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In this study, the authors estimate excess mortality at the regional level for five European countries (England, Greece, Italy, Spain, and Switzerland) in 2020. They identify the regions and time periods with highest excess mortality and show how these patterns evolved through different pandemic waves.

Abstract Aim To investigate the occurrence of traumatic stress symptoms (TSS) among healthcare workers active during the COVID-19 pandemic and to obtain insight as to which pandemic-related stressful experiences are associated with onset and persistence of traumatic stress. Methods This is a multicenter prospective cohort study. Spanish healthcare workers (N = 4,809) participated at an initial assessment (i.e., just after the first wave of the Spain COVID-19 pandemic) and at a 4-month follow-up assessment using web-based surveys. Logistic regression investigated associations of 19 pandemic-related stressful experiences across four domains (infection-related, work-related, health-related and financial) with TSS prevalence, incidence and persistence, including simulations of population attributable risk proportions (PARP). Results Thirty-day TSS prevalence at T1 was 22.1%. Four-month incidence and persistence were 11.6% and 54.2%, respectively. Auxiliary nurses had highest rates of TSS prevalence (35.1%) and incidence (16.1%). All 19 pandemic-related stressful experiences under study were associated with TSS prevalence or incidence, especially experiences from the domains of health-related (PARP range 88.4–95.6%) and work-related stressful experiences (PARP range 76.8–86.5%). Nine stressful experiences were also associated with TSS persistence, of which having patient(s) in care who died from COVID-19 had the strongest association. This association remained significant after adjusting for co-occurring depression and anxiety. Conclusions TSSs among Spanish healthcare workers active during the COVID-19 pandemic are common and associated with various pandemic-related stressful experiences. Future research should investigate if these stressful experiences represent truly traumatic experiences and carry risk for the development of post-traumatic stress disorder.

Annual influenza vaccination is the main strategy to reduce the burden of seasonal influenza epidemics and is recommended for the elderly in most countries with influenza vaccination strategies, with the main objective of preventing hospitalizations and mortality associated with seasonal influenza in this age group. Studies from different countries have estimated the benefits of seasonal influenza vaccination programs in the elderly, preventing a considerable number of cases, hospitalizations and deaths every year. A study measured the number of medically attended confirmed influenza cases in primary care that are prevented annually by vaccination in the population aged 65 and older in Spain, the Netherlands and Portugal, but estimates of the impact of the national influenza vaccination program in the prevention of severe disease in Spain are lacking. The two objectives of this study were to estimate the burden of severe influenza disease in the Spanish population and to measure the impact of influenza vaccination in the prevention of these outcomes in the population aged 65 years and older. Using influenza surveillance systems put in place before the COVID-19 pandemic, we conducted a retrospective observational study to estimate the burden of hospitalizations and ICU admissions in Spain between 2017–18 and 2019–20, by season and age group. Burden estimates for the 65+ group, combined with vaccine effectiveness (VE) and vaccination coverage (VC) data, were used as input data in an ecological, observational study to estimate the impact of the influenza vaccination program on the elderly. We found a higher burden of severe influenza disease in seasons 2017–18 and 2018–19, with A(H3N2) circulation, and in the youngest and oldest age groups. In those aged 65 and older, we estimated an average of 9900 influenza hospitalizations and 1541 ICU admissions averted by vaccination each year. Seasonal influenza vaccination was able to prevent between 11 and 26% influenza hospitalizations and around 40% ICU admissions in the elderly in the three pre-pandemic seasons. In conclusion, our study complements previous analyses in the primary care setting in Spain and demonstrates the benefits of the annual influenza vaccination program in the prevention of severe influenza disease in the elderly, even in seasons with moderate VE.

When responding to infectious disease outbreaks, rapid and accurate estimation of the epidemic trajectory is critical. However, two common data collection problems affect the reliability of the epidemiological data in real time: missing information on the time of first symptoms, and retrospective revision of historical information, including right censoring. Here, we propose an approach to construct epidemic curves in near real time that addresses these two challenges by 1) imputation of dates of symptom onset for reported cases using a dynamically-estimated "backward" reporting delay conditional distribution, and 2) adjustment for right censoring using the NobBS software package to nowcast cases by date of symptom onset. This process allows us to obtain an approximation of the time-varying reproduction number (Rt) in real time. We apply this approach to characterize the early SARS-CoV-2 outbreak in two Spanish regions between March and April 2020. We evaluate how these real-time estimates compare with more complete epidemiological data that became available later. We explore the impact of the different assumptions on the estimates, and compare our estimates with those obtained from commonly used surveillance approaches. Our framework can help improve accuracy, quantify uncertainty, and evaluate frequently unstated assumptions when recovering the epidemic curves from limited data obtained from public health systems in other locations.

Abstract Background Predicting the details of how an epidemic evolves is highly valuable as health institutions need to better plan towards limiting the infection propagation effects and optimizing their prediction and response capabilities. Simulation is a cost- and time-effective way of predicting the evolution of the infection as the joint influence of many different factors: interaction patterns, personal characteristics, travel patterns, meteorological conditions, previous vaccination, etc. The work presented in this paper extends EpiGraph, our influenza epidemic simulator, by introducing a meteorological model as a modular component that interacts with the rest of EpiGraph’s modules to refine our previous simulation results. Our goal is to estimate the effects of changes in temperature and relative humidity on the patterns of epidemic influenza based on data provided by the Spanish Influenza Sentinel Surveillance System (SISSS) and the Spanish Meteorological Agency (AEMET). Methods Our meteorological model is based on the regression model developed by AB and JS, and it is tuned with influenza surveillance data obtained from SISSS. After pre-processing this data to clean it and reconstruct missing samples, we obtain new values for the reproduction number of each urban region in Spain, every 10 minutes during 2011. We simulate the propagation of the influenza by setting the date of the epidemic onset and the initial influenza-illness rates for each urban region. Results We show that the simulation results have the same propagation shape as the weekly influenza rates as recorded by SISSS. We perform experiments for a realistic scenario based on actual meteorological data from 2010-2011, and for synthetic values assumed under simplified predicted climate change conditions. Results show that a diminishing relative humidity of 10% produces an increment of about 1.6% in the final infection rate. The effect of temperature changes on the infection spread is also noticeable, with a decrease of 1.1% per extra degree.Conclusions: Using a tool like ours could help predict the shape of developing epidemics and its peaks, and would permit to quickly run scenarios to determine the evolution of the epidemic under different conditions. We make EpiGraph source code and epidemic data publicly available.

We conducted a retrospective cohort study to assess the effect of influenza virus type and subtype on disease severity among hospitalized influenza patients in Spain. We analyzed the cases of 8,985 laboratory-confirmed case-patients hospitalized for severe influenza by using data from a national surveillance system for the period 2010–2017. Hospitalized patients with influenza A(H1N1)pdm09 virus were significantly younger, more frequently had class III obesity, and had a higher risk for pneumonia or acute respiratory distress syndrome than patients infected with influenza A(H3N2) or B (p

Abstract Background All aged individuals with a chronic condition and those with 65 and more years are at increased risk of severe influenza post-infection complications. There is limited research on cases averted by the yearly vaccination programs in high-risk individuals. The objective was to estimate the impact of trivalent seasonal influenza vaccination on averted hospitalizations and death among the high-risk population in Portugal. Methods The impact of trivalent seasonal influenza vaccination was estimated using vaccine coverage, vaccine effectiveness and the number of influenza-related hospitalizations and deaths. The number of averted events (NAE), prevented fraction (PF) and number needed to vaccinate (NVN) were estimated for seasons 2014/15 to 2016/17. Results The vaccination strategy averted on average approximately 1833 hospitalizations and 383 deaths per season. Highest NAE was observed in the ≥65 years population (85% of hospitalizations and 95% deaths) and in the 2016/17 season (1957 hospitalizations and 439 deaths). On average, seasonal vaccination prevented 21% of hospitalizations in the population aged 65 and more, and 18.5% in the population with chronic conditions. The vaccination also prevented 29% and 19.5% of deaths in each group of the high-risk population. It would be needed to vaccinate 3360 high-risk individuals, to prevent one hospitalization and 60,471 high-risk individuals to prevent one death. Conclusion The yearly influenza vaccination campaigns had a sustained positive benefit for the high-risk population, reducing hospitalizations and deaths. These results can support public health plans toward increased vaccine coverage in high-risk groups.

Introduction: Influenza A(H3N2) viruses predominated in Europe in 2016–17. In 2017–18 A(H3N2) and A(H1N1)pdm09 viruses co-circulated. The A(H3N2) vaccine component was the same in both seasons; while the A(H1N1)pdm09 component changed in 2017–18. In both seasons, vaccine seed A(H3N2) viruses developed adaptations/alterations during propagation in eggs, impacting antigenicity. Methods: We used the test-negative design in a multicentre primary care case-control study in 12 European countries to measure 2016–17 and 2017–18 influenza vaccine effectiveness (VE) against laboratory-confirmed influenza A(H1N1)pdm09 and A(H3N2) overall and by age group. Results: During the 2017–18 season, the overall VE against influenza A(H1N1)pdm09 was 59% (95% CI: 47–69). Among those aged 0–14, 15–64 and ≥65 years, VE against A(H1N1)pdm09 was 64% (95% CI: 37–79), 50% (95% CI: 28–66) and 66% (95% CI: 42–80), respectively. Overall VE against influenza A(H3N2) was 28% (95% CI: 17–38) in 2016–17 and 13% (95% CI: −15 to 34) in 2017–18. Among 0–14-year-olds VE against A(H3N2) was 28% (95%CI: −10 to 53) and 29% (95% CI: −87 to 73), among 15–64-year-olds 34% (95% CI: 18–46) and 33% (95% CI: −3 to 56) and among those aged ≥65 years 15% (95% CI: −10 to 34) and −9% (95% CI: −74 to 32) in 2016–17 and 2017–18, respectively. Conclusions: Our study suggests the new A(H1N1)pdm09 vaccine component conferred good protection against circulating strains, while VE against A(H3N2) was

Measuring mortality has been a challenge during the COVID-19 pandemic. Here, we compared the results from the Spanish daily mortality surveillance system (MoMo) of excess mortality estimates, using a time series analysis, with those obtained for the confirmed COVID-19 deaths reported to the National Epidemiological Surveillance Network (RENAVE). The excess mortality estimated at the beginning of March 2020 was much greater than what has been observed in previous years, and clustered in a very short time. The cumulated excess mortality increased with age. In the first epidemic wave, the excess mortality estimated by MoMo was 1.5 times higher than the confirmed COVID-19 deaths reported to RENAVE, but both estimates were similar in the following pandemic waves. Estimated excess mortality and confirmed COVID-19 mortality rates were geographically distributed in a very heterogeneous way. The greatest increase in mortality that has taken place in Spain in recent years was detected early by MoMo, coinciding with the spread of the COVID-19 pandemic. MoMo is able to identify risk situations for public health in a timely manner, relying on mortality in general as an indirect indicator of various important public health problems.

Based on previous observations during pandemics and seasonal epidemics, pregnant women are considered at risk of developing severe influenza outcomes after influenza infection. With the aim of preventing severe influenza illness, the World Health Organization (WHO) includes pregnant women as a target group for seasonal influenza vaccination. However, influenza vaccine uptake during pregnancy remains low in many countries, including Spain. The objectives of this study were to increase the evidence of pregnancy as a risk factor for severe influenza illness and to study the potential role of seasonal influenza vaccination in the prevention of severe outcomes in infected pregnant women. Using information from the surveillance of Severe Hospitalized Confirmed Influenza Cases (SHCIC) in Spain, from seasons 2010/11 to 2015/16, we estimated that pregnant women in our study had a relative risk of hospitalization with severe influenza nearly 7.8 times higher than non-pregnant women of reproductive age. Only 5 out of 167 pregnant women with known vaccination status in our study had been vaccinated (3.6%). Such extremely low vaccination coverage only allowed obtaining crude estimates suggesting a protective effect of the vaccine against influenza complications (ICU admission or death). Our overall results support that pregnant women could benefit from seasonal influenza vaccination, in line with national and international recommendations.

Objetivo: El sistema de monitorización de la mortalidad diaria en España y el programa European monitoring of excess mortality for public health action detectaron un exceso de mortalidad en España en febrero y marzo de 2012. El objetivo de este trabajo es estudiar el papel que puede atribuirse a la gripe como factor de sobremortalidad en ese periodo. Métodos: Se estudiaron los excesos de mortalidad por todas las causas en el periodo 2006-2012 utilizando series temporales en el sistema de vigilancia de la mortalidad diaria español y mediante regresión de Poisson en el sistema de vigilancia de la mortalidad europeo y en un modelo que estima la mortalidad atribuible a la gripe. Los excesos de mortalidad por gripe y neumonía atribuibles a la gripe se estudiaron con un modelo Serfling modificado. Para detectar los periodos de exceso se comparó la mortalidad observada con la esperada. Resultados: En febrero y marzo de 2012, en los sistemas de monitorización de mortalidad español y europeo se detectó un exceso de mortalidad de 8110 y 10.872 defunciones (razón de mortalidad: 1,22, intervalo de confianza del 95% [IC95%]: 1,21-1,23, y 1,32, IC95%: 1,29-1,31, respectivamente). El modelo que estima la mortalidad atribuible a la gripe identificó en la temporada 2011-2012 el máximo porcentaje (97%) de defunciones atribuibles a la gripe en mayores de 64 años con respecto al total de la mortalidad asociada a la gripe (13.822 defunciones). La tasa de excesos de defunciones por gripe y neumonía y causas respiratorias en mayores de 64 años, obtenida con el modelo Serfling, fue máxima en la temporada 2011-2012: 18,07 y 77,20 defunciones por 100.000 habitantes, respectivamente. Conclusiones: Uno de los principales incrementos significativos de la mortalidad acontecidos en España en los inviernos de los últimos años, en mayores de 64 años, fue detectado por los sistemas de monitorización de mortalidad español y europeo en la temporada 2011-2012, coincidiendo en el tiempo con una tardía temporada gripal, con predominio de virus A(H3N2), y una ola de bajas temperaturas. Este estudio muestra que la gripe pudo ser uno de los principales factores contribuyentes al exceso de mortalidad observado en el invierno de 2012 en España.

Recent studies suggest that the protective effect of the current influenza vaccine could be influenced by vaccination in previous seasons. We estimated the combined effect of the previous and current influenza vaccines from the 2010-2011 season to the 2015-2016 season in Spain.We performed a test-negative case-control study in patients ≥9 years old. We estimated the influenza vaccine effectiveness (IVE) against influenza A(H1N1)pdm09, A(H3N2), and B virus.We included 1206 influenza A(H1N1)pdm09 cases, 1358 A(H3N2) cases and 1079 B cases. IVE against A(H1N1)pdm09 virus in the pooled-season analysis was 53% (95% Confidence Interval (CI): 21% to 72%) for those vaccinated only in the current season and 50% (95%CI: 23% to 68%) for those vaccinated in the both current and previous seasons. Against the influenza A(H3N2) virus, IVE was 17% (95%CI: -43% to 52%) for those vaccinated only in the current season and 3% (95%CI: -33% to 28%) for those vaccinated in both seasons. Regarding influenza B, we obtained similar IVEs for those vaccinated only in the current and those vaccinated in both seasons: 57% (95%CI: 12% to 79%) and 56% (95%CI: 36% to 70%), respectively.Our results suggested no interference between the previous and current influenza vaccines against A(H1N1)pdm09 and B viruses, but a possible negative interference against A(H3N2) virus.

Fundamentos: Desde 2008-09 la efectividad de la vacuna (EV) antigripal en España se estima con el estudio de casos y controles para la evaluación de la EV antigripal (cycEVA), componente español de la red europea (Influenza-Monitoring Vaccine Effectiveness (I-MOVE). El objetivo es describir la evolución del estudio cycEVA durante las cinco temporadas del período 2008/09– 2012/13. Métodos: Se analizaron los siguientes indicadores: 1) participación de los médicos/pediatras centinela (MP); 2) población y periodo de estudio, 3) calidad de los datos y 4) difusión de los resultados mediantes publicaciones. Se calculó el porcentaje anual de cambio constante de los indicadores analizándose su tendencia mediante el test de Cochran-Armitage. Resultados: El número de MP participantes aumentó de 164 en 2008-09 hasta 246 en ediciones posteriores. El porcentaje de médicos que reclutaron al menos un paciente experimentó un cambio anual significativo (PCA) del 15,33%. El porcentaje de pacientes reclutados incluidos en el análisis aumen- tó del 77% en 2008-09 a más del 95% en las siguientes ediciones (PCA=5,91%). El porcentaje de casos y controles participantes en cycEVA sobre el total de pacientes que contribuyeron al estudio europeo I-MOVE osciló entre el 23% en la edición piloto y 30% en la temporada 2011-12. Los resultados finales se difundieron en revistas científicas con un factor de impacto situado en el cuartil 2 y en 2010-11 y 2011-12 se publicaron resultados preliminares en revistas con un factor de impacto situado en el cuartil 1 (97 citas). Conclusiones: La experiencia del estudio cycEVA se reflejó en una mejora en la oportunidad e impacto de sus resultados, cruciales para orientar las recomendaciones anuales de vacunación antigripal.

Objective: To estimate the excess deaths attributed to influenza in Spain, using age-specific generalized linear models (GLM) and the Serfling model for the period 1999-2005. Method: We reviewed mortality from influenza and pneumonia and all-cause deaths. We used an additive GLM procedure, including the numbers of weekly deaths as a response variable and the number of influenza virus and respiratory syncytial virus weekly isolates, the population and two variables to adjust for annual fluctuations as covariates. Using the Serfling model, we removed the trend and applied a temporal regression model, excluding data from December to April to account for the expected baseline mortality in the absence of influenza activity. Results: Globally, the excess mortality attributable to influenza was 1.1 deaths per 100,000 for influenza and pneumonia and 11 all-cause deaths per 100,000 using the GLM model. The highest mortality rates were obtained with the Serfling model in adults older than 64 years, with an excess mortality attributable to influenza of 57 and 164 deaths per 100,000 for influenza and pneumonia and all-cause, respectively. Conclusions: The GLM model, which takes viral activity into account, yields systematically lower estimates of excess mortality than the Serfling model. The GLM model provides independent estimates associated with the activity of different viruses and even with other factors, which is a significant advantage when trying to understand the impact of viral respiratory infections on mortality in the Spanish population.Objetivo: Estimar los excesos de mortalidad atribuible a la gripe en España por grupos de edad, usando modelos lineales generalizados (MLG) y modelos Serfling, para el periodo 1999-2005. Método: Se revisó la mortalidad por gripe y neumonía y por todas las causas. En el MLG aditivo se incluyó como variable respuesta el número de defunciones semanales, y como covariables el número de aislamientos semanales de virus de la gripe y de virus respiratorio sincitial, la población y dos variables que corrigen las fluctuaciones anuales. En el modelo Serfling se eliminó previamente la tendencia y se aplicó un modelo de regresión cíclica, excluyendo los valores desde diciembre hasta abril, para cuantificar la mortalidad esperada en ausencia de actividad gripal. Resultados: El exceso de mortalidad atribuible a la gripe fue de 1,1 defunciones por 100.000 habitantes por gripe y neumonía, y de 11 defunciones por todas las causas usando el MLG. Las tasas de mortalidad más altas se observaron con el modelo Serfling en los mayores de 64 años, con un exceso de mortalidad de 57 y 164 defunciones por 100.000 habitantes por gripe y neumonía y por todas las causas, respectivamente. Conclusiones: El MLG tiene en cuenta la actividad viral y produce de forma sistemática estimaciones de exceso de mortalidad más bajas que el modelo Serfling. El MLG tiene la ventaja de dar estimaciones independientes asociadas a la actividad de diferentes virus y otros factores, lo cual representa un paso importante cuando intentamos entender el impacto de las infecciones virales respiratorias en la mortalidad de nuestra población.

Fundamentos: El indicador Años Potenciales de Vida Perdidos (APVP) ha sido utilizado con frecuencia en análisis de mortalidad precoz, y recientemente ha servido para estimar el impacto de la última pandemia de gripe A(H1N1) pdm09. El objetivo de este estudio ha sido estimar los excesos de defunciones por gripe y neumonía (GyN) en España y los APVP durante el periodo 1980-2008, valorando la mortalidad atribuible a gripe en función del tipo/subtipo de virus predominante. Métodos: Los excesos de defunciones mensuales se calcularon con modelos de regresión cíclica. El cálculo de APVP se realizó como el producto del número de excesos de defunciones por la diferencia entre la esperanza de vida al nacer y los años vividos para cada grupo de edad. El análisis de la variación entre los excesos de defunciones por GyN y APVP, según el tipo/subtipo de virus de la gripe predominante, se llevó a cabo con un análisis de regresión de Poisson. Resultados: En las temporadas con predominio del virus de la gripe A(H3) el promedio de excesos de defunciones por GyN se estimó en 1.348 y de APVP en 5.297, mientras que en las temporadas con predominio de A(H1) o B el promedio de excesos por las mismas causas fue de 648 y de APVP de 2.885. Las razones de tasas ajustadas de excesos (2,11; IC-95%=2,05-2,16) y de APVP (1,86; IC-95%=1,83-1,88) señalaron que las frecuencias relativas de ambos indicadores son significativamente mayores en las temporadas con predominio de virus de la gripe A(H3). Conclusiones: Los excesos de defunciones y APVP se duplicaron al comparar las temporadas con predominio del subtipo A(H3) frente al resto de virus de la gripe.

Objetivos: Estimar el valor del número de reproducción básico durante la onda pandémica de gripe A(H1N1)2009 en España y evaluar su impacto en la mortalidad de la población española, en comparación con el de las temporadas de gripe estacional previas. Métodos: Los datos sobre la incidencia de gripe y las detecciones de virus se han obtenido del Sistema de Vigilancia de Gripe en España. Las defunciones por el virus pandémico se obtuvieron del Registro de casos graves y defunciones del Centro de Coordinación de Alertas y Emergencias del Ministerio de Sanidad y Política Social, y las producidas por la gripe estacional, durante el periodo 2003-2008, del Registro de Mortalidad del Instituto Nacional de Estadística. El número de reproducción se estimó por dos métodos: el primero utilizando la tasa de crecimiento de la incidencia acumulada de gripe durante la fase de crecimiento exponencial de la onda pandémica, y el segundo (estimación de máxima verosimilitud) mediante el análisis de las fechas de inicio de los síntomas observadas en pares de casos en función de la distribución del tiempo de generación. Se calcularon la tasa de letalidad y de mortalidad por gripe, comparando los años potenciales de vida perdidos de la temporada pandémica con anteriores temporadas interpandémicas. Resultados: El inicio de la onda pandémica en España se produjo precozmente en la semana 40/2009 (del 4 al 10 de octubre), con un absoluto predominio de la nueva cepa en el patrón de virus circulantes. El valor de R0 en la fase de crecimiento de la onda fue de 1,29 (IC95%: 1,25-1,33) estimado con el primer método, y de 1,01 (IC95%: 0,99-1,03) con el segundo método. Durante la temporada pandémica se registraron 318 defunciones por gripe, afectando a grupos de edad más jóvenes que en temporadas interpandémicas anteriores. Ello ha supuesto que el número de años potenciales de vida perdidos en la temporada pandémica (11.612) se estime en seis veces el promedio anual ajustado de las temporadas interpandémicas de comparación (1.802). Conclusiones: Los valores estimados de R0 durante la fase de crecimiento de la onda pandémica se encuentran en el rango inferior de estimaciones de ese parámetro en pandemias anteriores. Los indicadores de mortalidad calculados en el periodo pandémico señalan un aumento de las defunciones, en comparación con temporadas interpándemicas previas, más acusado en edades jóvenes.Objectives: To estimate the value of the basic reproduction number for the pandemic wave of influenza A (H1N1) 2009 in Spain and to assess its impact on morbidity and mortality in the Spanish population compared with those in the previous influenza season. Methods: Data on the incidence of influenza and viral detections were obtained from the Spanish Influenza Surveillance System. Deaths from pandemic influenza were obtained from the Coordinating Center for Health Alerts and Emergencies of the Spanish Ministry of Health and Social Policy, and deaths from seasonal influenza during the period 2003-2008 were obtained from the National Statistics Institute. The reproduction number was estimated by two methods: firstly, by using the growth rate of the cumulative incidence of influenza during the exponential growth phase of the pandemic wave, and secondly (maximum likelihood estimation), through analysis the dates of onset of symptoms observed in pairs of cases based on generation time distribution. We calculated the fatality rate and mortality from influenza by comparing potential years of life lost in the pandemic season with those in previous interpandemic seasons. Results: The start of the pandemic wave occurred in Spain earlier in week 40/2009 (from 4 to 10 October), with an absolute predominance of the new strain in the pattern of circulating viruses. The value of R0 in the growth phase of the wave was 1.29 (95% CI: 1.25-1.33), estimated with the first method, and was 1.01 (95% CI: 0.99-1.03) with the second method. During the pandemic season, there were 318 deaths from pandemic influenza, affecting younger age groups than in previous interpandemic seasons. Consequently, the number of potential years of life lost in the pandemic season (11,612) was estimated at six times the adjusted annual average of the interpandemic influenza seasons for comparison (1,802). Conclusions: The estimates of R0 for the growth phase of the pandemic wave were in the lower range of estimates of this parameter in previous pandemics. Mortality indicators calculated in the pandemic period showed an increase in deaths compared with previous interpandemic seasons, which was most pronounced in young patients.

Introduction: The Spanish influenza surveillance system (SISS) maintained its activity during the summer of 2009 to monitor the influenza pandemic. Objectives: To describe pandemic influenza activity from May to September 2009 and to estimate the effectiveness of the 2008-9 seasonal influenza vaccine against laboratory-confirmed pandemic (H1N1) 2009 influenza. Methods: Data from the SISS were used to identify the trend of pandemic (H1N1) 2009 influenza outside the influenza season. For the effectiveness study, we compared the vaccination status of notified cases [influenza-like illnesses (ILI) laboratory confirmed as pandemic influenza] with that of the test-negative controls. Results: The first laboratory-confirmed case of the pandemic virus was notified in the system in week 20/2009. The ILI rate increased gradually in the study period, exceeding basic activity in week 38. The proportion of pandemic (H1N1) 2009 influenza viruses detected by the system represented 14% in week 20/2009 and rapidly increased to 90% in week 34. The adjusted vaccine effectiveness of the 2008-9 seasonal vaccine against laboratory-confirmed pandemic influenza was 12% (-30; 41). Conclusions: The SISS became an essential tool for pandemic monitoring in Spain. The improved SISS will provide more accurate information on influenza activity in future seasonal or pandemic waves. Using surveillance data, we could not demonstrate the effectiveness of the seasonal 2008-9 vaccine against laboratory-confirmed pandemic influenza.Introducción: El Sistema de Vigilancia de Gripe en España (SVGE) continuó y reforzó su actividad durante el verano de 2009 con el objetivo de vigilar la evolución de la pandemia en España. Objetivos: Describir la actividad de la gripe pandémica en España de mayo a septiembre de 2009 y estimar la efectividad de la vacuna antigripal estacional 2008-2009 frente a casos confirmados de gripe pandémica (H1N1) 2009. Métodos: Se utilizaron datos del SVGE para presentar la evolución de la pandemia por virus (H1N1) 2009 fuera de la temporada de vigilancia 2008-2009. Para el estudio de la efectividad vacunal se comparó el estado vacunal de los casos de gripe pandémica confirmados por laboratorio con el de los casos negativos para el virus de la gripe (controles negativos). Resultados: El primer caso confirmado de virus pandémico se notificó en la semana 20/2009. La incidencia de gripe aumentó paulatinamente durante el periodo estudiado y sobrepasó el umbral basal en la semana 38/2009. La proporción de virus (H1N1) 2009 detectada por el SVGE fue del 14% en la semana 20 y aumentó rápidamente, llegando a alcanzar el 90% en la semana 34. La efectividad ajustada de la vacuna antigripal 2008-2009 frente a casos confirmados de gripe pandémica fue del 12% (-30; 41). Conclusiones: El SVGE se adaptó y mejoró de forma rápida a las exigencias nacionales e internacionales de vigilancia de la pandemia. Esta mejora supone información más precisa y de calidad en futuras ondas epidémicas/pandémicas. Con los datos obtenidos en vigilancia no se pudo demostrar alguna efectividad de la vacuna antigripal 2008-2009 frente a los casos de gripe pandémica confirmados por laboratorio.

Fundamento: El sistema español de monitorización de la mortalidad y el «Programa Europeo de monitorización de excesos de mortalidad para la acción en salud pública» detectaron dos excesos de mortalidad en España en noviembre y diciembre de 2009. El objetivo de este trabajo es valorar su posible asociación con la transmisión de gripe pandémica. Métodos: Se analizó la evolución de la mortalidad en España en los meses citados utilizando métodos de análisis de series temporales basados en las series históricas de mortalidad y se comparó en el tiempo con la transmisión de gripe. Resultados: La mortalidad observada en la población total fue mayor de lo esperado en dos periodos: semanas 46-47/2009 con 5,75% de exceso y las semanas 51-52/2009 con 7,35% de exceso. También se registró un exceso de mortalidad en niños de 5 a 14 años en las semanas 46-48/2009 con 41 defunciones vs las 21 esperadas. El exceso de mortalidad en noviembre fue concomitante con las mayores tasas de gripe. El exceso de diciembre se observó 5 semanas después del pico de gripe y coincidió con un descenso dramático de las temperaturas. El virus sincitial respiratorio y los accidentes de tráfico fueron descartados como factores asociados. Conclusiones: Mientras que las temperaturas podrían explicar la mayoría del exceso de mortalidad observado en diciembre, ningún factor por si solo podría explicar el exceso de noviembre.

Fundamento: España experimentó una circulación del nuevo virus de la gripe (H1N1)2009 durante el verano de 2009, que evolucionó de forma creciente hasta la presentación a principios del otoño de la primera onda pandémica por dicho virus. Los objetivos de este trabajo son describir la evolución de esta onda pandémica en nuestro país y evaluar su impacto en la morbilidad y mortalidad de la población española. Método: A partir de la información proporcionada por el Sistema de Vigilancia de la Gripe en España y el Centro de Coordinación de Alertas y Emergencias del Ministerio de Sanidad y Política Social se han estimado una serie de indicadores epidemiológicos y virológicos para evaluar el nivel de actividad e intensidad de la onda pandémica, así como su gravedad. Resultados: La onda pandémica por el virus (H1N1)2009 se inició a comienzos del otoño de 2009 y registró valores máximos de incidencia de gripe de 372,15 casos semanales/100.000 habitantes. Las mayores tasas de incidencia de gripe se observaron en los menores de 15 años. La tasa de detección viral en el periodo pandémico se mantuvo en el rango de las registradas previamente (46,4%). Se estimó una tasa de letalidad global de 0,43 defunciones por 1.000 casos de gripe pandémica. Un 64% de las defunciones por gripe pandémica se registraron en adultos jóvenes, con máximas tasas de mortalidad en el grupo de 45-64 años (9,35 defunciones/1.000.000 habitantes). La mortalidad asociada a gripe estacional en el periodo 2001- 2008 fue máxima en los mayores de 64 años (95% del total de defunciones). Conclusiones: La onda pandémica por el virus de la gripe (H1N1)2009 tuvo una presentación precoz en España y una intensidad media en comparación con las trece ondas estacionales previas de gripe. Esta primera onda también se caracterizó por un carácter leve, teniendo en cuenta tasas de letalidad o mortalidad, si bien un elevado porcentaje de las defunciones confirmadas por el nuevo virus se ha observado en menores de 65 años.

El potencial pandémico de la gripe ha convertido a esta enfermedad en el objetivo preferente de los sistemas de vigilancia nacionales e internacionales. Los sistemas centinela, por sus características, permiten una integración de información virológica y epidemiológica de esta enfermedad de elevada incidencia, ayudando a detectar y caracterizar precozmente los virus de la gripe circulantes y evaluando su capacidad de propagación en la población. La creación en España, hace más de 10 años, de un sistema centinela, que cubre actualmente el 75% de la población nacional, supuso una forma diferente de abordar la vigilancia de la gripe humana, a través de la declaración individualizada de los casos de la enfermedad y la unión de datos clínicos, epidemiológicos y microbiológicos, y ha contribuido a una evaluación más correcta de la actividad de la gripe en el territorio español. A pesar de las limitaciones de este sistema centinela, derivadas fundamentalmente de los problemas de representatividad que todo sistema de vigilancia basado en muestras de población puede presentar, los datos que aporta se han revelado útiles para el seguimiento y el control de la gripe. La rapidez en la transmisión de la información es uno de los principales atributos del sistema, que posibilita su integración en las redes de vigilancia internacional de la enfermedad y ayuda a lograr una mejor oportunidad en la difusión de la información y formulación de recomendaciones.The pandemic potential of influenza has made this disease the principal target of both national and international surveillance systems. The intrinsic characteristics of sentinel networks enable them to integrate epidemiological and virological information of a high incidence disease such as influenza, so helping in the early detection and characterization of the circulating influenza viruses and in evaluating their spread capacity in the population. A sentinel network, which covers 75% of the population, was created in Spain more than ten years ago. This provides a new approach to human influenza surveillance based on the individualized reporting of each case and the linkage of clinical, epidemiological and virological data. This system has contributed to a more accurate evaluation of influenza activity in Spain. In spite of the limitations of this sentinel system, which mainly derive from the lack of representativeness that any surveillance system based on population samples can encounter, it provides data which have proved useful for the follow-up and control of influenza. Rapid information transmission is one of the main advantages of the system, allowing its integration in the international disease surveillance networks and improving the timeliness of both information spread and formulation of recommendations.

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.