BMC Infect Dis. 2018 Jun 8;18(1):269. doi: 10.1186/s12879-018-3181-y.
Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014.
Caini S1, Spreeuwenberg P2, Kusznierz GF3, Rudi JM3, Owen R4, Pennington K4, Wangchuk S5, Gyeltshen S5, Ferreira de Almeida WA6, Pessanha Henriques CM6, Njouom R7, Vernet MA7, Fasce RA8, Andrade W8, Yu H9, Feng L9, Yang J9, Peng Z9, Lara J10, Bruno A11, de Mora D11, de Lozano C12, Zambon M13, Pebody R14, Castillo L15, Clara AW16, Matute ML17, Kosasih H18, Nurhayati18, Puzelli S19, Rizzo C20, Kadjo HA21, Daouda C22, Kiyanbekova L23, Ospanova A24, Mott JA25,26, Emukule GO25, Heraud JM27, Razanajatovo NH27, Barakat A28, El Falaki F28, Huang SQ29, Lopez L29, Balmaseda A30, Moreno B31, Rodrigues AP32, Guiomar R33, Ang LW34, Lee VJM35, Venter M36,37, Cohen C38,39, Badur S40, Ciblak MA40, Mironenko A41, Holubka O41, Bresee J42, Brammer L42, Hoang PVM43, Le MTQ43, Fleming D44, S?blain CE45, Schellevis F2,46, Paget J2; Global Influenza B Study group.
Collaborators (15)
Author information
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.
KEYWORDS:
Age distribution; H1N1 subtype; H3N2 subtype; Influenza; Influenza A virus; Influenza B virus; Meta-analysis
PMID: 29884140 DOI: 10.1186/s12879-018-3181-y
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Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014.
Caini S1, Spreeuwenberg P2, Kusznierz GF3, Rudi JM3, Owen R4, Pennington K4, Wangchuk S5, Gyeltshen S5, Ferreira de Almeida WA6, Pessanha Henriques CM6, Njouom R7, Vernet MA7, Fasce RA8, Andrade W8, Yu H9, Feng L9, Yang J9, Peng Z9, Lara J10, Bruno A11, de Mora D11, de Lozano C12, Zambon M13, Pebody R14, Castillo L15, Clara AW16, Matute ML17, Kosasih H18, Nurhayati18, Puzelli S19, Rizzo C20, Kadjo HA21, Daouda C22, Kiyanbekova L23, Ospanova A24, Mott JA25,26, Emukule GO25, Heraud JM27, Razanajatovo NH27, Barakat A28, El Falaki F28, Huang SQ29, Lopez L29, Balmaseda A30, Moreno B31, Rodrigues AP32, Guiomar R33, Ang LW34, Lee VJM35, Venter M36,37, Cohen C38,39, Badur S40, Ciblak MA40, Mironenko A41, Holubka O41, Bresee J42, Brammer L42, Hoang PVM43, Le MTQ43, Fleming D44, S?blain CE45, Schellevis F2,46, Paget J2; Global Influenza B Study group.
Collaborators (15)
Author information
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.
KEYWORDS:
Age distribution; H1N1 subtype; H3N2 subtype; Influenza; Influenza A virus; Influenza B virus; Meta-analysis
PMID: 29884140 DOI: 10.1186/s12879-018-3181-y
Free full text