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Results from a European multicentre case-control study reported by Marta Valenciano and colleagues suggest good protection by the pandemic monovalent H1N1 vaccine against pH1N1 and no effect of the 2009–2010 seasonal influenza vaccine on H1N1.

Since the 2008/9 influenza season, the I-MOVE multicentre case–control study measures influenza vaccine effectiveness (VE) against medically-attended influenza-like-illness (ILI) laboratory confirmed as influenza. In 2011/12, European studies reported a decline in VE against influenza A(H3N2) within the season. Using combined I-MOVE data from 2010/11 to 2014/15 we studied the effects of time since vaccination on influenza type/subtype-specific VE. We modelled influenza type/subtype-specific VE by time since vaccination using a restricted cubic spline, controlling for potential confounders (age, sex, time of onset, chronic conditions). Over 10,000 ILI cases were included in each analysis of influenza A(H3N2), A(H1N1)pdm09 and B; with 4,759, 3,152 and 3,617 influenza positive cases respectively. VE against influenza A(H3N2) reached 50.6% (95% CI: 30.0–65.1) 38 days after vaccination, declined to 0% (95% CI: -18.1–15.2) from 111 days onwards. At day 54 VE against influenza A(H1N1)pdm09 reached 55.3% (95% CI: 37.9–67.9) and remained between this value and 50.3% (95% CI: 34.8–62.1) until season end. VE against influenza B declined from 70.7% (95% CI: 51.3–82.4) 44 days after vaccination to 21.4% (95% CI: -57.4–60.8) at season end. To assess if vaccination campaign strategies need revising more evidence on VE by time since vaccination is urgently needed.

BackgroundIn the third season of I-MOVE (Influenza Monitoring Vaccine Effectiveness in Europe), we undertook a multicentre case-control study based on sentinel practitioner surveillance networks in eight European Union (EU) member states to estimate 2010/11 influenza vaccine effectiveness (VE) against medically-attended influenza-like illness (ILI) laboratory-confirmed as influenza.MethodsUsing systematic sampling, practitioners swabbed ILI/ARI patients within seven days of symptom onset. We compared influenza-positive to influenza laboratory-negative patients among those meeting the EU ILI case definition. A valid vaccination corresponded to > 14 days between receiving a dose of vaccine and symptom onset. We used multiple imputation with chained equations to estimate missing values. Using logistic regression with study as fixed effect we calculated influenza VE adjusting for potential confounders. We estimated influenza VE overall, by influenza type, age group and among the target group for vaccination.ResultsWe included 2019 cases and 2391 controls in the analysis. Adjusted VE was 52% (95% CI 30-67) overall (N = 4410), 55% (95% CI 29-72) against A(H1N1) and 50% (95% CI 14-71) against influenza B. Adjusted VE against all influenza subtypes was 66% (95% CI 15-86), 41% (95% CI -3-66) and 60% (95% CI 17-81) among those aged 0-14, 15-59 and ≥60 respectively. Among target groups for vaccination (N = 1004), VE was 56% (95% CI 34-71) overall, 59% (95% CI 32-75) against A(H1N1) and 63% (95% CI 31-81) against influenza B.ConclusionsResults suggest moderate protection from 2010-11 trivalent influenza vaccines against medically-attended ILI laboratory-confirmed as influenza across Europe. Adjusted and stratified influenza VE estimates are possible with the large sample size of this multi-centre case-control. I-MOVE shows how a network can provide precise summary VE measures across Europe.

COVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a considerable reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

COVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a huge reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

IntroductionWe describe COVID-19 morbidity, mortality, case fatality and excess death in a country-wide study of municipalities in Hungary, exploring the association with socioeconomic status.MethodsThe spatial distribution of morbidity, mortality and case fatality was mapped using hierarchical Bayesian smoothed indirectly standardised ratios. Indirectly standardised ratios were used to evaluate the association between deprivation and the outcome measures. We looked separately at morbidity and mortality in the 10 districts with the highest and 10 districts with the lowest share of Roma population.ResultsCompared with the national average, the relative incidence of cases was 30%–36% lower in the most deprived quintile but the relative mortality and case fatality were 27%–32% higher. Expressed as incidence ratios relative to the national average, the most deprived municipalities had a relative incidence ratio of 0.64 (CI: 0.62 to 0.65) and 0.70 (CI: 0.69 to 0.72) for males and females, respectively. The corresponding figures for mortality were 1.32 (CI: 1.20 to 1.44) for males and 1.27 (CI: 1.16 to 1.39) for females and for case fatality 1.27 (CI: 1.16 to 1.39) and 1.32 (CI: 1.20 to 1.44) for males and females, respectively. The excess death rate (per 100 000) increased with deprivation levels (least deprived: 114.12 (CI: 108.60 to 119.84) and most deprived: 158.07 (CI: 149.30 to 167.23)). The 10 districts where Roma formed the greatest share of the population had an excess mortality rate 17.46% higher than the average for the most deprived quintile.ConclusionsThose living in more deprived municipalities had a lower risk of being identified as a confirmed COVID-19 case but had a higher risk of death. An inverse association between trends in morbidity and mortality by socioeconomic conditions should be a cause for concern and points to the need for responses, including those involving vaccination, to pay particular attention to inequalities and their causes.

Within I-MOVE (European programme to monitor seasonal and pandemic influenza vaccine effectiveness (IVE)) five countries conducted IVE pilot case-control studies in 2008-9. One hundred and sixty sentinel general practitioners (GP) swabbed all elderly consulting for influenza-like illness (ILI). Influenza confirmed cases were compared to influenza negative controls. We conducted a pooled analysis to obtain a summary IVE in the age group of ≥65 years. We measured IVE in each study and assessed heterogeneity between studies qualitatively and using the I2 index. We used a one-stage pooled model with study as a fixed effect. We adjusted estimates for age-group, sex, chronic diseases, smoking, functional status, previous influenza vaccinations and previous hospitalisations. The pooled analysis included 138 cases and 189 test-negative controls. There was no statistical heterogeneity (I2=0) between studies but ILI case definition, previous hospitalisations and functional status were slightly different. The adjusted IVE was 59.1% (95% CI: 15.3-80.3%). IVE was 65.4% (95% CI: 15.6-85.8%) in the 65-74, 59.6% (95% CI: -72.6 -90.6%) in the age group of ≥75 and 56.4% (95% CI: -0.2-81.3%) for A(H3). Pooled analysis is feasible among European studies. The variables definitions need further standardisation. Larger sample sizes are needed to achieve greater precision for subgroup analysis. For 2009-10, I-MOVE will extend the study to obtain early IVE estimates in groups targeted for pandemic H1N1 influenza vaccination.