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

Abstract

The COVID-19 pandemic has heightened the urgency to understand and prevent pathogen transmission, specifically regarding infectious airborne particles. Extensive studies validate the understanding of larger (droplets) and smaller (aerosols) particles in disease transmission. Similarly, N95 respirators, and other forms of respiratory protection, have proven efficacy in reducing the risk of infection across various environments. Even though multiple studies confirm their protective effect when adopted in healthcare and public settings for infection prevention, studies on their adoption over the last several decades in both clinical trials and observational studies have not provided as clear an understanding. Here we show that the standard analytical equations used in the analysis of these studies do not accurately represent the random variables impacting study results. By correcting these equations, it is demonstrated that conclusions drawn from these studies are heavily biased and uncertain, providing little useful information. Despite these limitations, we show that when outcome measures are properly analyzed, existing results consistently point to the benefit of N95 respirators over medical masks, and masking over its absence. Correcting errors in widely reported meta-analyses also yields statistically significant estimates. These findings have important implications for study design and using existing evidence for infection control policy guidelines.