Future Influenza Research Articles

Molecular diagnostics using the QIAstat-Dx syndromic device for covering avian influenza pandemic preparedness

IntroductionA key factor in influenza pandemic preparedness is the ability to detect zoonotic influenza virus strains as they emerge in humans through spillover events, ideally before human-to-human transmission occurs. DesignIn this study, the utility of the QIAstat-Dx syndromic device for influenza surveillance was evaluated. Bioinformatic analysis was performed on all WHO-recommended influenza Candidate Vaccine Viruses (CVVs), including the common strains recommended for the 2023–2024 influenza vaccine composition in the northern hemisphere, and 16 different H5 highly pathogenic avian influenza virus (HPAIV) and two H9N2 low pathogenic avian influenza virus (LPAIV) strains. For laboratory validation, engineered gene fragments and real HPAIV and LPAIV samples were tested using the QIAstat-Dx Respiratory SARS-CoV-2 Panel. ResultsDuring the bioinformatic screening, common influenza strains were positive including influenza A subtypes, and all H5 HPAIV and LPAIV H9N2 were detected as Influenza A positive without subtype discrimination. In all cases, laboratory validation confirmed all bioinformatic results. ConclusionQIAstat-Dx can detect all tested potentially zoonotic influenza A virus strains, and discriminate them from human sesonal influenza A viruses, ensuring a correct diagnosis. Any tool available for surveillance and pandemic preparedness is essential for a rapid response to reduce healthcare costs and severity of future influenza pandemics.

Projected expansion in two influenza-susceptible birds' distribution under climate and land-cover changes on the Qinghai-Tibetan Plateau

Avian influenza is a global zoonotic disease influencing bird conservation and public health. Climate and land-cover changes can significantly impact influenza-susceptible species' distribution, thereby influencing avian influenza outbreaks. The Qinghai-Tibetan Plateau (QTP) plays a crucial role in avian influenza virus transmission and is susceptible to environmental changes. Here, we focused on two influenza-susceptible birds, the bar-headed goose (Anser indicus) and brown-headed gull (Chroicocephalus brunnicephalus), to predict their distribution on the QTP under climate and land-cover change scenarios. We integrated satellite tracking, field surveys, and publicly available datasets to collect species occurrence. Then, we utilized Biomod models to predict bird distribution under current and future scenarios. Our results indicated that the distance to water bodies (DW) and the mean temperature of the wettest quarter (BIO 8) significantly influenced the distribution of bar-headed geese and brown-headed gulls. The highly suitable distributions of both species are concentrated in the northeastern QTP and the Changtang Plateau, with only the Qaidam Basin showing a decrease in the future. Their future distribution has roughly doubled, with expansions toward western and higher elevations. We highlighted the influence of climate and land cover changes on bird distribution, and identified key areas of bird distribution, which are also critical areas for future avian influenza monitoring and prevention.

Optimizing influenza vaccine allocation: A predictive analytics approach for informed public health planning.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Excessive purchasing of influenza vaccine can lead to costly overages and waste of resources. Insufficient quantities, however, can jeopardize population health. Our project aimed to use predictive analytics to determine the influenza vaccine quantities that would be needed for the next influenza season while minimizing vaccine waste and meeting patient care demands. Several data sources were evaluated to develop a predictive analytics model to better estimate future influenza vaccine orders during upcoming influenza seasons. A retrospective analysis of influenza vaccine administrations over the last 4 influenza seasons allowed the team to develop an algorithm to predict influenza vaccine needs. Two regions within Mayo Clinic were selected to determine the validity of our ordering process. These 2 regions, identified as regions 3 and 5, ordered influenza vaccines based on the algorithm, while the other 3 regions acted as control groups, ordering though traditional methods based on purchasing data. Predictive analysis for the 2 intervention regions resulted in a savings of over $1 million when compared to traditional ordering methods. The model predicted that the quantity of vaccine ordered should be 17,574.16 and 9,164.29 quadrivalent influenza vaccines for regions 3 and 5, respectively. On the basis of actual administration data, 15,902 vaccines for region 3 and 9,016 vaccines for region 5 will be administered by the end of the season, both of which are less than the predicted amount needed, demonstrating the accuracy of the analytics. Compared to the traditional ordering method, ordering using predictive analytics allowed the team to more accurately determine future order volumes and spend, yielding significant cost savings.

Multi-strain modeling of influenza vaccine effectiveness in older adults and its dependence on antigenic distance

Influenza vaccine effectiveness (VE) varies seasonally due to host, virus and vaccine characteristics. To investigate how antigenic matching and dosage impact VE, we developed a mechanistic knowledge-based mathematical model. Immunization with a split vaccine is modeled for exposure to A/H1N1 or A/H3N2 virus strains. The model accounts for cross-reactivity of immune cells elicited during previous immunizations with new antigens. We simulated vaccine effectiveness (sVE) of high dose (HD) versus standard dose (SD) vaccines in the older population, from 2011 to 2022. We find that sVE is highly dependent on antigenic matching and that higher dosage improves immunogenicity, activation and memory formation of immune cells. In alignment with clinical observations, the HD vaccine performs better than the SD vaccine in all simulations, supporting the use of the HD vaccine in the older population. This model could be adapted to predict the impact of alternative virus strain selection on clinical outcomes in future influenza seasons.

Active offer of influenza vaccination during hospitalization: a multicenter study in Sicily (Italy)

Abstract Background Every cold season, the Italian health institutions strongly recommend influenza vaccination for categories at risk of complications, however influenza vaccination coverage is over and over far from the desirable target of 95%. After the pilot experience conducted in Palermo during the 2022-23 influenza season, the ‘Vaccinations in the ward’ project was extended to other Sicilian centers in order to evaluate the impact of the vaccination offer strategy in a broader territorial reality and to analyze the determinants of influenza vaccine acceptance among at risk people. Methods The project was conducted at the Umberto I Hospital in Enna and the University Hospitals of Messina and Palermo during the 2023-24 influenza season. A questionnaire was administered to the at risk hospitalized patients to investigate socio-demographic factors, behavioral habits, and clinical condition. Furthermore, influenza vaccination upon discharge was offered. Multivariable logistic regression was performed to identify the determinants of influenza vaccine acceptance. Results Overall, 374 patients with a median age of 65 years (IQR: 50-70) were recruited, of whom 36% had been vaccinated for influenza during the 2022-23 season (n = 136). The patients who accepted influenza vaccination in the ward were 57% (n = 214). The determinants of vaccination adherence were: age (OR: 1.03; p = 0.003); having quit smoking (OR: 2.68; p = 0.017); having received advice on vaccination from general practitioner (OR: 4.9; p < 0.001) and hospital healthcare workers (OR: 7.3; p < 0.001). Conclusions The offer of vaccination in the ward effectively increased influenza coverage among categories at risk of complications. Furthermore, the adoption of correct behavioral habits and the promotion of influenza vaccination by healthcare personnel have played a decisive role in the vaccine acceptance process. These findings could be useful for planning future influenza vaccination campaigns targeted to at risk people. Key messages • Vaccination strategies are needed to increase influenza coverage among at-risk categories. Active offer of influenza vaccine upon discharge can effectively increase vaccination compliance. • The adoption of correct behavioral habits and the promotion of vaccination by healthcare personnel play a decisive role in the influenza vaccine acceptance process among at risk people.

Gestational influenza A virus infection elicits nonresolving vascular dysfunction and T-cell accumulation in the aorta of mice.

T-cell accumulation within the aorta promotes endothelial dysfunction and the genesis of cardiovascular disease, including hypertension and atherosclerosis. Viral infection during pregnancy is also known to mediate marked acute endothelial dysfunction, but it is not clear whether T cells are recruited to the aorta and whether the dysfunction persists postpartum. Here, we demonstrate that influenza A virus (IAV) infection during pregnancy in a murine model resulted in endothelial dysfunction of the aorta, which persisted for up to 60 days postinfection and was associated with higher levels of IFN-γ mRNA expression within the tissue. In the absence of infection, low numbers of naïve CD4+ and CD8+ T cells, central memory T cells, and effector memory T cells were observed in the aorta. However, with IAV infection, these T-cell subsets were significantly increased with a notable accumulation of IAV-specific CD8+ effector memory T cells. Critically, this increase was maintained out to at least 60 days. In contrast, IAV infection in nonpregnant female mice resulted in modest endothelial dysfunction with no accumulation of T cells within the aorta. These data, therefore, demonstrate that the aorta is a site of T-cell recruitment and retention after IAV infection during pregnancy. Although IAV-specific memory T cells could theoretically confer protection against future influenza infection, nonspecific memory T-cell activation and IFN-γ production in the aorta could also contribute to future endothelial dysfunction and cardiovascular disease.NEW & NOTEWORTHY Pregnancy is a risk factor for cardiovascular complications to influenza A virus (IAV) infection. We demonstrate that gestational IAV infection caused endothelial dysfunction of the maternal aorta, which persisted for 60 days postinfection in mice. Various T cells accumulated within the aorta at 60 days because of the infection, and this was associated with elevated levels of the proinflammatory cytokine, IFN-γ. Our study demonstrates a novel "long influenza" cardiovascular phenotype in female mice.

A Recombinant Mosaic HAs Influenza Vaccine Elicits Broad-Spectrum Immune Response and Protection of Influenza a Viruses.

The annual co-circulation of two influenza A subtypes, H1N1 and H3N2, viruses in humans poses significant public health threats worldwide. However, the continuous antigenic drift and shift of influenza viruses limited the effectiveness of current seasonal influenza vaccines, necessitating the development of new vaccines against both seasonal and pandemic viruses. One potential solution to this challenge is to improve inactivated vaccines by including multiple T-cell epitopes. In this study, we designed stabilized trimeric recombinant mosaic HA proteins named HAm, which contain the most potential HA T-cell epitopes of seasonal influenza A virus. We further evaluated the antigenicity, hemagglutinin activity, and structural integrity of HAm and compared its immunogenicity and efficacy to a commercial quadrivalent inactivated influenza vaccine (QIV) in mice. Our results demonstrated that the HAm vaccine was able to induce broadly cross-reactive antibodies and T-cell responses against homologous, heterologous, and heterosubtypic influenza-naive mice. Additionally, the HAm antigens outperformed QIV vaccine antigens by eliciting protective antibodies against panels of antigenically drifted influenza vaccine strains from 2009 to 2024 and protecting against ancestral viruses' lethal challenge. These results suggest that the HAm vaccine is a promising potential candidate for future universal seasonal and pandemic influenza vaccine development.

Enhancing NA immunogenicity through novel VLP designs.

Current influenza virus vaccines poorly display key neuraminidase (NA) epitopes and do not robustly induce NA-reactive antibodies; instead, they focus on the induction of hemagglutinin (HA)-reactive antibodies. Next-generation influenza vaccines should be optimized in order to activate NA-reactive B cells and to induce a broadly cross-reactive and protective antibody response. We aimed at enhancing the immunogenicity of the NA on vaccines by two strategies: (i) modifying the HA:NA ratio of the vaccine preparation and (ii) exposing epitopes on the lateral surface or beneath the head of the NA by extending the NA stalk. The H1N1 glycoproteins from the influenza virus A/California/04/2009 strain were displayed on human immunodeficiency virus 1 (HIV-1) gag-based virus-like particles (VLP). Using the baculovirus insect cell expression system, we biased the quantity of surface glycoproteins employing two different promoters, the very late baculovirus p10 promoter and the early and late gp64 promoter. This led to a 1:1 to 2:1 HA:NA ratio, which was approximately double or triple the amount of NA as present on the wild-type influenza A virus (HA:NA ratio 3:1 to 5:1). Furthermore, by insertion of 15 amino acids from the A-New York/61/2012 strain (NY12) which prolongates the NA stalk (NA long stalk; NA-LS), we intended to improve the accessibility of the NA. Six different types of VLPs were produced and purified using a platform downstream process based on Capto-Core 700™ followed by Capto-Heparin™ affinity chromatography combined with ultracentrifugation. These VLPs were then tested in a mouse model. Robust titers of antibodies that inhibit the neuraminidase activity were elicited even after vaccination with two low doses (0.3 μg) of the H1N1 VLPs without compromising the anti-HA responses. In conclusion, our results demonstrate the feasibility of the two developed strategies to retain HA immunogenicity and improve NA immunogenicity as a future influenza vaccine candidate.

Disulfide-stabilized trimeric hemagglutinin ectodomains provide enhanced heterologous influenza protection

ABSTRACT Influenza virus infection poses a continual menace to public health. Here, we developed soluble trimeric HA ectodomain vaccines by establishing interprotomer disulfide bonds in the stem region, which effectively preserve the native antigenicity of stem epitopes. The stable trimeric H1 ectodomain proteins exhibited higher thermal stabilities in comparison with unmodified HAs and showed strong binding activities towards a panel of anti-stem cross-reactive antibodies that recognize either interprotomer or intraprotomer epitopes. Negative stain transmission electron microscopy (TEM) analysis revealed the stable trimer architecture of the interprotomer disulfide-stapled WA11#5, NC99#2, and FLD#1 proteins as well as the irregular aggregation of unmodified HA molecules. Immunizations of mice with those trimeric HA ectodomain vaccines formulated with incomplete Freund’s adjuvant elicited significantly more potent cross-neutralizing antibody responses and offered broader immuno-protection against lethal infections with heterologous influenza strains compared to unmodified HA proteins. Additionally, the findings of our study indicate that elevated levels of HA stem-specific antibody responses correlate with strengthened cross-protections. Our design strategy has proven effective in trimerizing HA ectodomains derived from both influenza A and B viruses, thereby providing a valuable reference for designing future influenza HA immunogens.

Integrating Genomic, Climatic, and Immunological Factors to Analyze Seasonal Patterns of Influenza Variants

Influenza, often referred to as the flu, is an extremely contagious respiratory illness caused by influenza viruses, impacting populations globally with significant health consequences annually. A hallmark of influenza is its seasonal patterns, influenced by a mix of geographic, evolutionary, immunological, and environmental factors. Understanding these seasonal trends is crucial for informing public health decisions, including the planning of vaccination campaigns and their formulation. In our study, we introduce a genotype-structured infectious disease model for influenza transmission, immunity, and evolution. In this model, the population of infected individuals is structured according to the virus they harbor. It considers a symmetrical fitness landscape where the influenza A and B variants are considered. The model incorporates the effects of population immunity, climate, and epidemic heterogeneity, which makes it suitable for investigating influenza seasonal dynamics. We parameterize the model to the genomic surveillance data of flu in the US and use numerical simulations to elucidate the scenarios that result in the alternating or consecutive prevalence of flu variants. We show that the speed of virus evolution determines the alternation and co-circulation patterns of seasonal influenza. Our simulations indicate that slow immune waning reduces how often variants change, while cross-immunity regulates the co-circulation of variants. The framework can be used to predict the composition of future influenza outbreaks and guide the development of cocktail vaccines and antivirals that mitigate influenza in both the short and long term.

Assessing population-level target product profiles of universal human influenza A vaccines

Influenza A has two hemagglutinin groups, with stronger cross-immunity to reinfection within than between groups. Here, we explore the implications of this heterogeneity for proposed cross-protective influenza vaccines that may offer broad, but not universal, protection. While the development goal for the breadth of human influenza A vaccine is to provide cross-group protection, vaccines in current development stages may provide better protection against target groups than non-target groups. To evaluate vaccine formulation and strategies, we propose a novel perspective: a vaccine population-level target product profile (PTPP). Under this perspective, we use dynamical models to quantify the epidemiological impacts of future influenza A vaccines as a function of their properties. Our results show that the interplay of natural and vaccine-induced immunity could strongly affect seasonal subtype dynamics. A broadly protective bivalent vaccine could lower the incidence of both groups and achieve elimination with sufficient vaccination coverage. However, a univalent vaccine at low vaccination rates could permit a resurgence of the non-target group when the vaccine provides weaker immunity than natural infection. Moreover, as a proxy for pandemic simulation, we analyze the invasion of a variant that evades natural immunity. We find that a future vaccine providing sufficiently broad and long-lived cross-group protection at a sufficiently high vaccination rate, could prevent pandemic emergence and lower the pandemic burden. This study highlights that as well as effectiveness, breadth and duration should be considered in epidemiologically informed TPPs for future human influenza A vaccines.

Knowledge, attitudes, and practices associated with influenza vaccine uptake among healthcare personnel in Israel during three influenza seasons, 2016–2019

IntroductionDespite a longstanding Israel Ministry of Health recommendation that all healthcare personnel (HCP) receive a seasonal influenza vaccine, vaccine uptake among HCP remains below the country’s target of 60% coverage. To understand factors related to vaccine hesitancy, we used data from a prospective three-year (2016–2019) influenza vaccine effectiveness study among Israeli HCP to examine knowledge, attitudes, and practices (KAP) about influenza vaccination and their association with vaccine uptake. MethodsAt the start of each influenza season, all participating HCP completed a questionnaire that included questions about socio-demographic and occupational characteristics, health status, and KAP related to seasonal influenza vaccination. We extracted vaccination history from electronic medical records and employee vaccination registries. We used logistic regression models to identify demographic and occupational factors, and KAP about influenza vaccination, associated with receipt of vaccination. ResultA total of 2,126 HCP were enrolled and had available data on vaccination history. Their median age was 42 years [IQR 35–52], and 73 % self-identified as female. Influenza vaccine uptake in 2016, 2017 and 2018 was 46 %, 48 % and 47 %, respectively. Overall, 36 % of HCP had received an influenza vaccine in ≥ 4 of the eight years prior. HCP aged 35–49 years were less likely to receive influenza vaccine compared to HCP aged ≥ 50 years (OR: 0.81 [95 % CI: 0.67–0.98]). Nurses and allied personnel were less likely to receive influenza vaccine compared to physicians (OR: 0.63 [95 % CI: 0.50–0.78] and OR: 0.53 [95 % CI: 0.40–0.70], respectively). The emotional benefit of vaccination (e.g., anticipating regret if not vaccinated) and the perception of vaccine safety were factors associated with vaccine uptake (OR: 7.60 [95 % CI: 6.27–9.22] and OR: 3.43 [95 % CI:2.91–4.03], respectively). ConclusionAmong HCP at two hospitals in Israel, less than half received an annual influenza vaccine. Older HCP, physicians, and those who reported the emotional benefit of vaccination or agreed that influenza vaccines are safe were more likely to be vaccinated. Future influenza vaccination campaigns could focus on these demographic groups and tailor messages emphasizing the emotional benefits of vaccination and vaccine safety to increase seasonal influenza vaccine uptake among HCP in Israel.

Neutralizing antibody responses against contemporary and future influenza A(H3N2) viruses in paradoxical clades elicited by repeated and single vaccinations.

As one of the most effective measures to prevent seasonal influenza viruses, annual influenza vaccination is globally recommended. Nevertheless, evidence regarding the impact of repeated vaccination to contemporary and future influenza has been inconclusive. A total of 100 subjects singly or repeatedly immunized with influenza vaccines including 3C.2a1 or 3C.3a1 A(H3N2) during 2018-2019 and 2019-2020 influenza season were recruited. We investigated neutralization antibody by microneutralization assay using four antigenically distinct A(H3N2) viruses circulating from 2018 to 2023, and tracked the dynamics of B cell receptor (BCR) repertoire for consecutive vaccinations. We found that vaccination elicited cross-reactive antibody responses against future emerging strains. Broader neutralizing antibodies to A(H3N2) viruses and more diverse BCR repertoires were observed in the repeated vaccination. Meanwhile, a higher frequency of BCR sequences shared among the repeated-vaccinated individuals with consistently boosting antibody response was found than those with a reduced antibody response. Our findings suggest that repeated seasonal vaccination could broaden the breadth of antibody responses, which may improve vaccine protection against future emerging viruses.

Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models

BackgroundInfluenza is a highly contagious respiratory disease that presents a significant challenge to public health globally. Therefore, effective influenza prediction and prevention are crucial for the timely allocation of resources, the development of vaccine strategies, and the implementation of targeted public health interventions.MethodIn this study, we utilized historical influenza case data from January 2013 to December 2021 in Fuzhou to develop four regression prediction models: SARIMA, Prophet, Holt-Winters, and XGBoost models. Their predicted performance was assessed by using influenza data from the period from January 2022 to December 2022 in Fuzhou. These models were used for fitting and prediction analysis. The evaluation metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were employed to compare the performance of these models.ResultsThe results indicate that the epidemic of influenza in Fuzhou exhibits a distinct seasonal and cyclical pattern. The influenza cases data displayed a noticeable upward trend and significant fluctuations. In our study, we employed SARIMA, Prophet, Holt-Winters, and XGBoost models to predict influenza outbreaks in Fuzhou. Among these models, the XGBoost model demonstrated the best performance on both the training and test sets, yielding the lowest values for MSE, RMSE, and MAE among the four models.ConclusionThe utilization of the XGBoost model significantly enhances the prediction accuracy of influenza in Fuzhou. This study makes a valuable contribution to the field of influenza prediction and provides substantial support for future influenza response efforts.

A combination influenza mRNA vaccine candidate provided broad protection against diverse influenza virus challenge

Influenza viruses present a significant threat to global health. The production of a universal vaccine is considered essential due to the ineffectiveness of current seasonal influenza vaccines against mutant strains. mRNA technology offers new prospects in vaccinology, with various candidates for different infectious diseases currently in development and testing phases. In this study, we encapsulated a universal influenza mRNA vaccine. The vaccine encoded influenza hemagglutinin (HA), nucleoprotein (NP), and three tandem repeats of matrix protein 2 (3M2e). Twice-vaccinated mice exhibited strong humoral and cell-mediated immune responses in vivo. Notably, these immune responses led to a significant reduction in viral load of the lungs in challenged mice, and also conferred protection against future wild-type H1N1, H3N2, or H5N1 influenza virus challenges. Our findings suggest that this mRNA-universal vaccine strategy for influenza virus may be instrumental in mitigating the impact of future influenza pandemics.

Mammalian adaptation risk in HPAI H5N8: a comprehensive model bridging experimental data with mathematical insights

ABSTRACT Understanding the mammalian pathogenesis and interspecies transmission of HPAI H5N8 virus hinges on mapping its adaptive markers. We used deep sequencing to track these markers over five passages in murine lung tissue. Subsequently, we evaluated the growth, selection, and RNA load of eight recombinant viruses with mammalian adaptive markers. By leveraging an integrated non-linear regression model, we quantitatively determined the influence of these markers on growth, adaptation, and RNA expression in mammalian hosts. Furthermore, our findings revealed that the interplay of these markers can lead to synergistic, additive, or antagonistic effects when combined. The elucidation distance method then transformed these results into distinct values, facilitating the derivation of a risk score for each marker. In vivo tests affirmed the accuracy of scores. As more mutations were incorporated, the overall risk score of virus heightened, and the optimal interplay between markers became essential for risk augmentation. Our study provides a robust model to assess risk from adaptive markers of HPAI H5N8, guiding strategies against future influenza threats.

Insights from Avian Influenza: A Review of Its Multifaceted Nature and Future Pandemic Preparedness.

Avian influenza viruses (AIVs) have posed a significant pandemic threat since their discovery. This review mainly focuses on the epidemiology, virology, pathogenesis, and treatments of avian influenza viruses. We delve into the global spread, past pandemics, clinical symptoms, severity, and immune response related to AIVs. The review also discusses various control measures, including antiviral drugs, vaccines, and potential future directions in influenza treatment and prevention. Lastly, by summarizing the insights from previous pandemic control, this review aims to direct effective strategies for managing future influenza pandemics.

White blood cells scattergram as a valuable tool for COVID-19 screening: A multicentric study.

New tools have been developed to distinguish the COVID-19 diagnosis from other viral infections presenting similar symptomatology and mitigate the lack of sensitivity of molecular testing. We previously identified a specific "sandglass" aspect on the white blood cells (WBC) scattergram of COVID-19 patients, as a highly reliable COVID-19 screening test (sensitivity: 85.9%, specificity: 83.5% and positive predictive value: 94.3%). We then decided to validate our previous data in a multicentric study. This retrospective study involved 817 patients with flu-like illness, among 20 centers, using the same CBC instrument (XN analyzer, SYSMEX, Japan). After training, one specialist per center independently evaluated, under the same conditions, the presence of the "sandglass" aspect of the WDF scattergram, likely representing plasmacytoid lymphocytes. Overall, this approach showed sensitivity: 59.0%, specificity: 72.9% and positive predictive value: 77.7%. Sensitivity improved with subgroup analysis, including in patients with lymphopenia (65.2%), patients presenting symptoms for more than 5 days (72.3%) and in patients with ARDS (70.1%). COVID-19 patients with larger plasmacytoid lymphocyte cluster (>15 cells) more often have severe outcomes (70% vs. 15% in the control group). Our findings confirm that the WBC scattergram analysis could be added to a diagnostic algorithm for screening and quickly categorizing symptomatic patients as either COVID-19 probable or improbable, especially during COVID-19 resurgence and overlapping with future influenza epidemics. The observed large size of the plasmacytoid lymphocytes cluster appears to be a hallmark of COVID-19 patients and was indicative of a severe outcome. Furthers studies are ongoing to evaluate the value of the new hematological parameters in combination with WDF analysis.

Influenza A virus resistance to 4'-fluorouridine coincides with viral attenuation in vitro and in vivo.

Pre-existing or rapidly emerging resistance of influenza viruses to approved antivirals makes the development of novel therapeutics to mitigate seasonal influenza and improve preparedness against future influenza pandemics an urgent priority. We have recently identified the chain-terminating broad-spectrum nucleoside analog clinical candidate 4'-fluorouridine (4'-FlU) and demonstrated oral efficacy against seasonal, pandemic, and highly pathogenic avian influenza viruses in the mouse and ferret model. Here, we have resistance-profiled 4'-FlU against a pandemic A/CA/07/2009 (H1N1) (CA09). In vitro viral adaptation yielded six independently generated escape lineages with distinct mutations that mediated moderate resistance to 4'-FlU in the genetically controlled background of recombinant CA09 (recCA09). Mutations adhered to three distinct structural clusters that are all predicted to affect the geometry of the active site of the viral RNA-dependent RNA polymerase (RdRP) complex for phosphodiester bond formation. Escape could be achieved through an individual causal mutation, a combination of mutations acting additively, or mutations functioning synergistically. Fitness of all resistant variants was impaired in cell culture, and all were attenuated in the mouse model. Oral 4'-FlU administered at lowest-efficacious (2 mg/kg) or elevated (10 mg/kg) dose overcame moderate resistance when mice were inoculated with 10 LD50 units of parental or resistant recCA09, demonstrated by significantly reduced virus load and complete survival. In the ferret model, invasion of the lower respiratory tract by variants representing four adaptation lineages was impaired. Resistant variants were either transmission-incompetent, or spread to untreated sentinels was fully blocked by therapeutic treatment of source animals with 4'-FlU.

Multivalent next generation influenza virus vaccines protect against seasonal and pre-pandemic viruses

Each year, new influenza virus vaccine formulations are generated to keep up with continuously circulating and mutating viral variants. A next-generation influenza virus vaccine would provide long-lasting, broadly-reactive immune protection against current and future influenza virus strains for both seasonal and pre-pandemic viruses. Next generation immunogens were designed using computationally optimized broadly reactive antigen (COBRA) methodology to protect against a broad range of strains over numerous seasons. Novel HA and NA amino acid sequences were derived from multilayered consensus sequence alignment for multiple subtypes of influenza. This multivalent formulation was hypothesized to elicit broadly protective immune responses against both seasonal and pre-pandemic influenza viruses. Mice were vaccinated with multivalent mixtures of HA and NA (H1, H2, H3, H5, H7, N1, N2) proteins. Multivalent COBRA vaccinations elicited antibodies that recognized a broad panel of strains and vaccinated mice were protected against viruses representing multiple subtypes. This is a promising candidate for a universal influenza vaccine that elicits protective immune responses against seasonal and pre-pandemic strains over multiple seasons.