Hervé Kadjo

INTRODUCTION: Literature on influenza focuses on influenza A, despite influenza B having a large public health impact. The Global Influenza B Study aims to collect information on global epidemiology and burden of disease of influenza B since 2000. METHODS: Twenty-six countries in the Southern (n = 5) and Northern (n = 7) hemispheres and intertropical belt (n = 14) provided virological and epidemiological data. We calculated the proportion of influenza cases due to type B and Victoria and Yamagata lineages in each country and season; tested the correlation between proportion of influenza B and maximum weekly influenza-like illness (ILI) rate during the same season; determined the frequency of vaccine mismatches; and described the age distribution of cases by virus type. RESULTS: The database included 935 673 influenza cases (2000-2013). Overall median proportion of influenza B was 22·6%, with no statistically significant differences across seasons. During seasons where influenza B was dominant or co-circulated (>20% of total detections), Victoria and Yamagata lineages predominated during 64% and 36% of seasons, respectively, and a vaccine mismatch was observed in ≈25% of seasons. Proportion of influenza B was inversely correlated with maximum ILI rate in the same season in the Northern and (with borderline significance) Southern hemispheres. Patients infected with influenza B were usually younger (5-17 years) than patients infected with influenza A. CONCLUSION: Influenza B is a common disease with some epidemiological differences from influenza A. This should be considered when optimizing control/prevention strategies in different regions and reducing the global burden of disease due to influenza.

We describe the epidemiological characteristics, pattern of circulation, and geographical distribution of influenza B viruses and its lineages using data from the Global Influenza B Study. We included over 1.8 million influenza cases occurred in thirty-one countries during 2000-2018. We calculated the proportion of cases caused by influenza B and its lineages; determined the timing of influenza A and B epidemics; compared the age distribution of B/Victoria and B/Yamagata cases; and evaluated the frequency of lineage-level mismatch for the trivalent vaccine. The median proportion of influenza cases caused by influenza B virus was 23.4%, with a tendency (borderline statistical significance, p = 0.060) to be higher in tropical vs. temperate countries. Influenza B was the dominant virus type in about one every seven seasons. In temperate countries, influenza B epidemics occurred on average three weeks later than influenza A epidemics; no consistent pattern emerged in the tropics. The two B lineages caused a comparable proportion of influenza B cases globally, however the B/Yamagata was more frequent in temperate countries, and the B/Victoria in the tropics (p = 0.048). B/Yamagata patients were significantly older than B/Victoria patients in almost all countries. A lineage-level vaccine mismatch was observed in over 40% of seasons in temperate countries and in 30% of seasons in the tropics. The type B virus caused a substantial proportion of influenza infections globally in the 21st century, and its two virus lineages differed in terms of age and geographical distribution of patients. These findings will help inform health policy decisions aiming to reduce disease burden associated with seasonal influenza.

BACKGROUND: In response to the potential threat of an influenza pandemic, several international institutions and governments, in partnership with African countries, invested in the development of epidemiologic and laboratory influenza surveillance capacity in Africa and the African Network of Influenza Surveillance and Epidemiology (ANISE) was formed. METHODS: We used a standardized form to collect information on influenza surveillance system characteristics, the number and percent of influenza-positive patients with influenza-like illness (ILI), or severe acute respiratory infection (SARI) and virologic data from countries participating in ANISE. RESULTS: Between 2006 and 2010, the number of ILI and SARI sites in 15 African countries increased from 21 to 127 and from 2 to 98, respectively. Children 0-4 years accounted for 48% of all ILI and SARI cases of which 22% and 10%, respectively, were positive for influenza. Influenza peaks were generally discernible in North and South Africa. Substantial cocirculation of influenza A and B occurred most years. CONCLUSIONS: Influenza is a major cause of respiratory illness in Africa, especially in children. Further strengthening influenza surveillance, along with conducting special studies on influenza burden, cost of illness, and role of other respiratory pathogens will help detect novel influenza viruses and inform and develop targeted influenza prevention policy decisions in the region.

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). 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. 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. These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.