tetano
Editor, Senior Moderator
BMC Infect Dis. 2018 Jun 8;18(1):269. doi: 10.1186/s12879-018-3181-y.
[h=1]Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014.[/h] Caini S[SUP]1[/SUP], Spreeuwenberg P[SUP]2[/SUP], Kusznierz GF[SUP]3[/SUP], Rudi JM[SUP]3[/SUP], Owen R[SUP]4[/SUP], Pennington K[SUP]4[/SUP], Wangchuk S[SUP]5[/SUP], Gyeltshen S[SUP]5[/SUP], Ferreira de Almeida WA[SUP]6[/SUP], Pessanha Henriques CM[SUP]6[/SUP], Njouom R[SUP]7[/SUP], Vernet MA[SUP]7[/SUP], Fasce RA[SUP]8[/SUP], Andrade W[SUP]8[/SUP], Yu H[SUP]9[/SUP], Feng L[SUP]9[/SUP], Yang J[SUP]9[/SUP], Peng Z[SUP]9[/SUP], Lara J[SUP]10[/SUP], Bruno A[SUP]11[/SUP], de Mora D[SUP]11[/SUP], de Lozano C[SUP]12[/SUP], Zambon M[SUP]13[/SUP], Pebody R[SUP]14[/SUP], Castillo L[SUP]15[/SUP], Clara AW[SUP]16[/SUP], Matute ML[SUP]17[/SUP], Kosasih H[SUP]18[/SUP], Nurhayati[SUP]18[/SUP], Puzelli S[SUP]19[/SUP], Rizzo C[SUP]20[/SUP], Kadjo HA[SUP]21[/SUP], Daouda C[SUP]22[/SUP], Kiyanbekova L[SUP]23[/SUP], Ospanova A[SUP]24[/SUP], Mott JA[SUP]25,[/SUP][SUP]26[/SUP], Emukule GO[SUP]25[/SUP], Heraud JM[SUP]27[/SUP], Razanajatovo NH[SUP]27[/SUP], Barakat A[SUP]28[/SUP], El Falaki F[SUP]28[/SUP], Huang SQ[SUP]29[/SUP], Lopez L[SUP]29[/SUP], Balmaseda A[SUP]30[/SUP], Moreno B[SUP]31[/SUP], Rodrigues AP[SUP]32[/SUP], Guiomar R[SUP]33[/SUP], Ang LW[SUP]34[/SUP], Lee VJM[SUP]35[/SUP], Venter M[SUP]36,[/SUP][SUP]37[/SUP], Cohen C[SUP]38,[/SUP][SUP]39[/SUP], Badur S[SUP]40[/SUP], Ciblak MA[SUP]40[/SUP], Mironenko A[SUP]41[/SUP], Holubka O[SUP]41[/SUP], Bresee J[SUP]42[/SUP], Brammer L[SUP]42[/SUP], Hoang PVM[SUP]43[/SUP], Le MTQ[SUP]43[/SUP], Fleming D[SUP]44[/SUP], S?blain CE[SUP]45[/SUP], Schellevis F[SUP]2,[/SUP][SUP]46[/SUP], Paget J[SUP]2[/SUP]; Global Influenza B Study group.
[h=3]Collaborators (15)[/h]
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] 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).
[h=4]METHODS:[/h] 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.
[h=4]RESULTS:[/h] 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[SUP]2[/SUP]>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.
[h=4]CONCLUSIONS:[/h] These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.
[h=4]KEYWORDS:[/h] 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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[h=1]Distribution of influenza virus types by age using case-based global surveillance data from twenty-nine countries, 1999-2014.[/h] Caini S[SUP]1[/SUP], Spreeuwenberg P[SUP]2[/SUP], Kusznierz GF[SUP]3[/SUP], Rudi JM[SUP]3[/SUP], Owen R[SUP]4[/SUP], Pennington K[SUP]4[/SUP], Wangchuk S[SUP]5[/SUP], Gyeltshen S[SUP]5[/SUP], Ferreira de Almeida WA[SUP]6[/SUP], Pessanha Henriques CM[SUP]6[/SUP], Njouom R[SUP]7[/SUP], Vernet MA[SUP]7[/SUP], Fasce RA[SUP]8[/SUP], Andrade W[SUP]8[/SUP], Yu H[SUP]9[/SUP], Feng L[SUP]9[/SUP], Yang J[SUP]9[/SUP], Peng Z[SUP]9[/SUP], Lara J[SUP]10[/SUP], Bruno A[SUP]11[/SUP], de Mora D[SUP]11[/SUP], de Lozano C[SUP]12[/SUP], Zambon M[SUP]13[/SUP], Pebody R[SUP]14[/SUP], Castillo L[SUP]15[/SUP], Clara AW[SUP]16[/SUP], Matute ML[SUP]17[/SUP], Kosasih H[SUP]18[/SUP], Nurhayati[SUP]18[/SUP], Puzelli S[SUP]19[/SUP], Rizzo C[SUP]20[/SUP], Kadjo HA[SUP]21[/SUP], Daouda C[SUP]22[/SUP], Kiyanbekova L[SUP]23[/SUP], Ospanova A[SUP]24[/SUP], Mott JA[SUP]25,[/SUP][SUP]26[/SUP], Emukule GO[SUP]25[/SUP], Heraud JM[SUP]27[/SUP], Razanajatovo NH[SUP]27[/SUP], Barakat A[SUP]28[/SUP], El Falaki F[SUP]28[/SUP], Huang SQ[SUP]29[/SUP], Lopez L[SUP]29[/SUP], Balmaseda A[SUP]30[/SUP], Moreno B[SUP]31[/SUP], Rodrigues AP[SUP]32[/SUP], Guiomar R[SUP]33[/SUP], Ang LW[SUP]34[/SUP], Lee VJM[SUP]35[/SUP], Venter M[SUP]36,[/SUP][SUP]37[/SUP], Cohen C[SUP]38,[/SUP][SUP]39[/SUP], Badur S[SUP]40[/SUP], Ciblak MA[SUP]40[/SUP], Mironenko A[SUP]41[/SUP], Holubka O[SUP]41[/SUP], Bresee J[SUP]42[/SUP], Brammer L[SUP]42[/SUP], Hoang PVM[SUP]43[/SUP], Le MTQ[SUP]43[/SUP], Fleming D[SUP]44[/SUP], S?blain CE[SUP]45[/SUP], Schellevis F[SUP]2,[/SUP][SUP]46[/SUP], Paget J[SUP]2[/SUP]; Global Influenza B Study group.
[h=3]Collaborators (15)[/h]
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] 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).
[h=4]METHODS:[/h] 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.
[h=4]RESULTS:[/h] 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[SUP]2[/SUP]>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.
[h=4]CONCLUSIONS:[/h] These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.
[h=4]KEYWORDS:[/h] 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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