Quantitative errors in the Cochrane review on "Physical interventions to interrupt or reduce the spread of respiratory viruses"

Abstract The COVID-19 pandemic has brought a heightened sense of urgency in the scientific community regarding the need to advance understanding and prevention of pathogen transmission, particularly concerning infectious airborne particles and the utility of various preventive strategies in reducing the risk of infection. There are extensive studies validating scientific understanding about the behavior of larger (droplets) and smaller (aerosols) particles in disease transmission and the dosimetry of particles in the respiratory track. Similarly, modalities for respiratory protection against particles in the size range spanned by infectious particles, such as N95 respirators, are available and known to be efficacious with tested standards for harm reduction across environments including physical, chemical and biological hazards. Even though multiple studies also confirm their protective effect when adopted in healthcare and public settings for infection prevention, overall, studies of protocols of their adoption over the last several decades in both clinical trials and observational studies have not provided as clear an understanding. Here we demonstrate that these studies are strongly biased towards the null by infections resulting from transmission outside of the investigated environments and study participants. Such study limitations are frequently mis-stated as not influencing the conclusions of research on respiratory protection. The reason for the failure to properly analyze the studies is that the standard analytical equations used do not correctly represent the random variables that play a role in the study results. By correcting the mathematical representation and the equations that result from them, we demonstrate that conclusions drawn from these studies are strongly biased and much more uncertain than is acknowledged, providing almost no useful information. Even with all these limitations, we show that existing results, when outcome measures are properly analyzed, consistently point to the benefit of precautionary measures such as N95 respirators over medical masks, and masking over its absence. We also show that correcting manifest errors of widely reported meta-analyses also leads to statistically significant estimates. Our results have implications for the design of studies and analyses on the effectiveness of respiratory protection and on using existing evidence for policy guidelines for infection control.