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Background: Influenza vaccines contain Influenza A and B antigens and are adjusted annually to match the characteristics of circulating viruses. In Germany, Influenza B viruses belonged to the B/Yamagata lineage, but since 2001, the antigenically distinct B/Victoria lineage has been co-circulating. Trivalent influenza vaccines (TIV) contain antigens of the two A subtypes A(H3N2) and A(H1N1), yet of only one B lineage, resulting in frequent vaccine mismatches. Since 2012, the WHO has been recommending vaccine strains from both B lineages, paving the way for quadrivalent influenza vaccines (QIV)., Methods: Using an individual-based simulation tool, we simulate the concomitant transmission of four influenza strains, and compare the effects of TIV and QIV on the infection incidence. Individuals are connected in a dynamically evolving age-dependent contact network based on the POLYMOD matrix; their age-distribution reproduces German demographic data and predictions. The model considers maternal protection, boosting of existing immunity, loss of immunity, and cross-immunizing events between the B lineages. Calibration to the observed annual infection incidence of 10.6% among young adults yielded a basic reproduction number of 1.575. Vaccinations are performed annually in October and November, whereby coverage depends on the vaccinees' age, their risk status and previous vaccination status. New drift variants are introduced at random time points, leading to a sudden loss of protective immunity for part of the population and occasionally to reduced vaccine efficacy. Simulations run for 50 years, the first 30 of which are used for initialization. During the final 20 years, individuals receive TIV or QIV, using a mirrored simulation approach., Results: Using QIV, the mean annual infection incidence can be reduced from 8,943,000 to 8,548,000, i.e. by 395,000 infections, preventing 11.2% of all Influenza B infections which still occur with TIV (95% CI: 10.7-11.8%). Using a lower B lineage cross protection than the baseline 60%, the number of Influenza B infections increases and the number additionally prevented by QIV can be 5.5 times as high., Conclusions: Vaccination with TIV substantially reduces the Influenza incidence compared to no vaccination. Depending on the assumed degree of B lineage cross protection, QIV further reduces Influenza B incidence by 11-33%.

In the state of Hesse (Germany) all vaccinations were administered either by the public health-care (ÖGD) or private health-care facilities and were registered by week and age group. In the following article, the benefit of the vaccination campaign will be looked at in terms of preventable consultations due to acute respiratory tract infections (AK-ARI). AK-ARI were registered with the nation-wide sentinel of the AGI. Scenarios regarding timing and age-specific coverage are modelled. The achieved timing and age distribution was compared to assumed ideal distributions, e. g., having achieved the final coverage 2 weeks before epidemic start or having applied the used vaccine exclusively for the most affected age group 5-14 years. The timing and coverage actually achieved (7% overall) prevented an estimated 1.4% or, respectively, 1.1% of the total consultation excess. With the same amount of vaccine but ideally applied at least 2 weeks -before the begin of the epidemic and exclusively to the age group of the 5- to 14-year olds, an estimated 13.9% or, respectively, 18.2% of the total excess could have been prevented. The simulated scenarios give estimations as to what benefit potentially could have been achieved during the A(H1N1)pdm09 pandemic. Both the delayed successive access to vaccine and the not ideal age distribution reduced the benefit to about 30% of the optimum. These exemplary estimates underline the importance of timeliness and valid prioritising of vaccination campaigns, although footing on just one outcome. It appears beneficial to reduce uncertainties for a solid prioritisation by, e. g., timely extended surveillance. Short-term decisions and adoptions are likely for future campaigns, e. g., due to unexpected changes in the epidemic, demanding flexibility in the application management., (© Georg Thieme Verlag KG Stuttgart · New York.)

During the autumn wave of the pandemic influenza virus A/(H1N1) 2009 (pIV) the German population was offered an AS03-adjuvanted vaccine. The authors compared results of two methods calculating the effectiveness of the vaccine (VE). The test-negative case-control method used data from virologic surveillance including influenza-positive and negative patients. An innovative case-series methodology explored data from all nationally reported laboratory-confirmed influenza cases. The proportion of reported cases occurring in vaccinees during an assumed unprotected phase after vaccination was compared with that occurring in vaccinees during their assumed protected phase. The test-negative case-control method included 1,749 pIV cases and 2,087 influenza test-negative individuals of whom 6 (0.3%) and 36 (1.7%), respectively, were vaccinated. The case series method included data from 73,280 cases. VE in the two methods was 79% (95% confidence interval (CI) = 35-93%; P = 0.007) and 87% (95% CI = 78-92%; P<0.001) for individuals less than 14 years of age and 70% (95% CI = -45%-94%, P = 0.13) and 74% (95% CI = 64-82%; P<0.001) for individuals above the age of 14. Both methods yielded similar VE in both age groups; and VE for the younger age group seemed to be higher.

A survey of directors and employees of 36 long-term care facilities in Hesse, Germany, revealed that influenza vaccine uptake among staff was less than 30% in 30 and greater than 50% in 6. The study identified policies and practices associated with vaccination uptake at long-term care facilities and factors associated with the decision of staff to get vaccinated.

The continuous antigenic drift of influenza viruses requires annual adaptation of the vaccine. Protection depends largely on the match of the variants represented in the vaccine with the viruses actually known to be in circulation and may differ considerably from season to season. Therefore studies to assess the efficacy and effectiveness of the vaccine are conducted rather sporadically on an annual basis and it would be desirable to make use of routinely available data from surveillance programs. We compared two different approaches: (1) the "screening method" where cases are identified from laboratory data and controls are taken from data on vaccination rates and (2) a second method that uses the same cases, but controls were influenza-negative individuals with influenza-like illness (also identified from laboratory data). The sensitivity of the methods to confounders that were considered as relevant was tested with a simulation. Both methods were applied to the data of the German influenza surveillance data of the season 2004/2005. The estimated effectiveness over all age groups was rather low with both methods, but comparable with other estimations from the literature. We observed differences in certain age groups between the methods as well as large differences between particular age groups within one method. Possible explanations are random variations due to low numbers in age strata and other influences not yet considered. Therefore the estimations should be interpreted with care; however, relative comparisons among seasons may still be meaningful.