"Then there’s this gem from Friday’s @IDPH webinar. The speaker actually said “nonrespirator masks cannot filter small particles...like viruses”.
I was stunned listening to that admission. Yet they continue to endorse mere cloth rags or procedure masks despite all the evidence that concludes they do little to nothing to prevent anything.
The Inoculum of Truth is the world's most comprehensive & accurate Coronavirus documentary film series to date.
I have provided over 9 hours of peer reviewed published medical science journals & the highest tiers of Published evidence on screen with government data resources for all claims made. This film is irrefutable. That is far more data & evidence than any public health authority has provided to the public.
There is so much misinformation & confusion going around. We need to do a deep dive into the available data & make sense from the worlds leading experts in the field & compare it to what is being recommended & how those recommendations are perfectly aligned with a pre ordained agenda by multinational tech, surveillance capitalism, & 4th industrial revolution giants, the patents & policies being put in place that serve their purpose. I do not wish to spread sensationalism, or false claims, which is why i've included all my cited references on screen for fact checking all claims made.
If you disagree or are offended with parts of the video, I ask you to actually take notes, make a researched rebuttal, please feel free & post the evidence that provides correction & I will take measures to review it and correct my work accordingly. #Coronavirus, #LiftingTheVeil #Science
CRUCIAL UPDATE!
PATREON SUPPORT IS TRYING TO MAKE ME DELETE THIS DATA, CLAIMING THAT IT VIOLATES "MEDICAL MISINFO" POLICY AGAINST "UNFOUNDED OR DEBUNKED THEORIES"!
Mask Debate: Review of Best Data
Masks are neither efective nor safe: Review of the Medical Literature
DEAR PATREON TRUST AND SAFETY TEAM: THIS POST IS NOT UNSUBSTANTIATED OR UNFOUNDED OR DEBUNKED THEORY, IT IS WELL ESTABLISHED MEDICAL SCIENTIFIC FACT IN THE PEER REVIEWED LITERATURE!
"The role of face masks in the control and prevention of COVID-19 remains an issue of debate.
Prior to COVID-19, most studies assessing the effectiveness of face masks as a protective measure in the community came from studies on influenza, which provided little evidence to support their use.
This technical report reviews the evidence that has been accumulated since the emergence of COVID-19, in addition to what has existed on this topic prior to the pandemic,"
. Evidence for the effectiveness of non-medical face masks, face shields/visors and respirators in the community is scarce and of very low certainty.
Importance " Clinical studies have been inconclusive about the effectiveness of N95 respirators and medical masks in preventing health care personnel (HCP) from acquiring workplace viral respiratory infections."
"MEDICAL MASKS FIT THE FACE LOOSELY AND DO NOT RELIABLY PREVENT INHALATION OF SMALL AIRBORNE PARTICLES."
"there was no significant difference between the effectiveness of N95 respirators and medical masks in preventing laboratory-confirmed influenza among participants routinely exposed to respiratory illnesses in the workplace.
In addition, there were no significant differences between N95 respirators and medical masks in the rates of acute respiratory illness, laboratory-detected respiratory infections, laboratory-confirmed respiratory illness, and influenza like illness among participants.
A sensitivity analysis suggested that the primary analysis reported was fairly robust to the missing outcome data with quantitative outcomes varying by less than 5%.
This supports the finding that neither N95 respirators nor medical masks were more effective in preventing laboratory-confirmed influenza or other viral respiratory infection or illness among participants when worn in a fashion consistent with current US clinical practice."
Respiratory viruses are primarily transmitted by large droplets. Because a fraction of respiratory viruses may be transmitted by aerosol, N95 respirators have been presumed to provide better protection than medical masks against viral respiratory infections in health care settings.2However, definitive evidence of greater clinical effectiveness of N95 respirators is lacking.
A well-designed trial6 found the effectiveness of medical masks to be noninferior to N95 respirators, but the trial was stopped prematurely and was limited by small sample size.
Two additional studies3,4 (and a pooled analysis12) concluded that N95 respirators may bemore effective than medical masks; however, these studies were limited by uncertain clinical significance of end points.24
The current study was undertaken because of remaining uncertainty based on previous studies, which made it challenging for infection control clinicians to effectively implement respiratory protection programs in health care settings.2,7,13,18,24,25
ORIGINAL ARTICLE
The Orthopaedic Trauma Service and COVID-19: Practice Considerations to Optimize Outcomes and Limit Exposure
Author Information Stinner, Daniel J. MD, PhDa; Lebrun, Christopher MDb; Hsu, Joseph R. MDc; Jahangir, A. Alex MD, MMHCa; Mir, Hassan R. MD, MBAd
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.
In 2020 people were told that business closures, stay-at-home orders, lockdowns, and mask mandates were necessary to slow the spread of Sars-Cov-2.
Some people expected that places where these measures were absent or implemented half-heartedly would have drastically worse results.
With more than a year of these measures behind us, it's time to evaluate the results.
Preliminary academic studies have already been published, and they deserve our attention. This quiz is intended for the layman, because if these radical measures were truly justified the results should be clear and unambiguous in the data.
Check out our charts for various locales, with dates of mask mandates superimposed on cases or hospitalizations. Sources are at the bottom of the page.
Data sources: 1. COVID Tracking Project Data Download: https://covidtracking.com/data/download 2. Our World in Data: https://github.com/owid/covid-19-data/tree/master/public/data 3. San Diego Open Data Portal: https://sdgis-sandag.opendata.arcgis.com/search?groupIds=2ee90ba1cdf84381935c591c2a125a45 4. Orange County, CA: https://data-ocpw.opendata.arcgis.com/search?tags=health
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.
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.
“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.”
“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% 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.
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% 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
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
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
Masks are neither effective nor safe:
A summary of the science https://www.primarydoctor.org/masks-not-effect
At this writing, there is a recent surge in widespread use by the public of facemasks when in public places, including for extended periods of time, in the United States as well as in other countries. The public has been instructed by media and their governments that one’s use of masks, even if not sick, may prevent others from being infected with SARS-CoV-2, the infectious agent of COVID-19.
A review of the peer-reviewed medical literature examines impacts on human health, both immunological, as well as physiological. The purpose of this paper is to examine data regarding the effectiveness of facemasks, as well as safety data. The reason that both are examined in one paper is that for the general public as a whole, as well as for every individual, a risk-benefit analysis is necessary to guide decisions on if and when to wear a mask.
Are masks effective at preventing transmission of respiratory pathogens?
In this meta-analysis, face masks were found to have no detectable effect against transmission of viral infections. (1) It found: “Compared to no masks, there was no reduction of influenza-like illness cases or influenza for masks in the general population, nor in healthcare workers.”
This 2020 meta-analysis found that evidence from randomized controlled trials of face masks did not support a substantial effect on transmission of laboratory-confirmed influenza, either when worn by infected persons (source control) or by persons in the general community to reduce their susceptibility. (2)
Another recent review found that masks had no effect specifically against Covid-19, although facemask use seemed linked to, in 3 of 31 studies, “very slightly reduced” odds of developing influenza-like illness. (3)
This 2019 study of 2862 participants showed that both N95 respirators and surgical masks “resulted in no significant difference in the incidence of laboratory confirmed influenza." (4)
This 2016 meta-analysis found that both randomized controlled trials and observational studies of N95 respirators and surgical masks used by healthcare workers did not show benefit against transmission of acute respiratory infections. It was also found that acute respiratory infection transmission “may have occurred via contamination of provided respiratory protective equipment during storage and reuse of masks and respirators throughout the workday.” (5)
A 2011 meta-analysis of 17 studies regarding masks and effect on transmission of influenza found that “none of the studies established a conclusive relationship between mask/respirator use and protection against influenza infection.” (6) However, authors speculated that effectiveness of masks may be linked to early, consistent and correct usage.
Face mask use was likewise found to be not protective against the common cold, compared to controls without face masks among healthcare workers. (7)
Airflow around masks
Masks have been assumed to be effective in obstructing forward travel of viral particles. Considering those positioned next to or behind a mask wearer, there have been farther transmission of virus-laden fluid particles from masked individuals than from unmasked individuals, by means of “several leakage jets, including intense backward and downwards jets that may present major hazards,” and a “potentially dangerous leakage jet of up to several meters.” (8) All masks were thought to reduce forward airflow by 90% or more over wearing no mask. However, Schlieren imaging showed that both surgical masks and cloth masks had farther brow jets (unfiltered upward airflow past eyebrows) than not wearing any mask at all, 182 mm and 203 mm respectively, vs none discernible with no mask. Backward unfiltered airflow was found to be strong with all masks compared to not masking.
For both N95 and surgical masks, it was found that expelled particles from 0.03 to 1 micron were deflected around the edges of each mask, and that there was measurable penetration of particles through the filter of each mask. (9)
Penetration through masks
A study of 44 mask brands found mean 35.6% penetration (+ 34.7%). Most medical masks had over 20% penetration, while “general masks and handkerchiefs had no protective function in terms of the aerosol filtration efficiency.” The study found that “Medical masks, general masks, and handkerchiefs were found to provide little protection against respiratory aerosols.” (10)
It may be helpful to remember that an aerosol is a colloidal suspension of liquid or solid particles in a gas. In respiration, the relevant aerosol is the suspension of bacterial or viral particles in inhaled or exhaled breath.
In another study, penetration of cloth masks by particles was almost 97% and medical masks 44%. (11)
N95 respirators
Honeywell is a manufacturer of N95 respirators. These are made with a 0.3 micron filter. (12) N95 respirators are so named, because 95% of particles having a diameter of 0.3 microns are filtered by the mask forward of the wearer, by use of an electrostatic mechanism. Coronaviruses are approximately 0.125 microns in diameter.
This meta-analysis found that N95 respirators did not provide superior protection to facemasks against viral infections or influenza-like infections. (13) This study did find superior protection by N95 respirators when they were fit-tested compared to surgical masks. (14)
This study found that 624 out of 714 people wearing N95 masks left visible gaps when putting on their own masks. (15)
Surgical masks
This study found that surgical masks offered no protection at all against influenza. (16) Another study found that surgical masks had about 85% penetration ratio of aerosolized inactivated influenza particles and about 90% of Staphylococcus aureus bacteria, although S aureus particles were about 6x the diameter of influenza particles. (17)
Use of masks in surgery were found to slightly increase incidence of infection over not masking in a study of 3,088 surgeries. (18) The surgeons’ masks were found to give no protective effect to the patients.
Other studies found no difference in wound infection rates with and without surgical masks. (19) (20)
This study found that “there is a lack of substantial evidence to support claims that facemasks protect either patient or surgeon from infectious contamination.” (21)
This study found that medical masks have a wide range of filtration efficiency, with most showing a 30% to 50% efficiency. (22)
Specifically, are surgical masks effective in stopping human transmission of coronaviruses? Both experimental and control groups, masked and unmasked respectively, were found to “not shed detectable virus in respiratory droplets or aerosols.” (23) In that study, they “did not confirm the infectivity of coronavirus” as found in exhaled breath.
A study of aerosol penetration showed that two of the five surgical masks studied had 51% to 89% penetration of polydisperse aerosols. (24)
In another study, that observed subjects while coughing, “neither surgical nor cotton masks effectively filtered SARS-CoV-2 during coughs by infected patients.” And more viral particles were found on the outside than on the inside of masks tested. (25)
Cloth masks
Cloth masks were found to have low efficiency for blocking particles of 0.3 microns and smaller. Aerosol penetration through the various cloth masks examined in this study were between 74 and 90%. Likewise, the filtration efficiency of fabric materials was 3% to 33% (26)
Healthcare workers wearing cloth masks were found to have 13 times the risk of influenza-like illness than those wearing medical masks. (27)
This 1920 analysis of cloth mask use during the 1918 pandemic examines the failure of masks to impede or stop flu transmission at that time, and concluded that the number of layers of fabric required to prevent pathogen penetration would have required a suffocating number of layers, and could not be used for that reason, as well as the problem of leakage vents around the edges of cloth masks. (28)
Masks against Covid-19
The New England Journal of Medicine editorial on the topic of mask use versus Covid-19 assesses the matter as follows:
“We know that wearing a mask outside health care facilities offers little, if any, protection from infection. Public health authorities define a significant exposure to Covid-19 as face-to-face contact within 6 feet with a patient with symptomatic Covid-19 that is sustained for at least a few minutes (and some say more than 10 minutes or even 20 minutes). The chance of catching Covid-19 from a passing interaction in a public space is therefore minimal. In many cases, the desire for widespread masking is a reflexive reaction to anxiety over the pandemic.” (29)
Are masks safe?
During walking or other exercise
Surgical mask wearers had significantly increased dyspnea after a 6-minute walk than non-mask wearers. (30)
Researchers are concerned about possible burden of facemasks during physical activity on pulmonary, circulatory and immune systems, due to oxygen reduction and air trapping reducing substantial carbon dioxide exchange. As a result of hypercapnia, there may be cardiac overload, renal overload, and a shift to metabolic acidosis. (31)
Risks of N95 respirators
Pregnant healthcare workers were found to have a loss in volume of oxygen consumption by 13.8% compared to controls when wearing N95 respirators. 17.7% less carbon dioxide was exhaled. (32) Patients with end-stage renal disease were studied during use of N95 respirators. Their partial pressure of oxygen (PaO2) decreased significantly compared to controls and increased respiratory adverse effects. (33) 19% of the patients developed various degrees of hypoxemia while wearing the masks.
Healthcare workers’ N95 respirators were measured by personal bioaerosol samplers to harbor influenza virus. (34) And 25% of healthcare workers’ facepiece respirators were found to contain influenza in an emergency department during the 2015 flu season. (35)
Risks of surgical masks
Healthcare workers’ surgical masks also were measured by personal bioaerosol samplers to harbor for influenza virus. (36)
Various respiratory pathogens were found on the outer surface of used medical masks, which could result in self-contamination. The risk was found to be higher with longer duration of mask use. (37)
Surgical masks were also found to be a repository of bacterial contamination. The source of the bacteria was determined to be the body surface of the surgeons, rather than the operating room environment. (38) Given that surgeons are gowned from head to foot for surgery, this finding should be especially concerning for laypeople who wear masks. Without the protective garb of surgeons, laypeople generally have even more exposed body surface to serve as a source for bacteria to collect on their masks.
Risks of cloth masks
Healthcare workers wearing cloth masks had significantly higher rates of influenza-like illness after four weeks of continuous on-the-job use, when compared to controls. (39)
The increased rate of infection in mask-wearers may be due to a weakening of immune function during mask use. Surgeons have been found to have lower oxygen saturation after surgeries even as short as 30 minutes. (40) Low oxygen induces hypoxia-inducible factor 1 alpha (HIF-1). (41) This in turn down-regulates CD4+ T-cells. CD4+ T-cells, in turn, are necessary for viral immunity. (42)
Weighing risks versus benefits of mask use
In the summer of 2020 the United States is experiencing a surge of popular mask use, which is frequently promoted by the media, political leaders and celebrities. Homemade and store-bought cloth masks and surgical masks or N95 masks are being used by the public especially when entering stores and other publicly accessible buildings. Sometimes bandanas or scarves are used. The use of face masks, whether cloth, surgical or N95, creates a poor obstacle to aerosolized pathogens as we can see from the meta-analyses and other studies in this paper, allowing both transmission of aerosolized pathogens to others in various directions, as well as self-contamination.
It must also be considered that masks impede the necessary volume of air intake required for adequate oxygen exchange, which results in observed physiological effects that may be undesirable. Even 6- minute walks, let alone more strenuous activity, resulted in dyspnea. The volume of unobstructed oxygen in a typical breath is about 100 ml, used for normal physiological processes. 100 ml O2 greatly exceeds the volume of a pathogen required for transmission.
The foregoing data show that masks serve more as instruments of obstruction of normal breathing, rather than as effective barriers to pathogens. Therefore, masks should not be used by the general public, either by adults or children, and their limitations as prophylaxis against pathogens should also be considered in medical settings.
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