From a false sense of safety to resilience under uncertainty.

Understanding and acting upon risk is notably challenging, and navigating complexity with understandings developed for stable environments may inadvertently build a false sense of safety. Neglecting the potential for non-linear change or "black swan" events - highly impactful but uncommon occurrences - may lead to naive optimisation under assumed stability, exposing systems to extreme risks. For instance, loss aversion is seen as a cognitive bias in stable environments, but it can be an evolutionarily advantageous heuristic when complete destruction is possible.

Unmasking the mask studies: why the effectiveness of surgical masks in preventing respiratory infections has been underestimated.

Background: Pre-pandemic empirical studies have produced mixed statistical results on the effectiveness of masks against respiratory viruses, leading to confusion that may have contributed to organizations such as the WHO and CDC initially not recommending that the general public wear masks during the coronavirus disease 2019 pandemic.

Methods: A threshold-based dose-response curve framework is used to analyse the effects of interventions on infection probabilities for both single and repeated exposure events. Empirical studies on mask effectiveness are evaluated with a statistical power analysis that includes the effect of adherence to mask usage protocols.

Unraveling the flaws of estimates of the infection fatality rate for COVID-19.

The infection fatality rate (IFR) of COVID-19 is of importance for policymaking. We show that there are significant flaws in many studies estimating the IFR and used as references by public health authorities.