Interim Estimates of 2018-19 Seasonal Influenza Vaccine Effectiveness - United States, February 2019

Protective Impact of Influenza Vaccination on Healthcare Workers

BACKGROUND

Influenza vaccine uptake among healthcare workers is crucial for preventing influenza infections, yet its effectiveness needs further investigation.

OBJECTIVES

This prospective observational study aimed to assess the protective effect of influenza vaccination among healthcare workers in Shenzhen.

METHODS

We enrolled 100 participants, with 50 receiving the 2023-2024 quadrivalent influenza vaccine (QIV) and 50 serving as unvaccinated controls. Epidemiological data were collected when the participants presented influenza-like illness. Serum samples were collected at three time points (pre-vaccination and 28 and 180 days after vaccination). Hemagglutination inhibition (HI) assay was performed against the strains included in the 2023-2024 QIV (H1N1, H3N2, BV and BY strains) to assess antibody protection levels. Demographics comparisons revealed no significant differences between the vaccinated and control groups (p > 0.05), ensuring group comparability.

RESULTS

The incidence of influenza-like illness was significantly lower in the vaccinated (18%) compared to the control group (36%; p = 0.046; OR = 0.39; 95% CI: 0.15 to 0.98). The vaccinated group also exhibited a higher rate of consecutive two-year vaccinations (48% vs. 24% in the control group, p < 0.05). Additionally, the vaccinated healthcare workers were more inclined to recommend vaccination to their families (80% vs. 48%, p < 0.05). HI titers against H1N1 (p < 0.01), H3N2 (p < 0.01), BV (p < 0.001) and BY (p < 0.01) significantly increased in the vaccinated group at 28 days post-vaccination. Moreover, a marked and sustained increase in HI titers against the H3N2 strain (p < 0.001) was observed at 180 days post-vaccination, highlighting the vaccine's enduring impact on the immune response. The fold change in the HI titers, indicative of the magnitude of the immune response, was significantly higher for H1N1 (p < 0.01), H3N2 (p < 0.001), BV (p < 0.01) and BY (p < 0.05) among the vaccinated individuals compared to the control group, underscoring the vaccine's efficacy in eliciting a robust and sustained antibody response.

CONCLUSION

Influenza vaccination significantly reduces the incidence of influenza-like illness among healthcare workers and promotes a sustained immune response. The study supports the importance of annual vaccination for this group to enhance personal and public health.

A broad-spectrum multiepitope vaccine against seasonal influenza A and B viruses in mice

BACKGROUND

Influenza viruses pose a persistent threat to global public health, necessitating the development of innovative and broadly effective vaccines.

METHODS

This study focuses on a multiepitope vaccine (MEV) designed to provide broad-spectrum protection against different influenza viruses. The MEV, containing 19 B-cell linear epitopes, 7 CD4+ T cells, and 11 CD8+ T cells epitopes identified through enzyme-linked immunospot assay (ELISPOT) in influenza viruses infected mice, was administered through a regimen of two doses of DNA vaccine followed by one dose of a protein vaccine in C57BL/6 female mice.

FINDINGS

Upon lethal challenge with both seasonal circulating strains (H1N1, H3N2, BV, and BY) and historical strains (H1N1-PR8 and H3N2-X31), MEV demonstrated substantial protection against different influenza seasonal strains, with partial efficacy against historical strains. Notably, the increased germinal centre B cells and antibody-secreting cells, along with robust T cell immune responses, highlighted the comprehensive immune defence elicited by MEV. Elevated hemagglutinin inhibition antibody was also observed against seasonal circulating and historical strains. Additionally, mice vaccinated with MEV exhibited significantly lower counts of inflammatory cells in the lungs compared to negative control groups.

INTERPRETATION

Our results demonstrated the efficacy of a broad-spectrum MEV against influenza viruses in mice. Conducting long-term studies to evaluate the durability of MEV-induced immune responses and explore its potential application in diverse populations will offer valuable insights for the continued advancement of this promising vaccine.

FUNDING

Funding bodies are described in the Acknowledgments section.

Timing of Assessment of Humoral and Cell-Mediated Immunity after Influenza Vaccination

Assessment of the immune response to influenza vaccines should include an assessment of both humoral and cell-mediated immunity. However, there is a lack of consensus regarding the timing of immunological assessment of humoral and cell-mediated immunity after vaccination. Therefore, we investigated the timing of immunological assessments after vaccination using markers of humoral and cell-mediated immunity. In the 2018/2019 influenza season, blood was collected from 29 healthy adults before and after vaccination with a quadrivalent inactivated influenza vaccine, and we performed serial measurements of humoral immunity (hemagglutination inhibition [HAI] and neutralizing antibody [NT]) and cell-mediated immunity (interferon-gamma [IFN-γ]). The HAI and NT titers before and after vaccination were strongly correlated, but no correlation was observed between the markers of cell-mediated and humoral immunity. The geometric mean titer and geometric mean concentration of humoral and cellular immune markers increased within 2 weeks after vaccination and had already declined by 8 weeks. This study suggests that the optimal time to assess the immune response is 2 weeks after vaccination. Appropriately timed immunological assessments can help ensure that vaccination is effective.

In silico design of a broad-spectrum multiepitope vaccine against influenza virus

Influenza remains a global health concern due to its potential to cause pandemics as a result of rapidly mutating influenza virus strains. Existing vaccines often struggle to keep up with these rapidly mutating flu viruses. Therefore, the development of a broad-spectrum peptide vaccine that can stimulate an optimal antibody response has emerged as an innovative approach to addressing the influenza threat. In this study, an immunoinformatic approach was employed to rapidly predict immunodominant epitopes from different antigens, aiming to develop an effective multiepitope influenza vaccine (MEV). The immunodominant B-cell linear epitopes of seasonal influenza strains hemagglutinin (HA) and neuraminidase (NA) were predicted using an antibody-peptide microarray, involving a human cohort including vaccinees and infected patients. On the other hand, bioinformatics tools were used to predict immunodominant cytotoxic T-cell (CTL) and helper T-cell (HTL) epitopes. Subsequently, these epitopes were evaluated by various immunoinformatic tools. Epitopes with high antigenicity, high immunogenicity, non-allergenicity, non-toxicity, as well as exemplary conservation were then connected in series with appropriate linkers and adjuvants to construct a broad-spectrum MEV. Moreover, the structural analysis revealed that the MEV candidates exhibited good stability, and the docking results demonstrated their strong affinity to Toll-like receptors 4 (TLR4). In addition, molecular dynamics simulation confirmed the stable interaction between TLR4 and MEVs. Three injections with MEVs showed a high level of B-cell and T-cell immune responses according to the immunological simulations in silico. Furthermore, in-silico cloning was performed, and the results indicated that the MEVs could be produced in considerable quantities in Escherichia coli (E. coli). Based on these findings, it is reasonable to create a broad-spectrum MEV against different subtypes of influenza A and B viruses in silico.

Catch the tweet to fight the flu: Using Twitter to promote flu shots on a college campus

Objective: Over the 2018-2019 flu season we conducted a randomized controlled trial examining the efficacy of a Twitter campaign on vaccination rates. Concurrently we investigated potential interactions between digital social network structure and vaccination status. Participants: Undergratuates at a large midwestern public university were randomly assigned to an intervention (n = 353) or control (n = 349) group. Methods: Vaccination data were collected via monthly surveys. Participant Twitter data were collected through the public-facing Twitter API. Intervention impact was assessed with logistic regression. Standard network science tools examined vaccination coverage over online social networks. Results: The campaign had no effect on vaccination outcome. Receiving a flu shot the prior year had a positive impact on participant vaccination. Evidence of an interaction between digital social network structure and vaccination status was detected. Conclusions: Social media campaigns may not be sufficient for increasing vaccination rates. There may be potential for social media campaigns that leverage network structure.

A mosaic influenza virus-like particles vaccine provides broad humoral and cellular immune responses against influenza A viruses

The development of a universal influenza vaccine to elicit broad immune responses is essential in reducing disease burden and pandemic impact. In this study, the mosaic vaccine design strategy and genetic algorithms were utilized to optimize the seasonal influenza A virus (H1N1, H3N2) hemagglutinin (HA) and neuraminidase (NA) antigens, which also contain most potential T-cell epitopes. These mosaic immunogens were then expressed as virus-like particles (VLPs) using the baculovirus expression system. The immunogenicity and protection effectiveness of the mosaic VLPs were compared to the commercial quadrivalent inactivated influenza vaccine (QIV) in the mice model. Strong cross-reactive antibody responses were observed in mice following two doses of vaccination with the mosaic VLPs, with HI titers higher than 40 in 15 of 16 tested strains as opposed to limited cross HI antibody levels with QIV vaccination. After a single vaccination, mice also show a stronger level of cross-reactive antibody responses than the QIV. The QIV vaccinations only elicited NI antibodies to a small number of vaccine strains, and not even strong NI antibodies to its corresponding vaccine components. In contrast, the mosaic VLPs caused robust NI antibodies to all tested seasonal influenza virus vaccine strains. Here, we demonstrated the mosaic vaccines induces stronger cross-reactive antibodies and robust more T-cell responses compared to the QIV. The mosaic VLPs also provided protection against challenges with ancestral influenza A viruses of both H1 and H3 subtypes. These findings indicated that the mosaic VLPs were a promising strategy for developing a broad influenza vaccine in future.

Designed nanoparticles elicit cross-reactive antibody responses to conserved influenza virus hemagglutinin stem epitopes

Despite the availability of seasonal vaccines and antiviral medications, influenza virus continues to be a major health concern and pandemic threat due to the continually changing antigenic regions of the major surface glycoprotein, hemagglutinin (HA). One emerging strategy for the development of more efficacious seasonal and universal influenza vaccines is structure-guided design of nanoparticles that display conserved regions of HA, such as the stem. Using the H1 HA subtype to establish proof of concept, we found that tandem copies of an alpha-helical fragment from the conserved stem region (helix-A) can be displayed on the protruding spikes structures of a capsid scaffold. The stem region of HA on these designed chimeric nanoparticles is immunogenic and the nanoparticles are biochemically robust in that heat exposure did not destroy the particles and immunogenicity was retained. Furthermore, mice vaccinated with H1-nanoparticles were protected from lethal challenge with H1N1 influenza virus. By using a nanoparticle library approach with this helix-A nanoparticle design, we show that this vaccine nanoparticle construct design could be applicable to different influenza HA subtypes. Importantly, antibodies elicited by H1, H5, and H7 nanoparticles demonstrated homosubtypic and heterosubtypic cross-reactivity binding to different HA subtypes. Also, helix-A nanoparticle immunizations were used to isolate mouse monoclonal antibodies that demonstrated heterosubtypic cross-reactivity and provided protection to mice from viral challenge via passive-transfer. This tandem helix-A nanoparticle construct represents a novel design to display several hundred copies of non-trimeric conserved HA stem epitopes on vaccine nanoparticles. This design concept provides a new approach to universal influenza vaccine development strategies and opens opportunities for the development of nanoparticles with broad coverage over many antigenically diverse influenza HA subtypes.

[Mathematical model for assessing the level of cross-immunity between strains of influenza virus subtype H3N2]

INTRODUCTION

The WHO regularly updates influenza vaccine recommendations to maximize their match with circulating strains. Nevertheless, the effectiveness of the influenza A vaccine, specifically its H3N2 component, has been low for several seasons. The aim of the study is to develop a mathematical model of cross-immunity based on the array of published WHO hemagglutination inhibition assay (HAI) data.

MATERIALS AND METHODS

In this study, a mathematical model was proposed, based on finding, using regression analysis, the dependence of HAI titers on substitutions in antigenic sites of sequences. The computer program we developed can process data (GISAID, NCBI, etc.) and create real-time databases according to the set tasks.

RESULTS

Based on our research, an additional antigenic site F was identified. The difference in 1.6 times the adjusted R2, on subsets of viruses grown in cell culture and grown in chicken embryos, demonstrates the validity of our decision to divide the original data array by passage histories. We have introduced the concept of a degree of homology between two arbitrary strains, which takes the value of a function depending on the Hamming distance, and it has been shown that the regression results significantly depend on the choice of function. The provided analysis showed that the most significant antigenic sites are A, B, and E. The obtained results on predicted HAI titers showed a good enough result, comparable to similar work by our colleagues.

CONCLUSION

The proposed method could serve as a useful tool for future forecasts, with further study to confirm its sustainability.

Design, Synthesis, Biological Evaluation, and Molecular Dynamics Simulation of Influenza Polymerase PB2 Inhibitors

The PB2 subunit of the influenza RNA-dependent RNA polymerase (RdRp) has been identified as a promising target for the treatment of influenza. To expand the chemical space of the known influenza polymerase PB2 inhibitor-pimodivir (formerly VX-787) and improve its pharmacokinetic profile, two pimodivir analogs containing 2,3-dihydro-imidazopyridine fragment (comp. I and comp. II) were designed, synthesized, and evaluated for anti-influenza virus activity. In the cytopathic effect (CPE) inhibition assay, comp. I and comp. II showed IC₅₀ values of 0.07 and 0.09 μM for A/Puerto Rico/8/34 (H1N1) and 0.04 and 0.07 μM for A/Hong Kong/8/68 (H3N2), respectively. Protein-binding affinity assay results showed a concentration-dependent association and dissociation pattern, with K_D values of 1.398 and 1.670 μM, respectively. In vitro metabolic stability assays showed that comp. I and comp. II exhibited good stability to liver microsomes and considerably less sensitivity to aldehyde oxidase compared to pimodivir. The binding modes of comp. I and comp. II were similar to those of VX-787; however, comp. I and comp. II had lower structural adaptability to PB2 than VX-787. Our results provide helpful information regarding the structure-activity relationship for the design of novel PB2 inhibitors and a reference for the development of drugs containing 2,3-dihydro-imidazopyridine fragments.

An anti-influenza combined therapy assessed by single cell RNA-sequencing

Influenza makes millions of people ill every year, placing a large burden on the healthcare system and the economy. To develop a treatment against influenza, we combined virucidal sialylated cyclodextrins with interferon lambda and demonstrated, in human airway epithelia, that the two compounds inhibit the replication of a clinical H1N1 strain more efficiently when administered together rather than alone. We investigated the mechanism of action of the combined treatment by single cell RNA-sequencing analysis and found that both the single and combined treatments impair viral replication to different extents across distinct epithelial cell types. We showed that each cell type comprises multiple sub-types, whose proportions are altered by H1N1 infection, and assessed the ability of the treatments to restore them. To the best of our knowledge this is the first study investigating the effectiveness of an antiviral therapy against influenza virus by single cell transcriptomic studies.

When combined with interferon lambda, virucidal sialylated cyclodextrins inhibit the replication of a clinical H1N1 influenza strain in ex vivo human airway epithelia more efficiently than when delivered alone.

Genome characterization and mutation analysis of human influenza A virus in Thailand

The influenza A viruses have high mutation rates and cause a serious health problem worldwide. Therefore, this study focused on genome characterization of the viruses isolated from Thai patients based on the next-generation sequencing technology. The nasal swabs were collected from patients with influenza-like illness in Thailand during 2017-2018. Then, the influenza A viruses were detected by reverse transcription-quantitative polymerase chain reaction and isolated by MDCK cells. The viral genomes were amplified and sequenced by Illumina MiSeq platform. Whole genome sequences were used for characterization, phylogenetic construction, mutation analysis and nucleotide diversity of the viruses. The result revealed that 90 samples were positive for the viruses including 44 of A/H1N1 and 46 of A/H3N2. Among these, 43 samples were successfully isolated and then the viral genomes of 25 samples were completely amplified. Finally, 17 whole genomes of the viruses (A/H1N1, n=12 and A/H3N2, n=5) were successfully sequenced with an average of 232,578 mapped reads and 1,720 genome coverage per sample. Phylogenetic analysis demonstrated that the A/H1N1 viruses were distinguishable from the recommended vaccine strains. However, the A/H3N2 viruses from this study were closely related to the recommended vaccine strains. The nonsynonymous mutations were found in all genes of both viruses, especially in HA and NA genes. The nucleotide diversity analysis revealed negative selection in the PB1, PA, hemagglutinin (HA) and neuraminidase (NA) genes of the A/H1N1 viruses. High-throughput data in this study allow for genetic characterization of circulating influenza viruses which would be crucial for preparation against pandemic and epidemic outbreaks in the future.

Human placental hematopoietic stem cell derived natural killer cells (CYNK-001) mediate protection against influenza a viral infection

Influenza A virus (IAV) infections are associated with a high healthcare burden around the world and there is an urgent need to develop more effective therapies. Natural killer (NK) cells have been shown to play a pivotal role in reducing IAV-induced pulmonary infections in preclinical models; however, little is known about the therapeutic potential of adoptively transferred NK cells for IAV infections. Here, we investigated the effects of CYNK-001, human placental hematopoietic stem cell derived NK cells that exhibited strong cytolytic activity against a range of malignant cells and expressed high levels of activating receptors, against IAV infections. In a severe IAV-induced acute lung injury model, mice treated with CYNK-001 showed a milder body weight loss and clinical symptoms, which led to a delayed onset of mortality, thus demonstrating their antiviral protection in vivo. Analysis of bronchoalveolar lavage fluid (BALF) revealed that CYNK-001 reduced proinflammatory cytokines and chemokines highlighting CYNK-001’s anti-inflammatory actions in viral induced-lung injury. Furthermore, CYNK-001-treated mice had altered immune responses to IAV with reduced number of neutrophils in BALF yet increased number of CD8+ T cells in the BALF and lung compared to vehicle-treated mice. Our results demonstrate that CYNK-001 displays protective functions against IAV via its anti-inflammatory and immunomodulating activities, which leads to alleviation of disease burden and progression in a severe IAV-infected mice model. The potential of adoptive NK therapy for IAV infections warrants clinical investigation.

Influenza vaccination influencing level of specific humoral immunity in healthy individuals

To assess an effect of vaccination on the level of humoral anti-influenza herd immunity, 2955 sera were collected and analyzed by HIT in the 2019–2020 and 2020–2021 epidemiological seasons. All sera were obtained from healthy adult donors residing in various cities of the Russian Federation. Among them, 1057 volunteers were vaccinated with seasonal influenza trivalent inactivated vaccine. Characteristics of humoral anti-influenza immunity (average geometric antibody titers and the proportion of individuals seropositive for the vaccine viruses) obtained in autumn 2019 and 2020 (1–2 months after vaccination) in vaccinated individuals vs. unvaccinated subjects were found to be markedly higher evidencing about a positive vaccination-related contribution to developing herd immunity against influenza in the preepidemic periods. After the 2019–2020 influenza epidemic, in spring 2020 (6–7 months after vaccination), the levels of antibodies to all vaccine components decreased by 2.6–3.5-fold in vaccinated donors compared to the pre-epidemic period in 2019 autumn. Antibody titers became substantially lower than the protective level (titer by HIT 1/40). At the same time, no significant differences between the groups of vaccinated vs. unvaccinated individuals were observed afterwards. This indicates instability of post-vaccination anti-influenza humoral immunity. As a result, it may decrease an influenza-resistant population cohort of working age on the eve of new epidemic season. The immunogenicity of the inactivated trivalent seasonal influenza vaccine was estimated by HIT while analyzing paired sera obtained from 295 and 112 healthy individuals of various ages vaccinated in autumn 2019 and 2020, respectively. The response to the vaccine was found to be age-related. Children aged 3–14 years vs. older subjects showed a more efficient response. Insufficient immunogenicity of influenza B virus vaccine components was shown. In all age groups, average geometric titers for influenza B virus antibodies were lower (2–8-fold) than for current A(H1N1)pdm09-like strains and influenza A(H3N2) viruses 1–1.5 months post-vaccination. Analyzing vaccine immunogenicity showed a significant inverse relationship between the level of preexisting strain-specific serum antibodies before vaccination and formation of antibodies to the corresponding vaccine virus 1–1.5 months after vaccination. Seroconversion to each vaccine component was remarkably more frequent in individuals with a low preexisting level of antibodies specific to the corresponding virus.

Effectiveness of the 2019-2020 Influenza Vaccine and the Effect of Prior Influenza Infection and Vaccination in Children during the First Influenza Season Overlapping with the COVID-19 Epidemic

BACKGROUND

Behavioral changes among Japanese, along with the coronavirus disease 2019 (COVID-19) epidemic, may affect the seasonal influenza epidemic in Japan and change influenza vaccine effectiveness (VE).

METHODS

This single-center, test-negative case-control (TNCC) study estimated influenza VE in children for the first influenza season (2019/20) to overlap the COVID-19 epidemic in. Effects of prior influenza infection and vaccination in children were assessed for the 2019-2020 season.

RESULTS

Among 386 children, adjusted VE was significant for influenza A/H1N1 (45.5%; 95% confidence interval [CI]: 2.0-69.7) and influenza B (66.7%; 95% CI: 35.9-82.7). Among patients aged 0-6 years, adjusted VE was significant for influenza A (total: A/H1N1+A/H3N2) (65.0%; 95% CI: 22.2-84.3), influenza A/H1N1 (64.8%; 95% CI: 16.9-85.1) and influenza B (87.4%; 95% CI: 50.5-96.8). No VE was observed in patients aged 7-15 years. Administration of two vaccine doses tended to decrease incidences of influenza A (total) and influenza A/H1N1 in patients aged 0-6 years. The adjusted odds ratios (ORs) of influenza B infection in patients, who had influenza during the previous season, were significantly lower among all participants (0.29; 95% CI: 0.11-0.78) and patients aged 7-15 years (0.34; 95% CI: 0.12-0.94). The adjusted ORs of influenza infections were not significant in patients vaccinated during the previous season.

CONCLUSIONS

TNCC-based estimates of influenza VE were consistent despite the overlapping COVID-19 epidemic.

Pharmacometric analysis of seasonal influenza epidemics and the effect of vaccination using sentinel surveillance data

The identification of influenza epidemics and assessment of the efficacy of vaccination against this infection are major challenges for the implementation of effective public health strategies, such as vaccination programs. In this study, we developed a new pharmacometric model to evaluate the efficacy of vaccination based on infection surveillance data from the 2010/2011 to 2018/2019 influenza seasons in Japan. A novel susceptible‐infected‐removed plus vaccination model, based on an indirect response structure with the effect of vaccination, was applied to describe seasonal influenza epidemics using a preseasonal collection of data regarding serological H₁ antibody titer positivity and the fraction of virus strains. Using this model, we evaluated K_in (a parameter describing the transmission rate of symptomatic influenza infection) for different age groups. Furthermore, we defined a new parameter (prevention factor) showing the efficacy of vaccination against each viral strain and in different age groups. We found that the prevention factor of vaccination against influenza varied among age groups. Notably, children aged 5–14 years showed the highest K_in value during the 10 influenza seasons and the greatest preventive effect of vaccination (prevention factor = 70.8%). The propagation of influenza epidemics varies in different age groups. Children aged 5–14 years most likely play a leading role in the transmission of influenza. Prioritized vaccination in this age group may be the most effective strategy for reducing the prevalence of influenza in the community.

Influenza vaccine effectiveness within prospective cohorts of healthcare personnel in Israel and Peru 2016-2019

BACKGROUND

There are limited data on influenza vaccine effectiveness (IVE) in preventing laboratory-confirmed influenza illness among healthcare personnel (HCP).

METHODS

HCP with direct patient contact working full-time in hospitals were followed during three influenza seasons in Israel (2016-2017 to 2018-2019) and Peru (2016 to 2018). Trivalent influenza vaccines were available at all sites, except during 2018-2019 when Israel used quadrivalent vaccines; vaccination was documented by electronic medical records, vaccine registries, and/or self-report (for vaccinations outside the hospital). Twice-weekly active surveillance identified acute respiratory symptoms or febrile illness (ARFI); self-collected respiratory specimens were tested by real-time reverse transcription polymerase chain reaction (PCR) assay. IVE was 100 × 1-hazard ratio (adjusted for sex, age, occupation, and hospital).

RESULTS

Among 5,489 HCP who contributed 10,041 person-seasons, influenza vaccination coverage was 47% in Israel and 32% in Peru. Of 3,056 ARFIs in Israel and 3,538 in Peru, A or B influenza virus infections were identified in 205 (7%) in Israel and 87 (2.5%) in Peru. IVE against all viruses across seasons was 1% (95% confidence interval [CI] = -30%, 25%) in Israel and 12% (95% CI = -61%, 52%) in Peru.

CONCLUSION

Estimates of IVE were null using person-time models during six study seasons in Israel and Peru.

Relative Effectiveness of Adjuvanted Trivalent Inactivated Influenza Vaccine Versus Egg-derived Quadrivalent Inactivated Influenza Vaccines and High-dose Trivalent Influenza Vaccine in Preventing Influenza-related Medical Encounters in US Adults ≥ 65 Years During the 2017-2018 and 2018-2019 Influenza Seasons

Background

The effectiveness of standard, egg-derived quadrivalent influenza vaccines (IIV4) may be reduced in adults ≥65 years of age, largely because of immunosenescence. An MF59-adjuvanted trivalent influenza vaccine (aIIV3) and a high-dose trivalent influenza vaccine (HD-IIV3) offer older adults enhanced protection versus standard vaccines. This study compared the relative effectiveness of aIIV3 with IIV4 and HD-IIV3 in preventing influenza-related medical encounters over 2 US influenza seasons.

Methods

This retrospective cohort study included US patients ≥65 years vaccinated with aIIV3, IIV4, or HD-IIV3. The outcome of interest was the occurrence of influenza-related medical encounters. Data were derived from a large dataset comprising primary and specialty care electronic medical records linked with pharmacy and medical claims. Adjusted odds ratios (OR) were derived from an inverse probability of treatment-weighted sample adjusted for age, sex, race, ethnicity, geographic region, vaccination week, and health status. Relative vaccine effectiveness (rVE) was determined using the formula (% VE = 1 – OR_adjusted) × 100.

Results

In 2017–2018, cohorts included: aIIV3, n = 524 223; IIV4, n = 917 609; and HD-IIV3, n = 3 377 860. After adjustment, 2017–2018 rVE of aIIV3 versus IIV4 was 18.2 (95% confidence interval [CI], 15.8–20.5); aIIV3 vs. HD-IIV3 was 7.7 (95% CI, 2.3–12.8). In 2018–2019, cohorts included: aIIV3, n = 1 031 145; IIV4, n = 915 380; HD-IIV3, n = 3 809 601, with adjusted rVEs of aIIV3 versus IIV4 of 27.8 (95% CI, 25.7–29.9) and vs. HD-IIV3 of 6.9 (95% CI, 3.1–10.6).

Conclusion

In the 2017–2018 and 2018–2019 influenza seasons in the United States, aIIV3 demonstrated greater reduction in influenza-related medical encounters than IIV4 and HD-IIV3 in adults ≥65 years.

3-Indoleacetonitrile Is Highly Effective in Treating Influenza A Virus Infection In Vitro and In Vivo

Influenza A viruses are serious zoonotic pathogens that continuously cause pandemics in several animal hosts, including birds, pigs, and humans. Indole derivatives containing an indole core framework have been extensively studied and developed to prevent and/or treat viral infection. This study evaluated the anti-influenza activity of several indole derivatives, including 3-indoleacetonitrile, indole-3-carboxaldehyde, 3-carboxyindole, and gramine, in A549 and MDCK cells. Among these compounds, 3-indoleacetonitrile exerts profound antiviral activity against a broad spectrum of influenza A viruses, as tested in A549 cells. Importantly, in a mouse model, 3-indoleacetonitrile with a non-toxic concentration of 20 mg/kg effectively reduced the mortality and weight loss, diminished lung virus titers, and alleviated lung lesions of mice lethally challenged with A/duck/Hubei/WH18/2015 H5N6 and A/Puerto Rico/8/1934 H1N1 influenza A viruses. The antiviral properties enable the potential use of 3-indoleacetonitrile for the treatment of IAV infection.

Incorporating Real-time Influenza Detection Into the Test-negative Design for Estimating Influenza Vaccine Effectiveness: The Real-time Test-negative Design (rtTND)

With rapid and accurate molecular influenza testing now widely available in clinical settings, influenza vaccine effectiveness (VE) studies can prospectively select participants for enrollment based on real-time results rather than enrolling all eligible patients regardless of influenza status, as in the traditional test-negative design (TND). Thus, we explore advantages and disadvantages of modifying the TND for estimating VE by using real-time, clinically available viral testing results paired with acute respiratory infection eligibility criteria for identifying influenza cases and test-negative controls prior to enrollment. This modification, which we have called the real-time test-negative design (rtTND), has the potential to improve influenza VE studies by optimizing the case-to-test-negative control ratio, more accurately classifying influenza status, improving study efficiency, reducing study cost, and increasing study power to adequately estimate VE. Important considerations for limiting biases in the rtTND include the need for comprehensive clinical influenza testing at study sites and accurate influenza tests.

Sample size considerations for mid-season estimates from a large influenza vaccine effectiveness network in the United States

INTRODUCTION

Mid-season influenza vaccine effectiveness (VE) estimates are a useful tool to help guide annual influenza vaccine strain selection, vaccine policy, and public health messaging. We propose using a sample size-driven approach with data-driven inputs for publication of mid-season influenza VE.

METHODS

We used pooled inputs for VE by (sub)type and average vaccine coverage by age groups using data from eight seasons of the US Influenza VE Network to calculate sample sizes needed to estimate mid-season VE.

RESULTS

We estimate that 135 influenza-positive cases would be needed to detect an overall VE of 40% with 55% vaccine coverage among test-negative controls. Larger sample sizes would be required to produce reliable estimates specifically against influenza A/H3N2 and for older age groups.

CONCLUSION

Using an existing network, most of the recent influenza seasons in the US would facilitate valid mid-season VE estimates using the proposed sample sizes for broad age groupings.

Effects of Influenza Vaccination in the United States During the 2018-2019 Influenza Season

BACKGROUND

Multivalent influenza vaccine products provide protection against influenza A(H1N1)pdm09, A(H3N2), and B lineage viruses. The 2018-2019 influenza season in the United States included prolonged circulation of A(H1N1)pdm09 viruses well-matched to the vaccine strain and A(H3N2) viruses, the majority of which were mismatched to the vaccine. We estimated the number of vaccine-prevented influenza-associated illnesses, medical visits, hospitalizations, and deaths for the season.

METHODS

We used a mathematical model and Monte Carlo algorithm to estimate numbers and 95% uncertainty intervals (UIs) of influenza-associated outcomes prevented by vaccination in the United States. The model incorporated age-specific estimates of national 2018-2019 influenza vaccine coverage, influenza virus-specific vaccine effectiveness from the US Influenza Vaccine Effectiveness Network, and disease burden estimated from population-based rates of influenza-associated hospitalizations through the Influenza Hospitalization Surveillance Network.

RESULTS

Influenza vaccination prevented an estimated 4.4 million (95%UI, 3.4 million-7.1 million) illnesses, 2.3 million (95%UI, 1.8 million-3.8 million) medical visits, 58 000 (95%UI, 30 000-156 000) hospitalizations, and 3500 (95%UI, 1000-13 000) deaths due to influenza viruses during the US 2018-2019 influenza season. Vaccination prevented 14% of projected hospitalizations associated with A(H1N1)pdm09 overall and 43% among children aged 6 months-4 years.

CONCLUSIONS

Influenza vaccination averted substantial influenza-associated disease including hospitalizations and deaths in the United States, primarily due to effectiveness against A(H1N1)pdm09. Our findings underscore the value of influenza vaccination, highlighting that vaccines measurably decrease illness and associated healthcare utilization even in a season in which a vaccine component does not match to a circulating virus.

Interim seasonal influenza vaccine effectiveness estimates as proxy for final estimates: analysis of systematically identified matched pairs of interim/final estimates from test-negative design studies in outpatient settings from 2010/11 to 2018/19

OBJECTIVES

Limited time for seasonal influenza vaccine development means that the World Health Organization has to consider interim (early) rather than final vaccine effectiveness (VE) estimates in deciding influenza vaccine composition. We assessed agreement between interim and final VE estimates, and factors that may determine a substantial difference (≥10%) between point estimates.

METHODS

This was a mixed methods study. We systematically searched, identified, and matched interim/final VE studies of test-negative design (TND) type in outpatient settings after the 2009/10 influenza pandemic. The chi-square statistic (χ2) was used to assess the statistical significance of the difference between paired interim/final VE estimates. We calculated the difference between point estimates and used multivariable logistic regression to assess factors that may determine a substantial difference.

RESULTS

We identified 68 interim/final VE pairs. There was no statistically significant difference between almost all compared pairs. An inconsistent statistical model for interim/final VE estimation and interim VE estimation before the epidemic peak increased the odds of having a substantial difference between estimates.

CONCLUSION

: Interim influenza VE appears to be sufficient for vaccine composition decision-making. Consistency in interim/final VE estimation, and interim VE estimation during/after epidemic peak may increase agreement between the VE estimates.

A retrospective cohort study assessing relative effectiveness of adjuvanted versus high-dose trivalent influenza vaccines among older adults in the United States during the 2018-19 influenza season

PURPOSE

To evaluate the relative vaccine effectiveness (rVE) against influenza-related hospitalizations/emergency room (ER) visits, influenza-related office visits, and cardio-respiratory disease (CRD)-related hospitalizations/ER visits and compare all-cause and influenza-related costs associated with two vaccines specifically indicated for older adults (≥65 years), adjuvanted (aTIV) and high-dose trivalent influenza vaccine (TIV-HD), for the 2018-19 influenza season.

METHODS

A retrospective analysis of older adults was conducted using claims and hospital data in the United States. For clinical evaluations, adjusted analyses were conducted following inverse probability of treatment weighting (IPTW) to control for selection bias. Poisson regression was used to estimate the adjusted rVE against influenza-related hospitalizations/ER visits, influenza-related office visits, and any CRD-related hospitalizations/ER visits. For the economic evaluation, treatment selection bias was adjusted through 1:1 propensity score matching (PSM). All-cause and influenza-related costs associated with hospitalizations/ER, physician office and pharmacy visits were adjusted using generalized estimating equation (GEE) models.

RESULTS

After IPTW and Poisson regression, aTIV (n = 561,315) was slightly more effective in reducing influenza-related office visits compared to TIV-HD (n = 1,672,779) (6.6%; 95% CI: 2.8-10.3%). aTIV was statistically comparable to TIV-HD (2.0%; 95% CI: -3.7%-7.3%) in preventing influenza-related hospitalizations/ER visits but more effective in reducing hospitalizations/ER visits for any CRD (2.6%; 95% CI: 2.0-3.2%). In the PSM-adjusted cohorts (n = 561,243 pairs), following GEE adjustments, predicted mean annualized all-cause and influenza-related total costs per patient were statistically similar between aTIV and TIV-HD (US$9676 vs. US$9625 and US$18.74 vs. US$17.28, respectively; both p > 0.05). Finally, influenza-related pharmacy costs were slightly lower for aTIV as compared to TIV-HD ($1.75 vs $1.85; p < 0.0001).

CONCLUSIONS

During the 2018-19 influenza season, influenza-related hospitalization/ER visits and associated costs among people aged ≥ 65 were comparable between aTIV and TIV-HD. aTIV was slightly more effective in preventing influenza-related office visits and any CRD event as compared to TIV-HD in this population.

Influenza vaccine effectiveness against influenza A in children based on the results of various rapid influenza tests in the 2018/19 season

During influenza epidemics, Japanese clinicians routinely conduct rapid influenza diagnostic tests (RIDTs) in patients with influenza-like illness, and patients with positive test results are treated with anti-influenza drugs within 48 h after the onset of illness. We assessed the vaccine effectiveness (VE) of inactivated influenza vaccine (IIV) in children (6 months-15 years old, N = 4243), using a test-negative case-control design based on the results of RIDTs in the 2018/19 season. The VE against influenza A(H1N1)pdm and A(H3N2) was analyzed separately using an RIDT kit specifically for detecting A(H1N1)pdm09. The adjusted VE against combined influenza A (H1N1pdm and H3N2) and against A(H1N1)pdm09 was 39% (95% confidence interval [CI], 30%-46%) and 74% (95% CI, 39%-89%), respectively. By contrast, the VE against non-A(H1N1)pdm09 influenza A (presumed to be H3N2) was very low at 7%. The adjusted VE for preventing hospitalization was 56% (95% CI, 16%-77%) against influenza A. The VE against A(H1N1)pdm09 was consistently high in our studies. By contrast, the VE against A(H3N2) was low not only in adults but also in children in the 2018/19 season.

Influenza Vaccine Effectiveness in Children at the Emergency Department during the 2018-2019 Season: the First Season School-aged Children Were Included in the Korean Influenza National Immunization Program

BACKGROUND

For the 2018-2019 season, the national influenza immunization program expanded to cover children aged from 6 months to 12 years in Korea. This study aimed to analyze vaccine effectiveness (VE) against influenza in children visiting the pediatric emergency room at a tertiary hospital during the 2018-2019 season.

METHODS

Patients tested for influenza antigens from October 1st 2018 to May 31st 2019 at the pediatric emergency room of Samsung Medical Center were included. Patients' influenza antigen test results, influenza vaccination history, and underlying medical conditions were reviewed retrospectively. VE was estimated from the test-negative design study.

RESULTS

Among the 2,901 visits with influenza test results 1,692 visits of 1,417 patients were included for analysis. Among these 1,417 patients, 285 (20.1%) were positive (influenza A, n = 211, 74.0%; influenza B, n = 74, 26.0%). The VE in all patients was 36.4% (95% confidence interval [CI], 13.9 to 53.1). The VE for influenza A was 37.6% (95% CI, 12.6 to 55.5) and VE for influenza B was 24.0% (?38.5 to 58.3). The VE in the age group 6 months to 12 years was significant with a value of 35.6% (95% CI, 10.5 to 53.7); it was not statistically significant in the age group 13 to 18 years. In a multivariate logistic regression model, patients who received an influenza vaccination were less likely to get influenza infection (OR, 0.6; 95% CI, 0.4 to 0.8; P = 0.001), with significant confounding factors such as age group 13 to 18 years (OR, 0.5; 95% CI, 0.3 to 0.8; P = 0.003) and underlying hematology-oncology disease (OR, 0.3; 95% CI, 0.1 to 0.6; P = 0.002).

CONCLUSION

We report moderate effectiveness of influenza vaccination in previously healthy children aged from 6 months to 12 years in the 2018-2019 season.

Influence of a COVID-19 vaccine's effectiveness and safety profile on vaccination acceptance

Although a safe and effective vaccine holds the greatest promise for resolving the COVID-19 pandemic, hesitancy to accept vaccines remains common. To explore vaccine acceptance decisions, we conducted a national survey of 1,000 people from all US states in August of 2020 and a replication in December of 2020. Using a 3 × 3 × 3 factorial experimental design, we estimated the impact of three factors: probability of 1) protection against COVID-19, 2) minor side effects, and 3) a serious adverse reactions. The outcome was respondents' reported likelihood of receiving a vaccine for the coronavirus. Probability of vaccine efficacy (50%, 70%, or 90%) had the largest effect among the three factors. The probability of minor side effects (50%, 75%, 90%) including fever and sore arm, did not significantly influence likelihood of receiving the vaccine. The chances of a serious adverse reaction, such as temporary or permanent paralysis, had a small but significant effect. A serious adverse reaction rate of 1/100,000 was more likely to discourage vaccine use in comparison to rates of 1/million or 1/100 million. All interactions between the factors were nonsignificant. A replication following the announcement that vaccines were 95% effective showed small, but significant increases in the likelihood of taking a vaccine. The main effects and interactions in the model remained unchanged. Expected benefit was more influential in respondents' decision making than expected side effects. The absence of interaction effects suggests that respondents consider the side effects and benefits independently.

Influence of a COVID-19 vaccine's effectiveness and safety profile on vaccination acceptance

Although a safe and effective vaccine holds the greatest promise for resolving the COVID-19 pandemic, hesitancy to accept vaccines remains common. To explore vaccine acceptance decisions, we conducted a national survey of 1,000 people from all US states in August of 2020 and a replication in December of 2020. Using a 3 × 3 × 3 factorial experimental design, we estimated the impact of three factors: probability of 1) protection against COVID-19, 2) minor side effects, and 3) a serious adverse reactions. The outcome was respondents' reported likelihood of receiving a vaccine for the coronavirus. Probability of vaccine efficacy (50%, 70%, or 90%) had the largest effect among the three factors. The probability of minor side effects (50%, 75%, 90%) including fever and sore arm, did not significantly influence likelihood of receiving the vaccine. The chances of a serious adverse reaction, such as temporary or permanent paralysis, had a small but significant effect. A serious adverse reaction rate of 1/100,000 was more likely to discourage vaccine use in comparison to rates of 1/million or 1/100 million. All interactions between the factors were nonsignificant. A replication following the announcement that vaccines were 95% effective showed small, but significant increases in the likelihood of taking a vaccine. The main effects and interactions in the model remained unchanged. Expected benefit was more influential in respondents' decision making than expected side effects. The absence of interaction effects suggests that respondents consider the side effects and benefits independently.

Optimizing antiviral treatment for seasonal influenza in the USA: a mathematical modeling analysis

BACKGROUND

Seasonal influenza remains a major cause of morbidity and mortality in the USA. Despite the US Centers for Disease Control and Prevention recommendation promoting the early antiviral treatment of high-risk patients, treatment coverage remains low.

METHODS

To evaluate the population-level impact of increasing antiviral treatment timeliness and coverage among high-risk patients in the USA, we developed an influenza transmission model that incorporates data on infectious viral load, social contact, and healthcare-seeking behavior. We modeled the reduction in transmissibility in treated individuals based on their reduced daily viral load. The reduction in hospitalizations following treatment was based on estimates from clinical trials. We calibrated the model to weekly influenza data from Texas, California, Connecticut, and Virginia between 2014 and 2019. We considered in the baseline scenario that 2.7-4.8% are treated within 48 h of symptom onset while an additional 7.3-12.8% are treated after 48 h of symptom onset. We evaluated the impact of improving the timeliness and uptake of antiviral treatment on influenza cases and hospitalizations.

RESULTS

Model projections suggest that treating high-risk individuals as early as 48 h after symptom onset while maintaining the current treatment coverage level would avert 2.9-4.5% of all symptomatic cases and 5.5-7.1% of all hospitalizations. Geographic variability in the effectiveness of earlier treatment arises primarily from variabilities in vaccination coverage and population demographics. Regardless of these variabilities, we found that when 20% of the high-risk individuals were treated within 48 h, the reduction in hospitalizations doubled. We found that treatment of the elderly population (> 65 years old) had the highest impact on reducing hospitalizations, whereas treating high-risk individuals aged 5-19 years old had the highest impact on reducing transmission. Furthermore, the population-level benefit per treated individual is enhanced under conditions of high vaccination coverage and a low attack rate during an influenza season.

CONCLUSIONS

Increased timeliness and coverage of antiviral treatment among high-risk patients have the potential to substantially reduce the burden of seasonal influenza in the USA, regardless of influenza vaccination coverage and the severity of the influenza season.

Relative Effectiveness of Influenza Vaccines Among the United States Elderly, 2018-2019

BACKGROUND

Studies among individuals ages ≥65 years have found a moderately higher relative vaccine effectiveness (RVE) for the high-dose (HD) influenza vaccine compared with standard-dose (SD) products for most seasons. Studies during the A(H3N2)-dominated 2017-2018 season showed slightly higher RVE for the cell-cultured vaccine compared with SD egg-based vaccines. We investigated the RVE of influenza vaccines among Medicare beneficiaries ages ≥65 years during the 2018-2019 season.

METHODS

This is a retrospective cohort study using inverse probability of treatment weighting and Poisson regression to evaluate RVE in preventing influenza hospital encounters.

RESULTS

Among 12 777 214 beneficiaries, the egg-based adjuvanted (RVE, 7.7%; 95% confidence interval [CI], 3.9%-11.4%) and HD (RVE, 4.9%; 95% CI, 1.7%-8.1%) vaccines were marginally more effective than the egg-based quadrivalent vaccines. The cell-cultured quadrivalent vaccine was not significantly more effective than the egg-based quadrivalent vaccine (RVE, 2.5%; 95% CI, -2.4% to 7.3%).

CONCLUSIONS

We did not find major effectiveness differences between licensed vaccines used among the elderly during the 2018-2019 season. Consistent with prior research, we found that the egg-based adjuvanted and HD vaccines were slightly more effective than the egg-based quadrivalent vaccines.

Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network

Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population. This paradigm has been useful in simplifying the biological reality of epidemics and has allowed the modelling community to focus on the complexity of other factors such as population structure and interventions. However, there is an increasing amount of evidence that the strain diversity of pathogens, and their interplay with the host immune system, can play a large role in shaping the dynamics of epidemics. Here, we introduce a disease model with an underlying genotype network to account for two important mechanisms. One, the disease can mutate along network pathways as it spreads in a host population. Two, the genotype network allows us to define a genetic distance between strains and therefore to model the transcendence of immunity often observed in real world pathogens. We study the emergence of epidemics in this model, through its epidemic phase transitions, and highlight the role of the genotype network in driving cyclicity of diseases, large scale fluctuations, sequential epidemic transitions, as well as localization around specific strains of the associated pathogen. More generally, our model illustrates the richness of behaviours that are possible even in well-mixed host populations once we consider strain diversity and go beyond the “one disease equals one pathogen” paradigm.

Epidemics rarely involve a single unique pathogen but are often modelled as such. Rather, most pathogens circulate under a family of strains which can interact differently with the host immune system and undergo further mutations. Here we extend a classic epidemiological model to consider the genetic structure connecting these strains—i.e., the genotype network mapping possible mutation pathways—and investigate the dynamics and emergence of epidemics beyond the “one disease equals one pathogen” paradigm. This simple model allows us to consider the impacts of (i) mutation, (ii) cross-immunity between strains, (iii) competition between strains, and (iv) the structure of the genotype network. We find that, altogether, these features do not affect the classic epidemic threshold but localize outbreaks around key strains and yield a second immune invasion threshold below which the epidemics follow almost cyclical and chaos-like dynamics. Our results illustrate how little biological realism is needed to introduce key features of real epidemics in even the simplest disease models: epidemic cycles, unpredictability, and heterogeneous strain prevalence.

Influenza Vaccine Effectiveness and Waning Effect in Hospitalized Older Adults. Valencia Region, Spain, 2018/2019 Season

Influenza vaccination is annually recommended for specific populations at risk, such as older adults. We estimated the 2018/2019 influenza vaccine effectiveness (IVE) overall, by influenza subtype, type of vaccine, and by time elapsed since vaccination among subjects 65 years old or over in a multicenter prospective study in the Valencia Hospital Surveillance Network for the Study of Influenza and other Respiratory Viruses (VAHNSI, Spain). Information about potential confounders was obtained from clinical registries and/or by interviewing patients and vaccination details were only ascertained by registries. A test-negative design was performed in order to estimate IVE. As a result, IVE was estimated at 46% (95% confidence interval (CI): (16%, 66%)), 41% (95% CI: (−34%, 74%)), and 45% (95% CI: (7%, 67%)) against overall influenza, A(H1N1)pdm09 and A(H3N2), respectively. An intra-seasonal not relevant waning effect was detected. The IVE for the adjuvanted vaccine in ≥75 years old was 45% (2%, 69%) and for the non-adjuvanted vaccine in 65–74 years old was 59% (−16%, 86%). Thus, our data revealed moderate vaccine effectiveness against influenza A(H3N2) and not significant against A(H1N1)pdm09. Significant protection was conferred by the adjuvanted vaccine to patients ≥75 years old. Moreover, an intra-seasonal not relevant waning effect was detected, and a not significant IVE decreasing trend was observed over time.

Investigating the Interaction between Negative Strand RNA Viruses and Their Hosts for Enhanced Vaccine Development and Production

The current pandemic has highlighted the ever-increasing risk of human to human spread of zoonotic pathogens. A number of medically-relevant zoonotic pathogens are negative-strand RNA viruses (NSVs). NSVs are derived from different virus families. Examples like Ebola are known for causing severe symptoms and high mortality rates. Some, like influenza, are known for their ease of person-to-person transmission and lack of pre-existing immunity, enabling rapid spread across many countries around the globe. Containment of outbreaks of NSVs can be difficult owing to their unpredictability and the absence of effective control measures, such as vaccines and antiviral therapeutics. In addition, there remains a lack of essential knowledge of the host–pathogen response that are induced by NSVs, particularly of the immune responses that provide protection. Vaccines are the most effective method for preventing infectious diseases. In fact, in the event of a pandemic, appropriate vaccine design and speed of vaccine supply is the most critical factor in protecting the population, as vaccination is the only sustainable defense. Vaccines need to be safe, efficient, and cost-effective, which is influenced by our understanding of the host–pathogen interface. Additionally, some of the major challenges of vaccines are the establishment of a long-lasting immunity offering cross protection to emerging strains. Although many NSVs are controlled through immunisations, for some, vaccine design has failed or efficacy has proven unreliable. The key behind designing a successful vaccine is understanding the host–pathogen interaction and the host immune response towards NSVs. In this paper, we review the recent research in vaccine design against NSVs and explore the immune responses induced by these viruses. The generation of a robust and integrated approach to development capability and vaccine manufacture can collaboratively support the management of outbreaking NSV disease health risks.

Characterizing genetic and antigenic divergence from vaccine strain of influenza A and B viruses circulating in Thailand, 2017-2020

We monitored the circulating strains and genetic variation among seasonal influenza A and B viruses in Thailand between July 2017 and March 2020. The hemagglutinin gene was amplified and sequenced. We identified amino acid (AA) changes and computed antigenic relatedness using the P_epitope model. Phylogenetic analyses revealed multiple clades/subclades of influenza A(H1N1)pdm09 and A(H3N2) were circulating simultaneously and evolved away from their vaccine strain, but not the influenza B virus. The predominant circulating strains of A(H1N1)pdm09 belonged to 6B.1A1 (2017-2018) and 6B.1A5 (2019-2020) with additional AA substitutions. Clade 3C.2a1b and 3C.2a2 viruses co-circulated in A(H3N2) and clade 3C.3a virus was found in 2020. The B/Victoria-like lineage predominated since 2019 with an additional three AA deletions. Antigenic drift was dominantly facilitated at epitopes Sa and Sb of A(H1N1)pdm09, epitopes A, B, D and E of A(H3N2), and the 120 loop and 190 helix of influenza B virus. Moderate computed antigenic relatedness was observed in A(H1N1)pdm09. The computed antigenic relatedness of A(H3N2) indicated a significant decline in 2019 (9.17%) and 2020 (- 18.94%) whereas the circulating influenza B virus was antigenically similar (94.81%) with its vaccine strain. Our findings offer insights into the genetic divergence from vaccine strains, which could aid vaccine updating.

Seasonal influenza vaccine effectiveness among health-care workers in Prince Sultan Military Medical City, Riyadh, KSA, 2018-2019

Background: Healthcare Workers (HCWs) constitute a major group exposed to influenza. Researchers herein try to determine the influenza vaccine effectiveness (VE). Influenza VE depends on the vaccinated personal characteristics and the closeness of matching between the vaccine and the prevalent strains of the virus. The aim of our research was to identify the 2018–2019 seasonal influenza VE in HCWs.

Methods: a record-based study was carried out using the test-negative design from October 2018 to September 2019 to calculate the influenza VE. HCWs with influenza like illness (ILI) were screened to detect the positive cases, and the vaccination status was determined based on vaccination database. VE was assessed from the ratio of the odds of vaccination among positive cases to the odds of vaccination among negative controls. Statistical analysis Multivariable logistic regression was used to estimate adjusted VE

Results: a total of 556 HCWs presented with ILI, 65.6% were females, and 54.1% were nurses, 152 HCWs (27.3%) had laboratory-confirmed influenza, shows two peaks in January and March 2019. VE for all types was 35.0% and rose to 42.0% after adjustment for HCWs age, gender, nationality, and job position, influenza A (H3N2) VE was 78.0%. H1N1 VE was 55.0% but no significant VE for type B was found.

Conclusion: Our VE estimates are in agreement with VE estimates published for that season. The use of quadrivalent vaccine with two stains of influenza B is recommended.

Identifying Potential Candidate Hub Genes and Functionally Enriched Pathways in the Immune Responses to Quadrivalent Inactivated Influenza Vaccines in the Elderly Through Co-Expression Network Analysis

Insights into the potential candidate hub genes may facilitate the generation of safe and effective immunity against seasonal influenza as well as the development of personalized influenza vaccines for the elderly at high risk of influenza virus infection. This study aimed to identify the potential hub genes related to the immune induction process of the 2018/19 seasonal quadrivalent inactivated influenza vaccines (QIVs) in the elderly ≥60 years by using weighted gene co-expression network analysis (WGCNA). From 63 whole blood samples from16 elderly individuals, a total of 13,345 genes were obtained and divided into eight co-expression modules, with two modules being significantly correlated with vaccine-induced immune responses. After functional enrichment analysis, genes under GO terms of vaccine-associated immunity were used to construct the sub-network for identification and functional validation of hub genes. MCEMP1 and SPARC were confirmed as the hub genes with an obvious effect on QIVs-induced immunity. The MCEMP1 expression was shown to be negatively correlated with the QIVs-associated reactogenicity within 7 days after vaccination, which could be suppressed by the CXCL 8/IL-8 and exacerbated by the Granzyme-B cytotoxic mediator. Meanwhile, the SPARC expression was found to increase the immune responses to the QIVs and contribute to the persistence of protective humoral antibody titers. These two genes can be used to predict QIVs-induced adverse reaction, the intensity of immune responses, and the persistence of humoral antibody against influenza. This work has shed light on further research on the development of personalized QIVs with appropriate immune responses and long-lasting immunity against the forthcoming seasonal influenza.

Comparative effectiveness of influenza vaccines among U.S. Medicare beneficiaries ages 65 years and older during the 2019-20 season

BACKGROUND

Around 50,000 influenza-associated deaths occur annually in the U.S., overwhelmingly among individuals ages >65 years. Although vaccination is the primary prevention tool, investigations have shown low vaccine effectiveness (VE) in recent years, particularly among the elderly. We analyzed the relative VE (RVE) of all influenza vaccines among Medicare beneficiaries ages >65 years to prevent influenza hospital encounters during the 2019-20 season.

METHODS

Retrospective cohort study using Poisson regression and inverse probability of treatment weighting (IPTW). Exposures included egg-based high-dose trivalent (HD-IIV3), egg-based adjuvanted trivalent (aIIV3), egg-based standard dose (SD) quadrivalent (IIV4), cell-based SD quadrivalent (cIIV4), and recombinant quadrivalent (RIV4) influenza vaccines.

RESULTS

We studied 12.7 million vaccinated beneficiaries. Following IPTW, cohorts were well balanced for all covariates and health-seeking behavior indicators. In the adjusted analysis, RIV4 (RVE 13.3%, 95% CI 7.4%, 18.9%), aIIV3 (RVE 8.2%, 95% CI 4.2%, 12.0%), and HD-IIV3 (RVE 6.8%, 95% CI 3.3%, 10.1%) were significantly more effective in preventing hospital encounters than the reference egg-based SD IIV4, while cIIV4 was not significantly more effective than IIV4 (RVE 2.8%, 95% CI -2.8%, 8.2%). Our results were consistent across all analyses.

CONCLUSIONS

In this influenza B-Victoria and A(H1N1)-dominated season, RIV4 was moderately more effective than other vaccines, while the HD-IIV3 and aIIV3 were more effective than the IIV4 vaccines, highlighting the contributions of antigen amount and adjuvant use to VE. Egg adaptation likely did not substantially affect our RVE evaluation. Our findings, specific to the 2019-20 season, should be evaluated in other studies using virological case confirmation.

Influenza Vaccine Requirements in United States Child Care Centers

BACKGROUND

Influenza vaccine is the most effective means to prevent influenza for the high-risk population of child care attendees. This national survey assessed child care center directors' reports of seasonal influenza vaccine requirements for children and adult caregivers.

METHODS

This was a 2016 telephone-based survey of child care center directors randomly selected from a national database of licensed United States child care centers and queried about influenza vaccine requirements. Conceptually related items were grouped into 4 indexes: general infection control, use of health consultants, quality of child care, and pandemic influenza preparedness. These indexes, along with other center and director characteristics, were used to predict director-reported influenza vaccine requirements.

RESULTS

Of 518 child care center directors, only 24.5% and 13.1% reported an influenza vaccine requirement for children and adult caregivers, respectively. Center and director characteristics and the indexes were not associated with a director-reported influenza vaccine requirement. After adjusting for covariates, only having a state influenza vaccine law for children and an adult influenza vaccine requirement predicted having a child influenza vaccine requirement. Only having a child influenza vaccine requirement predicted having an adult vaccine requirement.

CONCLUSIONS

Director-reported influenza vaccine requirements for children and adult caregivers were influenced primarily by state influenza vaccine laws. Given the high risk of children in child care and low director-reported influenza vaccine requirements, more states should pass laws requiring influenza vaccine for children and adult caregivers at child care programs.

Middle-aged individuals may be in a perpetual state of H3N2 influenza virus susceptibility

Influenza virus exposures in childhood can establish long-lived memory B cell responses that can be recalled later in life. Here, we complete a large serological survey to elucidate the specificity of antibodies against contemporary H3N2 viruses in differently aged individuals who were likely primed with different H3N2 strains in childhood. We find that most humans who were first infected in childhood with H3N2 viral strains from the 1960s and 1970s possess non-neutralizing antibodies against contemporary 3c2.A H3N2 viruses. We find that 3c2.A H3N2 virus infections boost non-neutralizing H3N2 antibodies in middle-aged individuals, potentially leaving many of them in a perpetual state of 3c2.A H3N2 viral susceptibility.

Assessment of the benefits of seasonal influenza vaccination: Elements of a framework to interpret estimates of vaccine effectiveness and support robust decision-making and communication

Systematic reviews and meta‐analyses confirm that influenza vaccination reduces the risk of influenza illness by between about 40% and 60% in seasons when circulating influenza stains are well matched to vaccine strains. Influenza vaccine effectiveness (IVE) estimates, however, are often discordant and a source of confusion for decision makers. IVE assessments are increasingly publicized and are often used by policy makers to make decisions about the value of seasonal influenza vaccination. But there is limited guidance on how IVE should be interpreted or used to inform policy. There are several limitations to the use of IVE for decision‐making: (a) IVE studies have methodological issues that often complicate the interpretation of their value; and (b) the full impact of vaccination will almost always be greater than the impact assessed by a point estimate of IVE in specific populations or settings. Understanding the strengths and weaknesses of study methodologies and the fundamental limitations of IVE estimates is important for the accuracy of interpretations and support of policy makers’ decisions. Here, we review a comprehensive set of issues that need to be considered when interpreting IVE and determining the full benefits of influenza vaccination. We propose that published IVE values should be assessed using an evaluative framework that includes influenza‐specific outcomes, types of VE study design, and confounders, among other factors. Better interpretation of IVE will improve the broader assessment of the value of influenza vaccination and ultimately optimize the public health benefits in seasonal influenza vaccination.

Health Information Sources and the Influenza Vaccination: The Mediating Roles of Perceived Vaccine Efficacy and Safety

Although the influenza vaccine is widely recognized as an effective preventive measure, influenza vaccination rates among U.S. adults remain low. Moreover, influenza-related respiratory illnesses may increase the risk of adverse outcomes of COVID-19. Thus, this study examines the mechanisms involved in influenza vaccination uptake. Specifically, this study investigates how health information sources are associated with perceived vaccine efficacy and safety, which, in turn, associated with influenza vaccine uptake. Analyzing cross-sectional survey data from a national U.S. adult sample (N = 19,420), mediation analyses were conducted. Results revealed that considering vaccine efficacy, health information seekers who assigned more value to medical professionals, medical journals, and newspaper articles were more likely to perceive a vaccine as effective, thus being more likely to receive the influenza vaccine. By contrast, individuals who placed more value in social media were less likely to perceive vaccine efficacy, and, in turn, were less likely to get the influenza vaccine. Turning to vaccine safety, the value ascribed to medical professionals was positively associated with vaccine safety, which, in turn, related to influenza vaccine uptake. By contrast, social media, family or friends, and promotions were negatively associated with vaccine safety, and then influenza vaccine uptake.

Pharmacodynamic and safety considerations for influenza vaccine and adjuvant design

INTRODUCTION

A novel adjuvant evaluation system for safety and immunogenicity is needed. Vaccination is important for infection prevention, for example, from influenza viruses. Adjuvants are considered critical for improving the effectiveness of influenza vaccines. Adjuvant development is an important issue in influenza vaccine design.

AREAS COVERED

A conventional in vivo evaluation method for vaccine safety has been limited in analyzing phenotypic and pathological changes. Therefore, it is difficult to obtain information on the changes at the molecular level. This review aims to explain the recently developed genomics analysis-based vaccine adjuvant safety evaluation tools verified by AddaVax^TM and polyinosinic-polycytidylic acid (poly I:C) using 18 biomarker genes and whole-virion inactivated influenza vaccine as a toxicity control. Genomics analyzes would help provide safety and efficacy information regarding influenza vaccine design by facilitating appropriate adjuvant selection.

EXPERT OPINION

The efficacy and safety profiles of influenza vaccines and adjuvants using genomics technologies provide useful information regarding immunogenicity, which is related to safety and efficacy. This approach provides important information to select appropriate inoculation routes, combinations of vaccine antigens and adjuvants, and dosing amounts. The efficacy of vaccine adjuvant evaluation by genomics analysis should be verified by various studies using various vaccines in the future.

Influenza vaccine effectiveness and disease burden in children and adolescents with sickle cell disease: 2012-2017

BACKGROUND

Data are limited on the burden of influenza and seasonal influenza vaccine effectiveness (VE) in children with sickle cell disease (SCD).

METHODS

We used a prospectively collected clinical registry of SCD patients 6 months to 21 years of age to determine the influenza cases per 100 patient-years, vaccination rates, and a test-negative case-control study design to estimate influenza VE against medically attended laboratory-confirmed influenza infection. Influenza-positive cases were randomly matched to test-negative controls on age and influenza season in 1:1 ratio. We used adjusted logistic regression models to compare odds ratio (OR) of vaccination in cases to controls. We calculated VE as [100% × (1 - adjusted OR)] and computed 95% confidence intervals (CIs) around the estimate.

RESULTS

There were 1037 children with SCD who were tested for influenza, 307 children (29.6%) had at least one influenza infection (338 infections, incidence rate 3.7 per 100 person-years; 95% CI, 3.4-4.1) and 56.2% of those tested received annual influenza vaccine. Overall VE pooled over five seasons was 22.3% (95% CI, -7.3% to 43.7%). Adjusted VE estimates ranged from 39.7% (95% CI, -70.1% to 78.6%) in 2015/2016 to -5.9% (95% CI, -88.4% to 40.4%) in the 2016/17 seasons. Influenza VE varied by age and was highest in children 1-5 years of age (66.6%; 95% CI, 30.3-84.0). Adjusted VE against acute chest syndrome during influenza infection was 39.4% (95% CI, -113.0 to 82.8%).

CONCLUSIONS

Influenza VE in patients with SCD varies by season and age. Multicenter prospective studies are needed to better establish and monitor influenza VE among children with SCD.

Predominance of influenza virus A(H3N2) 3C.2a1b and A(H1N1)pdm09 6B.1A5A genetic subclades in the WHO European Region, 2018-2019

BACKGROUND

The 2018/2019 influenza season in the WHO European Region was dominated by influenza A (H1N1)pdm09 and (H3N2) viruses, with very few influenza B viruses detected.

METHODS

Countries in the European Region reported virus characterization data to The European Surveillance System for weeks 40/2018 to 20/2019. These virus antigenic and genetic characterization and haemagglutinin (HA) sequence data were analysed to describe and assess circulating viruses relative to the 2018/2019 vaccine virus components for the northern hemisphere.

RESULTS

Thirty countries reported 4776 viruses characterized genetically and 3311 viruses antigenically. All genetically characterized A(H1N1)pdm09 viruses fell in subclade 6B.1A, of which 90% carried the amino acid substitution S183P in the HA gene. Antigenic data indicated that circulating A(H1N1)pdm09 viruses were similar to the 2018/2019 vaccine virus. Genetic data showed that A(H3N2) viruses mostly fell in clade 3C.2a (75%) and 90% of which were subclade 3C.2a1b. A lower proportion fell in clade 3C.3a (23%) and were antigenically distinct from the vaccine virus. All B/Victoria viruses belonged to clade 1A; 30% carried a double amino acid deletion in HA and were genetically and antigenically similar to the vaccine virus component, while 55% carried a triple amino acid deletion or no deletion in HA; these were antigenically distinct from each other and from the vaccine component. All B/Yamagata viruses belonged to clade 3 and were antigenically similar to the virus component in the quadrivalent vaccine for 2018/2019.

CONCLUSIONS

A simultaneous circulation of genetically and antigenically diverse A(H3N2) and B/Victoria viruses was observed and represented a challenge to vaccine strain selection.

Moderate Vaccine Effectiveness against Severe Acute Respiratory Infection Caused by A(H1N1)pdm09 Influenza Virus and No Effectiveness against A(H3N2) Influenza Virus in the 2018/2019 Season in Italy

Every season, circulating influenza viruses change; therefore, vaccines must be reformulated each year. We aimed to estimate vaccine effectiveness (VE) against severe influenza infection for the 2018/19 season in Italy. We conducted a test-negative design case-control study at five Italian hospitals. We estimated influenza VE against severe acute respiratory infection (SARI) requiring hospitalisation overall, and by virus subtype, vaccine brand, and age. The 2018/19 season was characterised by A(H1N1)pmd09 and A(H3N2) influenza viruses. Vaccine coverage among <18 years recruited SARI cases was very low (3.2%). Seasonal vaccines were moderately effective against type A influenza overall (adjusted VE = 40.5%; 95% confidence interval (CI) = 18.7–56.4%) and subtype A(H1N1)pmd09 viruses (adjusted VE = 55%; 95% CI = 34.5–69.1%), but ineffective against subtype A(H3N2) viruses (adjusted VE = 2.5%; 95% CI = −50.0–36.7%). Both Fluad and Fluarix Tetra vaccines were effective against type A influenza overall and subtype A(H1N1)pdm09 viruses. VE appeared to be similar across age groups (0–64 years, ≥65 years). Seasonal influenza vaccines in the 2018/19 season were moderately effective in preventing SARI caused by A(H1N1)pdm09 influenza but ineffective against A(H3N2).

Role of Extracellular Vesicles in Influenza Virus Infection

Influenza virus infection is a major health care concern associated with significant morbidity and mortality worldwide, and cause annual seasonal epidemics and pandemics at irregular intervals. Recent research has highlighted that viral components can be found on the extracellular vesicles (EVs) released from infected cells, implying a functional relevance of EVs with influenza virus dissemination. Therefore, exploring the role of EVs in influenza virus infection has been attracting significant attention. In this review, we will briefly introduce the biogenesis of EVs, and focus on the role of EVs in influenza virus infection, and then discuss the EVs-based influenza vaccines and the limitations of EVs studies, to further enrich and boost the development of preventative and therapeutic strategies to combat influenza virus.

A case of reassortant seasonal influenza A(H1N2) virus, Denmark, April 2019

A reassortant influenza A subtype H1N2 virus with gene segments from seasonal A(H1N1)pdm09 virus (HA, MP, NP, NS, PA, PB1 and PB2) and seasonal A(H3N2) virus (NA) was identified in a routine surveillance sample in Denmark. The patient recovered fully. This is the second reassortant influenza A(H1N2) virus identified in Europe in the 2018/19 influenza season, with the first case being detected December 2018 in Sweden.

Interim 2018/19 influenza vaccine effectiveness: six European studies, October 2018 to January 2019

Influenza A(H1N1)pdm09 and A(H3N2) viruses both circulated in Europe in October 2018–January 2019. Interim results from six studies indicate that 2018/19 influenza vaccine effectiveness (VE) estimates among all ages in primary care was 32–43% against influenza A; higher against A(H1N1)pdm09 and lower against A(H3N2). Among hospitalised older adults, VE estimates were 34–38% against influenza A and slightly lower against A(H1N1)pdm09. Influenza vaccination is of continued benefit during the ongoing 2018/19 influenza season.

Varying Vaccination Rates Among Patients Seeking Care for Acute Respiratory Illness: A Systematic Review and Meta-analysis

Background

Complications following influenza infection are a major cause of morbidity and mortality, and the Centers for Disease Control Advisory Committee on Immunization Practices recommends universal annual vaccination. However, vaccination rates have remained significantly lower than the Department of Health and Human Services goal. The aim of this work was to assess the vaccination rate among patients who present to health care providers with influenza-like illness and identify groups with lower vaccination rates.

Methods

We performed a systematic search of the PubMed and EMBASE databases with a time frame of January 1, 2010, to March 1, 2019 and focused on the vaccination rate among patients seeking care for acute respiratory illness in the United States. A random effects meta-analysis was performed to estimate the pooled seasonal influenza vaccination rate, and we used a time trend analysis to identify differences in annual vaccination over time.

Results

The overall pooled influenza vaccination rate was 48.61% (whites: 50.87%; blacks: 36.05%; Hispanics: 41.45%). There was no significant difference among gender groups (men: 46.43%; women: 50.11%). Interestingly, the vaccination rate varied by age group and was significantly higher among adults aged >65 (78.04%) and significantly lower among children 9–17 years old (36.45%). Finally, we found a significant upward time trend in the overall influenza vaccination rate among whites (coef. = .0107; P = .027).

Conclusions

In conclusion, because of the significantly lower influenza vaccination rates in black and Hispanic communities, societal initiatives and community outreach programs should focus on these populations and on children and adolescents aged 9–17 years.

Children under 10 years of age were more affected by the 2018/19 influenza A(H1N1)pdm09 epidemic in Canada: ‎possible cohort effect following the 2009 influenza pandemic

Introduction

Findings from the community-based Canadian Sentinel Practitioner Surveillance Network (SPSN) suggest children were more affected by the 2018/19 influenza A(H1N1)pdm09 epidemic.

Aim

To compare the age distribution of A(H1N1)pdm09 cases in 2018/19 to prior seasonal influenza epidemics in Canada.

Methods

The age distribution of unvaccinated influenza A(H1N1)pdm09 cases and test-negative controls were compared across A(H1N1)pdm09-dominant epidemics in 2018/19, 2015/16 and 2013/14 and with the general population of SPSN provinces. Similar comparisons were undertaken for influenza A(H3N2)-dominant epidemics.

Results

In 2018/19, more influenza A(H1N1)pdm09 cases were under 10 years old than controls (29% vs 16%; p < 0.001). In particular, children aged 5–9 years comprised 14% of cases, greater than their contribution to controls (4%) or the general population (5%) and at least twice their contribution in 2015/16 (7%; p < 0.001) or 2013/14 (5%; p < 0.001). Conversely, children aged 10–19 years (11% of the population) were under-represented among A(H1N1)pdm09 cases versus controls in 2018/19 (7% vs 12%; p < 0.001), 2015/16 (7% vs 13%; p < 0.001) and 2013/14 (9% vs 12%; p = 0.12).

Conclusion

Children under 10 years old contributed more to outpatient A(H1N1)pdm09 medical visits in 2018/19 than prior seasonal epidemics in Canada. In 2018/19, all children under 10 years old were born after the 2009 A(H1N1)pdm09 pandemic and therefore lacked pandemic-induced immunity. In addition, more than half those born after 2009 now attend school (i.e. 5–9-year-olds), a socio-behavioural context that may enhance transmission and did not apply during prior A(H1N1)pdm09 epidemics.