Detection of Novel Influenza Viruses Through Community and Healthcare Testing: Implications for Surveillance Efforts in the United States.

BACKGROUND: Novel influenza viruses pose a potential pandemic risk, and rapid detection of infections in humans is critical to characterizing the virus and facilitating the implementation of public health response measures. METHODS: We use a probabilistic framework to estimate the likelihood that novel influenza virus cases would be detected through testing in different community and healthcare settings (urgent care, emergency department, hospital, and intensive care unit [ICU]) while at low frequencies in the United States. Parameters were informed by data on seasonal influenza virus activity and existing testing practices. RESULTS: In a baseline scenario reflecting the presence of 100 novel virus infections with similar severity to seasonal influenza viruses, the median probability of detecting at least one infection per month was highest in urgent care settings (72%) and when community testing was conducted at random among the general population (77%). However, urgent care testing was over 15 times more efficient (estimated as the number of cases detected per 100,000 tests) due to the larger number of tests required for community testing. In scenarios that assumed increased clinical severity of novel virus infection, median detection probabilities increased across all healthcare settings, particularly in hospitals and ICUs (up to 100%) where testing also became more efficient. CONCLUSIONS: Our results suggest that novel influenza virus circulation is likely to be detected through existing healthcare surveillance, with the most efficient testing setting impacted by the disease severity profile. These analyses can help inform future testing strategies to maximize the likelihood of novel influenza detection.

Responding to the Return of Influenza in the United States by Applying Centers for Disease Control and Prevention Surveillance, Analysis, and Modeling to Inform Understanding of Seasonal Influenza.

We reviewed the tools that have been developed to characterize and communicate seasonal influenza activity in the United States. Here we focus on systematic surveillance and applied analytics, including seasonal burden and disease severity estimation, short-term forecasting, and longer-term modeling efforts. For each set of activities, we describe the challenges and opportunities that have arisen because of the COVID-19 pandemic. In conclusion, we highlight how collaboration and communication have been and will continue to be key components of reliable and actionable influenza monitoring, forecasting, and modeling activities.

Standard-dose versus MF59-adjuvanted, high-dose or recombinant-hemagglutinin influenza vaccine immunogenicity in older adults: comparison of A(H3N2) antibody response by prior season's vaccine status.

BACKGROUND: Annual influenza vaccination is recommended for older adults but repeated vaccination with standard-dose influenza vaccine has been linked to reduced immunogenicity and effectiveness, especially against A(H3N2) viruses. METHODS: Community-dwelling Hong Kong adults aged 65-82 years were randomly allocated to receive 2017/18 standard-dose quadrivalent, MF59-adjuvanted trivalent, high-dose trivalent, and recombinant-HA quadrivalent vaccination. Antibody response to unchanged A(H3N2) vaccine antigen was compared among participants with and without self-reported prior year (2016/17) standard-dose vaccination. RESULTS: Mean fold rise (MFR) in antibody titers from Day 0 to Day 30 by hemagglutination inhibition and virus microneutralization assays were lower among 2017/18 standard-dose and enhanced vaccine recipients with (range, 1.7-3.0) vs. without (range, 4.3-14.3) prior 2016/17 vaccination. MFR was significantly reduced by about one half to four fifths for previously vaccinated recipients of standard-dose and all three enhanced vaccines (ß range, 0.21-0.48). Among prior-year vaccinated older adults, enhanced vaccines induced higher 1.43 to 2.39-fold geometric mean titers and 1.28 to 1.74-fold MFR vs. standard-dose vaccine by microneutralization assay. CONCLUSIONS: In the context of unchanged A(H3N2) vaccine strain, prior-year vaccination was associated with reduced antibody response among both standard-dose and enhanced influenza vaccine recipients. Enhanced vaccines improved antibody response among older adults with prior-year standard-dose vaccination.

High Influenza Incidence and Disease Severity Among Children and Adolescents Aged <18 Years - United States, 2022-23 Season.

During the 2022-23 influenza season, early increases in influenza activity, co-circulation of influenza with other respiratory viruses, and high influenza-associated hospitalization rates, particularly among children and adolescents, were observed. This report describes the 2022-23 influenza season among children and adolescents aged <18 years, including the seasonal severity assessment; estimates of U.S. influenza-associated medical visits, hospitalizations, and deaths; and characteristics of influenza-associated hospitalizations. The 2022-23 influenza season had high severity among children and adolescents compared with thresholds based on previous seasons' influenza-associated outpatient visits, hospitalization rates, and deaths. Nationally, the incidences of influenza-associated outpatient visits and hospitalization for the 2022-23 season were similar for children aged <5 years and higher for children and adolescents aged 5-17 years compared with previous seasons. Peak influenza-associated outpatient and hospitalization activity occurred in late November and early December. Among children and adolescents hospitalized with influenza during the 2022-23 season in hospitals participating in the Influenza Hospitalization Surveillance Network, a lower proportion were vaccinated (18.3%) compared with previous seasons (35.8%-41.8%). Early influenza circulation, before many children and adolescents had been vaccinated, might have contributed to the high hospitalization rates during the 2022-23 season. Among symptomatic hospitalized patients, receipt of influenza antiviral treatment (64.9%) was lower than during pre-COVID-19 pandemic seasons (80.8%-87.1%). CDC recommends that all persons aged ≥6 months without contraindications should receive the annual influenza vaccine, ideally by the end of October.

Interpretation of molecular detection of avian influenza A virus in respiratory specimens collected from live bird market workers in Dhaka, Bangladesh: infection or contamination?

OBJECTIVES: Interpreting real-time reverse transcription-polymerase chain reaction (rRT-PCR) results for human avian influenza A virus (AIV) detection in contaminated settings like live bird markets (LBMs) without serology or viral culture poses a challenge. METHODS: During February-March 2012 and November 2012-February 2013, we screened workers at nine LBMs in Dhaka, Bangladesh, to confirm molecular detections of AIV RNA in respiratory specimens with serology. We tested nasopharyngeal (NP) and throat swabs from workers with influenza-like illness (ILI) and NP, throat, and arm swabs from asymptomatic workers for influenza virus by rRT-PCR and sera for seroconversion and antibodies against HPAI A(H5N1) and A(H9N2) viruses. RESULTS: Among 1273 ILI cases, 34 (2.6%) had A(H5), 56 (4%) had A(H9), and six (0.4%) had both A(H5) and A(H9) detected by rRT-PCR. Of 192 asymptomatic workers, A(H5) was detected in eight (4%) NP and 38 (20%) arm swabs. Of 28 ILI cases with A(H5) or A(H9) detected, none had evidence of seroconversion, but one (3.5%) and 12 (43%) were seropositive for A(H5) and A(H9), respectively. CONCLUSION: Detection of AIV RNA in respiratory specimens from symptomatic and asymptomatic LBM workers without evidence of seroconversion or virus isolation suggests environmental contamination, emphasizing caution in interpreting rRT-PCR results in high viral load settings.

Point Prevalence Estimates of Activity-Limiting Long-term Symptoms Among United States Adults ≥1 Month After Reported Severe Acute Respiratory Syndrome Coronavirus 2 Infection, 1 November 2021.

BACKGROUND: Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. METHODS: We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. RESULTS: On 1 November 2021, at least 3.0-5.0 million US adults, or 1.2%-1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month's duration. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%-3.8%. CONCLUSIONS: Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

Influenza Activity and Composition of the 2022-23 Influenza Vaccine - United States, 2021-22 Season.

Before the emergence of SARS-CoV-2, the virus that causes COVID-19, influenza activity in the United States typically began to increase in the fall and peaked in February. During the 2021-22 season, influenza activity began to increase in November and remained elevated until mid-June, featuring two distinct waves, with A(H3N2) viruses predominating for the entire season. This report summarizes influenza activity during October 3, 2021-June 11, 2022, in the United States and describes the composition of the Northern Hemisphere 2022-23 influenza vaccine. Although influenza activity is decreasing and circulation during summer is typically low, remaining vigilant for influenza infections, performing testing for seasonal influenza viruses, and monitoring for novel influenza A virus infections are important. An outbreak of highly pathogenic avian influenza A(H5N1) is ongoing; health care providers and persons with exposure to sick or infected birds should remain vigilant for onset of symptoms consistent with influenza. Receiving a seasonal influenza vaccine each year remains the best way to protect against seasonal influenza and its potentially severe consequences.

Estimating COVID-19 Hospitalizations in the United States With Surveillance Data Using a Bayesian Hierarchical Model: Modeling Study.

BACKGROUND: In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important. OBJECTIVE: We aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19. METHODS: We estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data. RESULTS: We estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states. CONCLUSIONS: Our novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.

Use of At-Home COVID-19 Tests - United States, August 23, 2021-March 12, 2022.

COVID-19 testing provides information regarding exposure and transmission risks, guides preventative measures (e.g., if and when to start and end isolation and quarantine), identifies opportunities for appropriate treatments, and helps assess disease prevalence (1). At-home rapid COVID-19 antigen tests (at-home tests) are a convenient and accessible alternative to laboratory-based diagnostic nucleic acid amplification tests (NAATs) for SARS-CoV-2, the virus that causes COVID-19 (2-4). With the emergence of the SARS-CoV-2 B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants in 2021, demand for at-home tests increased† (5). At-home tests are commonly used for school- or employer-mandated testing and for confirmation of SARS-CoV-2 infection in a COVID-19-like illness or following exposure (6). Mandated COVID-19 reporting requirements omit at-home tests, and there are no standard processes for test takers or manufacturers to share results with appropriate health officials (2). Therefore, with increased COVID-19 at-home test use, laboratory-based reporting systems might increasingly underreport the actual incidence of infection. Data from a cross-sectional, nonprobability-based online survey (August 23, 2021-March 12, 2022) of U.S. adults aged ≥18 years were used to estimate self-reported at-home test use over time, and by demographic characteristics, geography, symptoms/syndromes, and reasons for testing. From the Delta-predominant period (August 23-December 11, 2021) to the Omicron-predominant period (December 19, 2021-March 12, 2022)§ (7), at-home test use among respondents with self-reported COVID-19-like illness¶ more than tripled from 5.7% to 20.1%. The two most commonly reported reasons for testing among persons who used an at-home test were COVID-19 exposure (39.4%) and COVID-19-like symptoms (28.9%). At-home test use differed by race (e.g., self-identified as White [5.9%] versus self-identified as Black [2.8%]), age (adults aged 30-39 years [6.4%] versus adults aged ≥75 years [3.6%]), household income (>$150,000 [9.5%] versus $50,000-$74,999 [4.7%]), education (postgraduate degree [8.4%] versus high school or less [3.5%]), and geography (New England division [9.6%] versus West South Central division [3.7%]). COVID-19 testing, including at-home tests, along with prevention measures, such as quarantine and isolation when warranted, wearing a well-fitted mask when recommended after a positive test or known exposure, and staying up to date with vaccination,** can help reduce the spread of COVID-19. Further, providing reliable and low-cost or free at-home test kits to underserved populations with otherwise limited access to COVID-19 testing could assist with continued prevention efforts.

Estimates of mortality associated with seasonal influenza for the European Union from the GLaMOR project.

BACKGROUND: The European Centres for Disease Prevention and Control (ECDC) estimates that seasonal influenzacauses 4-50 million symptomatic infections in the EU/EEA each year and 15,000-70,000 European citizens die of causes associated with influenza. We used modelling methods to estimate influenza-associated mortality for the European Union by age group and country. METHODS: We compiled influenza-associated respiratory mortality estimates for 31 countries around the world (11 countries in the EU) during 2002-2011 (excluding the 2009 pandemic). From these we extrapolated the influenza mortality burden for all 193 countries of the world, including the 28 countries of the EU, using a multiple imputation approach. To study the effect of vaccination programs, we obtained data from the EU-funded VENICE project regarding the percentage of persons over 65 who were vaccinated in each country; the data ranged from 2% to 82% between the 21 countries which provided estimates for the 2006/07 reference season. RESULTS: We estimated that an average of 27,600 (range 16,200-39,000) respiratory deaths were associated with seasonal influenza in the 28 EU countries per winter; 88% were among people 65 years and older, and the rates of mortality in this age group were roughly 35 times higher compared with those < 65 years. Estimates varied considerably across the EU; for example, rates in the elderly ranged from 21.6 (12.5-35.1) per 100,000 in Portugal to 36.5 (16.4-62.5) in Luxembourg, a difference of nearly 70%. We were unable to find a negative correlation between vaccination coverage rates and influenza-associated mortality estimates in the elderly. CONCLUSION: Our EU estimate of influenza-associated respiratory mortality is broadly consistent with the ECDC estimate. More research is needed to explain the observed variation in mortality across the EU, and on possible bias that could explain the unexpected lack of mortality benefits associated with European elderly influenza vaccination programs.

Application of Bayesian spatial-temporal models for estimating unrecognized COVID-19 deaths in the United States.

In the United States, COVID-19 has become a leading cause of death since 2020. However, the number of COVID-19 deaths reported from death certificates is likely to represent an underestimate of the total deaths related to SARS-CoV-2 infections. Estimating those deaths not captured through death certificates is important to understanding the full burden of COVID-19 on mortality. In this work, we explored enhancements to an existing approach by employing Bayesian hierarchical models to estimate unrecognized deaths attributed to COVID-19 using weekly state-level COVID-19 viral surveillance and mortality data in the United States from March 2020 to April 2021. We demonstrated our model using those aged ≥ 85 years who died. First, we used a spatial-temporal binomial regression model to estimate the percent of positive SARS-CoV-2 test results. A spatial-temporal negative-binomial model was then used to estimate unrecognized COVID-19 deaths by exploiting the spatial-temporal association between SARS-CoV-2 percent positive and all-cause mortality counts using an excess mortality approach. Computationally efficient Bayesian inference was accomplished via the Polya-Gamma representation of the binomial and negative-binomial models. Among those aged ≥ 85 years, we estimated 58,200 (95% CI: 51,300, 64,900) unrecognized COVID-19 deaths, which accounts for 26% (95% CI: 24%, 29%) of total COVID-19 deaths in this age group. Our modeling results suggest that COVID-19 mortality and the proportion of unrecognized deaths among deaths attributed to COVID-19 vary by time and across states.

Trends in Disease Severity and Health Care Utilization During the Early Omicron Variant Period Compared with Previous SARS-CoV-2 High Transmission Periods - United States, December 2020-January 2022.

The B.1.1.529 (Omicron) variant of SARS-CoV-2, the virus that causes COVID-19, was first clinically identified in the United States on December 1, 2021, and spread rapidly. By late December, it became the predominant strain, and by January 15, 2022, it represented 99.5% of sequenced specimens in the United States* (1). The Omicron variant has been shown to be more transmissible and less virulent than previously circulating variants (2,3). To better understand the severity of disease and health care utilization associated with the emergence of the Omicron variant in the United States, CDC examined data from three surveillance systems and a large health care database to assess multiple indicators across three high-COVID-19 transmission periods: December 1, 2020-February 28, 2021 (winter 2020-21); July 15-October 31, 2021 (SARS-CoV-2 B.1.617.2 [Delta] predominance); and December 19, 2021-January 15, 2022 (Omicron predominance). The highest daily 7-day moving average to date of cases (798,976 daily cases during January 9-15, 2022), emergency department (ED) visits (48,238), and admissions (21,586) were reported during the Omicron period, however, the highest daily 7-day moving average of deaths (1,854) was lower than during previous periods. During the Omicron period, a maximum of 20.6% of staffed inpatient beds were in use for COVID-19 patients, 3.4 and 7.2 percentage points higher than during the winter 2020-21 and Delta periods, respectively. However, intensive care unit (ICU) bed use did not increase to the same degree: 30.4% of staffed ICU beds were in use for COVID-19 patients during the Omicron period, 0.5 percentage points lower than during the winter 2020-21 period and 1.2 percentage points higher than during the Delta period. The ratio of peak ED visits to cases (event-to-case ratios) (87 per 1,000 cases), hospital admissions (27 per 1,000 cases), and deaths (nine per 1,000 cases [lagged by 3 weeks]) during the Omicron period were lower than those observed during the winter 2020-21 (92, 68, and 16 respectively) and Delta (167, 78, and 13, respectively) periods. Further, among hospitalized COVID-19 patients from 199 U.S. hospitals, the mean length of stay and percentages who were admitted to an ICU, received invasive mechanical ventilation (IMV), and died while in the hospital were lower during the Omicron period than during previous periods. COVID-19 disease severity appears to be lower during the Omicron period than during previous periods of high transmission, likely related to higher vaccination coverage,† which reduces disease severity (4), lower virulence of the Omicron variant (3,5,6), and infection-acquired immunity (3,7). Although disease severity appears lower with the Omicron variant, the high volume of ED visits and hospitalizations can strain local health care systems in the United States, and the average daily number of deaths remains substantial.§ This underscores the importance of national emergency preparedness, specifically, hospital surge capacity and the ability to adequately staff local health care systems. In addition, being up to date on vaccination and following other recommended prevention strategies are critical to preventing infections, severe illness, or death from COVID-19.

Incidence rates of influenza illness during pregnancy in Suzhou, China, 2015-2018.

BACKGROUND: Data on influenza incidence during pregnancy in China are limited. METHODS: From October 2015 to September 2018, we conducted active surveillance for acute respiratory illness (ARI) among women during pregnancy. Nurses conducted twice weekly phone and text message follow-up upon enrollment until delivery to identify new episodes of ARI. Nasal and throat swabs were collected ≤10 days from illness onset to detect influenza. RESULTS: In total, we enrolled 18 724 pregnant women median aged 28 years old, 37% in first trimester, 48% in second trimester, and 15% in third trimester, with seven self-reported influenza vaccination during pregnancy. In the 18-week epidemic period during October 2015 to September 2016, influenza incidence was 0.7/100 person-months (95% CI: 0.5-0.9). In the cumulative 29-week-long epidemic during October 2016 to September 2017, influenza incidence was 1.0/100 person-months (95% CI: 0.8-1.2). In the 11-week epidemic period during October 2017 to September 2018, influenza incidence was 2.1/100 person-months (95% CI: 1.9-2.4). Influenza incidence was similar by trimester. More than half of the total influenza illnesses had no elevated temperature and cough. Most influenza-associated ARIs were mild, and <5.1% required hospitalization. CONCLUSIONS: Influenza illness in all trimesters of pregnancy was common. These data may help inform decisions regarding the use of influenza vaccine to prevent influenza during pregnancy.

Burden of Influenza-Associated Respiratory Hospitalizations, Vietnam, 2014-2016.

Influenza burden estimates are essential to informing prevention and control policies. To complement recent influenza vaccine production capacity in Vietnam, we used acute respiratory infection (ARI) hospitalization data, severe acute respiratory infection (SARI) surveillance data, and provincial population data from 4 provinces representing Vietnam's major regions during 2014-2016 to calculate provincial and national influenza-associated ARI and SARI hospitalization rates. We determined the proportion of ARI admissions meeting the World Health Organization SARI case definition through medical record review. The mean influenza-associated hospitalization rates per 100,000 population were 218 (95% uncertainty interval [UI] 197-238) for ARI and 134 (95% UI 119-149) for SARI. Influenza-associated SARI hospitalization rates per 100,000 population were highest among children <5 years of age (1,123; 95% UI 946-1,301) and adults >65 years of age (207; 95% UI 186-227), underscoring the need for prevention and control measures, such as vaccination, in these at-risk populations.

OPERA tau neutrino charged current interactions.

The OPERA experiment was designed to discover the vτ appearance in a vµ beam, due to neutrino oscillations. The detector, located in the underground Gran Sasso Laboratory, consisted of a nuclear photographic emulsion/lead target with a mass of about 1.25 kt, complemented by electronic detectors. It was exposed from 2008 to 2012 to the CNGS beam: an almost pure vµ beam with a baseline of 730 km, collecting a total of 1.8·1020 protons on target. The OPERA Collaboration eventually assessed the discovery of vµâ†’vτ oscillations with a statistical significance of 6.1 σ by observing ten vτ CC interaction candidates. These events have been published on the Open Data Portal at CERN. This paper provides a detailed description of the vτ data sample to make it usable by the whole community.

Estimating under-recognized COVID-19 deaths, United States, march 2020-may 2021 using an excess mortality modelling approach.

BACKGROUND: In the United States, Coronavirus Disease 2019 (COVID-19) deaths are captured through the National Notifiable Disease Surveillance System and death certificates reported to the National Vital Statistics System (NVSS). However, not all COVID-19 deaths are recognized and reported because of limitations in testing, exacerbation of chronic health conditions that are listed as the cause of death, or delays in reporting. Estimating deaths may provide a more comprehensive understanding of total COVID-19-attributable deaths. METHODS: We estimated COVID-19 unrecognized attributable deaths, from March 2020-April 2021, using all-cause deaths reported to NVSS by week and six age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) for 50 states, New York City, and the District of Columbia using a linear time series regression model. Reported COVID-19 deaths were subtracted from all-cause deaths before applying the model. Weekly expected deaths, assuming no SARS-CoV-2 circulation and predicted all-cause deaths using SARS-CoV-2 weekly percent positive as a covariate were modelled by age group and including state as a random intercept. COVID-19-attributable unrecognized deaths were calculated for each state and age group by subtracting the expected all-cause deaths from the predicted deaths. FINDINGS: We estimated that 766,611 deaths attributable to COVID-19 occurred in the United States from March 8, 2020-May 29, 2021. Of these, 184,477 (24%) deaths were not documented on death certificates. Eighty-two percent of unrecognized deaths were among persons aged ≥65 years; the proportion of unrecognized deaths were 0•24-0•31 times lower among those 0-17 years relative to all other age groups. More COVID-19-attributable deaths were not captured during the early months of the pandemic (March-May 2020) and during increases in SARS-CoV-2 activity (July 2020, November 2020-February 2021). INTERPRETATION: Estimating COVID-19-attributable unrecognized deaths provides a better understanding of the COVID-19 mortality burden and may better quantify the severity of the COVID-19 pandemic. FUNDING: None.

Immunogenicity of standard, high-dose, MF59-adjuvanted, and recombinant-HA seasonal influenza vaccination in older adults.

The vaccine efficacy of standard-dose seasonal inactivated influenza vaccines (S-IIV) can be improved by the use of vaccines with higher antigen content or adjuvants. We conducted a randomized controlled trial in older adults to compare cellular and antibody responses of S-IIV versus enhanced vaccines (eIIV): MF59-adjuvanted (A-eIIV), high-dose (H-eIIV), and recombinant-hemagglutinin (HA) (R-eIIV). All vaccines induced comparable H3-HA-specific IgG and elevated antibody-dependent cellular cytotoxicity (ADCC) activity at day 30 post vaccination. H3-HA-specific ADCC responses were greatest following H-eIIV. Only A-eIIV increased H3-HA-IgG avidity, HA-stalk IgG and ADCC activity. eIIVs also increased polyfunctional CD4+ and CD8+ T cell responses, while cellular immune responses were skewed toward single-cytokine-producing T cells among S-IIV subjects. Our study provides further immunological evidence for the preferential use of eIIVs in older adults as each vaccine platform had an advantage over the standard-dose vaccine in terms of NK cell activation, HA-stalk antibodies, and T cell responses.

Global Seasonal Influenza Mortality Estimates: A Comparison of 3 Different Approaches.

Prior to updating global influenza-associated mortality estimates, the World Health Organization convened a consultation in July 2017 to understand differences in methodology and implications for results of 3 influenza mortality projects from the US Centers for Disease Control and Prevention (CDC), the Netherlands Institute for Health Service Research's Global Pandemic Mortality Project II (GLaMOR), and the Institute for Health Metrics and Evaluation (IHME). The expert panel reviewed estimates and discussed differences in data sources, analysis, and modeling assumptions. We performed a comparison analysis of the estimates. Influenza-associated respiratory death counts were comparable between CDC and GLaMOR; the IHME estimate was considerably lower. The greatest country-specific influenza-associated fold differences in mortality rate between CDC and IHME estimates and between GLaMOR and IHME estimates were among countries in Southeast Asia and the Eastern Mediterranean region. The data envelope used for the calculation was one of the major differences (CDC and GLaMOR: all respiratory deaths; IHME: lower-respiratory infection deaths). With the assumption that there is only one cause of death for each death, IHME estimates a fraction of the full influenza-associated respiratory mortality that is measured by the other 2 groups. Wide variability of parameters was observed. Continued coordination between groups could assist with better understanding of methodological differences and new approaches to estimating influenza deaths globally.

Estimated Incidence of Coronavirus Disease 2019 (COVID-19) Illness and Hospitalization-United States, February-September 2020.

BACKGROUND: In the United States, laboratory-confirmed coronavirus disease 2019 (COVID-19) is nationally notifiable. However, reported case counts are recognized to be less than the true number of cases because detection and reporting are incomplete and can vary by disease severity, geography, and over time. METHODS: To estimate the cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, symptomatic illnesses, and hospitalizations, we adapted a simple probabilistic multiplier model. Laboratory-confirmed case counts that were reported nationally were adjusted for sources of underdetection based on testing practices in inpatient and outpatient settings and assay sensitivity. RESULTS: We estimated that through the end of September, 1 of every 2.5 (95% uncertainty interval [UI]: 2.0-3.1) hospitalized infections and 1 of every 7.1 (95% UI: 5.8-9.0) nonhospitalized illnesses may have been nationally reported. Applying these multipliers to reported SARS-CoV-2 cases along with data on the prevalence of asymptomatic infection from published systematic reviews, we estimate that 2.4 million hospitalizations, 44.8 million symptomatic illnesses, and 52.9 million total infections may have occurred in the US population from 27 February-30 September 2020. CONCLUSIONS: These preliminary estimates help demonstrate the societal and healthcare burdens of the COVID-19 pandemic and can help inform resource allocation and mitigation planning.

Variability in published rates of influenza-associated hospitalizations: A systematic review, 2007-2018.

BACKGROUND: Influenza burden estimates help provide evidence to support influenza prevention and control programs at local and international levels. METHODS: Through a systematic review, we aimed to identify all published articles estimating rates of influenza-associated hospitalizations, describe methods and data sources used, and identify regions of the world where estimates are still lacking. We evaluated study heterogeneity to determine if we could pool published rates to generate global estimates of influenza-associated hospitalization. RESULTS: We identified 98 published articles estimating influenza-associated hospitalization rates from 2007-2018. Most articles (65%) identified were from high-income countries, with 34 of those (53%) presenting estimates from the United States. While we identified fewer publications (18%) from low- and lower-middle-income countries, 50% of those were published from 2015-2018, suggesting an increase in publications from lower-income countries in recent years. Eighty percent (n = 78) used a multiplier approach. Regression modelling techniques were only used with data from upper-middle or high-income countries where hospital administrative data was available. We identified variability in the methods, case definitions, and data sources used, including 91 different age groups and 11 different categories of case definitions. Due to the high observed heterogeneity across articles (I2 >99%), we were unable to pool published estimates. CONCLUSIONS: The variety of methods, data sources, and case definitions adapted locally suggests that the current literature cannot be synthesized to generate global estimates of influenza-associated hospitalization burden.