Impact of early phase COVID-19 precautionary behaviours on seasonal influenza in Hong Kong: a time-series modelling approach
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Author(s)
Type
Journal Article
Abstract
Background: Before major non-pharmaceutical interventions were implemented, seasonal influenza incidence in Hong Kong showed a rapid and unexpected reduction immediately following the early spread of COVID-19 in mainland China in January 2020. This decline was presumably
associated with precautionary behavioural changes (e.g., wearing face masks and avoiding crowded places). Knowing their effectiveness on the transmissibility of seasonal influenza could inform future influenza prevention strategies.
Methods: We estimated the effective reproduction number (Rt) of seasonal influenza in 2019/20 winter using a Time-Series Susceptible-Infectious-Recovered (TS-SIR) model with a Bayesian inference by integrated nested Laplace approximation (INLA). After taking account of changes in under-reporting and herd immunity, the individual effects of the behavioural changes were calculated.
Findings: The model-estimated mean Rt reduced from 1.29 (95%CI, 1.27-1.32) to 0.73 (95%CI, 0.73-0.74) after the COVID-19 community spread began. Wearing face masks protected 17.4% (95%CI, 16.3%-18.3%) from infections, about half of the effect of avoiding crowded places (44.1%,
95%CI, 43.5%-44.7%). Within the current model, if more than 85% of people had adopted both behaviours, the initial Rt could have been less than 1.
Conclusion: Our model results indicate that wearing face masks and avoiding crowded places could have potentially significant suppressive impacts on influenza.
associated with precautionary behavioural changes (e.g., wearing face masks and avoiding crowded places). Knowing their effectiveness on the transmissibility of seasonal influenza could inform future influenza prevention strategies.
Methods: We estimated the effective reproduction number (Rt) of seasonal influenza in 2019/20 winter using a Time-Series Susceptible-Infectious-Recovered (TS-SIR) model with a Bayesian inference by integrated nested Laplace approximation (INLA). After taking account of changes in under-reporting and herd immunity, the individual effects of the behavioural changes were calculated.
Findings: The model-estimated mean Rt reduced from 1.29 (95%CI, 1.27-1.32) to 0.73 (95%CI, 0.73-0.74) after the COVID-19 community spread began. Wearing face masks protected 17.4% (95%CI, 16.3%-18.3%) from infections, about half of the effect of avoiding crowded places (44.1%,
95%CI, 43.5%-44.7%). Within the current model, if more than 85% of people had adopted both behaviours, the initial Rt could have been less than 1.
Conclusion: Our model results indicate that wearing face masks and avoiding crowded places could have potentially significant suppressive impacts on influenza.
Date Issued
2022-11-14
Date Acceptance
2022-09-28
Citation
Frontiers in Public Health, 2022, 10, pp.1-10
ISSN
2296-2565
Publisher
Frontiers Media
Start Page
1
End Page
10
Journal / Book Title
Frontiers in Public Health
Volume
10
Copyright Statement
Copyright © 2022 Lin, Dorigatti, Tsui, Xie, Ling and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
License URL
Identifier
https://www.frontiersin.org/articles/10.3389/fpubh.2022.992697/full
Publication Status
Published
Article Number
992697
Date Publish Online
2022-11-14