Estimated incidence of influenza-virus-associated severe pneumonia in children in El Salvador, 2008–2010

OBJECTIVE: To estimate the incidence of influenza-virus-associated severe pneumonia among Salvadorian children aged < 5 years. METHODS: Data on children aged < 5 years admitted with severe pneumonia to a sentinel hospital in the western region were collected weekly. Nasal and oropharyngeal swab specimens were collected from a convenience sample of case patients for respiratory virus testing. A health-care utilization survey was conducted in the hospital catchment area to determine the proportion of residents who sought care at the hospital. The incidence of influenza-virus-associated severe pneumonia among all Salvadorian children aged < 5 years was estimated from surveillance and census data, with adjustment for health-care utilization. Influenza virus strains were characterized by the United States Centers for Disease Control and Prevention to determine their correspondence with northern and southern hemisphere influenza vaccine formulations. FINDINGS: Physicians identified 2554 cases of severe pneumonia. Samples from 608 cases were tested for respiratory viruses and 37 (6%) were positive for influenza virus. The estimated incidence of influenza-virus-associated severe pneumonia was 3.2 cases per 1000 person–years (95% confidence interval, CI: 2.8–3.7) overall, 1.5 cases per 1000 person–years (95% CI: 1.0–2.0) during 2008, 7.6 cases per 1000 person–years (95% CI: 6.5–8.9) during 2009 and 0.6 cases per 1000 person–years (95% CI: 0.3–1.0) during 2010. Northern and southern hemisphere vaccine formulations matched influenza virus strains isolated during 2008 and 2010. CONCLUSION: Influenza-virus-associated severe pneumonia occurred frequently among young Salvadorian children during 2008–2010. Antigens in northern and southern hemisphere influenza vaccine formulations corresponded to circulating strains

Beal, William J. to S. Watson Sept. 9, 1891

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Temporal Patterns of Influenza A and B in Tropical and Temperate Countries: What Are the Lessons for Influenza Vaccination?

<div><p>Introduction</p><p>Determining the optimal time to vaccinate is important for influenza vaccination programmes. Here, we assessed the temporal characteristics of influenza epidemics in the Northern and Southern hemispheres and in the tropics, and discuss their implications for vaccination programmes.</p><p>Methods</p><p>This was a retrospective analysis of surveillance data between 2000 and 2014 from the Global Influenza B Study database. The seasonal peak of influenza was defined as the week with the most reported cases (overall, A, and B) in the season. The duration of seasonal activity was assessed using the maximum proportion of influenza cases during three consecutive months and the minimum number of months with ≥80% of cases in the season. We also assessed whether co-circulation of A and B virus types affected the duration of influenza epidemics.</p><p>Results</p><p>212 influenza seasons and 571,907 cases were included from 30 countries. In tropical countries, the seasonal influenza activity lasted longer and the peaks of influenza A and B coincided less frequently than in temperate countries. Temporal characteristics of influenza epidemics were heterogeneous in the tropics, with distinct seasonal epidemics observed only in some countries. Seasons with co-circulation of influenza A and B were longer than influenza A seasons, especially in the tropics.</p><p>Discussion</p><p>Our findings show that influenza seasonality is less well defined in the tropics than in temperate regions. This has important implications for vaccination programmes in these countries. High-quality influenza surveillance systems are needed in the tropics to enable decisions about when to vaccinate.</p></div

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

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)

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

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 metaregression 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.Table S1. Number of influenza cases caused by the difference influenza viruses that were included in the analysis. The Global Influenza B Study, 1999-2014.Figure S1. Forest plot of the Relative Illness Ratio for patients aged 0-4 years infected with A(H1N1) influenza virus. The Global Influenza B Study, 1999-2014. Figure S2. Forest plot of the Relative Illness Ratio for patients aged 5-17 years infected with A(H1N1) influenza virus. The Global Influenza B Study, 1999-2014. Figure S3. Forest plot of the Relative Illness Ratio for patients aged 18-39 years infected with A(H1N1) influenza virus. The Global Influenza B Study, 1999-2014. Figure S4. Forest plot of the Relative Illness Ratio for patients aged 40-64 years infected with A(H1N1) influenza virus. The Global Influenza B Study, 1999-2014. Figure S5. Forest plot of the Relative Illness Ratio for patients aged 65+ years infected with A(H1N1) influenza virus. The Global Influenza B Study, 1999-2014.Table S2. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by categories of country ageing index. The Global Influenza B Study, 1999- 2014. Table S3. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by percentage of outpatients among cases reported to the influenza surveillance system. The Global Influenza B Study, 1999-2014. Table S4. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by country latitude. The Global Influenza B Study, 1999-2014. Table S5. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by percentage of influenza cases caused by that influenza virus in the same season. The Global Influenza B Study, 1999-2014. Table S6. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by percentage of influenza cases caused by that influenza virus in the previous season. The Global Influenza B Study, 1999-2014. Table S7. Summary Relative Illness Ratio (sRIR), 95% confidence intervals (95% CI) across age groups and influenza viruses by categories of country gross domestic product (GDP) per capita. The Global Influenza B Study, 1999-2014.The Global Influenza B Study is funded by an unrestricted research grant from Sanofi Pasteur.https://bmcinfectdis.biomedcentral.comam2019Medical Virolog