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Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014

Saverio Caini 1, * Peter Spreeuwenberg 1 Gabriela Kusznierz 2 Juan Rudi 2 Rhonda Owen 3 Kate Pennington 4 Sonam Wangchuk 5 Sonam Gyeltshen 5 Walquiria Aparecida Ferreira de Almeida 6 Cláudio Maierovitch Pessanha Henriques 6 Richard Njouom 7 Marie-Astrid Vernet 7 Rodrigo Fasce 8 Winston Andrade 8 Hongjie Yu 9 Luzhao Feng 10 Juan Yang 10 Zhibin Peng 10 Jenny Lara 11 Alfredo Bruno 12 Domenica de Mora 12 Celina de Lozano 13 Maria Zambon 14 Richard Pebody 14 Leticia Le 15 Alexey Clara 16 Maria Luisa Matute 17 Herman Kosasih 18 N Nurhayati 18 Simona Puzelli 19 Caterina Rizzo 19 Herve Kadjo 20 Coulibaly Daouda 21 Lyazzat Kiyanbekova 22 Akerke Ospanova 22 Joshua Mott 23, 24 Gideon Emukule 23 Jean-Michel Heraud 25 Norosoa Harline Razanajatovo 25 Amal Barakat 26 Fatima El Falaki 26 Sue Huang 27 Liza Lopez 27 Angel Balmaseda 28 Brechla Moreno 29 Ana Paula Rodrigues 30 Raquel Guiomar 30 Li Wei Ang 31 Vernon Jian Ming Le 31 Marietjie Venter 32, 33 Cheryl Cohen 34, 35 Selim Badur 36 Meral Ciblak 36 Alla Mironenko 37 Olha Holubka 37 Joseph Bresee 38 Lynnette Brammer 38 Phuong Vu Mai Hoang 39 Mai Thi Quynh Le 39 Douglas Fleming 40 Clotilde El-Guerche Séblain 41 François Schellevis 1, 42 John Paget 43 Global Influenza B Study Group
* Corresponding author
Abstract : BACKGROUND: Influenza disease burden varies by age and this has important public health implications. We compared the proportional distribution of different influenza virus types within age strata using surveillance data from twenty-nine countries during 1999-2014 (N=358,796 influenza cases). METHODS: For each virus, we calculated a Relative Illness Ratio (defined as the ratio of the percentage of cases in an age group to the percentage of the country population in the same age group) for young children (0-4 years), older children (5-17 years), young adults (18-39 years), older adults (40-64 years), and the elderly (65+ years). We used random-effects meta-analysis models to obtain summary relative illness ratios (sRIRs), and conducted meta-regression and sub-group analyses to explore causes of between-estimates heterogeneity. RESULTS: The influenza virus with highest sRIR was A(H1N1) for young children, B for older children, A(H1N1)pdm2009 for adults, and (A(H3N2) for the elderly. As expected, considering the diverse nature of the national surveillance datasets included in our analysis, between-estimates heterogeneity was high (I2>90%) for most sRIRs. The variations of countries' geographic, demographic and economic characteristics and the proportion of outpatients among reported influenza cases explained only part of the heterogeneity, suggesting that multiple factors were at play. CONCLUSIONS: These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.
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Saverio Caini, Peter Spreeuwenberg, Gabriela Kusznierz, Juan Rudi, Rhonda Owen, et al.. Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014. BMC Infectious Diseases, BioMed Central, 2018, 18 (1), pp.269. ⟨10.1186/s12879-018-3181-y⟩. ⟨pasteur-01925131⟩

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