Why did experts delay mask-usage advisory, contributing to avoidable harm?
Updated: Jun 3
Experts and policy makers initially advised against mask usage to mitigate the spread of COVID-19, but many came around to it subsequently, after significant costs of the delay, in terms of infections and fatalities, had already been incurred. For example, the US Centre for Disease Control and Prevention originally advised the public against wearing masks during the covid-19 pandemic, but this advice was updated to extend to general public as well. The World Health Organization still recommends masks only for those with symptoms suggestive of covid-19, stating that masks should otherwise be reserved for healthcare workers.
What should be avoided/could be improved
1. The properties of the novel corona virus and its transmission were unfamiliar to scientists when it was discovered. While droplet transmission of the virus was established with evidence early on, the evidence for airborne transmission and efficacy of facemasks as a protective measure remained scarce and ambiguous. Absence of evidence was inferred as evidence of absence. This is a common logical trap which, unfortunately, affects experts as much as laymen.
2. One of the most frequently cited papers among experts regarding the benefits and harms of cloth is MacIntyre et al, 2015. The authors "caution against the use of cloth masks" for healthcare professionals compared to the use of surgical masks and regular procedures, based on an analysis of transmission in hospitals in Hanoi. It is important to note that the study did not have a "no mask" control group because it was deemed "unethical to ask participants to not wear a mask." The study does not inform policy pertaining to public mask wearing as compared to the absence of masks in a community setting, since there is not a "no mask" group. This exposes 2 key issues: a) constraints of research methods constraining outcomes of research and b) relative efficacy evaluations of protective measures being mistaken as absolute efficacy evaluations, even by experts.
3. There is the argument that without rigorous investigation and credible evidence, interventions may end up doing more harm than good. But rigor requires time, which is scarce when responding to a pandemic. Such trade-offs are complicated, and health and medicine experts may not be in the best position to make such trade-offs in face of ambiguity and uncertainty.
What is likely to work
1. The precautionary principle states that when faced with uncertainty and ambiguity, we should sometimes act without definitive evidence, just in case. But to avoid doing more harm than good with such interventions, positive asymmetries, as defined by Nassim Nicholas Taleb, must be leveraged. Positive asymmetries are actions for which the possibilities of negative outcomes are limited and acceptable, even when overall outcome probabilities are unknown. For example, even if cloth and DIY masks do not do much good, they can’t do much harm either, as long as supply of surgical masks are controlled for use by healthcare providers.
2. Evidence based medicine tends to focus predominantly on internal validity—whether primary research studies were “done right”—using tools to assess risk of bias and adequacy of statistical analysis. External validity relates to a different question: whether findings of primary studies done in a different population with a different disease or risk state are relevant to the current policy question. In contexts where risks are extreme and time is of the essence, rigor-responsiveness trade-offs can be managed by focusing more on external validity than internal validity.
3. Epidemiologists, medical experts and public health experts have been at the forefront of informing policy response to the covid-19 pandemic. A more heterogeneous group of experts should be engaged to ensure that precautionary principle and positive asymmetries are exploited. Experts who study complex systems and risk experts who deal with highly uncertain outcomes can add a valuable perspective to policy-making in context of uncertainty.