US are currently over 67,000 : These are the statistics we have all been following .
Now here are the recently publicized statistics from CDC @ @ @ @ @ @ @ to me is the number of flu deaths is about double that of past seasons – if you follow my protocol for undoing CDC ’ s inflation protocol that adds pneumonia to flu deaths so influenza qualifies as an epidemic .
Remember we are at the end of the flu season .
With the few months ’ reporting , the number of flu cases being this high is shocking because it is double that from past years for the entire season .
The second thing that sticks out to me is that a @ @ @ @ @ @ @ most – w/COVID-19 at death must not involve pneumonia .
Of a total of 37,308 people who died with COVID-19 , the table reports only 16,564 deaths “ with Pneumonia + COVID19 ” That ’ s only 44 % of people who died with COVID-19 also had a diagnosis of pneumonia .
The third thing that sticks out of course is the difference between 37K and 67K deaths that we have all been tracking .
This massive discrepancy between CDC ’ s 37K and the everywhere-else-reported 67K is due to the use of @ @ @ @ @ @ @ confirmed COVID-19 cases and “ suspected ” COVID-19 cases .
I ’ ve seen explanations attributing the discrepancy in the lower number – 37K – as being due to a “ lag ” in confirmation – in fact the 33K CDC source says precisely that .
But that is no explanation for the difference .
Why , and how , for example , does an estimate of 67K even exist ?
And how can other CDC sources such the National Center for Immunization and Respiratory Diseases ( NCIRD ) , Division of Viral @ @ @ @ @ @ @ Centers for Disease Control and Prevention .
2020 and places like Johns Hopkins , whom we can presume gets their data from CDC , have results two weeks ahead of… the CDC ?
Why are we being misled in our perception of risk by inflated death rates – at all ?
A probable case or death is defined by CDC by fulfillment of one of the following : “ Meeting clinical criteria AND epidemiologic evidence with no confirmatory laboratory testing performed for COVID-19 ; Meeting presumptive laboratory evidence AND either clinical criteria OR @ @ @ @ @ @ @ with no confirmatory laboratory testing performed for COVID19.
” That ’ s of little assurance given that policies have been founded on the 67K estimate – not the 33K confirmed cases .
CDC ’ s paradigm – some would call it their M.O .
– is to overestimate death rates from infectious disease – explicitly , as if that ’ s appropriate or even useful for a reason-based response .
We have been waiting to see how CDC would reconcile their shady practices on “ Influenza ” death reporting – outed in Scientific @ @ @ @ @ @ @ my report of the discrepancy on LinkedIn given the impact of COVID-19 on influenza death rates – since the default for “ flu-like symptoms ” has become “ suspected COVID-19 ” instead of “ suspected influenza ” .
When it comes to flu deaths reporting and COVID-19 ‘ suspected ’ cases taking an unfair share away from the annual faux “ Influenza ” aka “ Influenza Disease ” aka “ Pneumonia & Influenza ” , something had to – and still has to – give , if “ Influenza ” – however CDC @ @ @ @ @ @ @ to qualify as an “ epidemic ” .
Their efforts at correcting their oversight appears to have led to as many as four times more influenza cases than they need .
Oops .
Data fudgery , statistical shamwizardy , some shift was expected – I predicted it a month ago , but expected a gradual drip leaning toward bias in the updates in June – because , put plainly , CDC does not track influenza cases with integrity .
To learn exactly what I mean by that , and why you need to @ @ @ @ @ @ @ read on… CDC Uses Scientism , but That Pits Belief in Sciency Things vs. Science So much discussion these days online involve taking a “ position on ” or “ believing ” in something , and this is actually not very helpful when one is trying to understand an outbreak .
While the public has every reason , the right and the responsibility to remain vigilently skeptical of anything coming from the CDC , it ’ s important that we are able to discuss and focus on numbers and rates without giving up @ @ @ @ @ @ @ ’ t know what to believe ” .
Situations change in outbreaks and pandemics , thus the actual values change ( they are dynamic ) from day to day and week to week in response to complex variables that impact growth .
It ’ s best to think about values we discuss like the Stock Market .
While that makes these issues are complex , with a careful read of this article , and a follow-up viewing of the companion Unbreaking Science episode ( link forthcoming ) , you ’ ll be able @ @ @ @ @ @ @ at and be able to communicate your ideas and thoughts quickly and efficiently .
What Determines How Bad An Outbreak Will Be ?
[ Warning : Deep Dive into the Geek Arena Here , But You Will Learn ] During an outbreak , epidemic , or pandemic of a deadly disease from virus , people want to know the answer the following question : “ How bad will this be ?
” This is determined in part by characteristics of the virus ( transmissibility and virulence , see my article on these two @ @ @ @ @ @ @ host species .
This means it is largely determined by our ability to respond to the virus .
The characteristics of the virus and how we respond to it determines the following outcome measures , all of which can change depending on how we respond : ( 1 ) R0 ( R-Naught ) .
This is the number of people a person infected with SARS-CoV-2 ( or any pathogen ) may be expected to infect .
People often think that R0 is a fixed characteristic of a virus .
It is not .
@ @ @ @ @ @ @ as an outcome of all of the characteristics of a virus and a populations ’ respond to the virus up to a given point in time , but it ’ s even better in my view to consider R0 on a daily basis during an outbreak .
I have a measure of an effective R0 that is easy to calculate Effective R0 ( EffR0 ) for COVID-19 , as the ratio of the number of COVID-19 cases today to the number of cases five days ago ( given a 4-5 day asymptomatic period @ @ @ @ @ @ @ done for any town , county , state , country , or for the entire world .
Here is chart of EffR0 for the US from Day 1 of the first recognized case until 5/3/2020 : Note we are not yet below 1.0 .
See how responsive this number is to changes in our behavior ?
The peak value represents the day POTUS declared COVID-19 a national emergency , and the variation following represents bringing testing online following CDC ’ s Testing Fiasco .
The value of EffR0 peaked at about 5.8 , @ @ @ @ @ @ @ national emergency .
These are not number of cases ; the total ( cumulative ) number of cases in the US looks quite different : One thing is clear – the virus is not in full retreat by any means – but at least the curve is no longer nonlinear .
It ’ s worth pointing out that R0 > 1 means a constant increase in the number of cases – and therefore the number of deaths .
Weeks ago , before the lock-down , the issue was an ongoing increase in the @ @ @ @ @ @ @ The extent that this is due to social distancing or seasonality remains to be seen – it will take time to know the true and full nature of SARS-CoV-2 and COVID-19 .
For a long-view comparison of R0s among pathogens , one can compare overall R0 values of different pathogens over a season or a year ( over a fixed time period ) .
It is important to state specifically the time period a given value of R0 is referencing , because it can change from year to year or season to season @ @ @ @ @ @ @ mutation , seasonality , or due to a policy change .
The Attack Rate is the proportion of people who become ill from a disease in a population that was initially free of the disease .
Obviously , to be able to answer the question “ How Bad Will This Be ?
” , we have to try to understand how many people can be expected to become infected in total over the course of an epidemic , and over what period of time .
If only certain individuals are susceptible to infection @ @ @ @ @ @ @ , the general immediate concern over risk of infection and therefore risk of serious illness or death will be lower .
However , if all of the risk is in certain demographics , such as a diseases that only effects newborns , the general concern may be heightened .
Like R0 , the Attack Tate is determined by characteristics of a virus and of the host .
Initially the attack rate may appear to be high , before a population responds .
If the population response is effective , or if they are @ @ @ @ @ @ @ decreased .
In epidemiology , there are two closely related measures that have significant differences : Incidence and Prevalence .
• Prevalence tells us how widespread a disease is in a population .
Prevalence is the ratio of the total number of patients diagnosed at a given time to the total population .
( # Infected persons at one time / Size of Population at that time ) • Incidence refers to new cases of the disease in the population in a given time period ( such as a year ) .
Incidence @ @ @ @ @ @ @ in a population divided by total population size ( # Of New Cases During a Period of Time / Median Size of the Population Over that Time Period ) .
We know the prevalence and the incidence of influenza ( or we think we do , see below ) .
While we can know on any given day the prevalence of SARS-CoV-2 infection ( estimated , of course ) , we can not yet know the incidence for COVID-19 in a manner comparable to influenza annual case rates yet precisely because COVID-19 is @ @ @ @ @ @ @ the total numbers of people diagnosed depends on whether the pathogen has had time – and opportunity – to spread to throughout the population under whatever protocol of public health intervention has been in play .
All estimates related to the infection rate ( attack rate , incidence , prevalence ) of COVID-19 must therefore be interpreted as reflecting the lock-down , social distancing , etc .
Since our past annual rates of influenza are from non-lock-down years , we can not compare COVID-19 population mortality rates and numbers to Influenza in any @ @ @ @ @ @ @ is a measure of the proportion of infected individuals who have died from a disease .
It is calculated as # Deaths Due to Illness From A Pathogen / Number of People Infected Importantly , CFRs are NOT rate measures , as classically defined , because CFRs do not include a temporal component ( time between infection and death due to the pathogen ) .
Imagine a virus that is 100 % deadly , but infects people under the age of 5 but only kills them after the age of 60 ; other @ @ @ @ @ @ @ will reduce the apparent risk of death due to the virus .
Case Fatality Rates are , however , considered measures of risk for a specified time period .
People sometimes use the term “ Case Fatality Ratio ” interchangeable with “ Case Fatality Rate “ , but this should be avoided but Case Fatality Ratios are actually a measure that compares the Case Fatality Rate between two diseases .
Comparing CFR during an outbreak , epidemic or pandemic for one pathogen to an established , all-season CFR is hazardous .
Why ?
@ @ @ @ @ @ @ be known in a day-to-day in a manner that is quite as meaningful for understanding the full relative risk of mortality of a disease as we might think .
The use of CFR to compare different pathogens has to wait until the end of a outbreak/epidemic/pandemic , or the end of a season .
This is true due to the same reason we can not compare R0 under those conditions – we can not know the full attack rate until enough time has transpired for the full attack rate to be measured – @ @ @ @ @ @ @ other epidemics – until the full effects of a society ’ s response have materialize .
One could measure “ # of deaths per day ” and thereby make an attempt to understand a death rate , but since the full Attack Rate is not known the actual full death rate still would not be known until the end of an outbreak , epidemic or pandemic .
And this point is super-relevant for people who want to be able to compare death rates from COVID-19 to influenza : it can not and should @ @ @ @ @ @ @ reasons : a .
We don ’ t yet know the final Attack Rate of COVID-19 b .
We don ’ t know the long-term ( say , annual ) CFR of COVID-19 c. There is a vaccine program against influenza , so such a comparison is apples-to-oranges “ COVID-19 w/no vaccine vs .
Influenza w/a vaccine ” .
d. We have more experience treating influenza than COVID-19 .
The high incidence of mortality from ventilators , for example , in COVID-19 is currently high ; those deaths will become unlikely as we @ @ @ @ @ @ @ of care .
It should be understood that the CFR reflects a “ risk of dying ” IF one is infected .
Thus , the CFR is not relevant for the entire population at all unless the Attack Rate is 100 % .
The Population Mortality Risk , or Population Death Rate from a pathogen is ratio of number of deaths from illness from the infection by that pathogen to the total number of people in the population over a specified period of time .
The PMR will typically be far lower than @ @ @ @ @ @ @ Rate is 100 % .
To understand population-wide risk , we have to compare , if we can , the effect of real-life efforts at containment , mitigation , and suppression , ot a null “ do nothing model ” .
Each of any number of plausible scenarios have their own outcome variables , and this goes to a key point of modeling .
All models , by definition , are incorrect .
They are not reproductions of reality – they are not even attempted reproductions of reality .
Therefore even the most @ @ @ @ @ @ @ incorrect to some degree in detail .
In an oubreak , early models will almost always be more incorrect than later models , as more information becomes available .
But later models will also have more parameters , as the host species ( us ) , use our innate characteristics ( intelligence , behavior , technology , communication , treatments ) to change our susceptibility to infection , serious illness and mortality .
Any reasonable response will include factors that influence overall health ( nutrition , supplements ) , access to fresh air @ @ @ @ @ @ @ most risk , mitigating specific risk , and , most importantly , personal responsibility .
Individual actions such as informed self-isolation based on their COVID-19 status from private testing is a variable not yet explored .
Instead , testing is considered to be the responsibility of the medical community .
In clinical testing , however , the laboratory reports the results of the test to the physician who ordered the test , and to the CDC .
The patient is the last ot know the results , and for meaningful utility leading to @ @ @ @ @ @ @ patient ( or just a person ) should be the first to know .
So What Does All of This Mean ?
What this means is that CDC has , at the present time , at least 30K deaths it can attribute according to “ complex algorithsm ” either to COVID-19 or the Infleunza , or both , whatever fits their agenda in June .
What people really care about , though is risk to themselves… general population mortality risk due to COVID-19 .
If I were to take my best current shot @ @ @ @ @ @ @ I could do it in one of two ways : using data available before the US societal response , or data available after .
Any analysis using total present “ today ” data on cumulative numbers of cases , or numbers of deaths , in the US would be based on hybrid – not well-defined – set of response parameters .
Before the societal lock-down , our response was minimal and impotent .
After the lock-down , it ’ s still very messy because different states have developed different legal paradigms and overarching @ @ @ @ @ @ @ the effectiveness of each paradigm is unknown .
The fact remains : CDC has been combining probable and confirmed cases of COVID-19 , and all of our public health policies , and the public ’ s reactions to those policies , have been a result of using inflated death numbers .
Knowledge that the denominator – the total number of cases – is much , much higher than the number of clinical cases means the PMR is VASTLY inflated if one looks only at the Case Fatality Rate .
If the real rate @ @ @ @ @ @ @ from influenza , RSV and other non-COVID-19 pneumonia cases , it impacts population-rate estimates in the moment that makes it impossible to define a rational public health response that everyone can support .
Just as CDC inflated Influenza counts , they are inflating COVID-19 counts .
Still , let ’ s take a look at the overall US “ non-lagged ” data from Day 80 of the outbreak in the US .
The rate of increase in the number of cases and deaths is now constant – approximately linear – so let ’ @ @ @ @ @ @ @ right to the number of expected deaths after 365 days if nothing changes .
The number I come up with is 617,902 deaths , giving us a population-wide mortality risk of 0.00185 .
That ’ s 185 deaths per 100,000 individuals ( population mortality rate ) .
That ’ s with Probable Case data – and , very importantly – with the lock-down in place .
Now , with no lock-down , in three months ’ time , a power law model tells that we would have 3.3 million deaths ; ten days @ @ @ @ @ @ @ 8.2 million deaths .
All based on wildly biased estimates published by CDC .
The unbiased data – wherever it is – will now have to be analyzed to produce a lower-bound estimates of these two conditions , but let ’ s assume for now they will be approximately 1/2 of the size of the biased estimates .
So , lower bound annual population mortality risk , 90 deaths per 100,000 , or about 10 in 1,000,000 .
But no economy .
Neither estimate is realistic .
We need to dial into reality @ @ @ @ @ @ @ that period of time reflect the effects of CDC ’ s testing fiasco , reflect no new testing infrastructure , no real general knowledge of the value of self-isolation and sanitation of public spaces , and no widespread use of antivirals to keep viral titres down during infection to prevent serious illness , death and transmission .
Yesterday , for the first time , I saw our local grocery chain employees wiping down common surfaces , something I ’ ve been calling for since early February .
These individual factors will matter .
@ @ @ @ @ @ @ “ lock-down ” vs. “ no lock-down ” .
The two modeled scenarios actually represent extremes on a continuum .
A new factor that could be and I think should be added is private , in-home testing .
Hundreds of millions of Americans could be tested with a 15-min antibody test in the privacy of their home .
This would be far more effective and less costly than widespread testing w/contact tracing .
Further , those who seek medical care would receive a follow-up clinical test – and their data would be available @ @ @ @ @ @ @ , zip code , gender and COVID-19 status ) .
In-home private testing is the solution to so many problems .
It ’ s rapid , efficient and will prove very effective if the public can be taught how to interpret the test results and be provided simple guidance .
( See the IPAKBack2Work Plan ) .
No reporting .
No contact tracing .
Your employer does not know .
Individuals testing and then deciding to do the right thing – including whether they can yet rejoin society .
Simple .
And this @ @ @ @ @ @ @ , until allopathy catches up to highly effective curative protocols that do exist .
Our plan preserves HIPAA protections and relies on personal responsibility .
The bulk of the two projections above are , unfortunately , 100 % dependent on the CDC ’ s data reported to WHO .
It ’ s a shame we have to rely on thoroughly corrupted institutions for our data for such an important public health event .
WHO by the way , has the US at > 67,000 deaths whereas their domestic confirmed data reflects a mere @ @ @ @ @ @ @ memo ?
CDC will gyrate a few times before the settle on one cooked estimate , until June we are told .
Right now , it seems that CDC has a new tactic – to boldly estimate Influenza deaths at two to ten times the rate of past years no longer by combining pneumonia + influenza , but instead perhaps just borrowing from COVID-19 deaths .
Perhaps testing is up because of COVID .
We ’ ll see .
It ’ s tempting to make comparisons of COVID-19 rates to influenza , but @ @ @ @ @ @ @ being misleading – for methodological reasons and for GIGO ( garbage-in-garbage-out ) reasons .
Elsewhere I have outlined how that comparison is made impossible anyway because CDC has been cooking the books on “ Influenza ” since 2015 by combining “ Pneumonia ” deaths with laboratory-confirmed “ Influenza ” ( sometimes referenced by CDC to as “ Influenza ” , “ Influenza Disease ” or “ P & I ” ( “ Pneumonia & Influenza ” ) , meaning CDC has been misleading the public into perceiving that influenza virus infection is six @ @ @ @ @ @ @ is ( See “ Is CDC Borrowing Pneumonia Deaths “ From Flu ” for “ From COVID-19 ?
” April 3 , 2020 ) .
Some of the pneumonia cases intermixed with Influenza into “ Influenza Disease ” annually are caused by coronaviruses .
In the 2020 “ confirmed cases ” report on COVID deaths , CDC notes that for THAT report , “ Pneumonia death counts exclude pneumonia deaths involving influenza “ So there is absolutely no justification for the prior years ’ combination of Influenza + Pneumonia deaths .
Looking back @ @ @ @ @ @ @ % of influenza disease deaths were bona fide influenza .
When Influenza alone is considered , there are typically less than 5,000 deaths from influenza virus pear year .
Of course there is a range of error around that estimate .
However , at the most likely rate , nearer to 5,000 , influenza causes less than 7.3 % of deaths from all causes , and this leads to the stunning reality that influenza should no long be considered an epidemic in the US .
Without integrity and accuracy in assessing rates and @ @ @ @ @ @ @ to pathogens , we can not have evidence-based public health policies founded on science .
With practices such as those adopted by CDC , we merely have public health policies founded on dogma , which will always have to eventually be reconciled with reality .
COVID-19 has challenged the status quo misleading accounting practices used by the CDC , which , absolutely , must now change .
That ’ s part of why I am calling for a radically new public health system – one in which the CDC culture is absent , @ @ @ @ @ @ @ with no connection to profit oppotunities .
I am calling for a Public Health Integrity Network of 18 performance sites , located within private and public research institutions , each node of which acts completely independent of each other on the same public health problems simultaneously .
All results from these activities are sent to an independent body that compiles the range of information presented and best solutions are brought into the public eye .
We need pure academic research without perverse financial entanglements and incentives .
This network process will replace the @ @ @ @ @ @ @ in public health matters .
Period .
Things will look different when we finally have public health integrity with transparency , accountability and independence from profit motive providing core tenets of professionalism in public health research , and the public will know their privacy and right to autonomy are respected .
Which means , of course , no immunity cards , no mandatory testing , and , with respect , no mandatory vaccines .

By James Lyons-Weiler, PhD
THIS IS A COMPANION ARTICLE TO AN UPCOMING EPISODE OF THE PODCAST “UNBREAKING SCIENCE” IN WHICH DR. JACK EXPLAINS 1. WHICH RATES YOU NEED TO UNDERSTANDING TO DISCUSS THE COVID-19 PANDMIC, 2. WHY ESTIMATING DEATH RATES DURING AN OUTBREAK IS HAZARDOUS, 3. HOW TO NOT CONFUSE CASE FATALITY RATES AND POPULATION MORTALITY RATES, AND 4. HOW YOU CAN THINK ABOUT HOW YOU ARE THINKING ABOUT COVID-19 AND CONTRIBUTE TO THE CONVERSATION.
On 5/2/2020, CDC published the number of deaths from COVID as under 34,000. Surprised? You should be. By all accounts, the US has reported over 67,000 deaths – depending on who you read, confirmed deaths (e.g., The Weekly).
The point being, of course that when the public – and public health officials see “Number of Deaths” – they believe they are seeing confirmed deaths.
Johns Hopkins reports – without caveat = that the “Number of Deaths” in the US are currently over 67,000:
These are the statistics we have all been following.
Now here are the recently publicized statistics from CDC:
The first thing that pops out to me is the number of flu deaths is about double that of past seasons – if you follow my protocol for undoing CDC’s inflation protocol that adds pneumonia to flu deaths so influenza qualifies as an epidemic. Remember we are at the end of the flu season. With the few months’ reporting, the number of flu cases being this high is shocking because it is double that from past years for the entire season.
The second thing that sticks out to me is that a huge proportion of people – in fact most – w/COVID-19 at death must not involve pneumonia.
Of a total of 37,308 people who died with COVID-19, the table reports only 16,564 deaths “with Pneumonia + COVID19”
That’s only 44% of people who died with COVID-19 also had a diagnosis of pneumonia.
The third thing that sticks out of course is the difference between 37K and 67K deaths that we have all been tracking. This massive discrepancy between CDC’s 37K and the everywhere-else-reported 67K is due to the use of that set of statistics being based on confirmed COVID-19 cases and “suspected” COVID-19 cases. I’ve seen explanations attributing the discrepancy in the lower number – 37K – as being due to a “lag” in confirmation – in fact the 33K CDC source says precisely that. But that is no explanation for the difference. Why, and how, for example, does an estimate of 67K even exist? And how can other CDC sources such the
National Center for Immunization and Respiratory Diseases (NCIRD), Division of Viral Diseases. Cases in the US. Centers for Disease Control and Prevention. 2020
and places like Johns Hopkins, whom we can presume gets their data from CDC, have results two weeks ahead of… the CDC? Why are we being misled in our perception of risk by inflated death rates – at all?
A probable case or death is defined by CDC by fulfillment of one of the following: “Meeting clinical criteria AND epidemiologic evidence with no confirmatory laboratory testing performed for COVID-19; Meeting presumptive laboratory evidence AND either clinical criteria OR epidemiologic evidence; Meeting vital records criteria with no confirmatory laboratory testing performed for COVID19.”
That’s of little assurance given that policies have been founded on the 67K estimate – not the 33K confirmed cases. CDC’s paradigm – some would call it their M.O. – is to overestimate death rates from infectious disease – explicitly, as if that’s appropriate or even useful for a reason-based response.
We have been waiting to see how CDC would reconcile their shady practices on “Influenza” death reporting – outed in Scientific American as “wild overestimates” following my report of the discrepancy on LinkedIn given the impact of COVID-19 on influenza death rates – since the default for “flu-like symptoms” has become “suspected COVID-19” instead of “suspected influenza”.
When it comes to flu deaths reporting and COVID-19 ‘suspected’ cases taking an unfair share away from the annual faux “Influenza” aka “Influenza Disease” aka “Pneumonia & Influenza”, something had to – and still has to – give, if “Influenza” – however CDC will define it in June – is to qualify as an “epidemic”. Their efforts at correcting their oversight appears to have led to as many as four times more influenza cases than they need. Oops.
Data fudgery, statistical shamwizardy, some shift was expected – I predicted it a month ago, but expected a gradual drip leaning toward bias in the updates in June – because, put plainly, CDC does not track influenza cases with integrity. To learn exactly what I mean by that, and why you need to know how to think about rates, read on…
CDC Uses Scientism, but That Pits Belief in Sciency Things vs. Science
So much discussion these days online involve taking a “position on” or “believing” in something, and this is actually not very helpful when one is trying to understand an outbreak. While the public has every reason, the right and the responsibility to remain vigilently skeptical of anything coming from the CDC, it’s important that we are able to discuss and focus on numbers and rates without giving up in frustration and saying “I don’t know what to believe”. Situations change in outbreaks and pandemics, thus the actual values change (they are dynamic) from day to day and week to week in response to complex variables that impact growth. It’s best to think about values we discuss like the Stock Market.
While that makes these issues are complex, with a careful read of this article, and a follow-up viewing of the companion Unbreaking Science episode (link forthcoming), you’ll be able to quickly understand what you are looking at and be able to communicate your ideas and thoughts quickly and efficiently.
What Determines How Bad An Outbreak Will Be?
[Warning: Deep Dive into the Geek Arena Here, But You Will Learn]
During an outbreak, epidemic, or pandemic of a deadly disease from virus, people want to know the answer the following question: “How bad will this be?” This is determined in part by characteristics of the virus (transmissibility and virulence, see my article on these two), and the characteristics of the host species. This means it is largely determined by our ability to respond to the virus. The characteristics of the virus and how we respond to it determines the following outcome measures, all of which can change depending on how we respond:
(1) R0 (R-Naught). This is the number of people a person infected with SARS-CoV-2 (or any pathogen) may be expected to infect. People often think that R0 is a fixed characteristic of a virus. It is not. It is best to think of R0 as an outcome of all of the characteristics of a virus and a populations’ respond to the virus up to a given point in time, but it’s even better in my view to consider R0 on a daily basis during an outbreak.
I have a measure of an effective R0 that is easy to calculate Effective R0 (EffR0) for COVID-19, as the ratio of the number of COVID-19 cases today to the number of cases five days ago (given a 4-5 day asymptomatic period preceding diagnosis). This can be done for any town, county, state, country, or for the entire world.
Here is chart of EffR0 for the US from Day 1 of the first recognized case until 5/3/2020:
US Effective R0 as of 5/3/2020
Note we are not yet below 1.0. See how responsive this number is to changes in our behavior? The peak value represents the day POTUS declared COVID-19 a national emergency, and the variation following represents bringing testing online following CDC’s Testing Fiasco. The value of EffR0 peaked at about 5.8, when POTUS declared it to be a national emergency.
These are not number of cases; the total (cumulative) number of cases in the US looks quite different:
One thing is clear – the virus is not in full retreat by any means – but at least the curve is no longer nonlinear. It’s worth pointing out that R0 > 1 means a constant increase in the number of cases – and therefore the number of deaths. Weeks ago, before the lock-down, the issue was an ongoing increase in the increase of the number of infections. The extent that this is due to social distancing or seasonality remains to be seen – it will take time to know the true and full nature of SARS-CoV-2 and COVID-19.
For a long-view comparison of R0s among pathogens, one can compare overall R0 values of different pathogens over a season or a year (over a fixed time period). It is important to state specifically the time period a given value of R0 is referencing, because it can change from year to year or season to season. It can change due to a mutation, seasonality, or due to a policy change.
(2) Attack Rate
The Attack Rate is the proportion of people who become ill from a disease in a population that was initially free of the disease. Obviously, to be able to answer the question “How Bad Will This Be?”, we have to try to understand how many people can be expected to become infected in total over the course of an epidemic, and over what period of time. If only certain individuals are susceptible to infection, due to behavior or lifestyle choices, the general immediate concern over risk of infection and therefore risk of serious illness or death will be lower. However, if all of the risk is in certain demographics, such as a diseases that only effects newborns, the general concern may be heightened.
Like R0, the Attack Tate is determined by characteristics of a virus and of the host. Initially the attack rate may appear to be high, before a population responds. If the population response is effective, or if they are forewarned, the attack rate can be decreased.
In epidemiology, there are two closely related measures that have significant differences: Incidence and Prevalence.
• Prevalence tells us how widespread a disease is in a population. Prevalence is the ratio of the total number of patients diagnosed at a given time to the total population. (#Infected persons at one time / Size of Population at that time)
• Incidence refers to new cases of the disease in the population in a given time period (such as a year). Incidence is the ratio of total new cases in a population divided by total population size (#Of New Cases During a Period of Time / Median Size of the Population Over that Time Period).
We know the prevalence and the incidence of influenza (or we think we do, see below). While we can know on any given day the prevalence of SARS-CoV-2 infection (estimated, of course), we cannot yet know the incidence for COVID-19 in a manner comparable to influenza annual case rates yet precisely because COVID-19 is new.
For a given timeframe, the total numbers of people diagnosed depends on whether the pathogen has had time – and opportunity – to spread to throughout the population under whatever protocol of public health intervention has been in play. All estimates related to the infection rate (attack rate, incidence, prevalence) of COVID-19 must therefore be interpreted as reflecting the lock-down, social distancing, etc. Since our past annual rates of influenza are from non-lock-down years, we cannot compare COVID-19 population mortality rates and numbers to Influenza in any meaningful way.
(3) Case Fatality Rate (CFR)
The Case Fatality Rate is a measure of the proportion of infected individuals who have died from a disease. It is calculated as
#Deaths Due to Illness From A Pathogen / Number of People Infected
Importantly, CFRs are NOT rate measures, as classically defined, because CFRs do not include a temporal component (time between infection and death due to the pathogen). Imagine a virus that is 100% deadly, but infects people under the age of 5 but only kills them after the age of 60; other causes of mortality such as automobile accidents will reduce the apparent risk of death due to the virus. Case Fatality Rates are, however, considered measures of risk for a specified time period.
People sometimes use the term “Case Fatality Ratio” interchangeable with “Case Fatality Rate“, but this should be avoided but Case Fatality Ratios are actually a measure that compares the Case Fatality Rate between two diseases.
Comparing CFR during an outbreak, epidemic or pandemic for one pathogen to an established, all-season CFR is hazardous. Why?
The problem is that CFR cannot be known in a day-to-day in a manner that is quite as meaningful for understanding the full relative risk of mortality of a disease as we might think. The use of CFR to compare different pathogens has to wait until the end of a outbreak/epidemic/pandemic, or the end of a season. This is true due to the same reason we cannot compare R0 under those conditions – we cannot know the full attack rate until enough time has transpired for the full attack rate to be measured – and in the attempts to compare to other epidemics – until the full effects of a society’s response have materialize.
One could measure “# of deaths per day” and thereby make an attempt to understand a death rate, but since the full Attack Rate is not known the actual full death rate still would not be known until the end of an outbreak, epidemic or pandemic.
And this point is super-relevant for people who want to be able to compare death rates from COVID-19 to influenza: it cannot and should not be done for a few important reasons:
a. We don’t yet know the final Attack Rate of COVID-19
b. We don’t know the long-term (say, annual) CFR of COVID-19
c. There is a vaccine program against influenza, so such a comparison is apples-to-oranges “COVID-19 w/no vaccine vs. Influenza w/a vaccine”.
d. We have more experience treating influenza than COVID-19. The high incidence of mortality from ventilators, for example, in COVID-19 is currently high; those deaths will become unlikely as we change our use of ventilators as standard of care.
It should be understood that the CFR reflects a “risk of dying” IF one is infected. Thus, the CFR is not relevant for the entire population at all unless the Attack Rate is 100%.
(4) Population Mortality Risk
The Population Mortality Risk, or Population Death Rate from a pathogen is ratio of number of deaths from illness from the infection by that pathogen to the total number of people in the population over a specified period of time. The PMR will typically be far lower than the Case Fatality Ratio unless the Attack Rate is 100%.
Modeling
To understand population-wide risk, we have to compare, if we can, the effect of real-life efforts at containment, mitigation, and suppression, ot a null “do nothing model”. Each of any number of plausible scenarios have their own outcome variables, and this goes to a key point of modeling. All models, by definition, are incorrect. They are not reproductions of reality – they are not even attempted reproductions of reality. Therefore even the most granular and correctly arranged model will be incorrect to some degree in detail. In an oubreak, early models will almost always be more incorrect than later models, as more information becomes available. But later models will also have more parameters, as the host species (us), use our innate characteristics (intelligence, behavior, technology, communication, treatments) to change our susceptibility to infection, serious illness and mortality.
Any reasonable response will include factors that influence overall health (nutrition, supplements), access to fresh air and sunshine, understanding who is at most risk, mitigating specific risk, and, most importantly, personal responsibility. Individual actions such as informed self-isolation based on their COVID-19 status from private testing is a variable not yet explored. Instead, testing is considered to be the responsibility of the medical community. In clinical testing, however, the laboratory reports the results of the test to the physician who ordered the test, and to the CDC.
The patient is the last ot know the results, and for meaningful utility leading to rapid change in individual behavior, the patient (or just a person) should be the first to know.
So What Does All of This Mean?
What this means is that CDC has, at the present time, at least 30K deaths it can attribute according to “complex algorithsm” either to COVID-19 or the Infleunza, or both, whatever fits their agenda in June. What people really care about, though is risk to themselves… general population mortality risk due to COVID-19.
If I were to take my best current shot at estimating a population mortality rate, I could do it in one of two ways: using data available before the US societal response, or data available after. Any analysis using total present “today” data on cumulative numbers of cases, or numbers of deaths, in the US would be based on hybrid – not well-defined – set of response parameters. Before the societal lock-down, our response was minimal and impotent. After the lock-down, it’s still very messy because different states have developed different legal paradigms and overarching philosophies on how to respond, and the effectiveness of each paradigm is unknown.
The fact remains: CDC has been combining probable and confirmed cases of COVID-19, and all of our public health policies, and the public’s reactions to those policies, have been a result of using inflated death numbers. Knowledge that the denominator – the total number of cases – is much, much higher than the number of clinical cases means the PMR is VASTLY inflated if one looks only at the Case Fatality Rate. If the real rate of COVID-19 deaths are polluted with deaths from influenza, RSV and other non-COVID-19 pneumonia cases, it impacts population-rate estimates in the moment that makes it impossible to define a rational public health response that everyone can support.
Just as CDC inflated Influenza counts, they are inflating COVID-19 counts. Still, let’s take a look at the overall US “non-lagged” data from Day 80 of the outbreak in the US. The rate of increase in the number of cases and deaths is now constant – approximately linear – so let’s cut to the chase and go right to the number of expected deaths after 365 days if nothing changes.
The number I come up with is 617,902 deaths, giving us a population-wide mortality risk of 0.00185. That’s 185 deaths per 100,000 individuals (population mortality rate).
That’s with Probable Case data – and, very importantly – with the lock-down in place.
Now, with no lock-down, in three months’ time, a power law model tells that we would have 3.3 million deaths; ten days following that, we’d have 8.2 million deaths.
All based on wildly biased estimates published by CDC.
The unbiased data – wherever it is – will now have to be analyzed to produce a lower-bound estimates of these two conditions, but let’s assume for now they will be approximately 1/2 of the size of the biased estimates.
So, lower bound annual population mortality risk, 90 deaths per 100,000, or about 10 in 1,000,000. But no economy.
Neither estimate is realistic. We need to dial into reality.
Of couse the input data from that period of time reflect the effects of CDC’s testing fiasco, reflect no new testing infrastructure, no real general knowledge of the value of self-isolation and sanitation of public spaces, and no widespread use of antivirals to keep viral titres down during infection to prevent serious illness, death and transmission. Yesterday, for the first time, I saw our local grocery chain employees wiping down common surfaces, something I’ve been calling for since early February. These individual factors will matter.
But this is not as simple as “lock-down” vs. “no lock-down”. The two modeled scenarios actually represent extremes on a continuum. A new factor that could be and I think should be added is private, in-home testing. Hundreds of millions of Americans could be tested with a 15-min antibody test in the privacy of their home.
This would be far more effective and less costly than widespread testing w/contact tracing. Further, those who seek medical care would receive a follow-up clinical test – and their data would be available to CDC (standard reporting of age, zip code, gender and COVID-19 status). In-home private testing is the solution to so many problems. It’s rapid, efficient and will prove very effective if the public can be taught how to interpret the test results and be provided simple guidance. (See the IPAKBack2Work Plan). No reporting. No contact tracing. Your employer does not know. Individuals testing and then deciding to do the right thing – including whether they can yet rejoin society. Simple. And this could be done on a regular basis, until allopathy catches up to highly effective curative protocols that do exist.
Our plan preserves HIPAA protections and relies on personal responsibility.
The bulk of the two projections above are, unfortunately, 100% dependent on the CDC’s data reported to WHO. It’s a shame we have to rely on thoroughly corrupted institutions for our data for such an important public health event. WHO by the way, has the US at >67,000 deaths whereas their domestic confirmed data reflects a mere 37,000. Did WHO not get the memo? CDC will gyrate a few times before the settle on one cooked estimate, until June we are told.
Right now, it seems that CDC has a new tactic – to boldly estimate Influenza deaths at two to ten times the rate of past years no longer by combining pneumonia + influenza, but instead perhaps just borrowing from COVID-19 deaths. Perhaps testing is up because of COVID. We’ll see.
Summary
It’s tempting to make comparisons of COVID-19 rates to influenza, but they are fraught with the hazard of being misleading – for methodological reasons and for GIGO (garbage-in-garbage-out) reasons. Elsewhere I have outlined how that comparison is made impossible anyway because CDC has been cooking the books on “Influenza” since 2015 by combining “Pneumonia” deaths with laboratory-confirmed “Influenza” (sometimes referenced by CDC to as “Influenza”, “Influenza Disease” or “P&I” (“Pneumonia & Influenza”), meaning CDC has been misleading the public into perceiving that influenza virus infection is six to ten times more than it truly is (See “Is CDC Borrowing Pneumonia Deaths “From Flu” for “From COVID-19?” April 3, 2020). Some of the pneumonia cases intermixed with Influenza into “Influenza Disease” annually are caused by coronaviruses.
In the 2020 “confirmed cases” report on COVID deaths, CDC notes that for THAT report, “Pneumonia death counts exclude pneumonia deaths involving influenza“
So there is absolutely no justification for the prior years’ combination of Influenza + Pneumonia deaths.
Looking back at data from 2014, only 8.1% of influenza disease deaths were bona fide influenza. When Influenza alone is considered, there are typically less than 5,000 deaths from influenza virus pear year. Of course there is a range of error around that estimate. However, at the most likely rate, nearer to 5,000, influenza causes less than 7.3% of deaths from all causes, and this leads to the stunning reality that influenza should no long be considered an epidemic in the US.
Without integrity and accuracy in assessing rates and risk of serious illness and death due to pathogens, we cannot have evidence-based public health policies founded on science. With practices such as those adopted by CDC, we merely have public health policies founded on dogma, which will always have to eventually be reconciled with reality. COVID-19 has challenged the status quo misleading accounting practices used by the CDC, which, absolutely, must now change.
That’s part of why I am calling for a radically new public health system – one in which the CDC culture is absent, and integrity and accuracy reigns – one with no connection to profit oppotunities. I am calling for a Public Health Integrity Network of 18 performance sites, located within private and public research institutions, each node of which acts completely independent of each other on the same public health problems simultaneously. All results from these activities are sent to an independent body that compiles the range of information presented and best solutions are brought into the public eye. We need pure academic research without perverse financial entanglements and incentives. This network process will replace the CDC. CDC should not be involved in public health matters. Period.
Things will look different when we finally have public health integrity with transparency, accountability and independence from profit motive providing core tenets of professionalism in public health research, and the public will know their privacy and right to autonomy are respected. Which means, of course, no immunity cards, no mandatory testing, and, with respect, no mandatory vaccines.


australiannationalreview--2020-05-05--Vaccination-sceptic political party wins name change despite heavyweight objectors

A political party opposing compulsory vaccinations and fluoride in water has overcome objections from the nation ’ s highest health offices to win a name change with the Australian Electoral Commission .
The Involuntary Medication Objectors ( Vaccination/Fluoride ) Party will now be known as the Informed Medical Options Party , a change medical experts warned was an attempt to conceal the party ’ s true agenda and appear more mainstream .
Despite formal objections from the Australian Medical Association and federal Health Minister Greg Hunt , the AEC found the name change met the requirements of the Electoral Act @ @ @ @ @ @ @ the AEC decision was disappointing and maintained the name could mislead voters .
“ In the context of a pandemic , it ’ s hard for them to argue against vaccination given that it ’ s very likely it will be a way out of this for us , ” Professor Rait said .
“ Many illnesses , like smallpox and polio , were wiped out by earlier vaccination campaigns .
Measles , mumps and rubella are much less common because of vaccination .
“ Unfortunately this pandemic has reminded us of what @ @ @ @ @ @ @ and we don ’ t have that immunity.
” The party ’ s submission to the AEC said the objections were themselves misleading and the name change was to address supporters ’ concerns by “ embracing the broader definition of informed consent ” .
The micro-party ran eight Senate candidates at the 2019 federal election and received 17,055 first-preference votes on a platform opposing forced medications , compulsory or coerced vaccination and fluoride in the water supply .
Party secretary Michael O ’ Neill told The Sunday Age the “ anti-vaxxer ” label @ @ @ @ @ @ @ critics was “ insulting ” .
“ Our members only want their voice and concerns heard , and to be given an un-coerced choice in medical preferences , ” he said .
The AEC received a total of 27 objections to the change , with 13 considered valid under the Electoral Act .
But AEC acting assistant commissioner Joanne Reid found the party ’ s request was in accordance with Section 129 , which provides that a name must not be “ obscene ” or “ likely to be confused with , or @ @ @ @ @ @ @ recognised political party ” .
“ Further , I do not consider that the name ‘ Informed Medical Options Party ’ would bring the electoral system into disrepute or undermine the respect for and community standing of government agencies , registered political parties , or democratically elected members of Parliament , ” Ms Reid wrote in her findings .
In a statement following the AEC victory , the party said its objectives would remain the same .
“ However , we are now even more concerned at the looming pharmaceutical and media push @ @ @ @ @ @ @ on the entire population during the current COVID-19 pandemic , ” it said .
Professor Rait dismissed the party ’ s concerns , saying a more appropriate name would have been the “ Uninformed Medical Options Party ” .
“ There is a reason why people who know very little about some issues are utterly confident about their position , ” he said .
“ It ’ s a cognitive bias , a psychological phenomenon called the Dunning-Kruger effect , where basically your confidence about something is inversely proportionate to your knowledge about @ @ @ @ @ @ @ debates , less-informed members of the community get onto a hobby horse and sound confident about the position.
” Mr Hunt said the government “ condemns anti-vaccination actions or sentiment ” , though it would respect the AEC decision .
“ Vaccination safeguards Australians against disease , ” he said .
“ It is a powerful tool that is safe and effective to prevent the spread of many diseases that can cause serious ongoing health conditions and sometimes death .
“ Immunisation not only protects you , but others in the community , @ @ @ @ @ @ @ .
”

By Zach Hope
A political party opposing compulsory vaccinations and fluoride in water has overcome objections from the nation’s highest health offices to win a name change with the Australian Electoral Commission.
The Involuntary Medication Objectors (Vaccination/Fluoride) Party will now be known as the Informed Medical Options Party, a change medical experts warned was an attempt to conceal the party’s true agenda and appear more mainstream.
Despite formal objections from the Australian Medical Association and federal Health Minister Greg Hunt, the AEC found the name change met the requirements of the Electoral Act.
AMA Victoria president Julian Rait said the AEC decision was disappointing and maintained the name could mislead voters.
“In the context of a pandemic, it’s hard for them to argue against vaccination given that it’s very likely it will be a way out of this for us,” Professor Rait said.
“Many illnesses, like smallpox and polio, were wiped out by earlier vaccination campaigns. Measles, mumps and rubella are much less common because of vaccination. “Unfortunately this pandemic has reminded us of what can happen when a new infection emerges and we don’t have that immunity.” The party’s submission to the AEC said the objections were themselves misleading and the name change was to address supporters’ concerns by “embracing the broader definition of informed consent”.
The micro-party ran eight Senate candidates at the 2019 federal election and received 17,055 first-preference votes on a platform opposing forced medications, compulsory or coerced vaccination and fluoride in the water supply. Party secretary Michael O’Neill told The Sunday Age the “anti-vaxxer” label regularly used by the AMA and other critics was “insulting”. “Our members only want their voice and concerns heard, and to be given an un-coerced choice in medical preferences,” he said. The AEC received a total of 27 objections to the change, with 13 considered valid under the Electoral Act. But AEC acting assistant commissioner Joanne Reid found the party’s request was in accordance with Section 129, which provides that a name must not be “obscene” or “likely to be confused with, or mistaken for, the name of a recognised political party”.


australiannationalreview--2020-05-06--To The Mom Avoiding Unvaccinated Children

No Jab No Pay No Way – Freedom of Choice I saw your meme .
I saw your messages .
You want the world to know what you think about unvaccinated children .
You want them to know that you think of them as disease-ridden carriers and that you want to keep them as far away from your child as possible .
I get it .
You ’ re upset .
But you need to realize what you ’ re also saying when you post things like this .
Your posts are communicating fear and uncertainty about a product that @ @ @ @ @ @ @ They ’ re also telling the world that you really haven ’ t thought this all the way through .
Because let ’ s be honest , do you really want to know who is and is not vaccinated ?
Do you really intend on “ unfriending ” and avoiding every single unvaccinated person ?
If so , I suggest you brace yourself .
Because if you looked just a little bit deeper , this is what you would come to find .
YOU NEED TO KEEP YOUR CHILD AWAY FROM THE MAJORITY @ @ @ @ @ @ @ of the population is not “ up to date.
” The CDC recommended vaccine schedule is constantly adding more and more vaccines to the schedule , beginning with just a handful of vaccines in the mid 1900 ’ s to about 14 doses in the 1980 ’ s to the current recommendation of 72 doses from pregnancy to 18 years ( 1 ) .
Unless you ’ ve had all 72 doses of vaccines like your child is expected to get , you yourself are considered “ unvaccinated ” or “ partially vaccinated @ @ @ @ @ @ @ This also goes for all adults , teens , and even older children .
You also need to know that vaccine immunity , if even attained , wanes over time ( 2 , 3 ) .
It is unknown how long this so-called immunity lasts , and unless you pull titers on everyone in your family and contact list , it is impossible to know exactly what everyone is actually “ immune ” to .
The whole idea of herd immunity is just a myth , and if you look into the history @ @ @ @ @ @ @ find that it was a term coined in the 1930 ’ s to explain the immunity attained by natural infection–not vaccination .
If your goal is to avoid everyone who is unvaccinated by today ’ s standards , then you ’ ll have to find out when the last CDC recommendation was made in order to avoid everyone born before that time .
You ’ ll also have to find out what vaccines each person has received and declined from that point forward .
Doing this for each person you meet is what @ @ @ @ @ @ @ away from the “ unvaccinated.
” YOU SHOULD NEVER TRAVEL OUTSIDE OF THE UNITED STATES WITH YOUR CHILD .
I hope you don ’ t like traveling because you ’ ll really struggle with this if you are trying to avoid the unvaccinated .
You see , the United States vaccinates far more than the rest of the industrialized world ( 4 ) .
In most cases , we give up to twice as many vaccines .
Some countries have banned certain vaccines because of the associated adverse reactions .
Japan had postponed @ @ @ @ @ @ @ order to lower their incidences of SIDS ( 5 ) .
The UK does not vaccinate for the chicken pox because the vaccine can lead to more severe and higher incidences of shingles and chickenpox in adulthood ( 6 ) , and many countries just don ’ t think that the chicken pox is that big of a deal ( 7 ) .
If you truly want to stay away from all of the unvaccinated people in the world , then also stay away from foreign tourists , immigrants , and other countries @ @ @ @ @ @ @ to do to keep your child truly “ safe.
” YOU WOULD NEED TO KEEP YOUR CHILD AWAY FROM EVERYONE .
I know this sounds like a bit of a stretch , but the reality is that vaccines only somewhat “ protect ” us from about 16 diseases .
The media does a great job of focusing on these 16 diseases in order to ensure pharmaceutical profits and vaccine compliance .
They will cover every single case of the chicken pox or measles in a “ doom-and-gloom ” type of broadcast even if @ @ @ @ @ @ @ .
Notice that you will rarely hear anything about all of the other diseases in this world .
Look now at the world so fixated on the Coronavirus and the push for a Vaccine to save us all .
Which this Vaccine has skipped all protocols for safety and efficacy ( 12 ) You may find it overwhelming to find that there are hundreds of bacteria and viruses capable of spreading infection .
There ’ s leprosy , typhoid , scarlet fever , hand foot and mouth disease , tuberculosis , and so @ @ @ @ @ @ @ t even think about because they ’ re not being drilled into your psyche .
Should I fear you because you have not been vaccinated for any of those diseases ?
Think about that one for just a bit .
You can ’ t spread what you don ’ t have , and just because you haven ’ t been vaccinated for a disease , doesn ’ t mean you carry it .
We ’ re all unvaccinated for the majority of infectious diseases .
If you truly believe that vaccines are the @ @ @ @ @ @ @ disease , then they won ’ t be as safe as you think they should be .
YOU NEED TO RETHINK WHAT YOU ’ VE BEEN TOLD ABOUT VACCINES You may strongly believe in vaccines , but you need to understand that not all of them prevent the spread of infection like you think they do .
The pertussis vaccine only eliminates or reduces symptoms .
It does not prevent the spread of infection , which can make for a dangerous situation because of the possibility of asymptomatic transmission ( 8 ) .
@ @ @ @ @ @ @ vaccine , shed and are capable of transmitting infection as well , especially to those who are immune-compromised ( 9-section 5.4 ) .
Some vaccines only prevent infection against certain strains , leaving your child more vulnerable to mutated or alternative strains that are far more dangerous .
Tetanus is not contagious .
Hepatitis B can only be spread via sexual intercourse , shared needles , or by an infected mother at birth .
Did you know that if a child at your child ’ s school has Hepatitis B , they can @ @ @ @ @ @ @ same goes for HIV .
Or HPV .
If those do not concern you , then why should another child ’ s vaccination status matter ?
What should really matter is keeping your child as healthy as possible by feeding her nutrient-dense foods and making sure she gets proper exercise and sleep .
Reducing her toxicity load can also help immensely .
This can be done by limiting exposures to toxins and heavy metals , including those found in vaccines .
You may even find it interesting that unvaccinated children are often healthier @ @ @ @ @ @ @ reason ( 10 ) .
It really changes the message when you take a closer look , doesn ’ t it ?
I know you ’ re pretty set on what you believe .
You ’ re afraid .
You ’ ve been led to fear disease in order to vaccinate your child , and then further led to fear those who don ’ t vaccinate in order to make sure that they vaccinate their children as well .
Because let ’ s be honest–if vaccines really worked the way you ’ ve @ @ @ @ @ @ @ shouldn ’ t be worried and broadcasting your fears .
If you truly believed in vaccines , your memes should exert confidence instead of fear .
The truth is , however , you worry because you ’ ve been told to worry .
It wasn ’ t always like this though .
People weren ’ t always afraid–even long before we had 72 doses of vaccines and high levels of compliance .
You see , all of the infectious diseases we vaccinate for have not been deadly in this country since prior to @ @ @ @ @ @ @ just been used to sell vaccines .
It ’ s all part of the plan to get everyone vaccinated .
I know it ’ s not what you ’ ve been told , and I know that rethinking everything can be scary .
It may even be scarier for you than the diseases you fear , but you need to step back and do your own research .
Use logic and reasoning to think through the propaganda .
Learn the actual history behind vaccination ( 11 ) .
And then , ask yourself @ @ @ @ @ @ @ vaccinate their child ?
You may be surprised at what you discover .
You may also be surprised to find that many of us actually did vaccinate , and our children suffered from severe adverse reactions .
It ’ s not just 1 in a million like you ’ ve been told .
Instead of fearing the majority of the population for being unvaccinated , fear those who are spreading the lies in order to coerce the population into mandatory vaccine compliance .
Discover the truth for yourself and then rise up and @ @ @ @ @ @ @ do the same .
The truth is liberating , and it can truly set you free .
1. https : //www.cdc.gov/…/schedu…/hcp/imz/child-indications.html 2. http : //www.wbur.org/…/…/03/21/mumps-vaccine-protection-wanes 3. https : //www.ncbi.nlm.nih.gov/pubmed/26091979 4. http : //rescuepost.typepad.com/…/gr-autism_and_vaccines_worl… 5. http : //www.truthlibrary.info/…/japan-and-the-mmr-vaccine-a…/ 6. https : //www.nhs.uk/…/vaccinations/chickenpox-vaccine-ques…/… 7. https : //www.youtube.com/watch ?
v=v8CbgaDsoHs 8. https : //bmcmedicine.biomedcentral.com/…/1…/s12916-015-0382-8 9. https : //www.gsksource.com/…/…/Rotarix/pdf/ROTARIX-PI-PIL.PDF 10. http : //vactruth.com/…/02/26/unvaccinated-children-healthier/ 11 .
Dissolving Illusions : Disease , Vaccines , and the Forgotten History https : //www.dissolvingillusions.com/ 12 .
Coronavirus Vaccine Skips major protocol on safety testing : https : //www.livescience.com/…/coronavirus-vaccine-trial-no-…

I saw your meme. I saw your messages. You want the world to know what you think about unvaccinated children. You want them to know that you think of them as disease-ridden carriers and that you want to keep them as far away from your child as possible.
I get it. You’re upset. But you need to realize what you’re also saying when you post things like this. Your posts are communicating fear and uncertainty about a product that you’re trying to endorse.
They’re also telling the world that you really haven’t thought this all the way through. Because let’s be honest, do you really want to know who is and is not vaccinated? Do you really intend on “unfriending” and avoiding every single unvaccinated person? If so, I suggest you brace yourself. Because if you looked just a little bit deeper, this is what you would come to find.
YOU NEED TO KEEP YOUR CHILD AWAY FROM THE MAJORITY OF THE POPULATION–INCLUDING YOURSELF.
The majority of the population is not “up to date.” The CDC recommended vaccine schedule is constantly adding more and more vaccines to the schedule, beginning with just a handful of vaccines in the mid 1900’s to about 14 doses in the 1980’s to the current recommendation of 72 doses from pregnancy to 18 years (1). Unless you’ve had all 72 doses of vaccines like your child is expected to get, you yourself are considered “unvaccinated” or “partially vaccinated” and definitely not “up-to-date.” This also goes for all adults, teens, and even older children.
You also need to know that vaccine immunity, if even attained, wanes over time (2, 3). It is unknown how long this so-called immunity lasts, and unless you pull titers on everyone in your family and contact list, it is impossible to know exactly what everyone is actually “immune” to.
The whole idea of herd immunity is just a myth, and if you look into the history of the concept, you’d find that it was a term coined in the 1930’s to explain the immunity attained by natural infection–not vaccination.
If your goal is to avoid everyone who is unvaccinated by today’s standards, then you’ll have to find out when the last CDC recommendation was made in order to avoid everyone born before that time. You’ll also have to find out what vaccines each person has received and declined from that point forward. Doing this for each person you meet is what it takes to truly keep your child away from the “unvaccinated.”
YOU SHOULD NEVER TRAVEL OUTSIDE OF THE UNITED STATES WITH YOUR CHILD.
I hope you don’t like traveling because you’ll really struggle with this if you are trying to avoid the unvaccinated. You see, the United States vaccinates far more than the rest of the industrialized world (4). In most cases, we give up to twice as many vaccines.
Some countries have banned certain vaccines because of the associated adverse reactions. Japan had postponed vaccination to the age of two in order to lower their incidences of SIDS (5). The UK does not vaccinate for the chicken pox because the vaccine can lead to more severe and higher incidences of shingles and chickenpox in adulthood (6), and many countries just don’t think that the chicken pox is that big of a deal (7).
If you truly want to stay away from all of the unvaccinated people in the world, then also stay away from foreign tourists, immigrants, and other countries. This will be what you need to do to keep your child truly “safe.”
YOU WOULD NEED TO KEEP YOUR CHILD AWAY FROM EVERYONE.
I know this sounds like a bit of a stretch, but the reality is that vaccines only somewhat “protect” us from about 16 diseases. The media does a great job of focusing on these 16 diseases in order to ensure pharmaceutical profits and vaccine compliance. They will cover every single case of the chicken pox or measles in a “doom-and-gloom” type of broadcast even if the nearest incidence is 1000 miles away. Notice that you will rarely hear anything about all of the other diseases in this world.
Look now at the world so fixated on the Coronavirus and the push for a Vaccine to save us all. Which this Vaccine has skipped all protocols for safety and efficacy (12)
You may find it overwhelming to find that there are hundreds of bacteria and viruses capable of spreading infection. There’s leprosy, typhoid, scarlet fever, hand foot and mouth disease, tuberculosis, and so many more that you probably don’t even think about because they’re not being drilled into your psyche.
Should I fear you because you have not been vaccinated for any of those diseases? Think about that one for just a bit. You can’t spread what you don’t have, and just because you haven’t been vaccinated for a disease, doesn’t mean you carry it.
We’re all unvaccinated for the majority of infectious diseases. If you truly believe that vaccines are the only way to protect your child from disease, then they won’t be as safe as you think they should be.
YOU NEED TO RETHINK WHAT YOU’VE BEEN TOLD ABOUT VACCINES
You may strongly believe in vaccines, but you need to understand that not all of them prevent the spread of infection like you think they do. The pertussis vaccine only eliminates or reduces symptoms. It does not prevent the spread of infection, which can make for a dangerous situation because of the possibility of asymptomatic transmission (8).
Live-virus vaccines, such as the Rotavirus vaccine, shed and are capable of transmitting infection as well, especially to those who are immune-compromised (9-section 5.4). Some vaccines only prevent infection against certain strains, leaving your child more vulnerable to mutated or alternative strains that are far more dangerous.
Tetanus is not contagious. Hepatitis B can only be spread via sexual intercourse, shared needles, or by an infected mother at birth. Did you know that if a child at your child’s school has Hepatitis B, they cannot disclose this to you? The same goes for HIV. Or HPV. If those do not concern you, then why should another child’s vaccination status matter?
What should really matter is keeping your child as healthy as possible by feeding her nutrient-dense foods and making sure she gets proper exercise and sleep. Reducing her toxicity load can also help immensely. This can be done by limiting exposures to toxins and heavy metals, including those found in vaccines. You may even find it interesting that unvaccinated children are often healthier overall than vaccinated children for this very reason (10). It really changes the message when you take a closer look, doesn’t it?
I know you’re pretty set on what you believe. You’re afraid. You’ve been led to fear disease in order to vaccinate your child, and then further led to fear those who don’t vaccinate in order to make sure that they vaccinate their children as well. Because let’s be honest–if vaccines really worked the way you’ve been told they do, you really shouldn’t be worried and broadcasting your fears. If you truly believed in vaccines, your memes should exert confidence instead of fear.
The truth is, however, you worry because you’ve been told to worry. It wasn’t always like this though. People weren’t always afraid–even long before we had 72 doses of vaccines and high levels of compliance. You see, all of the infectious diseases we vaccinate for have not been deadly in this country since prior to the introduction of vaccines. Fear has just been used to sell vaccines. It’s all part of the plan to get everyone vaccinated.
I know it’s not what you’ve been told, and I know that rethinking everything can be scary. It may even be scarier for you than the diseases you fear, but you need to step back and do your own research. Use logic and reasoning to think through the propaganda. Learn the actual history behind vaccination (11).
And then, ask yourself, Why would someone choose not to vaccinate their child? You may be surprised at what you discover. You may also be surprised to find that many of us actually did vaccinate, and our children suffered from severe adverse reactions. It’s not just 1 in a million like you’ve been told.
Instead of fearing the majority of the population for being unvaccinated, fear those who are spreading the lies in order to coerce the population into mandatory vaccine compliance. Discover the truth for yourself and then rise up and share it, so that others may do the same. The truth is liberating, and it can truly set you free.
1. https://www.cdc.gov/…/schedu…/hcp/imz/child-indications.html
2. https://www.wbur.org/…/…/03/21/mumps-vaccine-protection-wanes
3. https://www.ncbi.nlm.nih.gov/pubmed/26091979
4. https://rescuepost.typepad.com/…/gr-autism_and_vaccines_worl…
5. https://www.truthlibrary.info/…/japan-and-the-mmr-vaccine-a…/
6. https://www.nhs.uk/…/vaccinations/chickenpox-vaccine-ques…/…
7. https://www.youtube.com/watch?v=v8CbgaDsoHs
8. https://bmcmedicine.biomedcentral.com/…/1…/s12916-015-0382-8
9. https://www.gsksource.com/…/…/Rotarix/pdf/ROTARIX-PI-PIL.PDF
10. https://vactruth.com/…/02/26/unvaccinated-children-healthier/
11. Dissolving Illusions: Disease, Vaccines, and the Forgotten History https://www.dissolvingillusions.com/
12. Coronavirus Vaccine Skips major protocol on safety testing: https://www.livescience.com/…/coronavirus-vaccine-trial-no-…


australiannationalreview--2020-05-06--George Soros And Bill Gates Funding Facebook’s Fact Checkers

Social media giant Facebook has announced that its fight against fake news will involve third-party fact checking organizations , however there are grave concerns about the legitimacy of those groups after it was revealed George Soros and Bill Gates , as well as other Clinton donors are funding the fact checking drive .
Many people are taking it for granted that these fact checkers are the quintessence of neutrality and unbiased reporting .
Well , judge for yourself .
Facebook released a statement on December 15 advising users that they were starting a program to “ work with third-party fact @ @ @ @ @ @ @ ’ s International Fact Checking Code of Principles ( IFCN ) ” .
Here ’ s an interesting fact about Poynter , the self-proclaimed “ global leader in journalism ” .
They are funded by George Soros ’ Open Society Foundations , The Bill & Melinda Gates Foundation , the National Endowment for Democracy ( which has financial links to the State Department ) , Ebay ’ s Omidyar Foundation , and Craig Newmark , the founder of Craigslist who donated a massive $ 1 million to Poynter to create this anti fake @ @ @ @ @ @ @ a Clinton campaign donor .
As is George Soros and Bill Gates , both big time supporters of the Clinton Foundation as well as Hillary ’ s election campaign fund .
And another Poynter donor , Ebay founder Pierre Omidyar , is also a massive donor to Clinton , giving millions of dollars to the Foundation .
Danish journalist Iben Thranholm said she was shocked that such obviously partisan fact checkers would be allowed to control the narrative in United States politics .
“ It gave me goosebumps to hear those names because @ @ @ @ @ @ @ agenda .
It ’ s like there are a lot of people who think that its dangerous not to be able to control the media , so to sort out what is supposedly the real news and the fake news is actually a way to control the narrative .
So if you want to be in opposition to these political powers then you are going to be censored .
Of course this is a kind of censorship.
” Welcome to 1984 ’ s Ministry of Truth , where only selected facts are allowed @ @ @ @ @ @ @ ’ t fit Washington ’ s neoliberal narrative will be labelled “ fake news ” and suppressed .

News, US
Social media giant Facebook has announced that its fight against fake news will involve third-party fact checking organizations, however there are grave concerns about the legitimacy of those groups after it was revealed George Soros and Bill Gates, as well as other Clinton donors are funding the fact checking drive.
Many people are taking it for granted that these fact checkers are the quintessence of neutrality and unbiased reporting. Well, judge for yourself.
Facebook released a statement on December 15 advising users that they were starting a program to “work with third-party fact checking organizations that are signatories of Poynter’s International Fact Checking Code of Principles (IFCN)”.
Here’s an interesting fact about Poynter, the self-proclaimed “global leader in journalism”. They are funded by George Soros’ Open Society Foundations, The Bill & Melinda Gates Foundation, the National Endowment for Democracy (which has financial links to the State Department), Ebay’s Omidyar Foundation, and Craig Newmark, the founder of Craigslist who donated a massive $1 million to Poynter to create this anti fake news mechanism.
Craig Newmark is also a Clinton campaign donor. As is George Soros and Bill Gates, both big time supporters of the Clinton Foundation as well as Hillary’s election campaign fund. And another Poynter donor, Ebay founder Pierre Omidyar, is also a massive donor to Clinton, giving millions of dollars to the Foundation.
Danish journalist Iben Thranholm said she was shocked that such obviously partisan fact checkers would be allowed to control the narrative in United States politics. “It gave me goosebumps to hear those names because they have actually a very strong political agenda. It’s like there are a lot of people who think that its dangerous not to be able to control the media, so to sort out what is supposedly the real news and the fake news is actually a way to control the narrative. So if you want to be in opposition to these political powers then you are going to be censored. Of course this is a kind of censorship.”
Welcome to 1984’s Ministry of Truth, where only selected facts are allowed to exist while other facts that don’t fit Washington’s neoliberal narrative will be labelled “fake news” and suppressed.


australiannationalreview--2020-05-06--COVID-19 turning out to be huge hoax perpetrated by media

That ’ s not good .
But it ’ s not as bad as the 2017-2018 flu season , when 80,000 -plus perished .
And it ’ s a long cry from what all the experts were warning about just a few weeks ago : First , they predicted 1.7 million Americans dead ; then they redid the models ( this time apparently entering a few more “ facts ” ) and said 100,000-240,000 dead .
SEE ALSO : Eighty percent of the population has little or nothing to fear from COVID-19 Now , a major model relied on by @ @ @ @ @ @ @ about 70,000 dead by the end of August .
And for that we shut down the U.S .
economy ?
!
As the coronavirus swept across China , then Europe — then everywhere — the U.S. media breathlessly reported every terrifying number , almost gleefully .
Their ratings soared , of course , as they scared the hell out of every American , many of whom have stayed home for the last 40 days , emerging only to buy toilet paper , but even then clad in masks and tiptoeing in fear .
@ @ @ @ @ @ @ Liberty University show dire need for impartial reporting But here are some facts : A recent Stanford University antibody study estimated the fatality rate from the virus is likely 0.1 % to 0.2 % .
The World Health Organization ( WHO ) had estimated that the death rate was 20 to 30 times higher and called for isolation policies .
On which version do you think the media focused ?
In New York City , the U.S. epicenter of the pandemic , the death rate for people 18 to 45 years old is @ @ @ @ @ @ @ in the population .
People aged 75 and older , though , have a death rate 80 times that .
For children under 18 , the rate of death is zero per 100,000 .
That ’ s zero .
More than half of the COVID-19 deaths in Europe occurred in long-term care or nursing-home facilities .
At least one-fifth of the deaths recorded in the U.S. so far have occurred there .
Nearly all the patients hospitalized for the coronavirus in New York City had underlying health conditions , according to a recent @ @ @ @ @ @ @ patients hospitalized within the Northwell Health system — which housed the most patients in the country throughout the pandemic — showed that 94 percent of patients had more than one disease other than COVID-19 , according to the Journal of the American Medical Association , ” Fox News reported .
The study found 42 % of the patients were overweight and 53 % had hypertension , and the others suffered from a variety of ailments .
Millions and millions of Americans have already been infected with the virus — even though the U.S. @ @ @ @ @ @ @ provided by Johns Hopkins , which says that 998,000 Americans have contracted the virus as of Tuesday .
An antibody study was conducted last week in New York City and found that 1 in 5 ( 21.2 % ) of residents have already been infected with the coronavirus .
There are 8.5 million people in New York City , so that would mean 1.8 million New Yorkers have had the virus .
At the time of the study , there were 16,249 deaths in the city attributed to COVID-19 , which means the @ @ @ @ @ @ @ % at the time — far lower than reports in the U.S. media .
Results of antibody survey last week in Los Angeles found as many as 442,000 Los Angeles County residents might have already been infected with the coronavirus by early April , a number far higher than the 8,000 cases confirmed at the time .
The survey suggested that the death rate from the virus could be as low as 0.18 % of COVID-19 patients , which means the actual death rate in the city is far lower than reported .
@ @ @ @ @ @ @ coronavirus may kill 70 times fewer patients than official UK death figures suggest , studies have shown.
” The Mail said a similar fatality rate — 0.19 % — was found in a study of residents in Helsinki , Finland .
A study , this one by Dr. Justin Silverman , estimates that there were 8.7 million coronavirus infections in the U.S. between March 8 and March 28 .
And as of April 17 , 10 % of Americans have been infected — which is roughly 33 million Americans .
The media has @ @ @ @ @ @ @ alarming Americans to the point where they voluntarily went along with shutting down the entire economy — a mistake that will likely reverberate for a decade or more .
Even as U.S. states begin to re-open — based on the data , which shows a far lower fatality rate than reported and a much wider spread of the virus — the media continue to report on what they deem frightening numbers over the deadly virus .
They aren ’ t , and it isn ’ t .
COVID-19 is a bad flu at @ @ @ @ @ @ @ held accountable for telling us otherwise before they knew the facts .
• Joseph Curl covered the White House and politics for a decade for The Washington Times .
He can be reached at josephcurl @ gmail.com and on Twitter @ josephcurl .

That’s not good. But it’s not as bad as the 2017-2018 flu season, when 80,000 -plus perished. And it’s a long cry from what all the experts were warning about just a few weeks ago: First, they predicted 1.7 million Americans dead; then they redid the models (this time apparently entering a few more “facts”) and said 100,000-240,000 dead.
SEE ALSO: Eighty percent of the population has little or nothing to fear from COVID-19
Now, a major model relied on by the White House Coronavirus Task Force predicts about 70,000 dead by the end of August.
And for that we shut down the U.S. economy?!
As the coronavirus swept across China, then Europe — then everywhere — the U.S. media breathlessly reported every terrifying number, almost gleefully. Their ratings soared, of course, as they scared the hell out of every American, many of whom have stayed home for the last 40 days, emerging only to buy toilet paper, but even then clad in masks and tiptoeing in fear.
SEE ALSO: Liberal media smears against Liberty University show dire need for impartial reporting
But here are some facts:
• Fatality Rate
A recent Stanford University antibody study estimated the fatality rate from the virus is likely 0.1% to 0.2%. The World Health Organization (WHO) had estimated that the death rate was 20 to 30 times higher and called for isolation policies. On which version do you think the media focused?
In New York City, the U.S. epicenter of the pandemic, the death rate for people 18 to 45 years old is 0.01%, or 10 per 100,000 in the population. People aged 75 and older, though, have a death rate 80 times that. For children under 18, the rate of death is zero per 100,000. That’s zero.
• Health and Age
More than half of the COVID-19 deaths in Europe occurred in long-term care or nursing-home facilities. At least one-fifth of the deaths recorded in the U.S. so far have occurred there.
Nearly all the patients hospitalized for the coronavirus in New York City had underlying health conditions, according to a recent study.
“Health records from 5,700 patients hospitalized within the Northwell Health system — which housed the most patients in the country throughout the pandemic — showed that 94 percent of patients had more than one disease other than COVID-19, according to the Journal of the American Medical Association,” Fox News reported.
The study found 42% of the patients were overweight and 53% had hypertension, and the others suffered from a variety of ailments.
• Far More Widespread
Millions and millions of Americans have already been infected with the virus — even though the U.S. media continues to report the low numbers provided by Johns Hopkins, which says that 998,000 Americans have contracted the virus as of Tuesday.
An antibody study was conducted last week in New York City and found that 1 in 5 (21.2%) of residents have already been infected with the coronavirus. There are 8.5 million people in New York City, so that would mean 1.8 million New Yorkers have had the virus.
At the time of the study, there were 16,249 deaths in the city attributed to COVID-19, which means the death rate in the city was 0.89% at the time — far lower than reports in the U.S. media.
Results of antibody survey last week in Los Angeles found as many as 442,000 Los Angeles County residents might have already been infected with the coronavirus by early April, a number far higher than the 8,000 cases confirmed at the time. The survey suggested that the death rate from the virus could be as low as 0.18% of COVID-19 patients, which means the actual death rate in the city is far lower than reported.
The Daily Mail reported Monday that “coronavirus may kill 70 times fewer patients than official UK death figures suggest, studies have shown.” The Mail said a similar fatality rate — 0.19% — was found in a study of residents in Helsinki, Finland.
A study, this one by Dr. Justin Silverman, estimates that there were 8.7 million coronavirus infections in the U.S. between March 8 and March 28. And as of April 17, 10% of Americans have been infected — which is roughly 33 million Americans.
The media has been hyping COVID-19 since Day One, alarming Americans to the point where they voluntarily went along with shutting down the entire economy — a mistake that will likely reverberate for a decade or more.
Even as U.S. states begin to re-open — based on the data, which shows a far lower fatality rate than reported and a much wider spread of the virus — the media continue to report on what they deem frightening numbers over the deadly virus.
They aren’t, and it isn’t. COVID-19 is a bad flu at worst. And the media should be held accountable for telling us otherwise before they knew the facts.
• Joseph Curl covered the White House and politics for a decade for The Washington Times. He can be reached at josephcurl@gmail.com and on Twitter @josephcurl.


australiannationalreview--2020-05-06--Bill Gates donates $10m to Australian trial of immune-boosting vaccine

Bill Gates has donated $ 10 million to an Australian trial of a vaccine that researchers hope will prevent severe cases of COVID-19 in at-risk groups such as healthcare workers and the elderly .
The billionaire Microsoft founder ’ s funding , the largest single donation to Australia ’ s COVID-19 research effort so far , comes after weeks of discussions between the Melbourne-based lead researcher , Professor Nigel Curtis , and Mr Gates ’ scientific advisers .
The study started on March 27 at the Royal Children ’ s Hospital in Melbourne and has so far recruited 2500 healthcare @ @ @ @ @ @ @ the Bill and Melinda Gates Foundation – which has so far donated about $ US250 million ( $ 388 million ) worldwide to COVID-19 research – made contact with his group about a month ago .
“ I then had numerous intense Zoom conversations with Bill Gates ’ scientific advisers , ” Professor Curtis said .
“ He has a whole system of advisers who check what you ’ re doing and help to optimise the design .
They were very helpful .
“ We had conversations most days , so it ’ @ @ @ @ @ @ @ , but this is the fastest time that Bill Gates ’ foundation has ever agreed to donate to a trial.
” Professor Curtis is hesitant to put a time frame on when the trial could produce results but said it would likely be at least three to six months .
“ We see it being used especially if there ’ s a second wave of COVID-19 in Australia or overseas , ” said Professor Curtis , a clinician and researcher at the Murdoch Children ’ s Research Institute and The University of Melbourne @ @ @ @ @ @ @ a proof of principle .
If we can show this boosts the immune system , this would be something off the shelf that can bridge the gap for other groups before coronavirus-specific vaccines come about.
” To assess the interaction between the BCG vaccine and COVID-19 , the trial relies on healthcare workers who have received the vaccine coming into contact with coronavirus cases .
That means the trial ’ s expansion in the coming weeks to 4000 healthcare workers in the Netherlands and Spain , where COVID-19 is currently more prominent than @ @ @ @ @ @ @ $ 10 million donation will also allow the trial to expand to Monash and Epworth hospitals in Melbourne and The Children ’ s Hospital at Westmead in Sydney , plus sites in Perth and Adelaide .
“ Generally the only risk is a small scar , ” Professor Curtis said .
“ The vaccine has been around almost 100 years .
About 130 million doses every year are given to children in countries where tuberculosis is still prominent … so production could be ramped up.
” Prime Minister Scott Morrison pledged $ 352 @ @ @ @ @ @ @ billion worldwide COVID-19 research fund arranged by the World Health Organisation .
Over the weekend , WHO director-general Tedros Adhanom Ghebreyesus and Professor Curtis ’ research team released a statement warning the BCG vaccine should only be used in clinical trials at the moment .
The stockpiling of anti-malaria drug hydroxychloroquine alarmed Australian authorities in March , after early but limited evidence of its effectiveness against COVID-19 led to US President Donald Trump spruiking its potential .
Trials have since shown the drug to be potentially harmful .

By Michael Fowler
Bill Gates has donated $10 million to an Australian trial of a vaccine that researchers hope will prevent severe cases of COVID-19 in at-risk groups such as healthcare workers and the elderly.
The billionaire Microsoft founder’s funding, the largest single donation to Australia’s COVID-19 research effort so far, comes after weeks of discussions between the Melbourne-based lead researcher, Professor Nigel Curtis, and Mr Gates’ scientific advisers.
The study started on March 27 at the Royal Children’s Hospital in Melbourne and has so far recruited 2500 healthcare workers across Australia.
Professor Curtis said the Bill and Melinda Gates Foundation – which has so far donated about $US250 million ($388 million) worldwide to COVID-19 research – made contact with his group about a month ago.
“I then had numerous intense Zoom conversations with Bill Gates’ scientific advisers,” Professor Curtis said. “He has a whole system of advisers who check what you’re doing and help to optimise the design. They were very helpful. “We had conversations most days, so it’s felt like a long few weeks, but this is the fastest time that Bill Gates’ foundation has ever agreed to donate to a trial.” Professor Curtis is hesitant to put a time frame on when the trial could produce results but said it would likely be at least three to six months.


australiannationalreview--2020-05-06--Tanzania president angry as pawpaw and goat test positive for coronavirus

President of Tanzania John Magufuli has cast doubt on the genuineness and quality of imported coronavirus testing kits after they returned positive results on samples taken from a goat and pawpaw .
Speaking at an event in Chato in northwestern Tanzania on Sunday , Magufuli alleged there were “ technical errors ” with the tests , hence he had instructed Tanzanian security forces to check the quality of the kits .
Reports say the country ’ s health officials had randomly obtained several non-human samples , including from pawpaw , a goat and a sheep , but had assigned them @ @ @ @ @ @ @ to Tanzania ’ s laboratory to test for the coronavirus Interestingly , the lab technicians had not had any clue about the origins of the samples submitted to them for testing .
To the surprise of the government , samples from the pawpaw and the goat tested positive for COVID-19 , making the president suspect that some people who were being tested positive for the deadly virus may not have been infected after all .
“ There is something happening .
I said before we should not accept that every aid is meant @ @ @ @ @ @ @ ” Magufuli said , adding the kits should be investigated .
Meanwhile , Magululi further announced that he had placed an order for a herbal treatment for the coronavirus touted by the president of Madagascar which some African countries seem to be in a mad rush to procure for the treatment of the coronavirus pandemic .
READ ALSO : “ Am I your mate ?
Is my rank your rank ?
” – Angry soldier and police clash over seniority ( video ) “ I have already written to Madagascar ’ s president @ @ @ @ @ @ @ to fetch the medicine so that Tanzania can also benefit from it , ” he said .
Called “ Covid Organics ” , the herbal concoction was prepared by the Malagasy Institute for Applied Research out of Artemisia , a plant cultivated on the Indian Ocean island of Madagascar .
Although there is no scientific evidence of the efficacy of “ Covid Organics ” , President Andry Rajoelina of Madagascar claimed that the remedy has already been used to cure some Madagascans of COVID-19 .

By News Metro
President of Tanzania John Magufuli has cast doubt on the genuineness and quality of imported coronavirus testing kits after they returned positive results on samples taken from a goat and pawpaw.
Speaking at an event in Chato in northwestern Tanzania on Sunday, Magufuli alleged there were “technical errors” with the tests, hence he had instructed Tanzanian security forces to check the quality of the kits.
Reports say the country’s health officials had randomly obtained several non-human samples, including from pawpaw, a goat and a sheep, but had assigned them human names and ages before submitting them to Tanzania’s laboratory to test for the coronavirus
Interestingly, the lab technicians had not had any clue about the origins of the samples submitted to them for testing.
To the surprise of the government, samples from the pawpaw and the goat tested positive for COVID-19, making the president suspect that some people who were being tested positive for the deadly virus may not have been infected after all.
“There is something happening. I said before we should not accept that every aid is meant to be good for this nation,” Magufuli said, adding the kits should be investigated.
Meanwhile, Magululi further announced that he had placed an order for a herbal treatment for the coronavirus touted by the president of Madagascar which some African countries seem to be in a mad rush to procure for the treatment of the coronavirus pandemic.
READ ALSO: “Am I your mate? Is my rank your rank?” – Angry soldier and police clash over seniority (video)
“I have already written to Madagascar’s president and we will soon dispatch a plane to fetch the medicine so that Tanzania can also benefit from it,” he said.
Called “Covid Organics”, the herbal concoction was prepared by the Malagasy Institute for Applied Research out of Artemisia, a plant cultivated on the Indian Ocean island of Madagascar.
Although there is no scientific evidence of the efficacy of “Covid Organics”, President Andry Rajoelina of Madagascar claimed that the remedy has already been used to cure some Madagascans of COVID-19.