principiascientificinternational--2020-07-06--Masks: A Review of Science Relevant to COVID-19 Social Policy

Masks and respirators will not work against COVID-19 .
There have been extensive randomized controlled trial ( RCT ) studies , and meta-analysis reviews of RCT studies , which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses , or respiratory illnesses believed to be transmitted by droplets and aerosol particles .
Furthermore , the relevant known physics and biology , which I review , are such that masks and respirators should not work .
It would be a paradox if masks and respirators worked , given what we know about viral respiratory diseases : @ @ @ @ @ @ @ particles ( < 2.5 μm ) , which are too fine to be blocked , and the minimum-infective dose is smaller than one aerosol particle .
The present paper about masks illustrates the degree to which governments , the mainstream media , and institutional propagandists can decide to operate in a science vacuum , or select only incomplete science that serves their interests .
Such recklessness is also certainly the case with the current global lockdown of over 1 billion people , an unprecedented experiment in medical and political history .
Here are @ @ @ @ @ @ @ literature that establishes that wearing surgical masks and respirators ( e.g.
, “ N95 ” ) does not reduce the risk of contracting a verified illness : Jacobs , J. L. et al .
( 2009 ) “ Use of surgical face masks to reduce the incidence of the common cold among health care workers in Japan : A randomized controlled trial , ” American Journal of Infection Control , Volume 37 , Issue 5 , 417 – 419. https : //www.ncbi.nlm.nih.gov/pubmed/19216002 N95-masked health-care workers ( HCW ) were significantly more likely to @ @ @ @ @ @ @ HCW was not demonstrated to provide benefit in terms of cold symptoms or getting colds .
Cowling , B. et al .
( 2010 ) “ Face masks to prevent transmission of influenza virus : A systematic review , ” Epidemiology and Infection , 138 ( 4 ) , 449-456. https : //www.cambridge.org/core/journals/epidemiology-and-infection/article/face-masks-to-prevent-transmission-of-influenza-virus-a-systematic- review/64D368496EBDE0AFCC6639CCC9D8BC05 None of the studies reviewed showed a benefit from wearing a mask , in either HCW or community members in households ( H ) .
See summary Tables 1 and 2 therein .
bin-Reza et al .
( 2012 @ @ @ @ @ @ @ respirators to prevent transmission of influenza : a systematic review of the scientific evidence , ” Influenza and Other Respiratory Viruses 6 ( 4 ) , 257–267 .
https : //onlinelibrary.wiley.com/doi/epdf/10.1111/j.1750-2659.2011.00307.x “ There were 17 eligible studies .
… None of the studies established a conclusive relationship between mask/respirator use and protection against influenza infection.
” Smith , J.D .
et al .
( 2016 ) “ Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection : a systematic review and meta-analysis , ” CMAJ Mar @ @ @ @ @ @ @ six clinical studies … .
In the meta-analysis of the clinical studies , we found no significant difference between N95 respirators and surgical masks in associated risk of ( a ) laboratory-confirmed respiratory infection , ( b ) influenza-like illness , or ( c ) reported work-place absenteeism.
” Offeddu , V. et al .
( 2017 ) “ Effectiveness of Masks and Respirators Against Respiratory Infections in Healthcare Workers : A Systematic Review and Meta-Analysis , ” Clinical Infectious Diseases , Volume 65 , Issue 11 , 1 December 2017 , Pages @ @ @ @ @ @ @ assessment of clinical outcomes was prone to bias .
Evidence of a protective effect of masks or respirators against verified respiratory infection ( VRI ) was not statistically significant ” ; as per Fig .
2c therein : Radonovich , L.J .
et al .
( 2019 ) “ N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel : A Randomized Clinical Trial , ” JAMA .
2019 ; 322 ( 9 ) : 824–833 .
https : //jamanetwork.com/journals/jama/fullarticle/2749214 “ Among 2862 randomized participants , 2371 completed the study and @ @ @ @ @ @ @ outpatient health care personnel , N95 respirators vs medical masks as worn by participants in this trial resulted in no significant difference in the incidence of laboratory-confirmed influenza.
” Long , Y. et al .
( 2020 ) “ Effectiveness of N95 respirators versus surgical masks against influenza : A systematic review and meta-analysis , ” J Evid Based Med .
2020 ; 1- 9. https : //onlinelibrary.wiley.com/doi/epdf/10.1111/jebm.12381 “ A total of six RCTs involving 9,171 participants were included .
There were no statistically significant differences in preventing laboratory-confirmed influenza , laboratory-confirmed respiratory @ @ @ @ @ @ @ and influenza-like illness using N95 respirators and surgical masks .
Meta-analysis indicated a protective effect of N95 respirators against laboratory-confirmed bacterial colonization ( RR = 0.58 , 95 % CI 0.43-0.78 ) .
The use of N95 respirators compared with surgical masks is not associated with a lower risk of laboratory-confirmed influenza.
” Conclusion Regarding That Masks Do Not Work No RCT study with verified outcome shows a benefit for HCW or community members in households to wearing a mask or respirator .
There is no such study .
There are no exceptions @ @ @ @ @ @ @ shows a benefit from a broad policy to wear masks in public ( more on this below ) .
Furthermore , if there were any benefit to wearing a mask , because of the blocking power against droplets and aerosol particles , then there should be more benefit from wearing a respirator ( N95 ) compared to a surgical mask , yet several large meta-analyses , and all the RCT , prove that there is no such relative benefit .
Masks and respirators do not work .
Precautionary Principle Turned on Its Head @ @ @ @ @ @ @ research , therefore , it is difficult to understand why public-health authorities are not consistently adamant about this established scientific result , since the distributed psychological , economic , and environmental harm from a broad recommendation to wear masks is significant , not to mention the unknown potential harm from concentration and distribution of pathogens on and from used masks .
In this case , public authorities would be turning the precautionary principle on its head ( see below ) .
Physics and Biology of Viral Respiratory Disease and of Why Masks Do @ @ @ @ @ @ @ masks can not possibly work , we must review established knowledge about viral respiratory diseases , the mechanism of seasonal variation of excess deaths from pneumonia and influenza , the aerosol mechanism of infectious disease transmission , the physics and chemistry of aerosols , and the mechanism of the so-called minimum-infective-dose .
In addition to pandemics that can occur anytime , in the temperate latitudes there is an extra burden of respiratory-disease mortality that is seasonal , and that is caused by viruses .
For example , see the review of influenza by @ @ @ @ @ @ @ This has been known for a long time , and the seasonal pattern is exceedingly regular .
( Publisher ’ s note : All links to source references to studies here forward are found at the end of this article . )
For example , see Figure 1 of Viboud ( 2010 ) , which has “ Weekly time series of the ratio of deaths from pneumonia and influenza to all deaths , based on the 122 cities surveillance in the US ( blue line ) .
The red line represents the expected @ @ @ @ @ @ @ activity , ” here : The seasonality of the phenomenon was largely not understood until a decade ago .
Until recently , it was debated whether the pattern arose primarily because of seasonal change in virulence of the pathogens , or because of seasonal change in susceptibility of the host ( such as from dry air causing tissue irritation , or diminished daylight causing vitamin deficiency or hormonal stress ) .
For example , see Dowell ( 2001 ) .
In a landmark study , Shaman et al .
( 2010 ) showed @ @ @ @ @ @ @ mortality can be explained quantitatively on the sole basis of absolute humidity , and its direct controlling impact on transmission of airborne pathogens .
Lowen et al .
( 2007 ) demonstrated the phenomenon of humidity-dependent airborne-virus virulence in actual disease transmission between guinea pigs , and discussed potential underlying mechanisms for the measured controlling effect of humidity .
The underlying mechanism is that the pathogen-laden aerosol particles or droplets are neutralized within a half-life that monotonically and significantly decreases with increasing ambient humidity .
This is based on the seminal work of @ @ @ @ @ @ @ showed that viral-pathogen-carrying droplets were inactivated within shorter and shorter times , as ambient humidity was increased .
Harper argued that the viruses themselves were made inoperative by the humidity ( “ viable decay ” ) , however , he admitted that the effect could be from humidity-enhanced physical removal or sedimentation of the droplets ( “ physical loss ” ) : “ Aerosol viabilities reported in this paper are based on the ratio of virus titre to radioactive count in suspension and cloud samples , and can be criticized on the ground @ @ @ @ @ @ @ physically identical.
” The latter ( “ physical loss ” ) seems more plausible to me , since humidity would have a universal physical effect of causing particle/droplet growth and sedimentation , and all tested viral pathogens have essentially the same humidity-driven “ decay.
” Furthermore , it is difficult to understand how a virion ( of all virus types ) in a droplet would be molecularly or structurally attacked or damaged by an increase in ambient humidity .
A “ virion ” is the complete , infective form of a virus outside @ @ @ @ @ @ @ of RNA or DNA and a capsid .
The actual mechanism of such humidity-driven intra-droplet “ viable decay ” of a virion has not been explained or studied .
In any case , the explanation and model of Shaman et al .
( 2010 ) is not dependent on the particular mechanism of the humidity-driven decay of virions in aerosol/droplets .
Shaman ’ s quantitatively demonstrated model of seasonal regional viral epidemiology is valid for either mechanism ( or combination of mechanisms ) , whether “ viable decay ” or “ physical loss.
@ @ @ @ @ @ @ al .
is not merely some academic point .
Rather , it has profound health-policy implications , which have been entirely ignored or overlooked in the current coronavirus pandemic .
In particular , Shaman ’ s work necessarily implies that , rather than being a fixed number ( dependent solely on the spatial-temporal structure of social interactions in a completely susceptible population , and on the viral strain ) , the epidemic ’ s basic reproduction number ( R0 ) is highly or predominantly dependent on ambient absolute humidity .
For a definition @ @ @ @ @ @ @ ) : R0 is “ the average number of secondary infections produced by a typical case of an infection in a population where everyone is susceptible.
” The average R0 for influenza is said to be 1.28 ( 1.19–1.37 ) ; see the comprehensive review by Biggerstaff et al .
( 2014 ) .
In fact , Shaman et al .
showed that R0 must be understood to seasonally vary between humid-summer values of just larger than “ 1 ” and dry-winter values typically as large as “ 4 ” ( for example @ @ @ @ @ @ @ In other words , the seasonal infectious viral respiratory diseases that plague temperate latitudes every year go from being intrinsically mildly contagious to virulently contagious , due simply to the bio-physical mode of transmission controlled by atmospheric humidity , irrespective of any other consideration .
Therefore , all the epidemiological mathematical modeling of the benefits of mediating policies ( such as social distancing ) , which assumes humidity-independent R0 values , has a large likelihood of being of little value , on this basis alone .
For studies about modeling and regarding mediation @ @ @ @ @ @ @ see Coburn ( 2009 ) and Tracht ( 2010 ) .
To put it simply , the “ second wave ” of an epidemic is not a consequence of human sin regarding mask wearing and hand shaking .
Rather , the “ second wave ” is an inescapable consequence of an air-dryness-driven many-fold increase in disease contagiousness , in a population that has not yet attained immunity .
If my view of the mechanism is correct ( i.e.
, “ physical loss ” ) , then Shaman ’ s work further necessarily implies @ @ @ @ @ @ @ R0 ) arises from small aerosol particles fluidly suspended in the air ; as opposed to large droplets that are quickly gravitationally removed from the air .
Such small aerosol particles fluidly suspended in air , of biological origin , are of every variety and are everywhere , including down to virion-sizes ( Despres , 2012 ) .
It is not entirely unlikely that viruses can thereby be physically transported over inter-continental distances ( e.g.
, Hammond , 1989 ) .
More to the point , indoor airborne virus concentrations have been shown @ @ @ @ @ @ @ health centers , and on-board airplanes ) primarily as aerosol particles of diameters smaller than 2.5 μm , such as in the work of Yang et al .
( 2011 ) : “ Half of the 16 samples were positive , and their total virus −3 concentrations ranged from 5800 to 37 000 genome copies m .
On average , 64 per cent of the viral genome copies were associated with fine particles smaller than 2.5 μm , which can remain suspended for hours .
Modeling of virus concentrations indoors suggested a source @ @ @ @ @ @ @ genome copies m−3 air h−1 and a deposition flux onto surfaces of 13 ± 7 genome copies m−2 h−1 by Brownian motion .
Over one hour , the inhalation dose was estimated to be 30 ± 18 median tissue culture infectious dose ( TCID50 ) , adequate to induce infection .
These results provide quantitative support for the idea that the aerosol route could be an important mode of influenza transmission.
” Such small particles ( < 2.5 μm ) are part of air fluidity , are not subject to gravitational sedimentation , @ @ @ @ @ @ @ inertial impact .
This means that the slightest ( even momentary ) facial misfit of a mask or respirator renders the design filtration norm of the mask or respirator entirely irrelevant .
In any case , the filtration material itself of N95 ( average pore size ~0.3−0.5 μm ) does not block virion penetration , not to mention surgical masks .
For example , see Balazy et al .
( 2006 ) .
Mask stoppage efficiency and host inhalation are only half of the equation , however , because the minimal infective dose @ @ @ @ @ @ @ .
For example , if a large number of pathogen-laden particles must be delivered to the lung within a certain time for the illness to take hold , then partial blocking by any mask or cloth can be enough to make a significant difference .
On the other hand , if the MID is amply surpassed by the virions carried in a single aerosol particle able to evade mask-capture , then the mask is of no practical utility , which is the case .
Yezli and Otter ( 2011 ) , in their @ @ @ @ @ @ @ relevant features : • Most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility • It is believed that a single virion can be enough to induce illness in the host • The 50-percent probability MID ( “ TCID50 ” ) has variably been found to be in the range 100−1000 virions • There are typically 10 to 3rd power − 10 to 7th power virions per aerolized influenza droplet with diameter 1 μm − 10 μm • The 50-percent probability MID easily fits into a single @ @ @ @ @ @ @ classic description of dose-response assessment is provided by Haas ( 1993 ) .
• Zwart et al .
( 2009 ) provided the first laboratory proof , in a virus-insect system , that the action of a single virion can be sufficient to cause disease .
• Baccam et al .
( 2006 ) calculated from empirical data that , with influenza A in humans , “ we estimate that after a delay of ~6 h , infected cells begin producing influenza virus and continue to do so for ~5 h. The average @ @ @ @ @ @ @ , and the half-life of free infectious virus is ~3 h. We calculated the [ in-body ] basic reproductive number , R0 , which indicated that a single infected cell could produce ~22 new productive infections.
” • Brooke et al .
( 2013 ) showed that , contrary to prior modeling assumptions , although not all influenza-A-infected cells in the human body produce infectious progeny ( virions ) , nonetheless , 90 percent of infected cell are significantly impacted , rather than simply surviving unharmed .
All of this to say that @ @ @ @ @ @ @ it always does , irrespective of the mask ) , then you are going to be infected .
Masks can not possibly work .
It is not surprising , therefore , that no bias-free study has ever found a benefit from wearing a mask or respirator in this application .
Therefore , the studies that show partial stopping power of masks , or that show that masks can capture many large droplets produced by a sneezing or coughing mask-wearer , in light of the above-described features of the problem , are irrelevant .
@ @ @ @ @ @ @ : Leung ( 2020 ) , Davies ( 2013 ) , Lai ( 2012 ) , and Sande ( 2008 ) .
Why There Can Never Be an Empirical Test of a Nation-Wide Mask-Wearing Policy As mentioned above , no study exists that shows a benefit from a broad policy to wear masks in public .
There is good reason for this .
It would be impossible to obtain unambiguous and bias-free results [ because ] : • Any benefit from mask-wearing would have to be a small effect , since undetected in @ @ @ @ @ @ @ by the larger effects , notably the large effect from changing atmospheric humidity .
• Mask compliance and mask adjustment habits would be unknown .
• Mask-wearing is associated ( correlated ) with several other health behaviors ; see Wada ( 2012 ) .
• The results would not be transferable , because of differing cultural habits .
• Compliance is achieved by fear , and individuals can habituate to fear-based propaganda , and can have disparate basic responses .
• Monitoring and compliance measurement are near-impossible , and subject to large errors @ @ @ @ @ @ @ surveys ) is notoriously biased , because individuals have the self-interested belief that their efforts are useful .
• Progression of the epidemic is not verified with reliable tests on large population samples , and generally relies on non-representative hospital visits or admissions .
• Several different pathogens ( viruses and strains of viruses ) causing respiratory illness generally act together , in the same population and/or in individuals , and are not resolved , while having different epidemiological characteristics .
Many potential harms may arise from broad public policies to wear masks @ @ @ @ @ @ @ : • Do used and loaded masks become sources of enhanced transmission , for the wearer and others ?
• Do masks become collectors and retainers of pathogens that the mask wearer would otherwise avoid when breathing without a mask ?
• Are large droplets captured by a mask atomized or aerolized into breathable components ?
Can virions escape an evaporating droplet stuck to a mask fiber ?
• What are the dangers of bacterial growth on a used and loaded mask ?
• How do pathogen-laden droplets interact with environmental dust and @ @ @ @ @ @ @ What are long-term health effects on HCW , such as headaches , arising from impeded breathing ?
• Are there negative social consequences to a masked society ?
• Are there negative psychological consequences to wearing a mask , as a fear-based behavioral modification ?
• What are the environmental consequences of mask manufacturing and disposal ?
• Do the masks shed fibers or substances that are harmful when inhaled ?
By making mask-wearing recommendations and policies for the general public , or by expressly condoning the practice , governments have both ignored @ @ @ @ @ @ @ of following the precautionary principle .
In an absence of knowledge , governments should not make policies that have a hypothetical potential to cause harm .
The government has an onus barrier before it instigates a broad social-engineering intervention , or allows corporations to exploit fear-based sentiments .
Furthermore , individuals should know that there is no known benefit arising from wearing a mask in a viral respiratory illness epidemic , and that scientific studies have shown that any benefit must be residually small , compared to other and determinative factors .
Otherwise @ @ @ @ @ @ @ funded science ?
The present paper about masks illustrates the degree to which governments , the mainstream media , and institutional propagandists can decide to operate in a science vacuum , or select only incomplete science that serves their interests .
Such recklessness is also certainly the case with the current global lockdown of over 1 billion people , an unprecedented experiment in medical and political history .
Denis G. Rancourt is a researcher at the Ontario Civil Liberties Association ( OCLA.ca ) and is formerly a tenured professor at the University of @ @ @ @ @ @ @ originally published at Rancourt ’ s account on ResearchGate.net .
As of June 5 , 2020 , this paper was removed from his profile by its administrators at Researchgate.net/profile/D_Rancourt .
At Rancourt ’ s blog ActivistTeacher.blogspot.com , he recounts the notification and responses he received from ResearchGate.net and states , “ This is censorship of my scientific work like I have never experienced before.
” The original April 2020 white paper in .pdf format is available here , complete with charts that have not been reprinted in the Reader print or web versions @ @ @ @ @ @ @ : Sometimes You Just Got ta Wear the Stupid Baccam , P. et al .
( 2006 ) “ Kinetics of Influenza A Virus Infection in Humans ” , Journal of Virology Jul 2006 , 80 ( 15 ) 7590-7599 ; DOI : 10.1128/JVI.01623-05 https : //jvi.asm.org/content/80/15/7590 Balazy et al .
( 2006 ) “ Do N95 respirators provide 95 % protection level against airborne viruses , and how adequate are surgical masks ?
” , American Journal of Infection Control , Volume 34 , Issue 2 , March 2006 , Pages 51-57.
@ @ @ @ @ @ @ rep=rep1 & type=pdf Biggerstaff , M. et al .
( 2014 ) “ Estimates of the reproduction number for seasonal , pandemic , and zoonotic influenza : a systematic review of the literature ” , BMC Infect Dis 14 , 480 ( 2014 ) .
https : //doi.org/10.1186/1471-2334-14-480 Brooke , C. B. et al .
( 2013 ) “ Most Influenza A Virions Fail To Express at Least One Essential Viral Protein ” , Journal of Virology Feb 2013 , 87 ( 6 ) 3155-3162 ; DOI : 10.1128/JVI.02284-12 https : //jvi.asm.org/content/87/6/3155 Coburn @ @ @ @ @ @ @ 2009 ) “ Modeling influenza epidemics and pandemics : insights into the future of swine flu ( H1N1 ) ” , BMC Med 7 , 30. https : //doi.org/10.1186/1741-7015-7-30 Davies , A. et al .
( 2013 ) “ Testing the Efficacy of Homemade Masks : Would They Protect in an Influenza Pandemic ?
” , Disaster Medicine and Public Health Preparedness , Available on CJO 2013 doi:10.1017/dmp.2013.43 http : //journals.cambridge.org/abstract_S1935789313000438 Despres , V. R. et al .
( 2012 ) “ Primary biological aerosol particles in the atmosphere : a review ” @ @ @ @ @ @ @ Meteorology , 64:1 , 15598 , DOI : 10.3402/tellusb.v64i0.15598 https : //doi.org/10.3402/tellusb.v64i0.15598 Dowell , S. F. ( 2001 ) “ Seasonal variation in host susceptibility and cycles of certain infectious diseases ” , Emerg Infect Dis .
2001 ; 7 ( 3 ) :369–374 .
doi:10.3201/eid0703.010301 https : //www.ncbi.nlm.nih.gov/pmc/articles/PMC2631809/ Hammond , G. W. et al .
( 1989 ) “ Impact of Atmospheric Dispersion and Transport of Viral Aerosols on the Epidemiology of Influenza ” , Reviews of Infectious Diseases , Volume 11 , Issue 3 , May 1989 , Pages 494–497 , @ @ @ @ @ @ @ et al .
( 1993 ) “ Risk Assessment of Virus in Drinking Water ” , Risk Analysis , 13 : 545-552. doi:10.1111/j.1539-6924.1993.tb00013.x https : //doi.org/10.1111/j.1539-6924.1993.tb00013.x HealthKnowlege-UK ( 2020 ) “ Charter 1a – Epidemiology : Epidemic theory ( effective & basic reproduction numbers , epidemic thresholds ) & techniques for analysis of infectious disease data ( construction & use of epidemic curves , generation numbers , exceptional reporting & identification of significant clusters ) ” , HealthKnowledge.org.uk , accessed on 2020-04-10. https : //www.healthknowledge.org.uk/public-health-textbook/research-methods/1a- epidemiology/epidemic-theory Lai , A. C. K. et al @ @ @ @ @ @ @ facemasks to reduce exposure hazards for airborne infections among general populations ” , J. R. Soc .
Interface .
9938–948 http : //doi.org/10.1098/rsif.2011.0537 Leung , N.H.L .
et al .
( 2020 ) “ Respiratory virus shedding in exhaled breath and efficacy of face masks ” , Nature Medicine ( 2020 ) .
https : //doi.org/10.1038/s41591-020-0843-2 Lowen , A. C. et al .
( 2007 ) “ Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature ” , PLoS Pathog 3 ( 10 ) : e151 .
https : //doi.org/10.1371/journal.ppat.0030151 Sande , @ @ @ @ @ @ @ ( 2008 ) “ Professional and Home-Made Face Masks Reduce Exposure to Respiratory Infections among the General Population ” , PLoS ONE 3 ( 7 ) : e2618 .
doi:10.1371/journal.pone.0002618 https : //doi.org/10.1371/journal.pone.0002618 Shaman , J. et al .
( 2010 ) “ Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States ” , PLoS Biol 8 ( 2 ) : e1000316 .
https : //doi.org/10.1371/journal.pbio.1000316 Tracht , S. M. et al .
( 2010 ) “ Mathematical Modeling of the Effectiveness of Facemasks in Reducing the Spread of @ @ @ @ @ @ @ , PLoS ONE 5 ( 2 ) : e9018 .
doi:10.1371/journal.pone.0009018 https : //doi.org/10.1371/journal.pone.0009018 Viboud C. et al .
( 2010 ) “ Preliminary Estimates of Mortality and Years of Life Lost Associated with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons ” , PLoS Curr .
2010 ; 2 : RRN1153 .
Published 2010 Mar 20. doi:10.1371/currents.rrn1153 https : //www.ncbi.nlm.nih.gov/pmc/articles/PMC2843747/ Wada , K. et al .
( 2012 ) “ Wearing face masks in public during the influenza season may reflect other positive hygiene practices in Japan @ @ @ @ @ @ @ 1065 ( 2012 ) .
https : //doi.org/10.1186/1471-2458-12-1065 Yang , W. et al .
( 2011 ) “ Concentrations and size distributions of airborne influenza A viruses measured indoors at a health centre , a day-care centre and on aeroplanes ” , Journal of the Royal Society , Interface .
2011 Aug ; 8 ( 61 ) :1176-1184 .
DOI : 10.1098/rsif.2010.0686 .
https : //royalsocietypublishing.org/doi/10.1098/rsif.2010.0686 Yezli , S. , Otter , J.A .
( 2011 ) “ Minimum Infective Dose of the Major Human Respiratory and Enteric Viruses Transmitted Through Food and @ @ @ @ @ @ @ 3 , 1–30 .
https : //doi.org/10.1007/s12560-011-9056-7 Zwart , M. P. et al .
( 2009 ) “ An experimental test of the independent action hypothesis in virus– insect pathosystems ” , Proc .
R. Soc .
B .
2762233–2242 http : //doi.org/10.1098/rspb.2009.0064 About the author : Denis Rancourt PhD is a former professor of physics at the University of Ottawa .
Known for applications of physics education research .
Published over 100 scientific articles in the areas of metal physics , materials science , measurement methods , and earth and environmental science @ @ @ @ @ @ @ Author of the book Hierarchy and Free Expression in the Fight Against Racism .
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Masks: A Review of Science Relevant to COVID-19 Social Policy
Written by Denis G. Rancourt, PhD
Masks and respirators will not work against COVID-19. There have been extensive randomized controlled trial (RCT) studies, and meta-analysis reviews of RCT studies, which all show that masks and respirators do not work to prevent respiratory influenza-like illnesses, or respiratory illnesses believed to be transmitted by droplets and aerosol particles.
Furthermore, the relevant known physics and biology, which I review, are such that masks and respirators should not work. It would be a paradox if masks and respirators worked, given what we know about viral respiratory diseases: The main transmission path is long-residence-time aerosol particles (< 2.5 μm), which are too fine to be blocked, and the minimum-infective dose is smaller than one aerosol particle.
The present paper about masks illustrates the degree to which governments, the mainstream media, and institutional propagandists can decide to operate in a science vacuum, or select only incomplete science that serves their interests. Such recklessness is also certainly the case with the current global lockdown of over 1 billion people, an unprecedented experiment in medical and political history.
(From Words from the Publisher: “We pledge to publish all letters, guest commentaries, or studies refuting [Rancourt’s] general premise that this mask-wearing culture and shaming could be more harmful than helpful. Please send your feedback to info@rcreader.com.”)
Review of the Medical Literature
Here are key anchor points to the extensive scientific literature that establishes that wearing surgical masks and respirators (e.g., “N95”) does not reduce the risk of contracting a verified illness:
Jacobs, J. L. et al. (2009) “Use of surgical face masks to reduce the incidence of the common cold among health care workers in Japan: A randomized controlled trial,” American Journal of Infection Control, Volume 37, Issue 5, 417 – 419. https://www.ncbi.nlm.nih.gov/pubmed/19216002
N95-masked health-care workers (HCW) were significantly more likely to experience headaches. Face mask use in HCW was not demonstrated to provide benefit in terms of cold symptoms or getting colds.
Cowling, B. et al. (2010) “Face masks to prevent transmission of influenza virus: A systematic review,” Epidemiology and Infection, 138(4), 449-456. https://www.cambridge.org/core/journals/epidemiology-and-infection/article/face-masks-to-prevent-transmission-of-influenza-virus-a-systematic- review/64D368496EBDE0AFCC6639CCC9D8BC05
None of the studies reviewed showed a benefit from wearing a mask, in either HCW or community members in households (H). See summary Tables 1 and 2 therein.
bin-Reza et al. (2012) “The use of masks and respirators to prevent transmission of influenza: a systematic review of the scientific evidence,” Influenza and Other Respiratory Viruses 6(4), 257–267. https://onlinelibrary.wiley.com/doi/epdf/10.1111/j.1750-2659.2011.00307.x
“There were 17 eligible studies. … None of the studies established a conclusive relationship between mask/respirator use and protection against influenza infection.”
Smith, J.D. et al. (2016) “Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis,” CMAJ Mar 2016 https://www.cmaj.ca/content/188/8/567
“We identified six clinical studies … . In the meta-analysis of the clinical studies, we found no significant difference between N95 respirators and surgical masks in associated risk of (a) laboratory-confirmed respiratory infection, (b) influenza-like illness, or (c) reported work-place absenteeism.”
Offeddu, V. et al. (2017) “Effectiveness of Masks and Respirators Against Respiratory Infections in Healthcare Workers: A Systematic Review and Meta-Analysis,” Clinical Infectious Diseases, Volume 65, Issue 11, 1 December 2017, Pages 1934–1942, https://academic.oup.com/cid/article/65/11/1934/4068747
“Self-reported assessment of clinical outcomes was prone to bias. Evidence of a protective effect of masks or respirators against verified respiratory infection (VRI) was not statistically significant”; as per Fig. 2c therein:
Radonovich, L.J. et al. (2019) “N95 Respirators vs Medical Masks for Preventing Influenza Among Health Care Personnel: A Randomized Clinical Trial,” JAMA. 2019; 322(9): 824–833. https://jamanetwork.com/journals/jama/fullarticle/2749214
“Among 2862 randomized participants, 2371 completed the study and accounted for 5180 HCW-seasons. … Among outpatient health care personnel, N95 respirators vs medical masks as worn by participants in this trial resulted in no significant difference in the incidence of laboratory-confirmed influenza.”
Long, Y. et al. (2020) “Effectiveness of N95 respirators versus surgical masks against influenza: A systematic review and meta-analysis,” J Evid Based Med. 2020; 1- 9. https://onlinelibrary.wiley.com/doi/epdf/10.1111/jebm.12381
“A total of six RCTs involving 9,171 participants were included. There were no statistically significant differences in preventing laboratory-confirmed influenza, laboratory-confirmed respiratory viral infections, laboratory-confirmed respiratory infection, and influenza-like illness using N95 respirators and surgical masks. Meta-analysis indicated a protective effect of N95 respirators against laboratory-confirmed bacterial colonization (RR = 0.58, 95{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} CI 0.43-0.78). The use of N95 respirators compared with surgical masks is not associated with a lower risk of laboratory-confirmed influenza.”
Conclusion Regarding That Masks Do Not Work
No RCT study with verified outcome shows a benefit for HCW or community members in households to wearing a mask or respirator. There is no such study. There are no exceptions.
Likewise, no study exists that shows a benefit from a broad policy to wear masks in public (more on this below).
Furthermore, if there were any benefit to wearing a mask, because of the blocking power against droplets and aerosol particles, then there should be more benefit from wearing a respirator (N95) compared to a surgical mask, yet several large meta-analyses, and all the RCT, prove that there is no such relative benefit.
Masks and respirators do not work.
Precautionary Principle Turned on Its Head with Masks
In light of the medical research, therefore, it is difficult to understand why public-health authorities are not consistently adamant about this established scientific result, since the distributed psychological, economic, and environmental harm from a broad recommendation to wear masks is significant, not to mention the unknown potential harm from concentration and distribution of pathogens on and from used masks. In this case, public authorities would be turning the precautionary principle on its head (see below).
Physics and Biology of Viral Respiratory Disease and of Why Masks Do Not Work
In order to understand why masks cannot possibly work, we must review established knowledge about viral respiratory diseases, the mechanism of seasonal variation of excess deaths from pneumonia and influenza, the aerosol mechanism of infectious disease transmission, the physics and chemistry of aerosols, and the mechanism of the so-called minimum-infective-dose.
In addition to pandemics that can occur anytime, in the temperate latitudes there is an extra burden of respiratory-disease mortality that is seasonal, and that is caused by viruses. For example, see the review of influenza by Paules and Subbarao (2017). This has been known for a long time, and the seasonal pattern is exceedingly regular. (Publisher’s note: All links to source references to studies here forward are found at the end of this article.)
For example, see Figure 1 of Viboud (2010), which has “Weekly time series of the ratio of deaths from pneumonia and influenza to all deaths, based on the 122 cities surveillance in the US (blue line). The red line represents the expected baseline ratio in the absence of influenza activity,” here:
The seasonality of the phenomenon was largely not understood until a decade ago. Until recently, it was debated whether the pattern arose primarily because of seasonal change in virulence of the pathogens, or because of seasonal change in susceptibility of the host (such as from dry air causing tissue irritation, or diminished daylight causing vitamin deficiency or hormonal stress). For example, see Dowell (2001).
In a landmark study, Shaman et al. (2010) showed that the seasonal pattern of extra respiratory-disease mortality can be explained quantitatively on the sole basis of absolute humidity, and its direct controlling impact on transmission of airborne pathogens.
Lowen et al. (2007) demonstrated the phenomenon of humidity-dependent airborne-virus virulence in actual disease transmission between guinea pigs, and discussed potential underlying mechanisms for the measured controlling effect of humidity.
The underlying mechanism is that the pathogen-laden aerosol particles or droplets are neutralized within a half-life that monotonically and significantly decreases with increasing ambient humidity. This is based on the seminal work of Harper (1961). Harper experimentally showed that viral-pathogen-carrying droplets were inactivated within shorter and shorter times, as ambient humidity was increased.
Harper argued that the viruses themselves were made inoperative by the humidity (“viable decay”), however, he admitted that the effect could be from humidity-enhanced physical removal or sedimentation of the droplets (“physical loss”): “Aerosol viabilities reported in this paper are based on the ratio of virus titre to radioactive count in suspension and cloud samples, and can be criticized on the ground that test and tracer materials were not physically identical.”
The latter (“physical loss”) seems more plausible to me, since humidity would have a universal physical effect of causing particle/droplet growth and sedimentation, and all tested viral pathogens have essentially the same humidity-driven “decay.” Furthermore, it is difficult to understand how a virion (of all virus types) in a droplet would be molecularly or structurally attacked or damaged by an increase in ambient humidity. A “virion” is the complete, infective form of a virus outside a host cell, with a core of RNA or DNA and a capsid. The actual mechanism of such humidity-driven intra-droplet “viable decay” of a virion has not been explained or studied.
In any case, the explanation and model of Shaman et al. (2010) is not dependent on the particular mechanism of the humidity-driven decay of virions in aerosol/droplets. Shaman’s quantitatively demonstrated model of seasonal regional viral epidemiology is valid for either mechanism (or combination of mechanisms), whether “viable decay” or “physical loss.”
The breakthrough achieved by Shaman et al. is not merely some academic point. Rather, it has profound health-policy implications, which have been entirely ignored or overlooked in the current coronavirus pandemic.
In particular, Shaman’s work necessarily implies that, rather than being a fixed number (dependent solely on the spatial-temporal structure of social interactions in a completely susceptible population, and on the viral strain), the epidemic’s basic reproduction number (R0) is highly or predominantly dependent on ambient absolute humidity.
For a definition of R0, see HealthKnowlege-UK (2020): R0 is “the average number of secondary infections produced by a typical case of an infection in a population where everyone is susceptible.” The average R0 for influenza is said to be 1.28 (1.19–1.37); see the comprehensive review by Biggerstaff et al. (2014).
In fact, Shaman et al. showed that R0 must be understood to seasonally vary between humid-summer values of just larger than “1” and dry-winter values typically as large as “4” (for example, see their Table 2). In other words, the seasonal infectious viral respiratory diseases that plague temperate latitudes every year go from being intrinsically mildly contagious to virulently contagious, due simply to the bio-physical mode of transmission controlled by atmospheric humidity, irrespective of any other consideration.
Therefore, all the epidemiological mathematical modeling of the benefits of mediating policies (such as social distancing), which assumes humidity-independent R0 values, has a large likelihood of being of little value, on this basis alone. For studies about modeling and regarding mediation effects on the effective reproduction number, see Coburn (2009) and Tracht (2010).
To put it simply, the “second wave” of an epidemic is not a consequence of human sin regarding mask wearing and hand shaking. Rather, the “second wave” is an inescapable consequence of an air-dryness-driven many-fold increase in disease contagiousness, in a population that has not yet attained immunity.
If my view of the mechanism is correct (i.e., “physical loss”), then Shaman’s work further necessarily implies that the dryness-driven high transmissibility (large R0) arises from small aerosol particles fluidly suspended in the air; as opposed to large droplets that are quickly gravitationally removed from the air.
Such small aerosol particles fluidly suspended in air, of biological origin, are of every variety and are everywhere, including down to virion-sizes (Despres, 2012). It is not entirely unlikely that viruses can thereby be physically transported over inter-continental distances (e.g., Hammond, 1989).
More to the point, indoor airborne virus concentrations have been shown to exist (in day-care facilities, health centers, and on-board airplanes) primarily as aerosol particles of diameters smaller than 2.5 μm, such as in the work of Yang et al. (2011):
“Half of the 16 samples were positive, and their total virus −3 concentrations ranged from 5800 to 37 000 genome copies m . On average, 64 per cent of the viral genome copies were associated with fine particles smaller than 2.5 μm, which can remain suspended for hours. Modeling of virus concentrations indoors suggested a source strength of 1.6 ± 1.2 × 105 genome copies m−3 air h−1 and a deposition flux onto surfaces of 13 ± 7 genome copies m−2 h−1 by Brownian motion. Over one hour, the inhalation dose was estimated to be 30 ± 18 median tissue culture infectious dose (TCID50), adequate to induce infection. These results provide quantitative support for the idea that the aerosol route could be an important mode of influenza transmission.”
Such small particles (< 2.5 μm) are part of air fluidity, are not subject to gravitational sedimentation, and would not be stopped by long-range inertial impact. This means that the slightest (even momentary) facial misfit of a mask or respirator renders the design filtration norm of the mask or respirator entirely irrelevant. In any case, the filtration material itself of N95 (average pore size ~0.3−0.5 μm) does not block virion penetration, not to mention surgical masks. For example, see Balazy et al. (2006).
Mask stoppage efficiency and host inhalation are only half of the equation, however, because the minimal infective dose (MID) must also be considered. For example, if a large number of pathogen-laden particles must be delivered to the lung within a certain time for the illness to take hold, then partial blocking by any mask or cloth can be enough to make a significant difference.
On the other hand, if the MID is amply surpassed by the virions carried in a single aerosol particle able to evade mask-capture, then the mask is of no practical utility, which is the case.
Yezli and Otter (2011), in their review of the MID, point out relevant features:
Most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility It is believed that a single virion can be enough to induce illness in the host The 50-percent probability MID (“TCID50”) has variably been found to be in the range 100−1000 virions There are typically 10 to 3rd power − 10 to 7th power virions per aerolized influenza droplet with diameter 1 μm − 10 μm The 50-percent probability MID easily fits into a single (one) aerolized droplet For further background: A classic description of dose-response assessment is provided by Haas (1993). Zwart et al. (2009) provided the first laboratory proof, in a virus-insect system, that the action of a single virion can be sufficient to cause disease. Baccam et al. (2006) calculated from empirical data that, with influenza A in humans,“we estimate that after a delay of ~6 h, infected cells begin producing influenza virus and continue to do so for ~5 h. The average lifetime of infected cells is ~11 h, and the half-life of free infectious virus is ~3 h. We calculated the [in-body] basic reproductive number, R0, which indicated that a single infected cell could produce ~22 new productive infections.” Brooke et al. (2013) showed that, contrary to prior modeling assumptions, although not all influenza-A-infected cells in the human body produce infectious progeny (virions), nonetheless, 90 percent of infected cell are significantly impacted, rather than simply surviving unharmed.
All of this to say that: if anything gets through (and it always does, irrespective of the mask), then you are going to be infected. Masks cannot possibly work. It is not surprising, therefore, that no bias-free study has ever found a benefit from wearing a mask or respirator in this application.
Therefore, the studies that show partial stopping power of masks, or that show that masks can capture many large droplets produced by a sneezing or coughing mask-wearer, in light of the above-described features of the problem, are irrelevant. For example, such studies as these: Leung (2020), Davies (2013), Lai (2012), and Sande (2008).
Why There Can Never Be an Empirical Test of a Nation-Wide Mask-Wearing Policy
As mentioned above, no study exists that shows a benefit from a broad policy to wear masks in public. There is good reason for this. It would be impossible to obtain unambiguous and bias-free results [because]:
Any benefit from mask-wearing would have to be a small effect, since undetected in controlled experiments, which would be swamped by the larger effects, notably the large effect from changing atmospheric humidity. Mask compliance and mask adjustment habits would be unknown. Mask-wearing is associated (correlated) with several other health behaviors; see Wada (2012). The results would not be transferable, because of differing cultural habits. Compliance is achieved by fear, and individuals can habituate to fear-based propaganda, and can have disparate basic responses. Monitoring and compliance measurement are near-impossible, and subject to large errors. Self-reporting (such as in surveys) is notoriously biased, because individuals have the self-interested belief that their efforts are useful. Progression of the epidemic is not verified with reliable tests on large population samples, and generally relies on non-representative hospital visits or admissions. Several different pathogens (viruses and strains of viruses) causing respiratory illness generally act together, in the same population and/or in individuals, and are not resolved, while having different epidemiological characteristics.
Unknown Aspects of Mask Wearing
Many potential harms may arise from broad public policies to wear masks, and the following unanswered questions arise:
Do used and loaded masks become sources of enhanced transmission, for the wearer and others? Do masks become collectors and retainers of pathogens that the mask wearer would otherwise avoid when breathing without a mask? Are large droplets captured by a mask atomized or aerolized into breathable components? Can virions escape an evaporating droplet stuck to a mask fiber? What are the dangers of bacterial growth on a used and loaded mask? How do pathogen-laden droplets interact with environmental dust and aerosols captured on the mask? What are long-term health effects on HCW, such as headaches, arising from impeded breathing? Are there negative social consequences to a masked society? Are there negative psychological consequences to wearing a mask, as a fear-based behavioral modification? What are the environmental consequences of mask manufacturing and disposal? Do the masks shed fibers or substances that are harmful when inhaled?
Conclusion
By making mask-wearing recommendations and policies for the general public, or by expressly condoning the practice, governments have both ignored the scientific evidence and done the opposite of following the precautionary principle.
In an absence of knowledge, governments should not make policies that have a hypothetical potential to cause harm. The government has an onus barrier before it instigates a broad social-engineering intervention, or allows corporations to exploit fear-based sentiments.
Furthermore, individuals should know that there is no known benefit arising from wearing a mask in a viral respiratory illness epidemic, and that scientific studies have shown that any benefit must be residually small, compared to other and determinative factors.
Otherwise, what is the point of publicly funded science?
The present paper about masks illustrates the degree to which governments, the mainstream media, and institutional propagandists can decide to operate in a science vacuum, or select only incomplete science that serves their interests. Such recklessness is also certainly the case with the current global lockdown of over 1 billion people, an unprecedented experiment in medical and political history.
Denis G. Rancourt is a researcher at the Ontario Civil Liberties Association (OCLA.ca) and is formerly a tenured professor at the University of Ottawa, Canada. This paper was originally published at Rancourt’s account on ResearchGate.net. As of June 5, 2020, this paper was removed from his profile by its administrators at Researchgate.net/profile/D_Rancourt. At Rancourt’s blog ActivistTeacher.blogspot.com, he recounts the notification and responses he received from ResearchGate.net and states, “This is censorship of my scientific work like I have never experienced before.”
The original April 2020 white paper in .pdf format is available here, complete with charts that have not been reprinted in the Reader print or web versions.
RELATED COMMENTARY: An Unprecedented Experiment: Sometimes You Just Gotta Wear the Stupid
Endnotes:
Baccam, P. et al. (2006) “Kinetics of Influenza A Virus Infection in Humans”, Journal of Virology Jul 2006, 80 (15) 7590-7599; DOI: 10.1128/JVI.01623-05 https://jvi.asm.org/content/80/15/7590
Balazy et al. (2006) “Do N95 respirators provide 95{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} protection level against airborne viruses, and how adequate are surgical masks?”, American Journal of Infection Control, Volume 34, Issue 2, March 2006, Pages 51-57. doi:10.1016/j.ajic.2005.08.018 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.488.4644&rep=rep1&type=pdf
Biggerstaff, M. et al. (2014) “Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature”, BMC Infect Dis 14, 480 (2014). https://doi.org/10.1186/1471-2334-14-480
Brooke, C. B. et al. (2013) “Most Influenza A Virions Fail To Express at Least One Essential Viral Protein”, Journal of Virology Feb 2013, 87 (6) 3155-3162; DOI: 10.1128/JVI.02284-12 https://jvi.asm.org/content/87/6/3155
Coburn, B. J. et al. (2009) “Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)”, BMC Med 7, 30. https://doi.org/10.1186/1741-7015-7-30
Davies, A. et al. (2013) “Testing the Efficacy of Homemade Masks: Would They Protect in an Influenza Pandemic?”, Disaster Medicine and Public Health Preparedness, Available on CJO 2013 doi:10.1017/dmp.2013.43 http://journals.cambridge.org/abstract_S1935789313000438
Despres, V. R. et al. (2012) “Primary biological aerosol particles in the atmosphere: a review”, Tellus B: Chemical and Physical Meteorology, 64:1, 15598, DOI: 10.3402/tellusb.v64i0.15598 https://doi.org/10.3402/tellusb.v64i0.15598
Dowell, S. F. (2001) “Seasonal variation in host susceptibility and cycles of certain infectious diseases”, Emerg Infect Dis. 2001;7(3):369–374. doi:10.3201/eid0703.010301 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2631809/
Hammond, G. W. et al. (1989) “Impact of Atmospheric Dispersion and Transport of Viral Aerosols on the Epidemiology of Influenza”, Reviews of Infectious Diseases, Volume 11, Issue 3, May 1989, Pages 494–497, https://doi.org/10.1093/clinids/11.3.494
Haas, C.N. et al. (1993) “Risk Assessment of Virus in Drinking Water”, Risk Analysis, 13: 545-552. doi:10.1111/j.1539-6924.1993.tb00013.x https://doi.org/10.1111/j.1539-6924.1993.tb00013.x
HealthKnowlege-UK (2020) “Charter 1a – Epidemiology: Epidemic theory (effective & basic reproduction numbers, epidemic thresholds) & techniques for analysis of infectious disease data (construction & use of epidemic curves, generation numbers, exceptional reporting & identification of significant clusters)”, HealthKnowledge.org.uk, accessed on 2020-04-10. https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a- epidemiology/epidemic-theory
Lai, A. C. K. et al. (2012) “Effectiveness of facemasks to reduce exposure hazards for airborne infections among general populations”, J. R. Soc. Interface. 9938–948 http://doi.org/10.1098/rsif.2011.0537
Leung, N.H.L. et al. (2020) “Respiratory virus shedding in exhaled breath and efficacy of face masks”, Nature Medicine (2020). https://doi.org/10.1038/s41591-020-0843-2
Lowen, A. C. et al. (2007) “Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature”, PLoS Pathog 3(10): e151. https://doi.org/10.1371/journal.ppat.0030151
Paules, C. and Subbarao, S. (2017) “Influenza”, Lancet, Seminar| Volume 390, ISSUE 10095, P697-708, August 12, 2017. http://dx.doi.org/10.1016/S0140-6736(17)30129-0
Sande, van der, M. et al. (2008) “Professional and Home-Made Face Masks Reduce Exposure to Respiratory Infections among the General Population”, PLoS ONE 3(7): e2618. doi:10.1371/journal.pone.0002618 https://doi.org/10.1371/journal.pone.0002618
Shaman, J. et al. (2010) “Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States”, PLoS Biol 8(2): e1000316. https://doi.org/10.1371/journal.pbio.1000316
Tracht, S. M. et al. (2010) “Mathematical Modeling of the Effectiveness of Facemasks in Reducing the Spread of Novel Influenza A (H1N1)”, PLoS ONE 5(2): e9018. doi:10.1371/journal.pone.0009018 https://doi.org/10.1371/journal.pone.0009018
Viboud C. et al. (2010) “Preliminary Estimates of Mortality and Years of Life Lost Associated with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons”, PLoS Curr. 2010; 2:RRN1153. Published 2010 Mar 20. doi:10.1371/currents.rrn1153 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2843747/
Wada, K. et al. (2012) “Wearing face masks in public during the influenza season may reflect other positive hygiene practices in Japan”, BMC Public Health 12, 1065 (2012). https://doi.org/10.1186/1471-2458-12-1065
Yang, W. et al. (2011) “Concentrations and size distributions of airborne influenza A viruses measured indoors at a health centre, a day-care centre and on aeroplanes”, Journal of the Royal Society, Interface. 2011 Aug;8(61):1176-1184. DOI: 10.1098/rsif.2010.0686. https://royalsocietypublishing.org/doi/10.1098/rsif.2010.0686
Yezli, S., Otter, J.A. (2011) “Minimum Infective Dose of the Major Human Respiratory and Enteric Viruses Transmitted Through Food and the Environment”, Food Environ Virol 3, 1–30. https://doi.org/10.1007/s12560-011-9056-7
Zwart, M. P. et al. (2009) “An experimental test of the independent action hypothesis in virus– insect pathosystems”, Proc. R. Soc. B. 2762233–2242 http://doi.org/10.1098/rspb.2009.0064
About the author: Denis Rancourt PhD is a former professor of physics at the University of Ottawa. Known for applications of physics education research. Published over 100 scientific articles in the areas of metal physics, materials science, measurement methods, and earth and environmental science, and many social commentary essays. Author of the book Hierarchy and Free Expression in the Fight Against Racism.
Read more at www.rcreader.com
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principiascientificinternational--2020-07-06--Why is the Sky Blue?

Why is the Sky Blue?

Why is the Sky Blue ?
It is an age-old question posed by children with an inadequate explanation .
The answer that it is caused by the short wavelength of light being scattered in the atmosphere is an excuse , used to provide an answer but not the reason .
Why would the short blue wavelength be scattered and not the longer wavelengths , when the shorter a wavelength is , the greater its energy and the more penetrating it is ?
If the cause is the scattering of light , why , when you see the horizon of the @ @ @ @ @ @ @ the black sky and blue sky but when in space when you look at the light coming from the Earth at night it is not blue ?
If the gases in the atmosphere , nitrogen , oxygen , and argon , do not absorb or reflect visible light what is causing the scattering of the blue light ?
The correct answer for why the sky is blue is that it is a result of how the nitrogen and oxygen in the atmosphere absorb and transfer energy coming from the sun .
What wavelength @ @ @ @ @ @ @ by its bonds and size and what wavelength of energy the object emits is also a function of these characteristics .
Both the length of bonds of a molecule and the molecule ’ s size vary and objects do not absorb and emit “ a ” wavelength but a range of wavelengths .
As the atoms of a molecule absorb energy they flex contracting and stretching changing the length of the bond and the size of the molecule .
A molecule will absorb energy both internally , by the atoms forming its bonds @ @ @ @ @ @ @ .
When it absorbs enough internal energy the vibrations of the atoms across the bond exceeds the attractive force between the atoms forming the bond and the molecules splits .
Oxygen and nitrogen absorb energy from the x-ray and ultraviolet spectrum of light emitted by the sun .
Since oxygen , with a double bond , is weaker than nitrogen with its triple bond , it will split into atoms before all the nitrogen bonds are broken .
This is why in the atmosphere above 100 km , where the energy from the @ @ @ @ @ @ @ nitrogen in the atmosphere decreases and the oxygen , in the form of oxygen atoms , increases .
It is also the reason why in the upper atmosphere nitrogen and oxygen combine to form nitrous oxide .
What wavelength of energy the bonds , atoms , and molecules radiate depends on the rate of vibration across a bond and the velocity or energy of the objects as a whole .
This energy is radiated in all directions and equalized with surrounding objects that are able to absorb these wavelengths .
As the altitude @ @ @ @ @ @ @ or number of molecules , increases which results in the energy being distributed to more molecules and the velocity of those molecules decreasing .
As the velocity of the objects decreases , the amount of energy emitted decreases and the wavelength of the energy increases .
In the stratosphere the absorption and radiation of energy by oxygen and nitrogen begin to convert ultraviolet light in blue visible light .
Since blue light is not absorbed by the gases the progression of increasing wavelengths ceases with no green , yellow , orange , or @ @ @ @ @ @ @ blue .
The sky is blue because the gases in the atmosphere absorb and radiate energy from the ultraviolet spectrum and converting it into visible blue light .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

Why is the Sky Blue?
Written by Herb Rose
It is an age-old question posed by children with an inadequate explanation. The answer that it is caused by the short wavelength of light being scattered in the atmosphere is an excuse, used to provide an answer but not the reason.
Why would the short blue wavelength be scattered and not the longer wavelengths, when the shorter a wavelength is, the greater its energy and the more penetrating it is?
If the cause is the scattering of light, why, when you see the horizon of the Earth is there a sharp delineation between the black sky and blue sky but when in space when you look at the light coming from the Earth at night it is not blue?
If the gases in the atmosphere, nitrogen, oxygen, and argon, do not absorb or reflect visible light what is causing the scattering of the blue light?
The correct answer for why the sky is blue is that it is a result of how the nitrogen and oxygen in the atmosphere absorb and transfer energy coming from the sun. What wavelength of energy an object absorbs is determined by its bonds and size and what wavelength of energy the object emits is also a function of these characteristics.
Both the length of bonds of a molecule and the molecule’s size vary and objects do not absorb and emit “a” wavelength but a range of wavelengths. As the atoms of a molecule absorb energy they flex contracting and stretching changing the length of the bond and the size of the molecule.
A molecule will absorb energy both internally, by the atoms forming its bonds and as a molecule as a whole. When it absorbs enough internal energy the vibrations of the atoms across the bond exceeds the attractive force between the atoms forming the bond and the molecules splits.
Oxygen and nitrogen absorb energy from the x-ray and ultraviolet spectrum of light emitted by the sun. Since oxygen, with a double bond, is weaker than nitrogen with its triple bond, it will split into atoms before all the nitrogen bonds are broken.
This is why in the atmosphere above 100 km, where the energy from the sun is greatest, the percentage of nitrogen in the atmosphere decreases and the oxygen, in the form of oxygen atoms, increases. It is also the reason why in the upper atmosphere nitrogen and oxygen combine to form nitrous oxide.
What wavelength of energy the bonds, atoms, and molecules radiate depends on the rate of vibration across a bond and the velocity or energy of the objects as a whole. This energy is radiated in all directions and equalized with surrounding objects that are able to absorb these wavelengths.
As the altitude of the atmosphere decreases the density, or number of molecules, increases which results in the energy being distributed to more molecules and the velocity of those molecules decreasing. As the velocity of the objects decreases, the amount of energy emitted decreases and the wavelength of the energy increases.
In the stratosphere the absorption and radiation of energy by oxygen and nitrogen begin to convert ultraviolet light in blue visible light. Since blue light is not absorbed by the gases the progression of increasing wavelengths ceases with no green, yellow, orange, or red being produced and the sky is blue.
The sky is blue because the gases in the atmosphere absorb and radiate energy from the ultraviolet spectrum and converting it into visible blue light.
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principiascientificinternational--2020-07-06--COVID Deaths at Lowest Levels Since Start of Pandemic – Media Silent

COVID Deaths at Lowest Levels Since Start of Pandemic – Media Silent The number of deaths attributed to the China coronavirus ( both actually tested and presumed ) reached the lowest number of cases since the beginning of the crisis .
On Saturday July 4th the number of cases recorded dropped to 254 deaths .
March 23 , 2020 , was the last time time the number of deaths for both actual and presumed cases of the China coronavirus were as low as 254 , when the total number of deaths reached 181 nationwide .
These are great news for @ @ @ @ @ @ @ decreasing daily .
However , the story in the liberal and corrupt MSM is that the number of cases is increasing .
What the media won ’ t tell you is that the CDC and states are now counting those who had the coronavirus and those who have the coronavirus in these daily tests .
But the number of deaths is at all time lows no doubt due to the faulty counting .
Update : The results for Sunday July 5th are in and the number of deaths reported confirmed or presumed related @ @ @ @ @ @ @ the totals from the 4th .
The number of deaths on the 5th were reported at 251 : The media won ’ t report this .
Why ?
But in two weeks , when deaths are even lower the MSM will have to come up with something else .
The China coronavirus was real but the reporting and media bias is as corrupt as it gets .
If we all knew the truth , America would be back to work now .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a @ @ @ @ @ @ @ Office : 27 Old Gloucester Street , London WC1N 3AX .
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COVID Deaths at Lowest Levels Since Start of Pandemic – Media Silent
Written by Joe Hoft
More great news ignored by the media: The number of coronavirus related deaths in the US on the 4th of July reached the lowest numbers since the beginning of the China coronavirus pandemic back in March.
The number of deaths attributed to the China coronavirus (both actually tested and presumed) reached the lowest number of cases since the beginning of the crisis. On Saturday July 4th the number of cases recorded dropped to 254 deaths.
March 23, 2020, was the last time time the number of deaths for both actual and presumed cases of the China coronavirus were as low as 254, when the total number of deaths reached 181 nationwide.
These are great news for America as the number of deaths is decreasing daily.
However, the story in the liberal and corrupt MSM is that the number of cases is increasing. What the media won’t tell you is that the CDC and states are now counting those who had the coronavirus and those who have the coronavirus in these daily tests. But the number of deaths is at all time lows no doubt due to the faulty counting.
Update: The results for Sunday July 5th are in and the number of deaths reported confirmed or presumed related to the China coronavirus are less than the totals from the 4th.
The number of deaths on the 5th were reported at 251:
The media won’t report this. Why? But in two weeks, when deaths are even lower the MSM will have to come up with something else.
The China coronavirus was real but the reporting and media bias is as corrupt as it gets. If we all knew the truth, America would be back to work now.
Read more at www.thegatewaypundit.com
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principiascientificinternational--2020-07-06--Quality not Quantity: Strange Events in Climate Science

I had a really excellent follow-up question come up on my “ Real Climate Physics vs .
Fake Political Physics ” video .
I will post the original question and response , and then discuss the follow up below : Leon Hiebert : Hi Joe .
Quick question .
You said the TE of earth is correct but if the FS ( 1-A ) /4 is wrong , wouldn ’ t that mean the TE isn ’ t -18 ?
Joe Postma : The TE of the Earth is correct…but…NOT AS THE SOLAR INPUT or forcing from said input .
@ @ @ @ @ @ @ TE as the solar input .
TE is the earth “ output ” …and it is way colder than the solar input .
This is the fundamental mistake…THE ONE .
And it originates in flat earth theory .
Great question for generating clarity !
Six months later Leon posted a follow up question : Leon Hiebert : 6-months later I return to this question .
If the output is less than the input , ( which I don ’ t dispute ) how is there an energy balance ?
I know the Trenberth @ @ @ @ @ @ @ surface should be more , and they try to balance it out by inverting output and fudging the 340W but an alarmist will say energy in must match energy out .
If there ’ s an olr deficit , we would overheat .
Which I can ’ t dispute .
So how come we don ’ t overheat when less is going out ?
Thanks .
Now this is an extremely important question .
The total energy in and out is indeed the same in quantity .
But the quality of the energy @ @ @ @ @ @ @ a question of quantity , which of course equal , but of quality , and that is not at all equal .
It is the quality of the energy that drives the physics .
Above , we used TE for the temperature of the earth output .
Temperature is a measure of the quality of energy , not the quantity .
The earth output temperature TE is -18C , so quite cool in quality .
The Earth solar input temperature we can denote as TS , and although it ’ s the same @ @ @ @ @ @ @ , the TS is actually +121C .
So you have the same total energies in the output and the input , but one energy is at -18C while the other is at +121C .
Do these energies have the same effect upon matter and in physics ?
Would they generate the same physical responses in matter ?
For the same total energies , what effect would -18C energy have on an ice cube vs +121C energy ?
For the same total energies , what effect would -18C energy have on generating and sustaining @ @ @ @ @ @ @ energy ?
Climate science and its greenhouse effect says that there is no difference .
Climate science says that we can use the output -18C energy of the Earth as the solar input of the Earth because there is the same total quantity of +121C solar input ; climate science says that we can ignore the difference in the quality of the energy because they have the same total quantity .
Climate science then even goes on to state their position that they believe that the Sun does not heat the Earth as @ @ @ @ @ @ @ : SUN DOES NOT CREATE EARTH ’ S WEATHER .
So here ’ s the sequence of events : • Climate science pretends that in physics we can ignore the quality ( temperature ) of energy as long as we have the same quantity of energy .
• Given 1 , climate science then uses Earth ’ s output energy with a quality of -18C in place of the the solar input energy of +121C to the Earth , since it is the same total energy .
• Given 2 , climate science @ @ @ @ @ @ @ not heat the Earth above -18C and thus can not create and sustain Earth ’ s climate and weather .
• Given 3 , climate science then invents a scheme of heat-recycling and heat-amplification which it calls a “ greenhouse effect ” even though real greenhouses do not operate by heat recycling or heat-amplification .
• Given 4 , climate science peer-review prevents anyone from pointing out that mistakes have been made , and that real greenhouses demonstrate that the alternative climate science “ greenhouse effect ” does not exist , and that @ @ @ @ @ @ @ of Thermodynamics , and that we should re-consider the quality of solar energy at +121C as being the force that directly creates and sustains the climate and weather .
• Given 5 , climate science with its pal-protected review process then turns into political theory where it claims that the life-creating molecule of carbon dioxide is the molecule which causes this heat-recycling and that more of it will threaten a “ runaway warming ” of the planet , with politicians together with the climate scientists then labeling the life-creating molecule of carbon-dioxide as @ @ @ @ @ @ @ regulated so that we can save the Earth from destruction .
And the final step of this process has been that all along the way , modern academic PhD ’ s in physics and astronomy and meteorology ( weather men ! )
now completely lack the intelligence and intellectual fortitude to comprehend the difference between quantity and quality and whether such distinctions make a difference to physics and science at all .
They can not even form the question in their minds , let alone begin to answer it .
This step is @ @ @ @ @ @ @ .
Quantity is not equal to quality , and it is quality , not quantity , which determines what physics occurs .
The quality of the energy dictates what type of physics can occur ; the quantity dictates how much of that physics can occur .
And when it comes to radiant energy , i.e .
the energy in light , its quality is measured by energy flux density , i.e.
, Watts per meter squared ( W/m² ) .
About the author : Joseph E Postma has a Masters Degree in Astrophysics @ @ @ @ @ @ @ be found here ( or here ) and is titled “ The observation and analysis of the Cepheid SZ Tauri ” ) .
He has debunked the consensus greenhouse gas theory extensively in his writing and Principia Scientific International proudly showcases his papers in our Publications section ( link above ) .
Please post any questions for Joe Postma at his blog : climateofsophistry.com PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
@ @ @ @ @ @ @ Mission To Defend The Scientific Method .

Quality not Quantity: Strange Events in Climate Science
Written by Joseph E Postma
I had a really excellent follow-up question come up on my “Real Climate Physics vs. Fake Political Physics” video. I will post the original question and response, and then discuss the follow up below:
Leon Hiebert: Hi Joe. Quick question. You said the TE of earth is correct but if the FS(1-A)/4 is wrong, wouldn’t that mean the TE isn’t -18? Joe Postma: The TE of the Earth is correct…but…NOT AS THE SOLAR INPUT or forcing from said input. It’s not correct to use TE as the solar input. TE is the earth “output”…and it is way colder than the solar input. This is the fundamental mistake…THE ONE. And it originates in flat earth theory. Great question for generating clarity!
Six months later Leon posted a follow up question:
Leon Hiebert: 6-months later I return to this question. If the output is less than the input, (which I don’t dispute) how is there an energy balance? I know the Trenberth chart is garbage and 163 hitting the surface should be more, and they try to balance it out by inverting output and fudging the 340W but an alarmist will say energy in must match energy out. If there’s an olr deficit, we would overheat. Which I can’t dispute. So how come we don’t overheat when less is going out? Thanks.
Now this is an extremely important question. The total energy in and out is indeed the same in quantity. But the quality of the energy is completely different. It is not a question of quantity, which of course equal, but of quality, and that is not at all equal. It is the quality of the energy that drives the physics.
Above, we used TE for the temperature of the earth output. Temperature is a measure of the quality of energy, not the quantity. The earth output temperature TE is -18C, so quite cool in quality.
The Earth solar input temperature we can denote as TS, and although it’s the same total energy as the output of Earth, the TS is actually +121C.
So you have the same total energies in the output and the input, but one energy is at -18C while the other is at +121C.
Do these energies have the same effect upon matter and in physics? Would they generate the same physical responses in matter? For the same total energies, what effect would -18C energy have on an ice cube vs +121C energy? For the same total energies, what effect would -18C energy have on generating and sustaining our known climate vs. that of +121C energy?
Climate science and its greenhouse effect says that there is no difference. Climate science says that we can use the output -18C energy of the Earth as the solar input of the Earth because there is the same total quantity of +121C solar input; climate science says that we can ignore the difference in the quality of the energy because they have the same total quantity. Climate science then even goes on to state their position that they believe that the Sun does not heat the Earth as I exposed in the video AMS Official: SUN DOES NOT CREATE EARTH’S WEATHER.
So here’s the sequence of events:
Climate science pretends that in physics we can ignore the quality (temperature) of energy as long as we have the same quantity of energy. Given 1, climate science then uses Earth’s output energy with a quality of -18C in place of the the solar input energy of +121C to the Earth, since it is the same total energy. Given 2, climate science then states that the solar input cannot heat the Earth above -18C and thus cannot create and sustain Earth’s climate and weather. Given 3, climate science then invents a scheme of heat-recycling and heat-amplification which it calls a “greenhouse effect” even though real greenhouses do not operate by heat recycling or heat-amplification. Given 4, climate science peer-review prevents anyone from pointing out that mistakes have been made, and that real greenhouses demonstrate that the alternative climate science “greenhouse effect” does not exist, and that this is because heat-recycling violates the Laws of Thermodynamics, and that we should re-consider the quality of solar energy at +121C as being the force that directly creates and sustains the climate and weather. Given 5, climate science with its pal-protected review process then turns into political theory where it claims that the life-creating molecule of carbon dioxide is the molecule which causes this heat-recycling and that more of it will threaten a “runaway warming” of the planet, with politicians together with the climate scientists then labeling the life-creating molecule of carbon-dioxide as a pollutant that must be taxed and regulated so that we can save the Earth from destruction.
And the final step of this process has been that all along the way, modern academic PhD’s in physics and astronomy and meteorology (weather men!) now completely lack the intelligence and intellectual fortitude to comprehend the difference between quantity and quality and whether such distinctions make a difference to physics and science at all. They cannot even form the question in their minds, let alone begin to answer it. This step is truly the most amazing part of all.
Quantity is not equal to quality, and it is quality, not quantity, which determines what physics occurs. The quality of the energy dictates what type of physics can occur; the quantity dictates how much of that physics can occur.
And when it comes to radiant energy, i.e. the energy in light, its quality is measured by energy flux density, i.e., Watts per meter squared (W/m²).
About the author: Joseph E Postma has a Masters Degree in Astrophysics received in 2007 (graduate thesis can be found here (or here) and is titled “The observation and analysis of the Cepheid SZ Tauri”). He has debunked the consensus greenhouse gas theory extensively in his writing and Principia Scientific International proudly showcases his papers in our Publications section (link above).
Please post any questions for Joe Postma at his blog: climateofsophistry.com
PRINCIPIA SCIENTIFIC INTERNATIONAL, legally registered in the UK as a company incorporated for charitable purposes. Head Office: 27 Old Gloucester Street, London WC1N 3AX.
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method.
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principiascientificinternational--2020-07-06--Huge COVID case-counting deception at the CDC

For this piece , we have to enter the official world ( of the insane ) —where everyone is quite sure a new coronavirus was discovered in China and the worthless diagnostic tests mean something and the case numbers are real and meaningful .
Once we execute all those absurd maneuvers , we land square in the middle of yet another scandal—this time at our favorite US agency for scandals , the CDC .
The Atlantic , May 21 , has the story , headlined , “ How could the CDC make that mistake ?
” I ’ ll give @ @ @ @ @ @ @ comment on the stark inference The Atlantic somehow failed to grasp .
“ We ’ ve learned that the CDC is making , at best , a debilitating mistake : combining test results that diagnose current coronavirus infections with test results that measure whether someone has ever had the virus…The agency confirmed to The Atlantic on Wednesday that it is mixing the results of viral [ PCR ] and antibody tests , even though the two tests reveal different information and are used for different reasons.
” “ Several states—including Pennsylvania , the @ @ @ @ @ @ @ s largest outbreaks , as well as Texas , Georgia , and Vermont—are blending the data in the same way .
Virginia likewise mixed viral and antibody test results until last week , but it reversed course and the governor apologized for the practice after it was covered by the Richmond Times-Dispatch and The Atlantic .
Maine similarly separated its data on Wednesday ; Vermont authorities claimed they didn ’ t even know they were doing this.
” “ ’ You ’ ve got to be kidding me , ’ Ashish Jha , @ @ @ @ @ @ @ Health at Harvard and the director of the Harvard Global Health Institute , told us when we described what the CDC was doing .
‘ How could the CDC make that mistake ?
This is a mess ’ .
” “ The CDC stopped publishing anything resembling a complete database of daily [ COVID ] test results on February 29 .
When it resumed publishing test data last week [ the middle of May ] … ” First of all , the CDC ’ s basic mission is publishing disease statistics on an @ @ @ @ @ @ @ in the face of what they ’ re supposed to be all about .
But the big deal , of course , is combining results from two different tests—the PCR and the antibody—and placing them in one lump .
I ’ ve read the Atlantic article forwards , backwards , and sideways , and it appears the experts believe only PCR viral tests should be used to count the number of COVID cases .
So here is a takeaway I find nowhere in the Atlantic article : COMBINING THE TWO TESTS WILL VASTLY @ @ @ @ @ @ @ ’ m not talking about categories like “ rate of infection ” or “ percentage.
” I ’ m talking about plain numbers of cases .
Some PCR tests will indicate COVID and some antibody tests will indicate COVID , and adding them together will pump up the number of cases .
You know , that big number they flash on TV screens a hundred times a day .
The number media and government and related con artists deploy to scare the people and justify lockdowns and use to stop reopening the economy @ @ @ @ @ @ @ acrobats and elephants and clown numbers .
Therefore , I ’ m not characterizing what the CDC is doing as a mistake .
They ’ ve managed to create the illusion that absolute case numbers are higher than they should be .
Somehow , these “ mistakes ” always seem to result in worse news , not better news .
The “ errors ” are always on the high side rather than the low side .
Case in point : the computer prediction of COVID deaths in the UK and US made by @ @ @ @ @ @ @ whose track record , going back to 2001 , has been one horrendous lunatic exaggeration after another .
His 2020 projections of 500,000 COVID deaths in the UK and two million in the US were directly used to justify lockdowns in many countries .
The CDC , back in 2009 , stopped reporting the number of Swine Flu cases in the US—while still claiming that number was in the tens of thousands .
I ’ ve written in great detail about the scandal , which was exposed by then-CBS investigative reporter , Sharyl @ @ @ @ @ @ @ , because the overwhelming percentage of tissue samples from patients was coming back from labs with no sign of Swine Flu or any other kind of flu .
And yet , in a later retrospective “ analysis , ” the CDC claimed that , at the height of the “ epidemic , ” there were 22 MILLION cases of Swine Flu in the US .
Going all the way back to 2003 and SARS , the CDC and other public health agencies around the world hyped the dangers to the sky ; the @ @ @ @ @ @ @ when the dust cleared ?
800 .
There is a tradition of lying on the high side , blowing up figures in order to create the illusion of destruction .
CDC ?
Mistake ?
The agency is certainly incompetent .
But that ’ s just the beginning of the story .
The only time they say there is no danger is when they ’ re lying about the effects of vaccines .
My headline for the Atlantic article would read : SO HOW MANY COVID CASES SHOULD WE SUBTRACT TO GET THE ACTUAL @ @ @ @ @ @ @ go this way : “ Just when governors are trying to reopen their economies , a gigantic case-counting deception at the CDC is taking the wind out of their sails .
The millions of Americans suffering financial devastation could be pushed back into a hole .
Who is screaming to high heaven about THAT on the nightly news ?
No one .
Why not ?
” About the author : Jon Rappoport is author of three explosive collections , THE MATRIX REVEALED , EXIT FROM THE MATRIX , and POWER OUTSIDE THE MATRIX @ @ @ @ @ @ @ US Congressional seat in the 29th District of California .
He maintains a consulting practice for private clients , the purpose of which is the expansion of personal creative power .
Nominated for a Pulitzer Prize , he has worked as an investigative reporter for 30 years , writing articles on politics , medicine , and health for CBS Healthwatch , LA Weekly , Spin Magazine , Stern , and other newspapers and magazines in the US and Europe .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated @ @ @ @ @ @ @ 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

Huge COVID case-counting deception at the CDC
Written by Jon Rappoport
For this piece, we have to enter the official world (of the insane)—where everyone is quite sure a new coronavirus was discovered in China and the worthless diagnostic tests mean something and the case numbers are real and meaningful.
Once we execute all those absurd maneuvers, we land square in the middle of yet another scandal—this time at our favorite US agency for scandals, the CDC.
The Atlantic, May 21, has the story, headlined, “How could the CDC make that mistake?”
I’ll give you the key quotes, and then comment on the stark inference The Atlantic somehow failed to grasp.
“We’ve learned that the CDC is making, at best, a debilitating mistake: combining test results that diagnose current coronavirus infections with test results that measure whether someone has ever had the virus…The agency confirmed to The Atlantic on Wednesday that it is mixing the results of viral [PCR] and antibody tests, even though the two tests reveal different information and are used for different reasons.” “Several states—including Pennsylvania, the site of one of the country’s largest outbreaks, as well as Texas, Georgia, and Vermont—are blending the data in the same way. Virginia likewise mixed viral and antibody test results until last week, but it reversed course and the governor apologized for the practice after it was covered by the Richmond Times-Dispatch and The Atlantic. Maine similarly separated its data on Wednesday; Vermont authorities claimed they didn’t even know they were doing this.” “’You’ve got to be kidding me,’ Ashish Jha, the K. T. Li Professor of Global Health at Harvard and the director of the Harvard Global Health Institute, told us when we described what the CDC was doing. ‘How could the CDC make that mistake? This is a mess’.” “The CDC stopped publishing anything resembling a complete database of daily [COVID] test results on February 29. When it resumed publishing test data last week [the middle of May]…”
First of all, the CDC’s basic mission is publishing disease statistics on an ongoing basis. Reporting partial data flies in the face of what they’re supposed to be all about.
But the big deal, of course, is combining results from two different tests—the PCR and the antibody—and placing them in one lump.
I’ve read the Atlantic article forwards, backwards, and sideways, and it appears the experts believe only PCR viral tests should be used to count the number of COVID cases.
So here is a takeaway I find nowhere in the Atlantic article: COMBINING THE TWO TESTS WILL VASTLY INFLATE THE NUMBER OF CASES.
I’m not talking about categories like “rate of infection” or “percentage.” I’m talking about plain numbers of cases.
Some PCR tests will indicate COVID and some antibody tests will indicate COVID, and adding them together will pump up the number of cases. You know, that big number they flash on TV screens a hundred times a day.
“Coronavirus cases jumped up again yesterday, and the grand total in the US is now…”
THAT number.
The number media and government and related con artists deploy to scare the people and justify lockdowns and use to stop reopening the economy.
The brass band circus with flying acrobats and elephants and clown numbers.
Therefore, I’m not characterizing what the CDC is doing as a mistake. They’ve managed to create the illusion that absolute case numbers are higher than they should be.
Somehow, these “mistakes” always seem to result in worse news, not better news. The “errors” are always on the high side rather than the low side.
Case in point: the computer prediction of COVID deaths in the UK and US made by that abject failure, Neil Ferguson, whose track record, going back to 2001, has been one horrendous lunatic exaggeration after another. His 2020 projections of 500,000 COVID deaths in the UK and two million in the US were directly used to justify lockdowns in many countries.
The CDC, back in 2009, stopped reporting the number of Swine Flu cases in the US—while still claiming that number was in the tens of thousands. I’ve written in great detail about the scandal, which was exposed by then-CBS investigative reporter, Sharyl Attkisson.
The CDC stopped counting cases, because the overwhelming percentage of tissue samples from patients was coming back from labs with no sign of Swine Flu or any other kind of flu. And yet, in a later retrospective “analysis,” the CDC claimed that, at the height of the “epidemic,” there were 22 MILLION cases of Swine Flu in the US.
Going all the way back to 2003 and SARS, the CDC and other public health agencies around the world hyped the dangers to the sky; the final official death count, globally, when the dust cleared? 800.
There is a tradition of lying on the high side, blowing up figures in order to create the illusion of destruction.
CDC? Mistake? The agency is certainly incompetent. But that’s just the beginning of the story. The only time they say there is no danger is when they’re lying about the effects of vaccines.
My headline for the Atlantic article would read: SO HOW MANY COVID CASES SHOULD WE SUBTRACT TO GET THE ACTUAL NUMBER?
And the first paragraph would go this way: “Just when governors are trying to reopen their economies, a gigantic case-counting deception at the CDC is taking the wind out of their sails. The millions of Americans suffering financial devastation could be pushed back into a hole. Who is screaming to high heaven about THAT on the nightly news? No one. Why not?”
SOURCES:
https://www.theatlantic.com/health/archive/2020/05/cdc-and-states-are-misreporting-covid-19-test-data-pennsylvania-georgia-texas/611935/
https://banned.video/watch?id=5efd0c2a672706002f3a8501 (video: “CDC Admits Mistakes in Covid Case Numbers,” 7/1/2020)
https://blog.nomorefakenews.com/tag/neil-ferguson/
https://www.webmd.com/cold-and-flu/news/20091112/over-22-million-in-us-had-h1n1-swine-flu#1
About the author: Jon Rappoport is author of three explosive collections, THE MATRIX REVEALED, EXIT FROM THE MATRIX, and POWER OUTSIDE THE MATRIX, Jon was a candidate for a US Congressional seat in the 29th District of California. He maintains a consulting practice for private clients, the purpose of which is the expansion of personal creative power. Nominated for a Pulitzer Prize, he has worked as an investigative reporter for 30 years, writing articles on politics, medicine, and health for CBS Healthwatch, LA Weekly, Spin Magazine, Stern, and other newspapers and magazines in the US and Europe.
Read more at blog.nomorefakenews.com
PRINCIPIA SCIENTIFIC INTERNATIONAL, legally registered in the UK as a company incorporated for charitable purposes. Head Office: 27 Old Gloucester Street, London WC1N 3AX.
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method.
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