Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014 Saverio Caini Peter Spreeuwenberg Gabriela F. Kusznierz Juan Manuel Rudi Rhonda Owen Kate Pennington Sonam Wangchuk Sonam Gyeltshen Walquiria Aparecida Ferreira de Almeida Cláudio Maierovitch Pessanha Henriques Richard Njouom Marie-Astrid Vernet Rodrigo A. Fasce Winston Andrade Hongjie Yu Luzhao Feng Juan Yang Zhibin Peng Jenny Lara Alfredo Bruno Doménica de Mora Celina de Lozano Maria Zambon Richard Pebody Leticia Castillo Alexey W. Clara Maria Luisa Matute Herman Kosasih Nurhayati Simona Puzelli Caterina Rizzo Herve A. Kadjo Coulibaly Daouda Lyazzat Kiyanbekova Akerke Ospanova Joshua A. Mott Gideon O. Emukule Jean-Michel Heraud Norosoa Harline Razanajatovo Amal Barakat Fatima el Falaki Qiu Sue Huang Liza Lopez Angel Balmaseda Brechla Moreno Ana Paula Rodrigues Raquel Guiomar Li Wei Ang Vernon Jian Ming Lee Marietjie Venter Cheryl Cohen Selim Badur Meral A. Ciblak Alla Mironenko Olha Holubka Joseph Bresee Lynnette Brammer Phuong Vu Mai Hoang Mai Thi Quynh Le Douglas Fleming Clotilde El-Guerche Séblain François Schellevis John Paget Global Influenza B Study group 10.26091/ESRNZ.8067131.v1 https://research.esr.cri.nz/articles/journal_contribution/Distribution_of_influenza_virus_types_by_age_using_case-based_global_surveillance_data_from_twenty-nine_countries_1999-2014/8067131 <b>Background: </b>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). <div><br></div><div><b>Methods:</b> 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 metaregression and sub-group analyses to explore causes of between-estimates heterogeneity. </div><div><br></div><div><b>Results:</b> 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 (I-2>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. </div><div><br></div><div><b>Conclusions:</b> These results highlight the importance of presenting burden of disease estimates by age group and virus (sub) type.</div> 2019-05-02 04:27:57 Influenza Age distribution Influenza A Virus H3N2 Subtype H1N1 Subtype influenza B viruses Meta-Analysis Global Surveillance Data 1999-2014 Epidemiology Health Information Systems (incl. Surveillance) Health Care