Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12879-018-3181-y
Title: Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014
Authors: Caini, S
Spreeuwenberg, P
Kusznierz, G.F
Keywords: adolescent
adult
age distribution
aged
Article
Australia
Bhutan
Brazil
Cameroon
child
Chile
China
Costa Rica
Cote d'Ivoire
economic aspect
Ecuador
England
female
geographic distribution
groups by age
Guatemala
health survey
Honduras
human
Indonesia
infant
influenza A
Influenza A virus (H1N1)
Influenza A virus (H3N2)
influenza B
Influenza B virus
Influenza virus
Italy
Kazakhstan
Kenya
Madagascar
major clinical study
male
middle aged
Morocco
New Zealand
newborn
Nicaragua
outpatient
Panama
population
Portugal
Singapore
South Africa
Turkey (republic)
Ukraine
Viet Nam
young adult
age
factual database
global health
influenza
isolation and purification
preschool child
virology
Adolescent
Adult
Age Factors
Aged
Child
Child, Preschool
Databases, Factual
Female
Global Health
Humans
Infant
Infant, Newborn
Influenza A Virus, H1N1 Subtype
Influenza A Virus, H3N2 Subtype
Influenza, Human
Male
Middle Aged
Young Adult
Issue Date: 2018
Citation: Caini, S, Spreeuwenberg, P, Kusznierz, G.F (2018). Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014. BMC Infectious Diseases 18 (1) : 269. ScholarBank@NUS Repository. https://doi.org/10.1186/s12879-018-3181-y
Rights: Attribution 4.0 International
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. © 2018 The Author(s).
Source Title: BMC Infectious Diseases
URI: https://scholarbank.nus.edu.sg/handle/10635/181198
ISSN: 14712334
DOI: 10.1186/s12879-018-3181-y
Rights: Attribution 4.0 International
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