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JMIRx Med . Mask Use to Curtail Influenza in a Post-COVID-19 World: Modeling Study

tetano

Editor, Senior Moderator
JMIRx Med


. 2022 May 27;3(2):e31955.
doi: 10.2196/31955. eCollection Apr-Jun 2022.
Mask Use to Curtail Influenza in a Post-COVID-19 World: Modeling Study


Henri Froese[SUP] #[/SUP][SUP] 1 [/SUP], Angel G A Prempeh[SUP] #[/SUP][SUP] 2 [/SUP]



Affiliations
Free PMC article

Abstract

Background: Face mask mandates have been instrumental in the reduction of transmission of airborne COVID-19. Thus, the question arises whether comparatively mild measures should be kept in place after the pandemic to reduce other airborne diseases such as influenza.
Objective: In this study, we aim to simulate the quantitative impact of face masks on the rate of influenza illnesses in the United States.
Methods: Using the Centers for Disease Control and Prevention data from 2010 to 2019, we used a series of differential equations to simulate past influenza seasons, assuming that people wore face masks. This was achieved by introducing a variable to account for the efficacy and prevalence of masks and then analyzing its impact on influenza transmission rate in a susceptible-exposed-infected-recovered model fit to the actual past seasons. We then compared influenza rates in this hypothetical scenario with the actual rates over the seasons.
Results: Our results show that several combinations of mask efficacy and prevalence can substantially reduce the burden of seasonal influenza. Across all the years modeled, a mask prevalence of 0.2 (20%) and assumed moderate inward and outward mask efficacy of 0.45 (45%) reduced influenza infections by >90%.
Conclusions: A minority of individuals wearing masks substantially reduced the number of influenza infections across seasons. Considering the efficacy rates of masks and the relatively insignificant monetary cost, we highlight that it may be a viable alternative or complement to influenza vaccinations.

Keywords: COVID-19; efficacy; infectious disease; influenza; intervention; mask; model; prevalence; protection; respiratory; simulation; transmission.
 
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