Masks Don’t Work: A Review of Science Relevant to COVID-19 Social Policy

[Leongsam]

rcreader.com

Masks Don’t Work: A Review of Science Relevant to COVID-19 Social Policy
Author T
Todd McGreevy

25-32 minutes


Masks and respirators do not work.

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.

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% 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:

1. Most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility
2. It is believed that a single virion can be enough to induce illness in the host
3. The 50-percent probability MID (“TCID50”) has variably been found to be in the range 100−1000 virions
4. There are typically 10 to 3rd power − 10 to 7th power virions per aerolized influenza droplet with diameter 1 μm − 10 μm
5. The 50-percent probability MID easily fits into a single (one) aerolized droplet
6. For further background:
7. A classic description of dose-response assessment is provided by Haas (1993).
8. 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.
9. 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.”
10. 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]:

1. 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.
2. Mask compliance and mask adjustment habits would be unknown.
3. Mask-wearing is associated (correlated) with several other health behaviors; see Wada (2012).
4. The results would not be transferable, because of differing cultural habits.
5. Compliance is achieved by fear, and individuals can habituate to fear-based propaganda, and can have disparate basic responses.
6. Monitoring and compliance measurement are near-impossible, and subject to large errors.
7. Self-reporting (such as in surveys) is notoriously biased, because individuals have the self-interested belief that their efforts are useful.
8. Progression of the epidemic is not verified with reliable tests on large population samples, and generally relies on non-representative hospital visits or admissions.
9. 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:

1. Do used and loaded masks become sources of enhanced transmission, for the wearer and others?
2. Do masks become collectors and retainers of pathogens that the mask wearer would otherwise avoid when breathing without a mask?
3. Are large droplets captured by a mask atomized or aerolized into breathable components? Can virions escape an evaporating droplet stuck to a mask fiber?
4. What are the dangers of bacterial growth on a used and loaded mask?
5. How do pathogen-laden droplets interact with environmental dust and aerosols captured on the mask?
6. What are long-term health effects on HCW, such as headaches, arising from impeded breathing?
7. Are there negative social consequences to a masked society?
8. Are there negative psychological consequences to wearing a mask, as a fear-based behavioral modification?
9. What are the environmental consequences of mask manufacturing and disposal?
10. 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.

 

[Leongsam]

 

[Leongsam]

 

[sweetiepie]

KNN my uncle think this type of science leeport only scientist can understand KNN

 

[Leongsam]

 

[Leongsam]

KNN my uncle think this type of science leeport only scientist can understand KNN

There is no equivalent report to prove that masks work but there are loads of reports to show that masks increase the risk of infection.

 

[Scrooball (clone)]

Give it a rest. For fuck’s sake.

 

[Leongsam]

Give it a rest. For fuck’s sake.

And allow lies and misinformation about the benefits of wearing a mask to go unchallenged? No way.

Expect more to come on a regular basis.

 

[laksaboy]

Only medical grade masks provide reliable protection against airborne pathogens.

The protection provided by hipster masks is highly suspect, especially those made by dubious sources.

 

[GramStroker]

Hopefully wave 2 will come soon.

 

[Scrooball (clone)]

http://www.advisory.com/daily-briefing/2020/06/16/mask-covid


Research shows wearing masks can significantly reduce risk of coronavirus transmission
However, new research could support some experts' and officials' calls for a more sweeping policy regarding face masks and coverings to curb the virus' spread, the Washington Post reports.

For instance, a study published Thursday in the Proceedings of the National Academy of Sciences (PNAS) found that requiring people to wear masks in epicenters of new coronavirus cases may have prevented tens of thousands of infections from the virus.

For the study, researchers examined how the new coronavirus is transmitted by reviewing infection trends in Wuhan, China; Italy; and New York City—all of which were early epicenters of the virus' transmission. The researchers also observed the precautions implicated to curb the virus' spread in those epicenters and compared the rates of coronavirus infection in Italy and New York City before and after rules regarding face masks and covering were put in place.

The researchers found that "airborne transmission" appears to be "the dominant route for infection" from the new coronavirus, according to the study. In addition, they found that coronavirus infection trends changed once governments enforced mask-wearing rules in Italy in April 6 and in New York City on April 17.

In New York, for instance, the daily new infection rate dropped by 3% per day after a policy requiring that people wear face masks or coverings in public took effect, the researchers found. Overall, the researchers estimated that requirements related to face masks and coverings "significantly reduced the number of infections … by over 78,000 in Italy from April 6 to May 9 and over 66,000 in New York City from April 17 to May 9."

Further, the researchers concluded that "[f]ace covering prevents both airborne transmission by blocking atomization and inhalation of virus-bearing aerosols and contact transmission by blocking viral shedding of droplets." Based on their findings, they wrote that CDC and the World Health Organization should enforce stricter policies on wearing face masks or coverings to further curb the novel coronavirus' spread. "The current mitigation measures, such as social distancing, quarantine, and isolation implemented in the United States, are insufficient by themselves in protecting the public," the researchers wrote.

Separately, Richard Stutt, a researcher at the University of Cambridge, on Wednesday published a model in the Proceedings of the Royal Society A that showed widespread use of face masks and coverings can help to reduce the new coronavirus' spread—even if the masks or coverings don't provide complete protection against droplets that may contain the pathogen. Stutt said wearing face masks or coverings can help to significantly curb the coronavirus' transmission when paired with lockdown orders.

"You can do lockdown, you can do masks, but you get the best result when you combine them," Stutt said.

In addition, a review of 172 observational studies published earlier this month in The Lancet also concluded that wearing face masks or coverings can help curb the risk of coronavirus infection and transmission, the Post reports. Holger Schünemann, a co-author of the review and an epidemiologist and physician at McMaster University, said the review indicated that, "n multiple ways … the use of masks is highly protective in health care and community settings."

 

[sweetiepie]

KNN basically it is chicken and egg lo KNN having a layer of protection definitely leeduce airborne transmission if the bacterial & virus did not or cannot cling on to the mask but same time if not handled properly the wearer will increase his own risk KNN now pap want to protect others but prefer to risk the wearer KNN if pap follow boss advice it will mean protecting ownself but risking others KNN

 

[laksaboy]

Mask or no mask, better demand compensation from the root cause:

 

[Leongsam]

http://www.advisory.com/daily-briefing/2020/06/16/mask-covid


Research shows wearing masks can significantly reduce risk of coronavirus transmission
However, new research could support some experts' and officials' calls for a more sweeping policy regarding face masks and coverings to curb the virus' spread, the Washington Post reports.

For instance, a study published Thursday in the Proceedings of the National Academy of Sciences (PNAS) found that requiring people to wear masks in epicenters of new coronavirus cases may have prevented tens of thousands of infections from the virus.

For the study, researchers examined how the new coronavirus is transmitted by reviewing infection trends in Wuhan, China; Italy; and New York City—all of which were early epicenters of the virus' transmission. The researchers also observed the precautions implicated to curb the virus' spread in those epicenters and compared the rates of coronavirus infection in Italy and New York City before and after rules regarding face masks and covering were put in place.

The researchers found that "airborne transmission" appears to be "the dominant route for infection" from the new coronavirus, according to the study. In addition, they found that coronavirus infection trends changed once governments enforced mask-wearing rules in Italy in April 6 and in New York City on April 17.

In New York, for instance, the daily new infection rate dropped by 3% per day after a policy requiring that people wear face masks or coverings in public took effect, the researchers found. Overall, the researchers estimated that requirements related to face masks and coverings "significantly reduced the number of infections … by over 78,000 in Italy from April 6 to May 9 and over 66,000 in New York City from April 17 to May 9."

Further, the researchers concluded that "[f]ace covering prevents both airborne transmission by blocking atomization and inhalation of virus-bearing aerosols and contact transmission by blocking viral shedding of droplets." Based on their findings, they wrote that CDC and the World Health Organization should enforce stricter policies on wearing face masks or coverings to further curb the novel coronavirus' spread. "The current mitigation measures, such as social distancing, quarantine, and isolation implemented in the United States, are insufficient by themselves in protecting the public," the researchers wrote.

Separately, Richard Stutt, a researcher at the University of Cambridge, on Wednesday published a model in the Proceedings of the Royal Society A that showed widespread use of face masks and coverings can help to reduce the new coronavirus' spread—even if the masks or coverings don't provide complete protection against droplets that may contain the pathogen. Stutt said wearing face masks or coverings can help to significantly curb the coronavirus' transmission when paired with lockdown orders.

"You can do lockdown, you can do masks, but you get the best result when you combine them," Stutt said.

In addition, a review of 172 observational studies published earlier this month in The Lancet also concluded that wearing face masks or coverings can help curb the risk of coronavirus infection and transmission, the Post reports. Holger Schünemann, a co-author of the review and an epidemiologist and physician at McMaster University, said the review indicated that, "n multiple ways … the use of masks is highly protective in health care and community settings."

Typical flawed science because no direct relation between cause and effect is established. The premise "Infections dropped when masks were introduced" without knowing what other variables came into play simply cannot hold water without further investigation.

I find that mankind has actually regressed when it comes to using scientific rigor to establish the facts. We have started winding back the clock where political doctrines dictate what can and cannot be debated or discussed. It's like the dark ages when anyone who contradicted the teachings of the church would pay a heavy penalty. The new players are interest groups like the climate change warriors and the BLM movement. Try publishing an article that suggests that climate change isn't man made and that the blacks actually have lower IQs and see where that leads.

https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation

In statistics, the phrase "correlation does not imply causation" refers to the inability to legitimately deduce a cause-and-effect relationship between two variables solely on the basis of an observed association or correlation between them.[1][2] The idea that "correlation implies causation" is an example of a questionable-cause logical fallacy, in which two events occurring together are taken to have established a cause-and-effect relationship. This fallacy is also known by the Latin phrase cum hoc ergo propter hoc ("with this, therefore because of this"). This differs from the fallacy known as post hoc ergo propter hoc ("after this, therefore because of this"), in which an event following another is seen as a necessary consequence of the former event.

In a widely studied example of the difficulties this possibility of this statistical fallacy poses in deciding cause, numerous epidemiological studies showed that women taking combined hormone replacement therapy (HRT) also had a lower-than-average incidence of coronary heart disease (CHD), leading doctors to propose that HRT was protective against CHD. But later randomized controlled trials showed that use of HRT led to a small but statistically significant increase in the risk of CHD.

 

[zhihau]

These reusable masks are good for trapping the droplets when you cough/sneeze at best.

 

[tanwahtiu]

Keyboard medical reviewers write shits...

Only way yo stop inhaling virus is a filter, thats it....

Aircon unit gas filter and it works, vacuum clearners, car air suction has filter.... blah blah...

Any engines sucking in air has filters...

Dickhead u twit...

rcreader.com

Masks Don’t Work: A Review of Science Relevant to COVID-19 Social Policy
Author T
Todd McGreevy

25-32 minutes


Masks and respirators do not work.

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.

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% 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:

1. Most respiratory viruses are as infective in humans as in tissue culture having optimal laboratory susceptibility
2. It is believed that a single virion can be enough to induce illness in the host
3. The 50-percent probability MID (“TCID50”) has variably been found to be in the range 100−1000 virions
4. There are typically 10 to 3rd power − 10 to 7th power virions per aerolized influenza droplet with diameter 1 μm − 10 μm
5. The 50-percent probability MID easily fits into a single (one) aerolized droplet
6. For further background:
7. A classic description of dose-response assessment is provided by Haas (1993).
8. 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.
9. 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.”
10. 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]:

1. 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.
2. Mask compliance and mask adjustment habits would be unknown.
3. Mask-wearing is associated (correlated) with several other health behaviors; see Wada (2012).
4. The results would not be transferable, because of differing cultural habits.
5. Compliance is achieved by fear, and individuals can habituate to fear-based propaganda, and can have disparate basic responses.
6. Monitoring and compliance measurement are near-impossible, and subject to large errors.
7. Self-reporting (such as in surveys) is notoriously biased, because individuals have the self-interested belief that their efforts are useful.
8. Progression of the epidemic is not verified with reliable tests on large population samples, and generally relies on non-representative hospital visits or admissions.
9. 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:

1. Do used and loaded masks become sources of enhanced transmission, for the wearer and others?
2. Do masks become collectors and retainers of pathogens that the mask wearer would otherwise avoid when breathing without a mask?
3. Are large droplets captured by a mask atomized or aerolized into breathable components? Can virions escape an evaporating droplet stuck to a mask fiber?
4. What are the dangers of bacterial growth on a used and loaded mask?
5. How do pathogen-laden droplets interact with environmental dust and aerosols captured on the mask?
6. What are long-term health effects on HCW, such as headaches, arising from impeded breathing?
7. Are there negative social consequences to a masked society?
8. Are there negative psychological consequences to wearing a mask, as a fear-based behavioral modification?
9. What are the environmental consequences of mask manufacturing and disposal?
10. 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.

 

[syed putra]

I will use it anyway otherwise they may bar you from entering certain shops and offices.
Their reason? I may be spreading the disease without one.

 

[Leongsam]

Keyboard medical reviewers write shits...

Only way yo stop inhaling virus is a filter, thats it....

Aircon unit gas filter and it works, vacuum clearners, car air suction has filter.... blah blah...

Any engines sucking in air has filters...

Dickhead u twit...

The problem is that the cloth masks don't filter anything. Instead they incubate.

 

[Leongsam]

I will use it anyway otherwise they may bar you from entering certain shops and offices.
Their reason? I may be spreading the disease without one.

That's because flawed science has become policy.

blog.chron.com

The top 10 most spectacularly wrong widely held scientific theories
By Eric Berger on November 24, 2010 at 8:34 AM

5-7 minutes



One of the very best things about science is that the discipline is self-correcting. A scientist makes a set of observations about nature, and then devises a theory to fit those observations.

Other scientists then test the theory, and if it withstands scrutiny it becomes widely accepted. At any point in the future, if contravening evidence emerges, the original theory is discarded. At its essence, and though in practice it’s more messy, this is how science works.

Needless to say there have been a lot of theories discarded along the way. The following represents my best efforts to select the 10 most spectacularly wrong scientific theories.

To qualify for the list, a large number of scientists at any given time must have subscribed to the particular theory before it was eventually discarded. Thus a long list of pseudoscientific ideas, crackpot though they might be, didn’t make the list.

1. Geocentric universe: The concept that the Earth was at the center of the universe dates back to at least 600 B.C. with Greek philosophers who proposed cosmologies of the Sun, Moon and other heavenly bodies orbiting the Earth. The most famous contortion of the system was Ptolemy’s epicycles to explain the retrograde motion of Mars. This is a prime example of fitting scientific evidence into preconceived notions. The theory was disproven with the publication of Nicholas Copernicus’ De revolutionibus orbium coelestium in 1543.

2. Miasmatic theory of disease: This theory holds that diseases such as cholera, chlamydia or the Black Death were caused by a miasma (ancient Greek: “pollution”), a noxious form of “bad air”. This concept was not disposed of until the late 1800s, with the rise of the germ theory of disease. Miasma was considered to be a poisonous vapor or mist filled with particles from decomposed matter that caused illnesses. It was identifiable by its foul smell.

3. Luminiferous aether: Assumed to exist for much of the 19th century, the theory held that a “medium” of aether pervaded the universe through which light could propagate. The celebrated Michelson-Morley experiment in 1887 was the first to provide hard evidence that aether did not exist, and the theory lost all popularity among scientists by the

1920s. A photo of the aether appears below.

4. Stress theory of ulcers: As peptic ulcers became more common in the 20th century, doctors increasingly linked them to the stress of modern life. Medical advice during the latter half of the 20th century was, essentially, for patients to take antacids and modify their lifestyle. In the 1980s Australian clinical researcher Barry Marshal discovered that the bacterium H. pylori caused peptic ulcer disease, leading him to win a Nobel Prize in 2005.

5. Immovable continents: Prior to the middle of the 20th century scientists believed the Earth’s continents were stable and did not move. This began to change in 1912 with Alfred Wegener’s formulation of the continental drift theory, and later and more properly the elucidation of plate tectonics during the 1950s and 1960s.

6. Phlogiston: Arising in the mid-17th century, physicians conjured up the existence of a fire-like element called “phlogiston”, which was contained within combustible bodies and released during combustion. Charcoal, for example, left little residue upon burning because it is nearly pure phlogiston. Experiments in the mid-1700s led chemists to conclude the theory was false, giving birth to the field of modern chemistry.

Phlogiston in nearly its most pure form?

7. The “four humours” theory of human physiology: From Hippocrates onward, the humoral theory was adopted by Greek, Roman and Islamic physicians, and became the most commonly held view of the human body among European physicians until the advent of modern medical research in the 19th century. The four humours of Hippocratic medicine were black bile, yellow bile, phlegm and blood.

8. Static universe: Prior to the observations made by astronomer Edwin Hubble during 1920s, scientists believed the universe was static, neither expanding nor contracting. Hubble found that distant objects in the universe were moving more quickly away than nearby ones. Very recently, in 1999, scientists unexpectedly found that not only was the universe expanding, but its expansion was accelerating.

9. A young Earth: In the mid-1800s many scientists, including Lord Kelvin, believed the Earth to be just 20 million to 40 million years old. It was around that time that geologists such as Charles Lyell began to believe that the Earth was much older, and this conformed to the views of biologists such as Charles Darwin, who needed a much older Earth for evolution to unfold. It wasn’t until the middle of the 20th century that scientists came to the accepted conclusion today that the Earth is about 4.55 billion years old.

10. The Earth is flat. Actually, this one doesn’t belong on the list but I put it here to prove a point. While there’s a popular belief that “flat earth” was somehow a widely held “scientific” idea, Greeks such as Aristotle knew the Earth was round, as did Thomas Aquinas. In short, most scholarship suggests learned men and women from the dawn of antiquity knew the Earth was round. So science gets a pass on this one.

 

[sam heng]

Doesn't matter true or not in Singapore context. You can argue with the garment and cite this article when paying them the fine.