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Epidemic modelling suggests that in specific circumstances masks may become more effective when fewer contacts wear them

Background: The effectiveness of non-pharmaceutical interventions to control the spread of SARS-CoV-2 depends on many contextual factors, including adherence. Conventional wisdom holds that the effectiveness of protective behaviours, such as wearing masks, increases with the number of people who adopt them. Here we show in a simulation study that this is not always true.

Methods: We use a parsimonious network model based on the well-established empirical facts that adherence to such interventions wanes over time and that individuals tend to align their adoption strategies with their close social ties (homophily).

Results: When these assumptions are combined, a broad dynamic regime emerges in which the individual-level reduction in infection risk for those adopting protective behaviour increases as adherence to protective behaviour decreases. For instance, at 10 % coverage, we find that adopters face nearly a 30 % lower infection risk than at 60 % coverage. Based on surgical mask effectiveness estimates, the relative risk reduction for masked individuals ranges from 5 % to 15 %, or a factor of three. This small coverage effect occurs when the outbreak is over before the pathogen is able to invade small but closely knit groups of individuals who protect themselves.

Conclusions: Our results confirm that lower coverage reduces protection at the population level while contradicting the common belief that masking becomes ineffective at the individual level as more people drop their masks.

P. Klimek, K. Ledebur, S. Thurner, Epidemic modelling suggests that in specific circumstances masks may become more effective when fewer contacts wear them, Communications Medicine 4 (2024), DOI: 10.1038/s43856-024-00561-4.

 

Katharina Ledebur, PhD Candidate at the Complexity Science Hub

Katharina Ledebur

Peter Klimek, Faculty member at the Complexity Science Hub

Peter Klimek

Stefan Thurner @ Franziska Liehl, President of the Complexity Science Hub

Stefan Thurner

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