Pratyush K. Kollepara, Alexander F. Siegenfeld, Nassim N. Taleb, Yaneer Bar-Yam
Face masks have been widely used as a protective measure against COVID-19. However, pre-pandemic experimental studies have produced mixed results regarding their effectiveness against respiratory viruses, leading to confusion over whether masks protect the wearer, or only those with whom the wearer interacts. Such confusion may have contributed to organizations such as the WHO and CDC initially not recommending that the general public wear masks. Here, we show that studies that did not find surgical masks to be effective were under-powered to such an extent that even if masks were 100% effective, the studies in question would still have been unlikely to find a statistically significant effect. Thus, such studies should not be interpreted as providing evidence against masks. We also provide a framework for understanding the effect of masks on the probability of infection for single and repeated exposures. The framework demonstrates that the impact of wearing a mask more frequently compounds super-linearly, as can the impact of both the susceptible and infected individual wearing a mask. This work shows that current research is consistent with recommendations for using masks at a population level in regions in which there is transmission of COVID-19, and that nonlinear effects and statistical considerations regarding the percentage of exposures for which the mask is worn must be taken into account when designing empirical studies and interpreting their results.
Read the full article at: arxiv.org