IntroductionLiterature 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.MethodsTwenty-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.ResultsThe 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.ConclusionInfluenza 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.

IntroductionDetermining 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.MethodsThis 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.Results212 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.DiscussionOur 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.

BackgroundInfluenza 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).MethodsFor 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.ResultsThe 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.ConclusionsThese results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3181-y) contains supplementary material, which is available to authorized users.

The ongoing pandemic disaster of coronavirus erupted with the first confirmed cases in Wuhan, China in December 2019, caused by the SARS-CoV-2 novel coronavirus, the disease referred to as “COVID-19.” The World Health Organization (WHO) confirmed the outbreak and determined it a global pandemic. The current pandemic has infected nearly 100 million people and killed over 2 million. The current COVID-19 pandemic is smashing every public health barrier, guardrail and safety measure in underdeveloped and the most developed countries alike with peaks and troughs across time. Greatly impacted are those regions experiencing conflict and war. Morbidity and mortality increase logarithmically for those communities at risk and that lack the ability to promote basic preventative measures. As states around the globe struggle to unify responses, make gains on preparedness levels, identify and symptomatically treat positive cases and labs across the globe frantically rollout various vaccines and effective surveillance and therapeutic mechanisms. The incidence and prevalence of COVID-19 may continue to increase globally as no unified disaster response is manifested and disinformation spreads. During this failure in response, virus variants are erupting at a dizzying pace. Ungoverned spaces where non-state actors predominate and active war zones may become the next epicenter for COVID-19 fatality rates. As the incidence rates continue to rise, hospitals in North America and Europe exceed surge capacity and immunity post infection struggles to be adequately described. The global threat in previously high-quality, robust infrastructure healthcare systems in the most developed economies are failing the challenge posed by COVID-19; how will less developed economies and those healthcare infrastructures that are destroyed by war and conflict until adequate vaccines penetrance in these communities or adequate treatment are established? Ukraine and other states in the Black Sea Region are under threat and are exposed to armed Russian aggression against territorial sovereignty daily. Ukraine, where Russia has been waging war since 2014, faces this specific dual threat: disaster response to violence and a deadly infectious disease. In order to best serve biosurveillance, aid in pandemic disaster response and bolster health security in Europe, across the North Atlantic Treaty Alliance (NATO) and Black Sea regions, increased NATO integration, across Ukraine’s disaster response structures within the Ministries of Health, Defense and Interior must be reenforced and expanded in order to mitigate the COVID-19 disaster.