Mandatory Masks: A Denial of Science

This is a long & exhaustive technical study which was quite tedious to copy and paste. You can either wade through it all to confirm it’s scientific validity, as I had to do, or you can accept what has always been known. The Covid mask is of no utility whatsoever, it is simply a means of instilling fear and gaining submission to totalitarian authorities.

Masks Don’t Work
A review of science relevant to COVID-19 social policy
Denis G. Rancourt, PhD
Researcher, Ontario Civil Liberties Association (ocla.ca)
Working report, published at Research Gate
(https://www.researchgate.net/profile/D_Rancourt)
April 2020

Summary / Abstract 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.
doi:10.1017/S0950268809991658
https://www.cambridge.org/core/journals/epidemiology-and-infection/article/facemasks-to-prevent-transmission-of-influenza-virus-a-systematicreview/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, cmaj.150835; DOI: 10.1503/cmaj.150835
https://www.cmaj.ca/content/188/8/567
“We identified 6 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://doi.org/10.1093/cid/cix681
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. doi:10.1001/jama.2019.11645
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://doi.org/10.1111/jebm.12381
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
4
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.
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.
6
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 dependant 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 humidsummer 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
7
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 modelling 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 modelling 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 centres, and onboard 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
concentrations ranged from 5800 to 37 000 genome copies m−3
. 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. Modelling 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 1 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 8 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%-probability MID (“TCID50”) has variably been found to be in the range 100−1000
virions
• there are typically 103−107 virions per aerolized influenza droplet with diameter 1 μm −
10 μm
• the 50%-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% 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.
9
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 biasfree results:

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 behaviours; 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?
10
• 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
behavioural modification?
• What are the environmental consequences of mask manufacturing and disposal?
• Do the masks shed fibres 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 socialengineering 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.

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
Haas, C.N. et al. (1993) “Risk Assessment of Virus in Drinking Water”, Risk Analysis, 13: 545-552.
doi:10.1111/j.1539-6924.1993.tb00013.x
https://doi.org/10.1111/j.1539-6924.1993.tb00013.x
12
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/1aepidemiology/epidemic-theory
Lai, A. C. K. et al. (2012) “Effectiveness of facemasks to reduce exposure hazards for airborne
infections among general populations”, J. R. Soc. Interface. 9938–948
http://doi.org/10.1098/rsif.2011.0537
Leung, N.H.L. et al. (2020) “Respiratory virus shedding in exhaled breath and efficacy of face
masks”, Nature Medicine (2020). https://doi.org/10.1038/s41591-020-0843-2
Lowen, A. C. et al. (2007) “Influenza Virus Transmission Is Dependent on Relative Humidity and
Temperature”, PLoS Pathog 3(10): e151. https://doi.org/10.1371/journal.ppat.0030151
Paules, C. and Subbarao, S. (2017) “Influenza”, Lancet, Seminar| Volume 390, ISSUE 10095,
P697-708, August 12, 2017.
http://dx.doi.org/10.1016/S0140-6736(17)30129-0
Sande, van der, M. et al. (2008) “Professional and Home-Made Face Masks Reduce Exposure to
Respiratory Infections among the General Population”, PLoS ONE 3(7): e2618.
doi:10.1371/journal.pone.0002618
https://doi.org/10.1371/journal.pone.0002618
Shaman, J. et al. (2010) “Absolute Humidity and the Seasonal Onset of Influenza in the
Continental United States”, PLoS Biol 8(2): e1000316.
https://doi.org/10.1371/journal.pbio.1000316
Tracht, S. M. et al. (2010) “Mathematical Modeling of the Effectiveness of Facemasks in
Reducing the Spread of Novel Influenza A (H1N1)”, PLoS ONE 5(2): e9018.
doi:10.1371/journal.pone.0009018
https://doi.org/10.1371/journal.pone.0009018
Viboud C. et al. (2010) “Preliminary Estimates of Mortality and Years of Life Lost Associated
with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons”, PLoS
Curr. 2010; 2:RRN1153. Published 2010 Mar 20. doi:10.1371/currents.rrn1153
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2843747/
Wada, K. et al. (2012) “Wearing face masks in public during the influenza season may reflect
other positive hygiene practices in Japan”, BMC Public Health 12, 1065 (2012).
https://doi.org/10.1186/1471-2458-12-1065
13
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

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