If you rely on the MSM as your source for news, you may be inclined to believe that a new non-peer-reviewed study on masks, released recently on 9/1/2021, is the holy grail of evidence that will end the mask debate once and for all. Just look at these headlines:
Largest study of masks yet details their importance in fighting Covid-19
“A study involving more than 340,000 people in Bangladesh offers some of the strongest real-world evidence yet that mask use can help communities slow the spread of Covid-19.”
Huge, gold-standard study shows unequivocally that surgical masks work to reduce coronavirus spread
“The results — from the highest-quality, gold-standard type of clinical trial, known as a randomized controlled trial — should “end any scientific debate” on whether masks are effective in battling the spread of COVID-19, Jason Abaluck, an economist at Yale and one of the authors who helped lead the study, told The Washington Post.“
The study that ‘should basically end any scientific debate’ about masks
“A massive randomized trial on how well masks hold up against symptomatic COVID-19 infections may be one of the most crucial studies of the coronavirus pandemic because it was able to solve the tricky issue of examining mask-wearing at a community level rather than an individual one.”
“Either way, Abaluck is pretty confident about the research, arguing that it “should basically end any scientific debate about whether masks can be effective in combating [COVID-19] at the population level” and calling it “a nail in the coffin” for anti-mask arguments.”
It’s nice that Jason Abaluck, co-author of the study, is so confident in his own work. He gives himself and his team very high praise indeed. However, is his study the end-all, be-all evidence that he and the MSM promote it to be?
A few highlights from the study itself may provide the answer:
The Impact of Community Masking on Covid-19: A Cluster-Randomized Trial in Bangladesh
“The proportion of individuals with COVID-like symptoms was 7.62% (N=13,273) in the intervention arm and 8.62% (N=13,893) in the control arm. Blood samples were collected
from N=10,952 consenting, symptomatic individuals. Adjusting for baseline covariates, the intervention reduced symptomatic seroprevalence by 9.3% (adjusted prevalence ratio (aPR) = 0.91 [0.82, 1.00]; control prevalence 0.76%; treatment prevalence 0.68%). In villages randomized to surgical masks (n = 200), the relative reduction was 11.2% overall (aPR = 0.89 [0.78, 1.00]) and 34.7% among individuals 60+ (aPR = 0.65 [0.46, 0.85]). No adverse events were reported.”
“We powered our intervention around the primary outcome of symptomatic seroprevalence. During our intervention, we collected survey data on the prevalence of WHO-defined COVID-19 symptoms from all available study participants, and then collected blood samples at endline from those who reported symptoms anytime during the 8-week study duration. Our trial is therefore designed to track the fraction of individuals who are both symptomatic and seropositive.”
Our primary outcome was symptomatic seroprevalence for SARS-CoV-2. Our secondary outcomes were prevalence of proper mask-wearing, physical distancing, and symptoms consistent with COVID-19. For COVID-19 symptoms, we used the symptoms that correspond to the WHO case definition of probable COVID-19 given epidemiological risk factors: (a) fever and cough; (b) three or more of the following symptoms (fever, cough, general weakness/fatigue, headache, myalgia, sore throat, coryza, dyspnea, anorexia/nausea/vomiting, diarrhea, altered mental status); or (c) loss of taste or smell. Seropositivity was defined by having detectable IgG antibodies against SARS-CoV-2.”
“3.6 Symptomatic SARS-CoV-2 Testing
Symptom reporting The owner of the household’s primary phone completed surveys by phone or in-person at weeks 5 and 9 after the start of the intervention. They were asked to report symptoms experienced by any household member that occurred in the previous week and over the previous month. COVID-like symptoms were defined by whether they were consistent with the WHO COVID-19 case definition for suspected or probable cases with an epidemiological link .
SARS-CoV-2 testing Blood samples were tested for the presence of IgG antibodies against SARS-CoV-2 using the SCoV-2 Detect™ IgG ELISA kit (InBios, Seattle, Washington). This assay detects IgG antibodies against the spike protein subunit (S1) of SARS-CoV-2. The assays were performed according to the manufacturer’s instructions. Briefly, serum samples were diluted 1:100 with sample dilution buffer. 50 microliters of diluted specimens were added to the SCoV-2 antigen-coated microtiter strip plates. After one hour of incubation at 37°C, the plate was washed six times with wash buffer, and conjugate solution was added to each well. The plate was incubated for another 30 minutes at 37°C and washed six times with wash buffer. 75 microliters of liquid TMB substrate were added to all wells followed by 20 minutes of incubation in the dark at room temperature before the reaction was stopped. The absorbance was read on a microplate reader at 450nm (GloMax® Microplate Reader, Promega Corporation, Madison, WI). After calibration according to positive, negative, and cut-off controls, the immunological status ratio (ISR) was calculated as the ratio of optical density divided by the cut-off value. Samples were considered positive if the ISR value was determined to be at least 1.1. Samples with an ISR value 0.9 or below were considered negative. Samples with equivocal ISR values were retested in duplicate, and resulting ISR values were averaged. Individuals were coded as symptomatic seropositive if they reported symptoms consistent with the WHO COVID-19 case definition, their blood was collected, and the antibody test was positive.
Symptomatic Seroprevalence Among the 335,382 participants who completed symptom surveys, 27,166 (8.1%) reported experiencing COVID-like illnesses during the study period. More participants in the control villages reported incident COVID-like illnesses (n=13,893, 8.6%) compared with participants in the intervention villages (n=13,273, 7.6%). Over one-third (40.3%) of symptomatic participants agreed to blood collection. Omitting symptomatic participants who did not consent to blood collection, symptomatic seroprevalence was 0.76% in control villages and 0.68% in the intervention villages. Because these numbers omit non-consenters, it is likely that the true rates of symptomatic seroprevalence are substantially higher (perhaps by 2.5 times, if non-consenters have similar seroprevalence to consenters).”
“We found clear evidence that surgical masks are effective in reducing symptomatic seroprevalence of SARS-CoV-2; while cloth masks clearly reduce symptoms, we cannot reject that they have zero or only a small impact on symptomatic SARS-CoV-2 infections (perhaps reducing symptoms of other respiratory diseases). “
“Our study has several limitations. The distinct appearance of project-associated masks and elevated mask-wearing in intervention villages made it impossible to blind surveillance staff to study arm assignment (although the staff were not informed of the exact purpose of the study). Even though surveillance staff were plain-clothed and were instructed to remain discreet, community members could have recognized that they were being observed and changed their behavior. Additionally, survey respondents could have changed their likelihood of reporting symptoms in places where mask-wearing was more widespread. We might expect this to bias us towards higher symptomatic rates in treatment areas. While we confirm that blood consent rates are not significantly different in the treatment and control group and are comparable across all demographic groups, we cannot rule out that the composition of consenters differed between the treatment and control groups. The slightly higher point estimate for consent in the treatment group again biases us away from finding an effect, since it raises symptomatic seroprevalence in the treatment group. Although control villages were at least 2 km from intervention villages, adults from control villages may have come to intervention villages to receive masks, reducing the apparent impact of the intervention. While we did not directly assess harms in this study, there could be costs resulting from discomfort with increased mask-wearing, adverse health effects such as dermatitis or headaches, or impaired communication.”
“We selected the WHO case definition of COVID-19 for its sensitivity, though its limited specificity may imply that the impact of masks on symptoms comes partly from non-SARS-CoV-2 respiratory infections. “
- The proportion of individuals with COVID-like symptoms was 7.62% (N=13,273) in the intervention arm and 8.62% (N=13,893) in the control arm
- They powered their intervention around the primary outcome of symptomatic seroprevalence
- They collected survey data on the prevalence of WHO-defined COVID-19 symptoms from all available study participants
- They then collected blood samples at endline from those who reported symptoms anytime during the 8-week study duration
- For COVID-19 symptoms, they used the symptoms that correspond to the WHO case definition of probable COVID-19 given epidemiological risk factors
- These symptoms included:
- fever and cough;
- three or more of the following symptoms (fever, cough, general weakness/fatigue, headache, myalgia, sore throat, coryza, dyspnea, anorexia/nausea/vomiting, diarrhea, altered mental status); or
- loss of taste or smell
- Blood samples were tested for the presence of IgG antibodies against SARS-CoV-2 using the SCoV-2 Detect™ IgG ELISA kit (InBios)
A Quick Detour on the SCoV-2 Detect™ IgG ELISA kit (InBios):
“The SCoV-2 Detect™ IgG ELISA is intended as an aid in identifying individuals with an adaptive immune
response to SARS-CoV-2, indicating recent or prior infection. At this time, it is unknown for how long antibodies persist following infection and if the presence of antibodies confers protective immunity. The SCoV-2 Detect™ IgG ELISA should not be used to diagnose or exclude acute SARS-CoV-2 infection.”
“False positive results for SCoV-2 Detect™ IgG ELISA may occur due to cross-reactivity from pre-existing antibodies or other possible causes.”
- The assay should not be used to diagnose or exclude acute infection. Results are not intended to be used as the sole basis for patient management decisions.
- A positive result may not indicate previous SARS-CoV-2 infection. Consider other information, including clinical history and local disease prevalence, in assessing the need for a second but different serology test to confirm an immune response.
- A negative result for an individual subject indicates absence of detectable anti-SARS-CoV-2 antibodies.
- Negative results do not preclude SARS-CoV-2 infection and should not be used as the sole basis for patient management decisions. A negative result can occur if the quantity of the anti-SARS-CoV-2 antibodies present in the specimen is below the detection limits of the assay, or the antibodies that are detected are not present during the stage of disease in which a sample is collected.
- It is not known at this time if the presence of antibodies to SARS-CoV-2 confers immunity to infection.
- False positive results due to cross-reactivity with antibodies to other coronaviruses can occur.
According to the EUA for the SCoV-2 Detect™ IgG ELISA kit, it is intended as an aid and should not be used to diagnose. It is not known if antibodies persist or if they confer immunity. False-positives occur due to cross-reactivity to existing antibodies, antibodies to other “Coronaviruses,” and other possible causes (there goes SPECIFICITY). A positive result may not indicate a previous “SARS-COV-2” infection. In other words, the results from this test are absolutely MEANINGLESS.
End of Detour
- Individuals were coded as symptomatic seropositive if they reported symptoms consistent with the WHO COVID-19 case definition, their blood was collected, and the antibody test was positive
- The control villages reported incident COVID-like illnesses (n=13,893, 8.6%) compared with participants in the intervention villages (n=13,273, 7.6%) FOR A WHOPPING 1% DIFFERENCE
- Symptomatic seroprevalence was 0.76% in control villages and 0.68% in the intervention villages FOR A WHOPPING 0.08% DIFFERENCE
- They admit that they cannot reject that cloth masks have zero or only a small impact on symptomatic “SARS-CoV-2” infections
- They admit to several limitations of their study such as:
- It was impossible to blind surveillance staff to study arm assignment
- Community members could have recognized that they were being observed and changed their behavior
- Survey respondents could have changed their likelihood of reporting symptoms in places where mask-wearing was more widespread
- They admit they may have a bias towards higher symptomatic rates in treatment areas
- They admit that there could be costs resulting from discomfort with increased mask-wearing, adverse health effects such as dermatitis or headaches, or impaired communication
- They selected the WHO case definition of COVID-19 for its sensitivity, though its limited specificity may imply that the impact of masks on symptoms comes partly from non-SARS-CoV-2 respiratory infections
It is clear that this study has several limitations and the results appear statistically insignificant. I admit I am not a statistics guy, but a 0.08% difference seems to me to be quite small.
However, beyond the unimpressive statistics lies a much deeper problem with this study. The researchers based their results on symptomatic seroprevalence. They did not use the “gold standard” PCR test to label anyone positive. Instead, they looked at a list of clinical symptoms from the WHO which overlap with numerous other diseases and used an antibody test to label probable “Covid” cases. Unfortunately for these researchers, they must have missed the sections in the EUA for the antibody test where the manufacturers admit that it can not diagnose one positive for previous infection nor tell if the antibodies detected relate to “SARS-COV-2” at all. In the end, all the data from this study is built off of highly inaccurate test results and non-distinguishable clinical symptoms.
In other words, this study is scientific FRAUD and is not the end of the scientific debate on masks.
Not even close.