Excess mortality in Europe coincides with peaks of COVID-19, influenza and respiratory syncytial virus (RSV), November 2023 to February 2024.

Since the end of November 2023, the European Mortality Monitoring Network (EuroMOMO) has observed excess mortality in Europe. During weeks 48 2023-6 2024, preliminary results show a substantially increased rate of 95.3 (95% CI:  91.7-98.9) excess all-cause deaths per 100,000 person-years for all ages. This excess mortality is seen in adults aged 45 years and older, and coincides with widespread presence of COVID-19, influenza and respiratory syncytial virus (RSV) observed in many European countries during the 2023/24 winter season.

Role of Age in the Spread of Influenza, 2011-2019: Data From the US Influenza Vaccine Effectiveness Network.

Intraseason timing of influenza infection among persons of different ages could reflect relative contributions to propagation of seasonal epidemics and has not been examined among ambulatory patients. Using data from the US Influenza Vaccine Effectiveness Network, we calculated risk ratios derived from comparing weekly numbers of influenza cases prepeak with those postpeak during the 2010-2011 through 2018-2019 influenza seasons. We sought to determine age-specific differences during the ascent versus descent of an influenza season by influenza virus type and subtype. We estimated 95% credible intervals around the risk ratios using Bayesian joint posterior sampling of weekly cases. Our population consisted of ambulatory patients with laboratory-confirmed influenza who enrolled in an influenza vaccine effectiveness study at 5 US sites during 9 influenza seasons after the 2009 influenza A virus subtype H1N1 (H1N1) pandemic. We observed that young children aged <5 years tended to more often be infected with H1N1 during the prepeak period, while adults aged ≥65 years tended to more often be infected with H1N1 during the postpeak period. However, for influenza A virus subtype H3N2, children aged <5 years were more often infected during the postpeak period. These results may reflect a contribution of different age groups to seasonal spread, which may differ by influenza virus type and subtype.

Household transmission of influenza A and B within a prospective cohort during the 2013-2014 and 2014-2015 seasons.

People living within the same household as someone ill with influenza are at increased risk of infection. Here, we use Markov chain Monte Carlo methods to partition the hazard of influenza illness within a cohort into the hazard from the community and the hazard from the household. During the 2013-2014 influenza season, 49 (4.7%) of the 1044 people enrolled in a community surveillance cohort had an acute respiratory illness (ARI) attributable to influenza. During the 2014-2015 influenza season, 50 (4.7%) of the 1063 people in the cohort had an ARI attributable to influenza. The secondary attack rate from a household member was 2.3% for influenza A (H1) during 2013-2014, 5.3% for influenza B during 2013-2014, and 7.6% for influenza A (H3) during 2014-2015. Living in a household with a person ill with influenza increased the risk of an ARI attributable to influenza up to 350%, depending on the season and the influenza virus circulating within the household.

Longitudinal Testing for Respiratory and Gastrointestinal Shedding of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Day Care Centers in Hesse, Germany.

BACKGROUND: With the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ongoing in Europe in June 2020, day care centers were reopened in the state of Hesse, Germany, after the lockdown. The role young children play in the dynamics of the transmission was unknown. METHODS: We conducted a longitudinal study over 12 weeks and 2 days (18 June 2020-10 September 2020) to screen attendees and staff from day care centers in the state of Hesse, Germany, for both respiratory and gastrointestinal shedding of SARS-CoV-2. A total of 859 children (age range, 3 months-8 years) and 376 staff members from 50 day care centers, which were chosen representatively from throughout the state, participated in the study. Parents were asked to collect both a buccal mucosa and an anal swab from their children once a week. Staff were asked to self-administer the swabs. Reverse transcriptas polymerase chain reaction for SARS-CoV-2 was performed in a multiple-swab pooling protocol. RESULTS: A total of 7366 buccal mucosa swabs and 5907 anal swabs were analyzed. No respiratory or gastrointestinal shedding of SARS-CoV-2 was detected in any of the children. Shedding of SARS-CoV-2 was detected in 2 staff members from distinct day care centers. One was asymptomatic at the time of testing, and one was symptomatic and did not attend the facility on that day. CONCLUSION: Detection of either respiratory or gastrointestinal shedding of SARS-CoV-2 RNA in children and staff members attending day care centers was rare in the context of limited community activity and with infection prevention measures in the facilities in place.

Effects of Prior Season Vaccination on Current Season Vaccine Effectiveness in the United States Flu Vaccine Effectiveness Network, 2012-2013 Through 2017-2018.

BACKGROUND: We compared effects of prior vaccination and added or lost protection from current season vaccination among those previously vaccinated. METHODS: Our analysis included data from the US Flu Vaccine Effectiveness Network among participants ≥9 years old with acute respiratory illness from 2012-2013 through 2017-2018. Vaccine protection was estimated using multivariate logistic regression with an interaction term for effect of prior season vaccination on current season vaccine effectiveness. Models were adjusted for age, calendar time, high-risk status, site, and season for combined estimates. We estimated protection by combinations of current and prior vaccination compared to unvaccinated in both seasons or current vaccination among prior vaccinated. RESULTS: A total of 31 819 participants were included. Vaccine protection against any influenza averaged 42% (95% confidence interval [CI], 38%-47%) among those vaccinated only the current season, 37% (95% CI, 33-40) among those vaccinated both seasons, and 26% (95% CI, 18%-32%) among those vaccinated only the prior season, compared with participants vaccinated neither season. Current season vaccination reduced the odds of any influenza among patients unvaccinated the prior season by 42% (95% CI, 37%-46%), including 57%, 27%, and 55% against A(H1N1), A(H3N2), and influenza B, respectively. Among participants vaccinated the prior season, current season vaccination further reduced the odds of any influenza by 15% (95% CI, 7%-23%), including 29% against A(H1N1) and 26% against B viruses, but not against A(H3N2). CONCLUSIONS: Our findings support Advisory Committee on Immunization Practices recommendations for annual influenza vaccination. Benefits of current season vaccination varied among participants with and without prior season vaccination, by virus type/subtype and season.

Waning of Measured Influenza Vaccine Effectiveness Over Time: The Potential Contribution of Leaky Vaccine Effect.

BACKGROUND: Several observational studies have shown decreases in measured influenza vaccine effectiveness (mVE) during influenza seasons. One study found decreases of 6-11%/month during the 2011-2012 to 2014-2015 seasons. These findings could indicate waning immunity but could also occur if vaccine effectiveness is stable and vaccine provides partial protection in all vaccinees ("leaky") rather than complete protection in a subset of vaccinees. Since it is unknown whether influenza vaccine is leaky, we simulated the 2011-2012 to 2014-2015 influenza seasons to estimate the potential contribution of leaky vaccine effect to the observed decline in mVE. METHODS: We used available data to estimate daily numbers of vaccinations and infections with A/H1N1, A/H3N2, and B viruses. We assumed that vaccine effect was leaky, calculated mVE as 1 minus the Mantel-Haenszel relative risk of vaccine on incident cases, and determined the mean mVE change per 30 days since vaccination. Because change in mVE was highly dependent on infection rates, we performed simulations using low (15%) and high (31%) total (including symptomatic and asymptomatic) seasonal infection rates. RESULTS: For the low infection rate, decreases (absolute) in mVE per 30 days after vaccination were 2% for A/H1N1 and 1% for A/H3N2and B viruses. For the high infection rate, decreases were 5% for A/H1N1, 4% for A/H3, and 3% for B viruses. CONCLUSIONS: The leaky vaccine bias could account for some, but probably not all, of the observed intraseasonal decreases in mVE. These results underscore the need for strategies to deal with intraseasonal vaccine effectiveness decline.

Vaccination history as a confounder of studies of influenza vaccine effectiveness.

BACKGROUND: Vaccination history may confound estimates of influenza vaccine effectiveness (VE) when two conditions are present: (1) Influenza vaccination is associated with vaccination history and (2) vaccination modifies the risk of natural infection in the following seasons, either due to persisting vaccination immunity or due to lower previous risk of natural infection. METHODS: Analytic arguments are used to define conditions for confounding of VE estimates by vaccination history. Simulation studies, both with accurate and inaccurate assessment of current and previous vaccination status, are used to explore the potential magnitude of these biases when using different statistical models to address confounding by vaccination history. RESULTS: We found a potential for substantial bias of VE estimates by vaccination history if infection- and/or vaccination-derived immunity persisted from one season to the next and if vaccination uptake in individuals was seasonally correlated. Full adjustment by vaccination history, which is usually not feasible, resulted in unbiased VE estimates. Partial adjustment, i.e. only by prior season's vaccination status, significantly reduced confounding bias. Misclassification of vaccination status, which can also lead to substantial bias, interferes with the adjustment of VE estimates for vaccination history. CONCLUSIONS: Confounding by vaccination history may bias VE estimates, but even partial adjustment by only the prior season's vaccination status substantially reduces confounding bias. Misclassification of vaccination status may compromise VE estimates and efforts to adjust for vaccination history.

A review of the cost-effectiveness of adult influenza vaccination and other preventive services.

The Centers for Disease Control and Prevention recommend annual influenza vaccination of persons ≥6 months old. However, in 2016-17, only 43.3% of U.S. adults reported receiving an influenza vaccination. Limited awareness about the cost-effectiveness (CE) or the economic value of influenza vaccination may contribute to low vaccination coverage. In 2017, we conducted a literature review to survey estimates of the CE of influenza vaccination of adults compared to no vaccination. We also summarized CE estimates of other common preventive interventions that are recommended for adults by the U.S. Preventive Services Task Force. Results are presented as costs in US$2015 per quality-adjusted life-year (QALY) saved. Among adults aged 18-64, the CE of influenza vaccination ranged from $8000 to $39,000 per QALY. Assessments for adults aged ≥65 yielded lower CE ratios, ranging from being cost-saving to $15,300 per QALY. Influenza vaccination was cost-saving to $85,000 per QALY for pregnant women in moderate or severe influenza seasons and $260,000 per QALY in low-incidence seasons. For other preventive interventions, CE estimates ranged from cost-saving to $170,000 per QALY saved for breast cancer screening among women aged 50-74, from cost-saving to $16,000 per QALY for colorectal cancer screening, and from $27,000 to $600,000 per QALY for hypertension screening and treatment. Influenza vaccination in adults appears to have a similar CE profile as other commonly utilized preventive services for adults. Efforts to improve adult vaccination should be considered by adult-patient providers, healthcare systems and payers given the health and economic benefits of influenza vaccination.

An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States.

INTRODUCTION: To evaluate the public health benefit of yearly influenza vaccinations, CDC estimates the number of influenza cases and hospitalizations averted by vaccine. Available input data on cases and vaccinations is aggregated by month and the estimation model is intentionally simple, raising concerns about the accuracy of estimates. METHODS: We created a synthetic dataset with daily counts of influenza cases and vaccinations, calculated "true" averted cases using a reference model applied to the daily data, aggregated the data by month to simulate data that would actually be available, and evaluated the month-level data with seven test methods (including the current method). Methods with averted case estimates closest to the reference model were considered most accurate. To examine their performance under varying conditions, we re-evaluated the test methods when synthetic data parameters (timing of vaccination relative to cases, vaccination coverage, infection rate, and vaccine effectiveness) were varied over wide ranges. Finally, we analyzed real (i.e., collected by surveillance) data from 2010 to 2017 comparing the current method used by CDC with the best-performing test methods. RESULTS: In the synthetic dataset (population 1 million persons, vaccination uptake 55%, seasonal infection risk without vaccination 12%, vaccine effectiveness 48%) the reference model estimated 28,768 averted cases. The current method underestimated averted cases by 9%. The two best test methods estimated averted cases with <1% error. These two methods also worked well when synthetic data parameters were varied over wide ranges (≤6.2% error). With the real data, these two methods estimated numbers of averted cases that are a median 8% higher than the currently-used method. CONCLUSIONS: We identified two methods for estimating numbers of influenza cases averted by vaccine that are more accurate than the currently-used algorithm. These methods will help us to better assess the benefits of influenza vaccination.

Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness.

BACKGROUND: Estimates of influenza disease burden are broadly useful for public health, helping national and local authorities monitor epidemiologic trends, plan and allocate resources, and promote influenza vaccination. Historically, estimates of the burden of seasonal influenza in the United States, focused mainly on influenza-related mortality and hospitalization, were generated every few years. Since the 2010-2011 influenza season, annual US influenza burden estimates have been generated and expanded to include estimates of influenza-related outpatient medical visits and symptomatic illness in the community. METHODS: We used routinely collected surveillance data, outbreak field investigations, and proportions of people seeking health care from survey results to estimate the number of illnesses, medical visits, hospitalizations, and deaths due to influenza during six influenza seasons (2010-2011 through 2015-2016). RESULTS: We estimate that the number of influenza-related illnesses that have occurred during influenza season has ranged from 9.2 million to 35.6 million, including 140 000 to 710 000 influenza-related hospitalizations. DISCUSSION: These annual efforts have strengthened public health communications products and supported timely assessment of the impact of vaccination through estimates of illness and hospitalizations averted. Additionally, annual estimates of influenza burden have highlighted areas where disease surveillance needs improvement to better support public health decision making for seasonal influenza epidemics as well as future pandemics.

Influenza Vaccine Effectiveness Against Pediatric Deaths: 2010-2014.

BACKGROUND AND OBJECTIVES: Surveillance for laboratory-confirmed influenza-associated pediatric deaths since 2004 has shown that most deaths occur in unvaccinated children. We assessed whether influenza vaccination reduced the risk of influenza-associated death in children and adolescents. METHODS: We conducted a case-cohort analysis comparing vaccination uptake among laboratory-confirmed influenza-associated pediatric deaths with estimated vaccination coverage among pediatric cohorts in the United States. Case vaccination and high-risk status were determined by case investigation. Influenza vaccination coverage estimates were obtained from national survey data or a national insurance claims database. We estimated odds ratios from logistic regression comparing odds of vaccination among cases with odds of vaccination in comparison cohorts. We used Bayesian methods to compute 95% credible intervals (CIs) for vaccine effectiveness (VE), calculated as (1 - odds ratio) × 100. RESULTS: From July 2010 through June 2014, 358 laboratory-confirmed influenza-associated pediatric deaths were reported among children aged 6 months through 17 years. Vaccination status was determined for 291 deaths; 75 (26%) received vaccine before illness onset. Average vaccination coverage in survey cohorts was 48%. Overall VE against death was 65% (95% CI, 54% to 74%). Among 153 deaths in children with underlying high-risk medical conditions, 47 (31%) were vaccinated. VE among children with high-risk conditions was 51% (95% CI, 31% to 67%), compared with 65% (95% CI, 47% to 78%) among children without high-risk conditions. CONCLUSIONS: Influenza vaccination was associated with reduced risk of laboratory-confirmed influenza-associated pediatric death. Increasing influenza vaccination could prevent influenza-associated deaths among children and adolescents.

Estimating Direct and Indirect Protective Effect of Influenza Vaccination in the United States.

With influenza vaccination rates in the United States recently exceeding 45% of the population, it is important to understand the impact that vaccination is having on influenza transmission. In this study, we used a Bayesian modeling approach, combined with a simple dynamical model of influenza transmission, to estimate this impact. The combined framework synthesized evidence from a range of data sources relating to influenza transmission and vaccination in the United States. We found that, for seasonal epidemics, the number of infections averted ranged from 9.6 million in the 2006-2007 season (95% credible interval (CI): 8.7, 10.9) to 37.2 million (95% CI: 34.1, 39.6) in the 2012-2013 season. Expressed in relative terms, the proportion averted ranged from 20.8% (95% CI: 16.8, 24.3) of potential infections in the 2011-2012 season to 47.5% (95% CI: 43.7, 50.8) in the 2008-2009 season. The percentage averted was only 1.04% (95% CI: 0.15, 3.2) for the 2009 H1N1 pandemic, owing to the late timing of the vaccination program in relation to the pandemic in the Northern hemisphere. In the future, further vaccination coverage, as well as improved influenza vaccines (especially those offering better protection in the elderly), could have an even stronger effect on annual influenza epidemics.

Comparative Effectiveness of High-Dose Versus Standard-Dose Influenza Vaccines Among US Medicare Beneficiaries in Preventing Postinfluenza Deaths During 2012-2013 and 2013-2014.

Background: Recipients of high-dose vs standard-dose influenza vaccines have fewer influenza illnesses. We evaluated the comparative effectiveness of high-dose vaccine in preventing postinfluenza deaths during 2012-2013 and 2013-2014, when influenza viruses and vaccines were similar. Methods: We identified Medicare beneficiaries aged ≥65 years who received high-dose or standard-dose vaccines in community-located pharmacies offering both vaccines. The primary outcome was death in the 30 days following an inpatient or emergency department encounter listing an influenza International of Classification of Diseases, Ninth Revision, Clinical Modification code. Effectiveness was estimated by using multivariate Poisson regression models; effectiveness was allowed to vary by season. Results: We studied 1039645 recipients of high-dose and 1683264 recipients of standard-dose vaccines during 2012-2013, and 1508176 high-dose and 1877327 standard-dose recipients during 2013-2014. Vaccinees were well-balanced for medical conditions and indicators of frail health. Rates of postinfluenza death were 0.028 and 0.038/10000 person-weeks in high-dose and standard-dose recipients, respectively. Comparative effectiveness was 24.0% (95% confidence interval [CI], .6%-42%); there was evidence of variation by season (P = .12). In 2012-2013, high-dose was 36.4% (95% CI, 9.0%-56%) more effective in reducing mortality; in 2013-2014, it was 2.5% (95% CI, -47% to 35%). Conclusions: High-dose vaccine was significantly more effective in preventing postinfluenza deaths in 2012-2013, when A(H3N2) circulation was common, but not in 2013-2014.

The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings.

Background: The test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting. Methods: We derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies. Results: VE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates. Conclusions: The inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis.

Association Between Hospitalization With Community-Acquired Laboratory-Confirmed Influenza Pneumonia and Prior Receipt of Influenza Vaccination.

IMPORTANCE: Few studies have evaluated the relationship between influenza vaccination and pneumonia, a serious complication of influenza infection. OBJECTIVE: To assess the association between influenza vaccination status and hospitalization for community-acquired laboratory-confirmed influenza pneumonia. DESIGN, SETTING, AND PARTICIPANTS: The Etiology of Pneumonia in the Community (EPIC) study was a prospective observational multicenter study of hospitalizations for community-acquired pneumonia conducted from January 2010 through June 2012 at 4 US sites. In this case-control study, we used EPIC data from patients 6 months or older with laboratory-confirmed influenza infection and verified vaccination status during the influenza seasons and excluded patients with recent hospitalization, from chronic care residential facilities, and with severe immunosuppression. Logistic regression was used to calculate odds ratios, comparing the odds of vaccination between influenza-positive (case) and influenza-negative (control) patients with pneumonia, controlling for demographics, comorbidities, season, study site, and timing of disease onset. Vaccine effectiveness was estimated as (1 - adjusted odds ratio) × 100%. EXPOSURE: Influenza vaccination, verified through record review. MAIN OUTCOMES AND MEASURES: Influenza pneumonia, confirmed by real-time reverse-transcription polymerase chain reaction performed on nasal/oropharyngeal swabs. RESULTS: Overall, 2767 patients hospitalized for pneumonia were eligible for the study; 162 (5.9%) had laboratory-confirmed influenza. Twenty-eight of 162 cases (17%) with influenza-associated pneumonia and 766 of 2605 controls (29%) with influenza-negative pneumonia had been vaccinated. The adjusted odds ratio of prior influenza vaccination between cases and controls was 0.43 (95% CI, 0.28-0.68; estimated vaccine effectiveness, 56.7%; 95% CI, 31.9%-72.5%). CONCLUSIONS AND RELEVANCE: Among children and adults hospitalized with community-acquired pneumonia, those with laboratory-confirmed influenza-associated pneumonia, compared with those with pneumonia not associated with influenza, had lower odds of having received influenza vaccination.

Incidence of medically attended influenza infection and cases averted by vaccination, 2011/2012 and 2012/2013 influenza seasons.

BACKGROUND: We estimated the burden of outpatient influenza and cases prevented by vaccination during the 2011/2012 and 2012/2013 influenza seasons using data from the United States Influenza Vaccine Effectiveness (US Flu VE) Network. METHODS: We defined source populations of persons who could seek care for acute respiratory illness (ARI) at each of the five US Flu VE Network sites. We identified all members of the source population who were tested for influenza during US Flu VE influenza surveillance. Each influenza-positive subject received a sampling weight based on the proportion of source population members who were tested for influenza, stratified by site, age, and other factors. We used the sampling weights to estimate the cumulative incidence of medically attended influenza in the source populations. We estimated cases averted by vaccination using estimates of cumulative incidence, vaccine coverage, and vaccine effectiveness. RESULTS: Cumulative incidence of medically attended influenza ranged from 0.8% to 2.8% across sites during 2011/2012 and from 2.6% to 6.5% during the 2012/2013 season. Stratified by age, incidence ranged from 1.2% among adults 50 years of age and older in 2011/2012 to 10.9% among children 6 months to 8 years of age in 2012/2013. Cases averted by vaccination ranged from 4 to 41 per 1000 vaccinees, depending on the study site and year. CONCLUSIONS: The incidence of medically attended influenza varies greatly by year and even by geographic region within the same year. The number of cases averted by vaccination varies greatly based on overall incidence and on vaccine coverage.