Control Of Influenza Research Articles

Challenges in Influenza Control and Surveillance in the Republic of Kazakhstan

The COVID-19 pandemic has significantly disrupted the circulation of influenza viruses in Kazakhstan, highlighting the vulnerabilities in the country’s public health infrastructure. This review critically examines the challenges faced in infiltrating and controlling influenza in Kazakhstan, particularly in light of the shifting epidemiological landscape post-pandemic. Key issues include the decline in influenza cases during the pandemic, which complicates the assessment of influenza epidemiology, vaccine effectiveness, and planning of vaccination campaigns. Although part of the Global Influenza Hospital Surveillance Network (GIHSN), Kazakhstan's surveillance systems face data collection, coordination, and public awareness gaps. The review discusses the prevalence of various influenza strains, the impact of zoonotic infections, and the necessity for improved monitoring frameworks. Additionally, the historical context of infectious disease control in Kazakhstan is explored, emphasising the need for enhanced international collaboration and targeted public health strategies. The findings underscore the importance of vaccination and robust surveillance to mitigate the risks of seasonal and pandemic influenza, advocating for a comprehensive approach to safeguard public health in Kazakhstan.

Epidemiology and population-based incidence of influenza in two communities, Bandung district, West Java, Indonesia, 2008–2011

Influenza surveillance is important for monitoring influenza virus circulation and disease burden to inform influenza prevention and control measures. The aim of this study was to describe the epidemiology and to estimate the incidence of influenza in two communities in West Java, Indonesia, before and after the 2009 H1N1 pandemic. A population-based surveillance study in the community health care setting was conducted to estimate the annual incidence of influenza. A real-time reverse transcription polymerase chain reaction (RT-PCR) assay was used for influenza case ascertainment. A population census was implemented to calculate the population at risk and estimate community health care utilization rate. The mean annual incidence of influenza A and B, adjusted for healthcare utilization, was 1.6 (95%CI: 1.3–2.0) and 0.7 (95%CI: 0.5–1.0) per 1000 persons, respectively, with the most affected group being young and school-age children. The annual cumulative incidence of influenza A for children under five in 2009, 2010, and 2011 was 7.0 (95%CI: 4.4–11.2), 10.6 (95%CI: 7.3–15.4), and 6.3 (95%CI: 3.8–10.2). For influenza B was 4.3 (95%CI: 2.4–7.8), 2.0 (95%CI: 0.8–4.7), and 0.4 (95%CI: 0.1–2.8), respectively. This study highlights that the incidence of influenza among young and school-age children is consistently higher compared to adults and the elderly throughout these periods. These populations are potential targets for influenza vaccination in Indonesia.

Recombinant avian-derived antiviral proteins cIFITM1, cIFITM3, and cViperin as effective adjuvants in inactivated H9N2 subtype avian influenza vaccines

Vaccine adjuvants, serving as non-specific immune enhancers, play a pivotal role in the immunoprevention and control of animal diseases. This study utilized prokaryotic expression systems to express and purify chicken-derived cIFITM1, cIFITM3, and cViperin, which were then formulated as adjuvants with H9N2 avian influenza virus antigens to create inactivated vaccines. These vaccines were administered to SPF chickens to investigate their immunopotentiating functions. Additionally, the proteins were assessed for their ability to act as standalone immune enhancers. The results demonstrated that cIFITM1, cIFITM3, and cViperin significantly elevated serum hemagglutination inhibition (HI) antibody titers. Notably, when used individually, these proteins markedly enhanced the antiviral capabilities of challenged chickens, leading to alleviated clinical symptoms, reduced tracheal virus replication, diminished virus shedding, and lessened histopathological damage, with cIFITM1 exhibiting the most pronounced effect. Furthermore, the protective efficacy of two H9N2 recombinant virus inactivated vaccines supplemented with cIFITM1 adjuvant was validated, achieving a 100 % vaccine protection efficiency. In conclusion, cIFITM1, cIFITM3, and cViperin as adjuvants for influenza vaccines effectively inhibit virus replication and shedding, highlighting their significant potential in influenza prevention and control.

Temperature variability and influenza incidence in China: Effect modification by ambient fine particulate matter

This study aims to examine the association between temperature variabilit (TV) exposure and influenza incidence in China, and the modification effect of PM2.5 levels. Data on daily influenza cases, weather conditions, and PM2.5 concentrations were collected from 339 cities across mainland China from 2014 to 2019. TV was computed as the standard deviation of daily maximum and minimum temperatures for the current day and the previous several days (i.e., TV0–1 to TV0–7). A space-time-stratified case-crossover design with conditional Poisson regression was employed. Overall, each 1 °C increase in TV0–6 was linked to 3.3 % (95 % CI: 3.1 %, 3.5 %) rise in influenza incidence, potentially attributing 14.73 % (95 % CI: 14.08 %, 15.37 %) of cases to this exposure. PM2.5 concentration showed substantial modification effect on the association, such that the relative risk (RR) of influenza incidence grew from 1.027 (95 % CI: 1.025, 1.029) to 1.040 (95 % CI: 1.038, 1.042) as PM2.5 levels increased from 15 to 75 μg/m³ . Females and individuals over 65 years old were more susceptible to TV exposure and the PM2.5 modification. Stronger effects were observed during cold season and in North region. The findings highlight the integrating considerations of TV and PM2.5 exposures into public health measures for influenza prevention and control.

Post-viral symptoms and conditions are more frequent in COVID-19 than influenza, but not more persistent

BackgroundPost-viral symptoms have long been known in the medical community but have received more public attention during the COVID-19 pandemic. Many post-viral symptoms were reported as particularly frequent after SARS-CoV-2 infection. However, there is still a lack of evidence regarding the specificity, frequency and persistence of these symptoms in comparison to other viral infectious diseases such as influenza.MethodsWe investigated a large population-based cohort based on German routine healthcare data. We matched 573,791 individuals with a PCR-test confirmed SARS-CoV-2 infection from the year 2020 to contemporary controls without SARS-CoV-2 infection and controls from the last influenza outbreak in 2018 and followed them up to 18 months.ResultsWe found that post-viral symptoms as defined for COVID-19 by the WHO as well as tissue damage were more frequent among the COVID-19 cohort than the influenza or contemporary control cohort. The persistence of post-viral symptoms was similar between COVID-19 and influenza.ConclusionPost-viral symptoms following SARS-CoV-2 infection constitute a substantial disease burden as they are frequent and often persist for many months. As COVID-19 is becoming endemic, the disease must not be trivialized. Research should focus on the development of effective treatments for post-viral symptoms.

Molecular epidemiology and vaccine compatibility analysis of seasonal influenza A viruses in the context of COVID-19 epidemic in Wuhan, China.

The COVID-19 pandemic had a significant impact on the global influenza vaccination and the epidemics of seasonal influenza. To further explore the molecular epidemiology of influenza viruses and assess vaccine effectiveness, we collected influenza cases in Wuhan during the 2022-2023 influenza season. Among 1312 clinical samples, 312 samples tested positive for influenza viruses using reverse transcription polymerase chain reaction. These positive samples included 146A/H1N1 subtypes (46.8%), 164A/H3N2 subtypes (52.6%) and 2 influenza B virus types (0.6%). Based on the whole genome sequence information of hemagglutinin (HA) and neuraminidase (NA) from 27A/H1N1 influenza virus strains and 26A/H3N2 influenza virus strains obtained in this study, a phylogenetic analysis was conducted. The analysis revealed that all A/H1N1 strains belonged to the evolutionary branch 6B.1A.5a.2a, and they exhibited specific substitutions at positions K71Q, Q206E, E241A, and R276K. Similarly, all A/H3N2 strains were classified into the 3C.2a1b.2a.1a subclade and displayed amino acid substitutions at positions S172H, N175Y, I176T, K187N, and S214P. Notably, the A/H3N2 strains also acquired a new potential glycosylation site at position N174. Using an epitope model, the predicted vaccine effectiveness was assessed for the A/H1N1 and A/H3N2 strains. The predicted vaccine effectiveness against the Wuhan influenza epidemic strain was over 85% for the A/H1N1 vaccine strain. However, the effectiveness against the A/H3N2 vaccine strain was only 48.7%. To further verify the protection of influenza vaccine against circulating influenza viruses in the region, we conducted in vivo and in vitro animal studies. The results of in vitro neutralization experiment showed that rabbit serum antibodies inoculated with quadrivalent isolated influenza vaccine had neutralization ability against all 24 isolated influenza viruses. In vivo experiments showed that vaccinated mice had fewer lung lesions when infected with the influenza strain circulating in Wuhan, suggesting that vaccination can effectively reduce the occurrence of severe lung damage. These findings emphasize the importance of accurately predicting seasonal influenza strains for effective influenza prevention and control, especially during the co-circulation of SARS-CoV-2 and influenza viruses. This study provides valuable information on the seasonal influenza virus in Wuhan during the COVID-19 pandemic and serves as a basis for vaccine prediction and updates.

Quantifying and Adjusting for Confounding From Health-Seeking Behavior and Health Care Access in Observational Research.

Health-seeking behavior and health care access (HSB/HCA) are recognized confounders in many observational studies but are not directly measurable in electronic health records. We used proxy markers of HSB/HCA to quantify and adjust for confounding in observational studies of influenza and COVID-19 vaccine effectiveness (VE). This cohort study used primary care data prelinked to secondary care and death data in England. We included individuals aged ≥66 years on 1 September 2019 and assessed influenza VE in the 2019-2020 season and early COVID-19 VE (December 2020-March 2021). VE was estimated with sequential adjustment for demographics, comorbidities, and 14 markers of HSB/HCA. Influenza vaccination in the 2019-2020 season was also considered a negative control exposure against COVID-19 before COVID-19 vaccine rollout. We included 1 991 284, 1 796 667, and 1 946 943 individuals in the influenza, COVID-19, and negative control exposure populations, respectively. Markers of HSB/HCA were positively correlated with influenza and COVID-19 vaccine uptake. For influenza, adjusting for HSB/HCA markers in addition to demographics and comorbidities increased VE against influenza-like illness from -1.5% (95% CI, -3.2% to .1%) to 7.1% (95% CI, 5.4%-8.7%) with a less apparent trend for more severe outcomes. For COVID-19, adjusting for HSB/HCA markers did not change VE estimates against infection or severe disease (eg, 2 doses of BNT162b2 against infection: 82.8% [95% CI, 78.4%-86.3%] to 83.1% [95% CI, 78.7%-86.5%]). Adjusting for HSB/HCA markers removed bias in the negative control exposure analysis (-7.5% [95% CI, -10.6% to -4.5%] vs -2.1% [95% CI, -6.0% to 1.7%] before vs after adjusting for HSB/HCA markers). Markers of HSB/HCA can be used to quantify and account for confounding in observational vaccine studies.

Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models.

Influenza is a respiratory infection that poses a significant health burden worldwide. Environmental indicators, such as air pollutants and meteorological factors, play a role in the onset and propagation of influenza. Accurate predictions of influenza incidence and understanding the factors influencing it are crucial for public health interventions. Our study aims to investigate the impact of various environmental indicators on influenza incidence and apply the ARIMAX model to integrate these exogenous variables to enhance the accuracy of influenza incidence predictions. Descriptive statistics and time series analysis were employed to illustrate changes in influenza incidence, air pollutants, and meteorological indicators. Cross correlation function (CCF) was used to evaluate the correlation between environmental indicators and the influenza incidence. We used ARIMA and ARIMAX models to perform predictive analysis of influenza incidence. From January 2014 to September 2023, a total of 21,573 cases of influenza were reported in Fuzhou, with a noticeable year-by-year increase in incidence. The peak of influenza typically occurred around January each year. The results of CCF analysis showed that all 10 environmental indicators had a significant impact on the incidence of influenza. The ARIMAX(0, 0, 1) (1, 0, 0)12 with PM10(lag5) model exhibited the best prediction performance, as indicated by the lowest AIC, AICc, and BIC values, which were 529.740, 530.360, and 542.910, respectively. The model achieved a fitting RMSE of 2.999 and a predicting RMSE of 12.033. This study provides insights into the impact of environmental indicators on influenza incidence in Fuzhou. The ARIMAX(0, 0, 1) (1, 0, 0)12 with PM10(lag5) model could provide a scientific basis for formulating influenza control policies and public health interventions. Timely prediction of influenza incidence is essential for effective epidemic control strategies and minimizing disease transmission risks.

CircRNA based multivalent neuraminidase vaccine induces broad protection against influenza viruses in mice

Developing broad-spectrum influenza vaccines is crucial for influenza control and potential pandemic preparedness. Here, we reported a novel vaccine design utilizing circular RNA (circRNA) as a delivery platform for multi-subtype neuraminidases (NA) (influenza A N1, N2, and influenza B Victoria lineage NA) immunogens. Individual NA circRNA lipid nanoparticles (LNP) elicited robust NA-specific antibody responses with neuraminidase inhibition activity (NAI), preventing the virus from egressing and infecting neighboring cells. Additionally, the administration of circRNA LNP induced cellular immunity in mice. To achieve a universal influenza vaccine, we combined all three subtypes of NA circRNA-LNPs to generate a trivalent circRNA vaccine. The trivalent vaccine elicited a balanced antibody response against all three NA subtypes and a Th1-biased immune response in mice. Moreover, it protected mice against the lethal challenge of matched and mismatched H1N1, H3N2, and influenza B viruses, encompassing circulating and ancestral influenza virus strains. This study highlights the potential of delivering multiple NA antigens through circRNA-LNPs as a promising strategy for effectively developing a universal influenza vaccine against diverse influenza viruses.

Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.202, p < 0.01). Global spatial autocorrelation analysis indicated significant positive spatial autocorrelation in influenza incidence rates from 2016 and from 2018 to 2023 (Moran’s I > 0, P < 0.05). Local spatial autocorrelation analysis further revealed clustering patterns in different regions, with high-high clustering and low-high clustering predominating in northern Xinjiang, and low-low clustering predominating in southern Xinjiang. Hotspot analysis indicated a progressive rise in the number of influenza incidence hotspots, primarily concentrated in northern Xinjiang, particularly in Urumqi, Ili Kazakh Autonomous Prefecture, and Hotan Prefecture. Standard deviation ellipse analysis and the trajectory of influenza incidence gravity center migration showed that the transmission range of influenza in Xinjiang has been expanding, with the epidemic center gradually moving northward. The spatiotemporal heterogeneity of influenza incidence in Xinjiang highlights the need for differentiated and precise influenza prevention and control strategies in different regions to address the changing trends in influenza prevalence.

Digital Gamification Tool (Let's Control Flu) to Increase Vaccination Coverage Rates: Proposal for Algorithm Development.

Influenza represents a critical public health challenge, disproportionately affecting at-risk populations, including older adults and those with chronic conditions, often compounded by socioeconomic factors. Innovative strategies, such as gamification, are essential for augmenting risk communication and community engagement efforts to address this threat. This study aims to introduce the "Let's Control Flu" (LCF) tool, a gamified, interactive platform aimed at simulating the impact of various public health policies (PHPs) on influenza vaccination coverage rates and health outcomes. The tool aligns with the World Health Organization's goal of achieving a 75% influenza vaccination rate by 2030, facilitating strategic decision-making to enhance vaccination uptake. The LCF tool integrates a selection of 13 PHPs from an initial set proposed in another study, targeting specific population groups to evaluate 7 key health outcomes. A prioritization mechanism accounts for societal resistance and the synergistic effects of PHPs, projecting the potential policy impacts from 2022 to 2031. This methodology enables users to assess how PHPs could influence public health strategies within distinct target groups. The LCF project began in February 2021 and is scheduled to end in December 2024. The model creation phase and its application to the pilot country, Sweden, took place between May 2021 and May 2023, with subsequent application to other European countries. The pilot phase demonstrated the tool's potential, indicating a promising increase in the national influenza vaccination coverage rate, with uniform improvements across all targeted demographic groups. These initial findings highlight the tool's capacity to model the effects of PHPs on improving vaccination rates and mitigating the health impact of influenza. By incorporating gamification into the analysis of PHPs, the LCF tool offers an innovative and accessible approach to supporting health decision makers and patient advocacy groups. It enhances the comprehension of policy impacts, promoting more effective influenza prevention and control strategies. This paper underscores the critical need for adaptable and engaging tools in PHP planning and implementation. RR1-10.2196/55613.

Research on influenza epidemic and clinical characteristics based on influenza research database.

To compare the epidemic trends of different types of influenza viruses and the clinical characteristics of patients, so as to provide reference for influenza prevention and control. This was descriptive research. The human monitoring data collected from the Influenza Research Database (IRD) from 2006 to 2016 were used to descriptively analyze the distribution of influenza viruses in terms of time, geography, gender and age. The positive samples were divided into three groups based on the type of pathogen (H1N1 influenza A viruses, H3N2 influenza A viruses, and influenza B viruses). Compared and analyzed the distribution and clinical characteristics among groups. There were statistically significant differences in the positive rates among different countries (p< 0.001). The proportion of positive samples gradually decreased with age. The proportion of oseltamivir resistance was significantly higher in H1N1-positive patients compared with that in H3N2-positive patients (p< 0.001). Significant differences were observed in the vaccination status among H1N1, H3N2 and influenza B viruses (p< 0.001). Cough was common in all cases with H1N1, H3N2 and influenza B infections, while cough, fever and running nose occurred more frequently in influenza B-positive cases than those of H1N1-positive and H3N2-positive cases (p< 0.001). People aged 0-18 years are the major susceptible population to influenza, and H1N1 influenza viruses are the main pathogens of infection in this population, with major clinical manifestations of fever, cough and headache. The findings in this study highlight the necessity to strengthen the protection for this age group in clinical practice.

Influenza A Vaccine Candidates Based on Virus-like Particles Formed by Coat Proteins of Single-Stranded RNA Phages Beihai32 and PQ465.

Efficient control of influenza A infection can potentially be achieved through the development of broad-spectrum recombinant vaccines based on conserved antigens. The extracellular domain of the transmembrane protein M2 of influenza A virus (M2e) is highly conserved but poorly immunogenic and needs to be fused to an adjuvant protein or carrier virus-like particles (VLPs) to increase immunogenicity and provide protection against infection. In this study, we obtained VLPs based on capsid proteins (CPs) of single-stranded RNA phages Beihai32 and PQ465 bearing the M2e peptides. Four copies of the M2e peptide were linked to the C-terminus of the CP of phage Beihai32 and to the N and C termini of the CP of phage PQ465. The hybrid proteins, being expressed in Escherichia coli, formed spherical VLPs of about 30 nm in size. Immunogold transmission electron microscopy showed that VLPs formed by the phage PQ465 CP with a C-terminal M2e fusion present the M2e peptide on the surface. Subcutaneous immunization of mice with VLPs formed by both CPs containing four copies of the M2e peptide at the C termini induced high levels of M2e-specific IgG antibodies in serum and provided mice with protection against lethal influenza A virus challenge. In the case of an N-terminal fusion of M2e with the phage PQ465 CP, the immune response against M2e was significantly lower. CPs of phages Beihai32 and PQ465, containing four copies of the M2e peptide at their C termini, can be used to develop recombinant influenza A vaccine.

Financial impact of low pathogenic avian influenza virus subtype H9N2 on commercial broiler chicken and egg layer production systems in Pakistan

Low Pathogenic Avian Influenza (LPAI) subtype H9N2 is endemic in Pakistan and impacts poultry farming through disease related mortality, poor weight gain and reduced egg production. This study aims to estimate the farm-level financial impact of LPAI H9N2 infection on commercial broiler and layer production systems in Pakistan.A questionnaire based cross-sectional survey of 138 broiler farms and 136 layer farms in Pakistan was conducted in 2019. Primary data collected by cross-sectional survey along with expert opinion and published literature were used to parameterize five stochastic production and gross margin models for three broiler and two layer production systems: fully integrated production (FIP), partially integrated production (PIP) and independent farming production (IP) systems. Partial budget analysis were then carried out to estimate the financial impact of LPAI H9N2.Results indicate that in broiler production systems, starting with 35,000 day old chicks (DOC) per batch, the net cost of disease (million PKR/production cycle) was estimated at 4.10 (14,862 USD), 4.62 (16,747 USD) and 2.46 (8917 USD) for IP, PIP and FIP systems, respectively. The disease produced a negative gross margin (defined here as revenue minus replacement and variable costs) in IP (-53 PKR (-0.19 USD)/DOC bought) and PI (-25 PKR (-0.091 USD)/DOC bought) systems, while remained positive for FIP systems (87 PKR (0.32 USD)/DOC bought). For layer production systems, (mean flock size as 48,000 DOCs) the net cost (million PKR/production cycle) was 29.75 (107,095.21 USD) and 29.51 (106,223.45 USD) IP and PIP systems, respectively, and produced negative gross margin in both systems.The outcomes of the study highlight the vulnerability of independent and partially integrated production systems to the disease. These findings also offer a decision-making tool to the farmers and policy makers to evaluate avian influenza surveillance systems and control interventions in Pakistan.

Mechanistic Models of Influenza Transmission in Commercial Swine Populations: A Systematic Review.

Influenza in commercial swine populations leads to reduced gain in fattening pigs and reproductive issues in sows. This literature review aims to analyze the contributions of mathematical modeling in understanding influenza transmission and control among domestic swine. Twenty-two full-text research articles from seven databases were reviewed, categorized into swine-only (n = 13), swine-avian (n = 3), and swine-human models (n = 6). Strains of influenza models were limited to H1N1 (n = 7) and H3N2 (n = 1), with many studies generalizing the disease as influenza A. Half of the studies (n = 14) considered at least one control strategy, with vaccination being the primary investigated strategy. Vaccination was shown to reduce disease prevalence in single animal cohorts. With a continuous flow of new susceptible animals, such as in farrow-to-finish farms, it was shown that influenza became endemic despite vaccination strategies such as mass or batch-to-batch vaccination. Human vaccination was shown to be effective at mitigating human-to-human influenza transmission and to reduce spillover events from pigs. Current control strategies cannot stop influenza in livestock or prevent viral reassortment in swine, so mechanistic models are crucial for developing and testing new biosecurity measures to prevent future swine pandemics.

Prevention and Control of Seasonal Influenza with Vaccines: Recommendations of the Advisory Committee on Immunization Practices - United States, 2024-25 Influenza Season.

This report updates the 2023-24 recommendations of the Advisory Committee on Immunization Practices (ACIP) concerning the use of seasonal influenza vaccines in the United States (MMWR Recomm Rep 2022;72[No. RR-2]:1-24). Routine annual influenza vaccination is recommended for all persons aged ≥6 months who do not have contraindications. Trivalent inactivated influenza vaccines (IIV3s), trivalent recombinant influenza vaccine (RIV3), and trivalent live attenuated influenza vaccine (LAIV3) are expected to be available. All persons should receive an age-appropriate influenza vaccine (i.e., one approved for their age), with the exception that solid organ transplant recipients aged 18 through 64 years who are receiving immunosuppressive medication regimens may receive either high-dose inactivated influenza vaccine (HD-IIV3) or adjuvanted inactivated influenza vaccine (aIIV3) as acceptable options (without a preference over other age-appropriate IIV3s or RIV3). Except for vaccination for adults aged ≥65 years, ACIP makes no preferential recommendation for a specific vaccine when more than one licensed and recommended vaccine is available. ACIP recommends that adults aged ≥65 years preferentially receive any one of the following higher dose or adjuvanted influenza vaccines: trivalent high-dose inactivated influenza vaccine (HD-IIV3), trivalent recombinant influenza vaccine (RIV3), or trivalent adjuvanted inactivated influenza vaccine (aIIV3). If none of these three vaccines is available at an opportunity for vaccine administration, then any other age-appropriate influenza vaccine should be used.Primary updates to this report include the following two topics: the composition of 2024-25 U.S. seasonal influenza vaccines and updated recommendations for vaccination of adult solid organ transplant recipients. First, following a period of no confirmed detections of wild-type influenza B/Yamagata lineage viruses in global surveillance since March 2020, 2024-25 U.S. influenza vaccines will not include an influenza B/Yamagata component. All influenza vaccines available in the United States during the 2024-25 season will be trivalent vaccines containing hemagglutinin derived from 1) an influenza A/Victoria/4897/2022 (H1N1)pdm09-like virus (for egg-based vaccines) or an influenza A/Wisconsin/67/2022 (H1N1)pdm09-like virus (for cell culture-based and recombinant vaccines); 2) an influenza A/Thailand/8/2022 (H3N2)-like virus (for egg-based vaccines) or an influenza A/Massachusetts/18/2022 (H3N2)-like virus (for cell culture-based and recombinant vaccines); and 3) an influenza B/Austria/1359417/2021 (Victoria lineage)-like virus. Second, recommendations for vaccination of adult solid organ transplant recipients have been updated to include HD-IIV3 and aIIV3 as acceptable options for solid organ transplant recipients aged 18 through 64 years who are receiving immunosuppressive medication regimens (without a preference over other age-appropriate IIV3s or RIV3).This report focuses on recommendations for the use of vaccines for the prevention and control of seasonal influenza during the 2024-25 influenza season in the United States. A brief summary of the recommendations and a link to the most recent Background Document containing additional information are available at https://www.cdc.gov/acip-recs/hcp/vaccine-specific/flu.html?CDC_AAref_Val=https://www.cdc.gov/vaccines/hcp/acip-recs/vacc-specific/flu.html. These recommendations apply to U.S.-licensed influenza vaccines. Updates and other information are available from CDC's influenza website (https://www.cdc.gov/flu). Vaccination and health care providers should check this site periodically for additional information.

Recommendations for Prevention and Control of Influenza in Children, 2024-2025: Technical Report.

This technical report accompanies the recommendations of the American Academy of Pediatrics for the routine use of influenza vaccine and antiviral medications in the prevention and treatment of influenza in children during the 2024 to 2025 season. The rationale for the American Academy of Pediatrics recommendation for annual influenza vaccination of all children without medical contraindications starting at 6 months of age is provided. Influenza vaccination is an important strategy for protecting children and the broader community against influenza. This technical report summarizes recent influenza seasons, morbidity and mortality in children, vaccine effectiveness, and vaccination coverage and provides detailed guidance on vaccine storage, administration, and implementation. The report also provides a brief background on inactivated (nonlive) and live attenuated influenza vaccines, available vaccines for the 2024-2025 influenza season, vaccination during pregnancy and breastfeeding, diagnostic testing for influenza, and antiviral medications for treatment and chemoprophylaxis. Strategies to promote vaccine uptake are emphasized.

Recommendations for Prevention and Control of Influenza in Children, 2024-2025: Policy Statement.

This statement updates the recommendations of the American Academy of Pediatrics for the routine use of influenza vaccines and antiviral medications in the prevention and treatment of influenza in children during the 2024-2025 influenza season. A detailed review of the evidence supporting these recommendations is published in the accompanying technical report (www.pediatrics.org/cgi/doi/10.1542/peds.2024-068508). The American Academy of Pediatrics recommends annual influenza vaccination of all children without medical contraindications starting at 6 months of age. Children are at risk for hospitalization and death from influenza. Influenza vaccination is an important strategy for protecting children and the broader community as well as reducing the overall burden of respiratory illnesses when other viruses are cocirculating. Any licensed influenza vaccine appropriate for age and health status can be administered, ideally as soon as possible in the season, without preference for one product or formulation over another. All licensed influenza vaccines for use in the United States are trivalent for the 2024-2025 influenza season. Antiviral treatment of influenza is recommended for children with suspected (eg, influenza-like illness [fever with either cough or sore throat]) or confirmed influenza who are hospitalized or have severe or progressive disease or have underlying conditions that increase their risk of complications of influenza, regardless of duration of illness. Antiviral treatment should be initiated as soon as possible. Antiviral treatment may be considered in the outpatient setting for symptomatic children who are not at high risk for influenza complications with suspected or confirmed influenza disease, if treatment can be initiated within 48 hours of illness onset. Antiviral treatment may also be considered for children with suspected or confirmed influenza disease whose siblings or household contacts either are younger than 6 months or have a high-risk condition that predisposes them to complications of influenza. Antiviral chemoprophylaxis is recommended for the prevention of influenza virus infection as an adjunct to vaccination in certain individuals, especially exposed children who are asymptomatic and are at high risk for influenza complications but have not yet been immunized or those who are not expected to mount an effective immune response.

Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model

BackgroundInfluenza, an acute infectious respiratory disease, presents a significant global health challenge. Accurate prediction of influenza activity is crucial for reducing its impact. Therefore, this study seeks to develop a hybrid Convolution Neural Network—Long Short Term Memory neural network (CNN-LSTM) model to forecast the percentage of influenza-like-illness (ILI) rate in Hebei Province, China. The aim is to provide more precise guidance for influenza prevention and control measures.MethodsUsing ILI% data from 28 national sentinel hospitals in the Hebei Province, spanning from 2010 to 2022, we employed the Python deep learning framework PyTorch to develop the CNN-LSTM model. Additionally, we utilized R and Python to develop four other models commonly used for predicting infectious diseases. After constructing the models, we employed these models to make retrospective predictions, and compared each model’s prediction performance using mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and other evaluation metrics.ResultsBased on historical ILI% data from 28 national sentinel hospitals in Hebei Province, the Seasonal Auto-Regressive Indagate Moving Average (SARIMA), Extreme Gradient Boosting (XGBoost), Convolution Neural Network (CNN), Long Short Term Memory neural network (LSTM) models were constructed. On the testing set, all models effectively predicted the ILI% trends. Subsequently, these models were used to forecast over different time spans. Across various forecasting periods, the CNN-LSTM model demonstrated the best predictive performance, followed by the XGBoost model, LSTM model, CNN model, and SARIMA model, which exhibited the least favorable performance.ConclusionThe hybrid CNN-LSTM model had better prediction performances than the SARIMA model, CNN model, LSTM model, and XGBoost model. This hybrid model could provide more accurate influenza activity projections in the Hebei Province.

The relative effectiveness of a high-dose quadrivalent influenza vaccine versus standard-dose quadrivalent influenza vaccines in older adults in France: a retrospective cohort study during the 2021–2022 influenza season

ObjectivesHigh-dose quadrivalent influenza vaccine (HD-QIV) was introduced during the 2021/2022 influenza season in France for adults aged ≥65 years as an alternative to standard-dose quadrivalent influenza vaccine (SD-QIV). The aim of this study is to estimate the relative vaccine effectiveness of HD-QIV vs. SD-QIV against influenza-related hospitalizations in France. MethodsCommunity-dwelling individuals aged ≥65 years with reimbursed influenza vaccine claims during the 2021/2022 influenza season were included in the French national health insurance database. Individuals were followed up from vaccination day to 30 June 2022, nursing home admission or death date. Baseline socio-demographic and health characteristics were identified from medical records over the five previous years. Hospitalizations for influenza and other causes were recorded from 14 days after vaccination until the end of follow-up. HD-QIV and SD-QIV vaccinees were matched using 1:4 propensity score matching with an exact constraint on age group, sex, week of vaccination, and region. Incidence rate ratios were estimated using zero-inflated Poisson or zero-inflated negative binomial regression models. ResultsWe matched 405 385 HD-QIV to 1 621 540 SD-QIV vaccinees. HD-QIV was associated with a 23.3% (95% CI, 8.4–35.8) lower rate of influenza hospitalizations compared with SD-QIV (69.5/100 000 person years vs. 90.5/100 000 person years). Post-matching, we observed higher rates in the HD-QIV group for hospitalizations non-specific to influenza and negative control outcomes, suggesting residual confounding by indication. DiscussionHD-QIV was associated with lower influenza-related hospitalization rates vs. SD-QIV, consistent with existing evidence, in the context of high SARS-CoV-2 circulation in France and likely prioritization of HD-QIV for older/more comorbid individuals.