Vaccine effectiveness against COVID-19 hospitalisation in adults (≥ 20 years) during Omicron-dominant circulation: I-MOVE-COVID-19 and VEBIS SARI VE networks, Europe, 2021 to 2022.

IntroductionThe I-MOVE-COVID-19 and VEBIS hospital networks have been measuring COVID-19 vaccine effectiveness (VE) in participating European countries since early 2021.AimWe aimed to measure VE against PCR-confirmed SARS-CoV-2 in patients ≥ 20 years hospitalised with severe acute respiratory infection (SARI) from December 2021 to July 2022 (Omicron-dominant period).MethodsIn both networks, 46 hospitals (13 countries) follow a similar test-negative case-control protocol. We defined complete primary series vaccination (PSV) and first booster dose vaccination as last dose of either vaccine received ≥ 14 days before symptom onset (stratifying first booster into received < 150 and ≥ 150 days after last PSV dose). We measured VE overall, by vaccine category/product, age group and time since first mRNA booster dose, adjusting by site as a fixed effect, and by swab date, age, sex, and presence/absence of at least one commonly collected chronic condition.ResultsWe included 2,779 cases and 2,362 controls. The VE of all vaccine products combined against hospitalisation for laboratory-confirmed SARS-CoV-2 was 43% (95% CI: 29-54) for complete PSV (with last dose received ≥ 150 days before onset), while it was 59% (95% CI: 51-66) after addition of one booster dose. The VE was 85% (95% CI: 78-89), 70% (95% CI: 61-77) and 36% (95% CI: 17-51) for those with onset 14-59 days, 60-119 days and 120-179 days after booster vaccination, respectively.ConclusionsOur results suggest that, during the Omicron period, observed VE against SARI hospitalisation improved with first mRNA booster dose, particularly for those having symptom onset < 120 days after first booster dose.

Influenza hospitalisations in Spain between the last influenza and COVID-19 pandemic (2009-2019).

Knowing the burden of severe disease caused by influenza is essential for disease risk communication, to understand the true impact of vaccination programmes and to guide public health and disease control measures. We estimated the number of influenza-attributable hospitalisations in Spain during the 2010-2011 to 2019-2020 seasons - based on the hospitalisations due to severe acute respiratory infection (SARI) in Spain using the hospital discharge database and virological influenza information from the Spanish Influenza Sentinel Surveillance System (SISSS). The weekly numbers of influenza-attributable hospitalisations were calculated by multiplying the weekly SARI hospitalisations by the weekly influenza virus positivity, obtained from the SISSS in each season, stratified by age group and sex. The influenza-related hospitalisation burden is age-specific and varies significantly by influenza season. People aged 65 and over yielded the highest average influenza-attributable hospitalisation rates per season (615.6 per 100,000), followed by children aged under 5 (251.2 per 100,000). These results provide an essential contribution to influenza control and to improving existing vaccination programmes, as well as to the optimisation and planning of health resources and policies.

Impact of Influenza Vaccination on the Burden of Severe Influenza in the Elderly: Spain, 2017-2020.

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.

Corrigendum: Simulation of COVID-19 propagation scenarios in the Madrid metropolitan area.

[This corrects the article DOI: 10.3389/fpubh.2021.636023.].

Effect of neuraminidase inhibitor (oseltamivir) treatment on outcome of hospitalised influenza patients, surveillance data from 11 EU countries, 2010 to 2020.

BackgroundTimely treatment with neuraminidase inhibitors (NAI) can reduce severe outcomes in influenza patients.AimWe assessed the impact of antiviral treatment on in-hospital deaths of laboratory-confirmed influenza patients in 11 European Union countries from 2010/11 to 2019/20.MethodsCase-based surveillance data from hospitalised patients with known age, sex, outcome, ward, vaccination status, timing of antiviral treatment, and hospitalisation were obtained. A mixed effect logistic regression model using country as random intercept was applied to estimate the adjusted odds ratio (aOR) for in-hospital death in patients treated with NAIs vs not treated.ResultsOf 19,937 patients, 31% received NAIs within 48 hours of hospital admission. Older age (60-79 years aOR 3.0, 95% CI: 2.4-3.8; 80 years 8.3 (6.6-10.5)) and intensive care unit admission (3.8, 95% CI: 3.4-4.2) increased risk of dying, while early hospital admission after symptom onset decreased risk (aOR 0.91, 95% CI: 0.90-0.93). NAI treatment initiation within 48 hours and up to 7 days reduced risk of dying (0-48 hours aOR 0.51, 95% CI: 0.45-0.59; 3-4 days 0.59 (0.51-0.67); 5-7 days 0.64 (0.56-0.74)), in particular in patients 40 years and older (e.g. treatment within 48 hours: 40-59 years aOR 0.43, 95% CI: 0.28-0.66; 60-79 years 0.50 (0.39-0.63); ≥80 years 0.51 (0.42-0.63)).ConclusionNAI treatment given within 48 hours and possibly up to 7 days after symptom onset reduced risk of in-hospital death. NAI treatment should be considered in older patients to prevent severe outcomes.

COVID-19 vaccine effectiveness against hospitalization due to SARS-CoV-2: A test-negative design study based on Severe Acute Respiratory Infection (SARI) sentinel surveillance in Spain.

BACKGROUND: With the emergence of SARS-CoV-2, influenza surveillance systems in Spain were transformed into a new syndromic sentinel surveillance system. The Acute Respiratory Infection Surveillance System (SiVIRA in Spanish) is based on a sentinel network for acute respiratory infection (ARI) surveillance in primary care and a network of sentinel hospitals for severe ARI (SARI) surveillance in hospitals. METHODS: Using a test-negative design and data from SARI admissions notified to SiVIRA between January 1 and October 3, 2021, we estimated COVID-19 vaccine effectiveness (VE) against hospitalization, by age group, vaccine type, time since vaccination, and SARS-CoV-2 variant. RESULTS: VE was 89% (95% CI: 83-93) against COVID-19 hospitalization overall in persons aged 20 years and older. VE was higher for mRNA vaccines, and lower for those aged 80 years and older, with a decrease in protection beyond 3 months of completing vaccination, and a further decrease after 5 months. We found no differences between periods with circulation of Alpha or Delta SARS-CoV-2 variants, although variant-specific VE was slightly higher against Alpha. CONCLUSIONS: The SiVIRA sentinel hospital surveillance network in Spain was able to describe clinical and epidemiological characteristics of SARI hospitalizations and provide estimates of COVID-19 VE in the population under surveillance. Our estimates add to evidence of high effectiveness of mRNA vaccines against severe COVID-19 and waning of protection with time since vaccination in those aged 80 or older. No substantial differences were observed between SARS-CoV-2 variants (Alpha vs. Delta).

Evaluation of vaccination strategies for the metropolitan area of Madrid via agent-based simulation.

OBJECTIVE: We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. MATERIALS AND METHODS: The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator-including the vaccination model-is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million. RESULTS: The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation. CONCLUSION: The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities.

Initial assessment of the COVID-19 vaccination's impact on case numbers, hospitalisations and deaths in people aged 80 years and older, 15 EU/EEA countries, December 2020 to May 2021.

Prioritisation of elderly people in COVID-19 vaccination campaigns aimed at reducing severe outcomes in this group. Using EU/EEA surveillance and vaccination uptake, we estimated the risk ratio of case, hospitalisation and death notifications in people 80 years and older compared with 25-59-year-olds. Highest impact was observed for full vaccination uptake 80% or higher with reductions in notification rates of cases up to 65% (IRR: 0.35; 95% CI: 0.13-0.99), hospitalisations up to 78% (IRR: 0.22; 95% CI: 0.13-0.37) and deaths up to 84% (IRR: 0.16; 95% CI: 0.13-0.20).

The Impact of COVID-19 on Mortality in Spain: Monitoring Excess Mortality (MoMo) and the Surveillance of Confirmed COVID-19 Deaths.

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.

Assessing population-sampling strategies for reducing the COVID-19 incidence.

As long as critical levels of vaccination have not been reached to ensure heard immunity, and new SARS-CoV-2 strains are developing, the only realistic way to reduce the infection speed in a population is to track the infected individuals before they pass on the virus. Testing the population via sampling has shown good results in slowing the epidemic spread. Sampling can be implemented at different times during the epidemic and may be done either per individual or for combined groups of people at a time. The work we present here makes two main contributions. We first extend and refine our scalable agent-based COVID-19 simulator to incorporate an improved socio-demographic model which considers professions, as well as a more realistic population mixing model based on contact matrices per country. These extensions are necessary to develop and test various sampling strategies in a scenario including the 62 largest cities in Spain; this is our second contribution. As part of the evaluation, we also analyze the impact of different parameters, such as testing frequency, quarantine time, percentage of quarantine breakers, or group testing, on sampling efficacy. Our results show that the most effective strategies are pooling, rapid antigen test campaigns, and requiring negative testing for access to public areas. The effectiveness of all these strategies can be greatly increased by reducing the number of contacts for infected individual.

The Global Epidemiology of RSV in Community and Hospitalized Care: Findings From 15 Countries.

BACKGROUND: Respiratory syncytial virus (RSV) is one of the leading causes of acute respiratory tract infections. To optimize control strategies, a better understanding of the global epidemiology of RSV is critical. To this end, we initiated the Global Epidemiology of RSV in Hospitalized and Community care study (GERi). METHODS: Focal points from 44 countries were approached to join GERi and share detailed RSV surveillance data. Countries completed a questionnaire on the characteristics of their surveillance system. RESULTS: Fifteen countries provided granular surveillance data and information on their surveillance system. A median (interquartile range) of 1641 (552-2415) RSV cases per season were reported from 2000 and 2020. The majority (55%) of RSV cases occurred in the <1-year-olds, with 8% of cases reported in those aged ≥65 years. Hospitalized cases were younger than those in community care. We found no age difference between RSV subtypes and no clear pattern of dominant subtypes. CONCLUSIONS: The high number of cases in the <1-year-olds indicates a need to focus prevention efforts in this group. The minimal differences between RSV subtypes and their co-circulation implies that prevention needs to target both subtypes. Importantly, there appears to be a lack of RSV surveillance data in the elderly.

Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries.

BACKGROUND: Respiratory syncytial virus (RSV) infections are one of the leading causes of lower respiratory tract infections and have a major burden on society. For prevention and control to be deployed effectively, an improved understanding of the seasonality of RSV is necessary. OBJECTIVES: The main objective of this study was to contribute to a better understanding of RSV seasonality by examining the GERi multi-country surveillance dataset. METHODS: RSV seasons were included in the analysis if they contained ≥100 cases. Seasonality was determined using the "average annual percentage" method. Analyses were performed at a subnational level for the United States and Brazil. RESULTS: We included 601 425 RSV cases from 12 countries. Most temperate countries experienced RSV epidemics in the winter, with a median duration of 10-21 weeks. Not all epidemics fit this pattern in a consistent manner, with some occurring later or in an irregular manner. More variation in timing was observed in (sub)tropical countries, and we found substantial differences in seasonality at a subnational level. No association was found between the timing of the epidemic and the dominant RSV subtype. CONCLUSIONS: Our findings suggest that geographical location or climatic characteristics cannot be used as a definitive predictor for the timing of RSV epidemics and highlight the need for (sub)national data collection and analysis.

Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area.

This work presents simulation results for different mitigation and confinement scenarios for the propagation of COVID-19 in the metropolitan area of Madrid. These scenarios were implemented and tested using EpiGraph, an epidemic simulator which has been extended to simulate COVID-19 propagation. EpiGraph implements a social interaction model, which realistically captures a large number of characteristics of individuals and groups, as well as their individual interconnections, which are extracted from connection patterns in social networks. Besides the epidemiological and social interaction components, it also models people's short and long-distance movements as part of a transportation model. These features, together with the capacity to simulate scenarios with millions of individuals and apply different contention and mitigation measures, gives EpiGraph the potential to reproduce the COVID-19 evolution and study medium-term effects of the virus when applying mitigation methods. EpiGraph, obtains closely aligned infected and death curves related to the first wave in the Madrid metropolitan area, achieving similar seroprevalence values. We also show that selective lockdown for people over 60 would reduce the number of deaths. In addition, evaluate the effect of the use of face masks after the first wave, which shows that the percentage of people that comply with mask use is a crucial factor for mitigating the infection's spread.

Infection fatality risk for SARS-CoV-2 in community dwelling population of Spain: nationwide seroepidemiological study.

OBJECTIVE: To estimate the infection fatality risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), based on deaths with confirmed coronavirus disease 2019 (covid-19) and excess deaths from all causes. DESIGN: Nationwide seroepidemiological study. SETTING: First wave of covid-19 pandemic in Spain. PARTICIPANTS: Community dwelling individuals of all ages. MAIN OUTCOME MEASURES: The main outcome measure was overall, and age and sex specific, infection fatality risk for SARS-CoV-2 (the number of covid-19 deaths and excess deaths divided by the estimated number of SARS-CoV-2 infections) in the community dwelling Spanish population. Deaths with laboratory confirmed covid-19 were obtained from the National Epidemiological Surveillance Network (RENAVE) and excess all cause deaths from the Monitoring Mortality System (MoMo), up to 15 July 2020. SARS-CoV-2 infections in Spain were derived from the estimated seroprevalence by a chemiluminescent microparticle immunoassay for IgG antibodies in 61 098 participants in the ENE-COVID nationwide seroepidemiological survey between 27 April and 22 June 2020. RESULTS: The overall infection fatality risk was 0.8% (19 228 of 2.3 million infected individuals, 95% confidence interval 0.8% to 0.9%) for confirmed covid-19 deaths and 1.1% (24 778 of 2.3 million infected individuals, 1.0% to 1.2%) for excess deaths. The infection fatality risk was 1.1% (95% confidence interval 1.0% to 1.2%) to 1.4% (1.3% to 1.5%) in men and 0.6% (0.5% to 0.6%) to 0.8% (0.7% to 0.8%) in women. The infection fatality risk increased sharply after age 50, ranging from 11.6% (8.1% to 16.5%) to 16.4% (11.4% to 23.2%) in men aged 80 or more and from 4.6% (3.4% to 6.3%) to 6.5% (4.7% to 8.8%) in women aged 80 or more. CONCLUSION: The increase in SARS-CoV-2 infection fatality risk after age 50 appeared to be more noticeable in men than in women. Based on the results of this study, fatality from covid-19 was greater than that reported for other common respiratory diseases, such as seasonal influenza.

Excess all-cause mortality during the COVID-19 pandemic in Europe - preliminary pooled estimates from the EuroMOMO network, March to April 2020.

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds.

Transmissibility of influenza during the 21st-century epidemics, Spain, influenza seasons 2001/02 to 2017/18.

BackgroundUnderstanding influenza seasonality is necessary for determining policies for influenza control.AimWe characterised transmissibility during seasonal influenza epidemics, including one influenza pandemic, in Spain during the 21th century by using the moving epidemic method (MEM) to calculate intensity levels and estimate differences across seasons and age groups.MethodsWe applied the MEM to Spanish Influenza Sentinel Surveillance System data from influenza seasons 2001/02 to 2017/18. A modified version of Goldstein's proxy was used as an epidemiological-virological parameter. We calculated the average starting week and peak, the length of the epidemic period and the length from the starting week to the peak of the epidemic, by age group and according to seasonal virus circulation.ResultsIndividuals under 15 years of age presented higher transmissibility, especially in the 2009 influenza A(H1N1) pandemic. Seasons with dominance/co-dominance of influenza A(H3N2) virus presented high intensities in older adults. The 2004/05 influenza season showed the highest influenza-intensity level for all age groups. In 12 seasons, the epidemic started between week 50 and week 3. Epidemics started earlier in individuals under 15 years of age (-1.8 weeks; 95% confidence interval (CI):-2.8 to -0.7) than in those over 64 years when influenza B virus circulated as dominant/co-dominant. The average time from start to peak was 4.3 weeks (95% CI: 3.6-5.0) and the average epidemic length was 8.7 weeks (95% CI: 7.9-9.6).ConclusionsThese findings provide evidence for intensity differences across seasons and age groups, and can be used guide public health actions to diminish influenza-related morbidity and mortality.

Evaluating the impact of the weather conditions on the influenza propagation.

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.

Illness Severity in Hospitalized Influenza Patients by Virus Type and Subtype, Spain, 2010-2017.

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<0.05). Hospitalized patients with influenza A(H1N1)pdm09 also had a higher risk for intensive care unit admission, death, or both than patients with influenza A(H3N2) or B, independent of other factors. Determining the patterns of influenza-associated severity and how they might differ by virus type and subtype can help guide planning and implementation of adequate control and preventive measures during influenza epidemics.

Determinants of Fatal Outcome in Patients Admitted to Intensive Care Units With Influenza, European Union 2009-2017.

BACKGROUND: Morbidity, severity, and mortality associated with annual influenza epidemics are of public health concern. We analyzed surveillance data on hospitalized laboratory-confirmed influenza cases admitted to intensive care units to identify common determinants for fatal outcome and inform and target public health prevention strategies, including risk communication. METHODS: We performed a descriptive analysis and used Poisson regression models with robust variance to estimate the association of age, sex, virus (sub)type, and underlying medical condition with fatal outcome using European Union data from 2009 to 2017. RESULTS: Of 13 368 cases included in the basic dataset, 2806 (21%) were fatal. Age ≥40 years and infection with influenza A virus were associated with fatal outcome. Of 5886 cases with known underlying medical conditions and virus A subtype included in a more detailed analysis, 1349 (23%) were fatal. Influenza virus A(H1N1)pdm09 or A(H3N2) infection, age ≥60 years, cancer, human immunodeficiency virus infection and/or other immune deficiency, and heart, kidney, and liver disease were associated with fatal outcome; the risk of death was lower for patients with chronic lung disease and for pregnant women. CONCLUSIONS: This study re-emphasises the importance of preventing influenza in the elderly and tailoring strategies to risk groups with underlying medical conditions.

Exploring the risk of severe outcomes and the role of seasonal influenza vaccination in pregnant women hospitalized with confirmed influenza, Spain, 2010/11-2015/16.

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.