Denis Rancourt, in familiar intellectually disciplined form, unmasks the substantial defects in the latest study mainstream media is lauding as ending the “masks-don't-work debate.” In his white paper “Do Face Masks Reduce COVID-19 Spread in Bangladesh? Are the Abaluck et al. Results Reliable?” (RCReader.com/y/mask10), Rancourt surgically dissects the study “The Impact of Community Masking on COVID-19: A Cluster-Randomized Trial in Bangladesh,” August 31, 2021, by Jason Abaluck, et al, Yale School of Management (RCReader.com/y/mask11). Rancourt does a thorough, highly technical deconstruction of the trial, unraveling the squishy science underpinning the study.
For science geeks, this analysis is riveting. For data lovers, this analysis is evidence-based and powerful not just in showing the specific flaws relative to the study's stated achievements, but as a case study itself for how so many white papers and studies are propped up rather than keeping to scientific methodology that has prevailed until now, jeopardizing trusted journals and peer-review processes essential to scientific integrity.
For example, cross-reactivity was not properly addressed in the study's parameters. There was no reference document for evaluating the assay used for detecting specific SARS-CoV-2 IgG antibodies, nor was it validated for the ability to independently distinguish between IgM and IgG antibodies. This matters, according to Denis, due to tests not approved for patients and “would be used to diagnose participants in a trial, as having COVID-19, without any clinical evaluation beyond self-reporting of symptoms with survey questions, in order to justify long-term application of a treatment to millions of people, which has known and unknown associated harms. (Rancourt 2021)”
The study was featured in the Washington Post, quoting one of the lead authors of the study, Jason Abaluck. “I think this should basically end any scientific debate about whether masks can be effective in combating COVID at the population level,” Jason Abaluck, an economist at Yale who helped lead the study, said in an interview, calling it “a nail in the coffin” of the arguments against masks.” (RCReader.com/y/mask12)
The study's summary states that it's randomized trial of community-level mask promotion in rural Bangladesh during COVID-19 shows that their “interventions tripled mask usage and reduced symptomatic SARS-CoV-2 infections, demonstrating that promoting community mask-wearing can improve public health.”
It is not surprising that the specific interventions tripled mask-wearing, but whether it prevented infection and/or transmission of SARS2, thus improving public health is a total stretch in this context.
The study implemented, publicly surveilled, and recorded impacts of “intervention measures” and “incentives” for 600 villages of 342,126 adults from November 2020 to April 2021, using cloth and surgical masks. Periodic blood samples were collected and analyzed for previous COVID infection.
Intervention measures and incentives (for 178,288 individuals) included “free masks, information on the importance of masking, role-modeling by community leaders with scheduled speeches and videos from the prime minister, in-person reminders for eight weeks that included scheduled daily text messages, social signaling, verbal commitments to increase mask-wearing, and village-level incentives for village leaders for increased mask-wearing, (the control group of 163,838 individuals did not receive interventions).” [It is relevant to note that alternative face-coverings were counted as complying with mask-wearing.]
It would seem all but guaranteed that increased mask-wearing would follow using strategies specifically designed for “low-resource, rural settings,” making this randomized-trial far less a study of mask efficacy and far more a study for best practices in behavior modification.
Denis expressed this best: “A trial in which the researchers spend significant resources to convince the non-control group to accept or adopt the treatment is not a 'randomized' trial, nor is it 'controlled.' Rather it is a trial in which one group is chosen to be intrusively manipulated to receive the treatment, whereas the other group is free from this manipulation.”
He further observed, “It is one thing to design and evaluate interventions intended to generate mask use, but it is quite another thing to measure the health impact of increased mask use alone, without introducing co-factors arsing from the interventions.”
After five months, mask-wearing remained 10 percentage points higher in the intervention group. The proportion of individuals with COVID-like symptoms was 7.62 percent (13,273 individuals) in the intervention group and 8.62 percent (13,893 individuals) in the control group. [Other mitigations were also included, such as distancing and isolation.]
The final conclusion is that cloth mask-wearing reported statistical zero difference between the intervention and control groups' instances of COVID-like symptoms, while the use of surgical masks showed a minor improvement of 11.2 percent in instances of COVID-like symptoms. Needless to say, the results are unpersuasive relative to the demonstration of efficacy of mask-wearing in preventing COVID-19. [The study reported some problems with blood samples being insufficient in quantity or could not be matched to individuals.]
Of interest is the financial component identified in the study's interventions and outcomes. “We estimate that a scaled version of our intervention being implemented in Bangladesh will cost between $10K and $52K per life saved, depending on what fraction of excess deaths are attributable to COVID-19. This is considerably lower than the value of a statistical life in Bangladesh ($205,000) and under severe outbreaks, is comparable to the most cost-efficient humanitarian programs at scale (e.g. distributing insecticide nets to prevent malaria costs $9,200 per life saved.”
