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Transmission dynamics of seasonal influenza in a remote island population

Seasonal influenza outbreaks remain an important public health concern, causing large numbers of hospitalizations and deaths among high-risk groups. Understanding the dynamics of individual transmission is crucial to design effective control measures and ultimately reduce the burden caused by influe...

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Autores principales: Han, Su Myat, Robert, Alexis, Masuda, Shingo, Yasaka, Takahiro, Kanda, Satoshi, Komori, Kazuhiri, Saito, Nobuo, Suzuki, Motoi, Endo, Akira, Baguelin, Marc, Ariyoshi, Koya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068240/
https://www.ncbi.nlm.nih.gov/pubmed/37012350
http://dx.doi.org/10.1038/s41598-023-32537-0
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author Han, Su Myat
Robert, Alexis
Masuda, Shingo
Yasaka, Takahiro
Kanda, Satoshi
Komori, Kazuhiri
Saito, Nobuo
Suzuki, Motoi
Endo, Akira
Baguelin, Marc
Ariyoshi, Koya
author_facet Han, Su Myat
Robert, Alexis
Masuda, Shingo
Yasaka, Takahiro
Kanda, Satoshi
Komori, Kazuhiri
Saito, Nobuo
Suzuki, Motoi
Endo, Akira
Baguelin, Marc
Ariyoshi, Koya
author_sort Han, Su Myat
collection PubMed
description Seasonal influenza outbreaks remain an important public health concern, causing large numbers of hospitalizations and deaths among high-risk groups. Understanding the dynamics of individual transmission is crucial to design effective control measures and ultimately reduce the burden caused by influenza outbreaks. In this study, we analyzed surveillance data from Kamigoto Island, Japan, a semi-isolated island population, to identify the drivers of influenza transmission during outbreaks. We used rapid influenza diagnostic test (RDT)-confirmed surveillance data from Kamigoto island, Japan and estimated age-specific influenza relative illness ratios (RIRs) over eight epidemic seasons (2010/11 to 2017/18). We reconstructed the probabilistic transmission trees (i.e., a network of who-infected-whom) using Bayesian inference with Markov-chain Monte Carlo method and then performed a negative binomial regression on the inferred transmission trees to identify the factors associated with onwards transmission risk. Pre-school and school-aged children were most at risk of getting infected with influenza, with RIRs values consistently above one. The maximal RIR values were 5.99 (95% CI 5.23, 6.78) in the 7–12 aged-group and 5.68 (95%CI 4.59, 6.99) in the 4–6 aged-group in 2011/12. The transmission tree reconstruction suggested that the number of imported cases were consistently higher in the most populated and busy districts (Tainoura-go and Arikawa-go) ranged from 10–20 to 30–36 imported cases per season. The number of secondary cases generated by each case were also higher in these districts, which had the highest individual reproduction number (R(eff): 1.2–1.7) across the seasons. Across all inferred transmission trees, the regression analysis showed that cases reported in districts with lower local vaccination coverage (incidence rate ratio IRR = 1.45 (95% CI 1.02, 2.05)) or higher number of inhabitants (IRR = 2.00 (95% CI 1.89, 2.12)) caused more secondary transmissions. Being younger than 18 years old (IRR = 1.38 (95%CI 1.21, 1.57) among 4–6 years old and 1.45 (95% CI 1.33, 1.59) 7–12 years old) and infection with influenza type A (type B IRR = 0.83 (95% CI 0.77, 0.90)) were also associated with higher numbers of onwards transmissions. However, conditional on being infected, we did not find any association between individual vaccination status and onwards transmissibility. Our study showed the importance of focusing public health efforts on achieving high vaccine coverage throughout the island, especially in more populated districts. The strong association between local vaccine coverage (including neighboring regions), and the risk of transmission indicate the importance of achieving homogeneously high vaccine coverage. The individual vaccine status may not prevent onwards transmission, though it may reduce the severity of infection.
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spelling pubmed-100682402023-04-03 Transmission dynamics of seasonal influenza in a remote island population Han, Su Myat Robert, Alexis Masuda, Shingo Yasaka, Takahiro Kanda, Satoshi Komori, Kazuhiri Saito, Nobuo Suzuki, Motoi Endo, Akira Baguelin, Marc Ariyoshi, Koya Sci Rep Article Seasonal influenza outbreaks remain an important public health concern, causing large numbers of hospitalizations and deaths among high-risk groups. Understanding the dynamics of individual transmission is crucial to design effective control measures and ultimately reduce the burden caused by influenza outbreaks. In this study, we analyzed surveillance data from Kamigoto Island, Japan, a semi-isolated island population, to identify the drivers of influenza transmission during outbreaks. We used rapid influenza diagnostic test (RDT)-confirmed surveillance data from Kamigoto island, Japan and estimated age-specific influenza relative illness ratios (RIRs) over eight epidemic seasons (2010/11 to 2017/18). We reconstructed the probabilistic transmission trees (i.e., a network of who-infected-whom) using Bayesian inference with Markov-chain Monte Carlo method and then performed a negative binomial regression on the inferred transmission trees to identify the factors associated with onwards transmission risk. Pre-school and school-aged children were most at risk of getting infected with influenza, with RIRs values consistently above one. The maximal RIR values were 5.99 (95% CI 5.23, 6.78) in the 7–12 aged-group and 5.68 (95%CI 4.59, 6.99) in the 4–6 aged-group in 2011/12. The transmission tree reconstruction suggested that the number of imported cases were consistently higher in the most populated and busy districts (Tainoura-go and Arikawa-go) ranged from 10–20 to 30–36 imported cases per season. The number of secondary cases generated by each case were also higher in these districts, which had the highest individual reproduction number (R(eff): 1.2–1.7) across the seasons. Across all inferred transmission trees, the regression analysis showed that cases reported in districts with lower local vaccination coverage (incidence rate ratio IRR = 1.45 (95% CI 1.02, 2.05)) or higher number of inhabitants (IRR = 2.00 (95% CI 1.89, 2.12)) caused more secondary transmissions. Being younger than 18 years old (IRR = 1.38 (95%CI 1.21, 1.57) among 4–6 years old and 1.45 (95% CI 1.33, 1.59) 7–12 years old) and infection with influenza type A (type B IRR = 0.83 (95% CI 0.77, 0.90)) were also associated with higher numbers of onwards transmissions. However, conditional on being infected, we did not find any association between individual vaccination status and onwards transmissibility. Our study showed the importance of focusing public health efforts on achieving high vaccine coverage throughout the island, especially in more populated districts. The strong association between local vaccine coverage (including neighboring regions), and the risk of transmission indicate the importance of achieving homogeneously high vaccine coverage. The individual vaccine status may not prevent onwards transmission, though it may reduce the severity of infection. Nature Publishing Group UK 2023-04-03 /pmc/articles/PMC10068240/ /pubmed/37012350 http://dx.doi.org/10.1038/s41598-023-32537-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Han, Su Myat
Robert, Alexis
Masuda, Shingo
Yasaka, Takahiro
Kanda, Satoshi
Komori, Kazuhiri
Saito, Nobuo
Suzuki, Motoi
Endo, Akira
Baguelin, Marc
Ariyoshi, Koya
Transmission dynamics of seasonal influenza in a remote island population
title Transmission dynamics of seasonal influenza in a remote island population
title_full Transmission dynamics of seasonal influenza in a remote island population
title_fullStr Transmission dynamics of seasonal influenza in a remote island population
title_full_unstemmed Transmission dynamics of seasonal influenza in a remote island population
title_short Transmission dynamics of seasonal influenza in a remote island population
title_sort transmission dynamics of seasonal influenza in a remote island population
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068240/
https://www.ncbi.nlm.nih.gov/pubmed/37012350
http://dx.doi.org/10.1038/s41598-023-32537-0
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