"When you’re in the middle of an outbreak, wearing a
mask might make people feel a little bit better and
it might even block a droplet"
but it’s not providing the perfect protection that
people think that it is. And, often, there are
unintended consequences — people keep fiddling with
the mask and they keep touching their face.”
What is the
average size of a virus?
Viruses are much smaller than
bacteria. The smallest viruses are about 17
nanometers in diameter, and the largest viruses are
up to 1,000 nanometers in length. By comparison, the
bacterium E. coli is 2,000 nanometers in
length, a cell nucleus is 2,800 nanometers in
diameter, and an average eukaryotic cell is 10,000
nanometers in length. The following are the average
sizes of some specific common viruses (note: 1
nanometer is equal to 0.001 micrometers; the head of
a pin is about 1,000 micrometers in diameter):
Virus
Size (in
nanometers)
Size (in
micrometers)
Smallpox
250
0.25
Tobacco mosaic (seen in
plants)
240
0.24
Rabies
150
0.15
Influenza
100
0.1
Bacteriophage
95
0.095
Common cold
70
0.07
Covid-19
50
0.05
Polio
27
0.027
Parvovirus (often seen in
domesticated animals)
20
0.02
Fauci said masks were not 'really effective' at
blocking virus, emails reveal
Lawrence Richard
Dr. Anthony Fauci said in an email
correspondence last year that face masks aren’t
needed unless an individual was sick and that
the coronavirus was able to pass through
personal face masks easily.
Dr. Anthony Fauci said in an email correspondence
last year that face masks aren’t needed unless an
individual was sick and that the coronavirus was
able to pass through personal face masks easily.
“Masks are really for infected people to prevent
them from spreading [an] infection to people who are
not infected rather than protecting uninfected
people from acquiring infection,” Fauci wrote to who
is believed to be Obama-era Health and Human
Services Secretary Sylvia Burwell in February 2020.
Fauci, also the director of the National
Institute of Allergy and Infectious Diseases, added:
“The typical mask you buy in the drug store is not
really effective in keeping out [the] virus, which
is small enough to pass through the material. It
might, however, provide some slight benefit in
[keeping] out gross droplets if someone coughs or
sneezes on you.”
The country’s leading infectious disease expert
ultimately did not recommend she wear a face mask.
“I do not recommend that you wear a mask,
particularly since you are going to a [very] low-risk
location. Your instincts are correct, money is best
spent on medical countermeasures such as diagnostics and
vaccines.”
“Safe travels,” he added, at a time when government
officials were urging states to limit travel.
The email was shared online after BuzzFeed News
published more than
3,200 pages of Fauci's emails written from January 2020
to June 2020, and the Washington Post
published
866 pages of his emails written between March
2020 and April 2020.
The correspondence, which was released to the public
on Tuesday, sparked backlash on social media.
The common cold virus is .07
micrometers in size - The Covid-19 virus is .05
micrometers in size and the Covid-19 particles are
smaller than the
common cold coronavirus
Background: Health care
workers outside surgical suites in Asia use surgical-type
face masks commonly. Prevention of upper respiratory
infection is one reason given, although evidence of
effectiveness is lacking.
Methods: Health care
workers in a tertiary care hospital in Japan were randomized
into 2 groups: 1 that wore face masks and 1 that did not.
They provided information about demographics, health habits,
and quality of life. Participants recorded symptoms daily
for 77 consecutive days, starting in January 2008. Presence
of a cold was determined based on a previously validated
measure of self-reported symptoms. The number of colds
between groups was compared, as were risk factors for
experiencing cold symptoms.
Results: Thirty-two
health care workers completed the study, resulting in 2464
subject days. There were 2 colds during this time period, 1
in each group. Of the 8 symptoms recorded daily, subjects in
the mask group were significantly more likely to experience
headache during the study period (P < .05). Subjects living
with children were more likely to have high cold severity
scores over the course of the study.
Conclusion: Face mask use in
health care workers has not been demonstrated to provide
benefit in terms of cold symptoms or getting colds. A larger
study is needed to definitively establish noninferiority of
no mask use.
The common
cold virus is .07 micrometers in size - The Covid-19
virus is .05 micrometers in size and the particles
are smaller than the common cold
coronavirus
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.
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.
The common cold virus is .07
micrometers in size - The Covid-19 virus is .05
micrometers in size and the particles are smaller
than the
common cold coronavirus
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
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
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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
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
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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
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Some people are calling
the convicted felons who were seen on multiple
Videos attacking Kyle Rittenhouse "Victims" - I
would ask them to
watch the Trial Videos in their entirety so they can see
their attacks caught on video and educate
themselves.
I decided to watch the
videos and to research this topic myself and
after watching those videos and examining other
items I found that people were calling these
criminals "Victims". I have made a few items
available for you to verify the truth for
yourself
These are the convicted
felons shown on video attacking Kyle Rittenhouse
Earned Credit Release
Date is provided for
guidance. Confirmation
can be sought by
contacting ADCRR.
It is important to note
that all Release Dates
are projected
and are subject to
change; confirm
with ADCRR Time
Computation Unit or the
Offender Information
Unit where the inmate is
housed for potential
changes
If you are a victim of
crime, please call or
email the Office of
Victim Services for
assistance with your
victim rights or
concerns: 602-542-1853
azvictims@azadc.gov
Details of inmate
offenses can be accessed
by reviewing the case
file at the Office of
the Clerk of the Court
where the case was
adjudicated.