Influenza and Other Respiratory Viruses最新文献

{"title":"Improved Resolution of Influenza Vaccination Responses With High-Throughput Live Virus Microneutralisation","authors":"Lorin Adams,&nbsp;Phoebe Stevenson-Leggett,&nbsp;Jia Le Lee,&nbsp;James Bazire,&nbsp;Giulia Dowgier,&nbsp;Agnieszka Hobbs,&nbsp;Chloë Roustan,&nbsp;Annabel Borg,&nbsp;Christine Carr,&nbsp;Silvia Innocentin,&nbsp;Louise M. C. Webb,&nbsp;Callie Smith,&nbsp;Philip Bawumia,&nbsp;Nicola Lewis,&nbsp;Nicola O'Reilly,&nbsp;Svend Kjaer,&nbsp;Michelle A. Linterman,&nbsp;Ruth Harvey,&nbsp;Mary Y. Wu,&nbsp;Edward J. Carr","doi":"10.1111/irv.70140","DOIUrl":"https://doi.org/10.1111/irv.70140","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Influenza remains a significant threat to human and animal health. Assessing serological protection against influenza has relied upon haemagglutinin inhibition (HAI) assays, which are used to gauge existing immune landscapes, seasonal vaccine decisions and in systems vaccinology studies. HAI assays were first described in the 1940s. Here, we adapt our high-throughput live virus microneutralisation (LV-N) assay for SARS-CoV-2, benchmark against HAI assays, and report serological vaccine responsiveness in a cohort of older (&gt; 65 yo) community dwelling adults.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Influenza-specific antibody responses were assessed in 73 individuals, before and after receipt of the adjuvanted 2021–22 Northern Hemisphere quadrivalent vaccine. We performed both HAI and LV-N assays against all four viruses represented in the vaccine [A/Cambodia/e0826360/2020 (H3N2), IVR-215 (A/Victoria/2570/2019-like) (H1N1)pdm09, B/Phuket/3073/2013 (B/Yamagata lineage), B/Washington/02/2019 (B/Victoria lineage)], using sera drawn before vaccination [range: d-82 to d-5], and days 7 [d6–10] and 181 [d156–200] after vaccination. We compared serological responses within each assay and between assays.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Both the traditional HAI assay and our high-throughput live virus microneutralisation identified vaccine-induced boosts in antibody titres. We found population-level concordance between the two assays (Spearman's correlation coefficient range 0.49–0.88; all <i>p</i> ≤ 1.4 × 10⁻⁵). The improved granularity of microneutralisation was better able to estimate fold changes of responses and quantify the inhibitory effect of pre-existing antibody.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our high-throughput method offers an alternative approach to assess influenza-specific serological responses with improved resolution, with the potential to improve the annual assessment of existing antibody landscapes, to improve new vaccine strain evaluation, and to offer a step-change in systems vaccinology, and a facet of laboratory-based pandemic preparedness.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144843666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics of Adults With Non-Hospitalized Severe Respiratory Illness: Findings From a COVID-19 Vaccine Effectiveness Evaluation in Kenya, 2022–2023","authors":"Radhika Gharpure,&nbsp;Young M. Yoo,&nbsp;Bryan O. Nyawanda,&nbsp;Raphael O. Anyango,&nbsp;Brian O. Onyando,&nbsp;Sidney Ogolla,&nbsp;Billy Ogwel,&nbsp;Eric Osoro,&nbsp;Philip Ngere,&nbsp;Samuel Kadivane,&nbsp;Nzisa Liku,&nbsp;Eva Leidman,&nbsp;Gideon O. Emukule,&nbsp;Richard Omore,&nbsp;Kathryn E. Lafond","doi":"10.1111/irv.70145","DOIUrl":"https://doi.org/10.1111/irv.70145","url":null,"abstract":"<p>Studies suggest the burden of non-hospitalized severe respiratory illness might be substantial in Kenya. Using data from a Kenya COVID-19 vaccine effectiveness evaluation, we compared characteristics of patients aged ≥12 years who were hospitalized with severe respiratory illness to outpatients who were referred for hospitalization and declined (non-hospitalized). Symptom presentation and lung radiograph findings were similar among both groups, and patients in both were diagnosed with critical conditions, including acute respiratory distress syndrome (12% hospitalized; 4% non-hospitalized) and sepsis (10% both). Findings underscore the importance of including non-hospitalized severe illness when estimating the burden of disease for respiratory viruses.</p>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144782771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Rapid Isothermal Assay for Detection of Adenovirus Types Important in Respiratory Infections","authors":"Benedikt Beilstein,&nbsp;Iris Bachmann,&nbsp;Martin Spiegel,&nbsp;Frank T. Hufert,&nbsp;Gregory Dame","doi":"10.1111/irv.70142","DOIUrl":"https://doi.org/10.1111/irv.70142","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Nucleic acid amplification tests (NAATs) for human adenoviruses (HAdVs) causing respiratory infections usually target the hexon gene. However, new HAdV types with substantial variations in the hexon gene may not be detected. Thus, we focus on NAATs based on a conserved region in the penton gene to detect all HAdV types causing respiratory infections.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A highly conserved region at the 3′ end of the penton gene was chosen as a target for NAAT. Primers and probes for quantitative polymerase chain reaction (qPCR) and isothermal recombinase polymerase amplification (RPA) were designed for the detection of all HAdV types causing respiratory infections.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Two highly sensitive qPCR assays were established, one for the detection of HAdV-E4 and HAdV-B types and another for the detection of HAdV-C types (LOD &lt; 10 standard DNA copies for both assays). Furthermore, a one-tube RPA with a universal RPA probe was developed for rapid detection of all HAdV types causing respiratory infections (LOD ≤ 244 standard DNA copies). All three assays were used for testing clinical nasopharyngeal swabs obtained from SARS-CoV-2-negative children with respiratory disease symptoms. Eight out of 243 samples tested were found to be HAdV positive by qPCR and by one-tube RPA, except for one sample with a very low viral load of 30 genome equivalents.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Penton gene-based NAAT systems were developed and successfully used for the detection of HAdV in clinical samples. The newly developed one-tube RPA assay offers the possibility for rapid and simple detection of respiratory HAdV infections at the point of need.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance of International Travel of COVID-19 Cases (SuITCases) in England","authors":"Mary A. Sinnathamby,&nbsp;Katherine Twohig,&nbsp;Nurin Abdul Aziz,&nbsp;Florence Halford,&nbsp;Asad Zaidi,&nbsp;Katie Harman,&nbsp;Simon Thelwall,&nbsp;Alex Allen,&nbsp;Gavin Dabrera","doi":"10.1111/irv.70141","DOIUrl":"https://doi.org/10.1111/irv.70141","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The emergence of SARS-CoV-2 variants necessitated identification of travel-associated COVID-19 cases in England.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We implemented a novel integrated COVID-19-episode-level travel surveillance system, Surveillance of International COVID-19 Cases (SuITCases), to assign imported, sporadic or unknown travel status to COVID-19 cases, using data linkage between two enhanced and two routine data sources.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>SuITCases identified 517,988 travel-associated SARS-CoV-2 episodes (3.0% of total), where the two enhanced systems assigned most travel statuses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our unique system facilitated rapid identification of travel-associated COVID-19 cases, reducing transmission and informing public health actions. Enhanced surveillance data sources should be considered as potential tools for future outbreak investigations and pandemic preparedness.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"No Evidence of Novel Respiratory Viruses on Two Texas Dairy Farms Before the H5N1 Avian Influenza Virus Epizootic","authors":"Laura A. Pulscher,&nbsp;Lyudmyla V. Maruschak,&nbsp;Ismaila Shittu,&nbsp;Hisham Alsharif,&nbsp;Gregory C. Gray","doi":"10.1111/irv.70146","DOIUrl":"https://doi.org/10.1111/irv.70146","url":null,"abstract":"<p>Livestock intensification and modern farming practices, such as confinement and increased livestock densities, are thought to be strongly linked to zoonotic disease emergence and amplification [<span>1, 2</span>]. This may favor increased transmission, particularly to those working in close contact with livestock [<span>1</span>]. The recent introduction and spread of H5N1 avian influenza virus into dairy farms and dairy farm workers in early 2024 [<span>3</span>] highlights a need for surveillance of emerging zoonotic respiratory diseases at the cattle worker–cattle interface. In addition to influenza A viruses (IAV), influenza D virus [<span>4</span>] (IDV) and bovine coronaviruses [<span>5</span>] (BCoVs) are reservoired in cattle and may spill over into other animals, including sometimes to humans. For example, recent molecular and serological evidence suggests IDV may be spilling over into humans, specifically those with close contact to cattle [<span>6-8</span>]. Similarly, BCoVs have a large host range, and most notably, the seasonal human coronavirus, OC43-CoV, is thought to have originated from cattle, sharing a 96% global nucleotide identity with BCoV [<span>9</span>]. To this end, this one health-oriented study sought to determine IAV, IDV, and coronavirus transmission on dairy farms. We did so by prospectively collecting samples from cattle workers, their cattle, and the dairy farm environment to better understand the epidemiology and ecology of IAV, IDV, and coronaviruses.</p><p>From December 2022 to December 2023, we prospectively collected samples from 53 dairy workers, 60 dairy cows, 30 bioaerosol samples, and 22 dust samples from farm environments on two dairy operations in Texas. With farm owners' approval, dairy farms were visited every 3–4 months over the course of the study. After obtaining signed consent, nasal washes were collected from cattle workers by injecting 5 mL of sterile water into one nostril and collecting the expressed fluid. Participants also permitted the collection of up to 10 mL of whole blood. Within 12 h of collection, blood was spun down, and sera aliquoted and placed on ice. Nasal swabs were also collected from five cows at each encounter and up to three cows each month in-between encounters, prioritizing cows with signs of respiratory illness. Briefly, animal technicians on farms placed 6-in. polyester swabs into the nare of a cow and then placed the swab into 3 mL of viral transport media (Huachenyang [Shenzhen] Technology Co. Ltd. or Rocky Mountain Biologicals LLC) samples were placed on ice or shipped on cold packs to UTMB for analysis.</p><p>Environmental sampling, including bioaerosol and dust sampling, was also conducted at each farm encounter. National Institute for Occupational Safety and Health (NIOSH) <span>BC</span>251 multi-stage bioaerosol samplers were placed in four locations on each farm where humans and cows were in close contact or where sick cows were located. Samplers were placed ","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Framework for Evaluating the Use of Surveillance Systems for Short-Term Influenza Forecasting","authors":"Negin Maroufi,&nbsp;Lucy Telfar Barnard,&nbsp;Qiu Sue Huang,&nbsp;Gillian Dobbie,&nbsp;Nayyereh Aminisani,&nbsp;Steffen Albrecht,&nbsp;Nhung Nghiem,&nbsp;Michael G. Baker","doi":"10.1111/irv.70144","DOIUrl":"https://doi.org/10.1111/irv.70144","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Public health surveillance systems need to monitor influenza activity and guide measures to mitigate its high impact on morbidity, mortality and healthcare systems. There is an increasing expectation that surveillance data will support the modeling of future short-term disease scenarios using artificial intelligence (AI) and machine learning (ML). This study examines how influenza surveillance can support AI/ML-based short-term forecasting for influenza at the community and hospital levels in a high-income country setting (Aotearoa/New Zealand).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study used a two-phase approach. The first phase involved a comprehensive review of government reports, official websites, and literature to characterize existing influenza surveillance systems. The second phase evaluated systems against eight key attributes—timeliness, sensitivity, specificity, representativeness, coverage, robustness, completeness, and historical data—using a five-level ranking system. Attribute selection was informed by experts' knowledge, ML requirements, and established frameworks. Weighted scores for training and short-term forecasting capabilities were calculated to determine alignment with AI/ML requirements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS) community cohort and Severe Acute Respiratory Infection (SARI) hospital surveillance emerged as the most useful systems, achieving the highest scores in both training and short-term forecasting in community and hospital settings, respectively. The National Minimum Dataset of hospitalizations and mortality datasets demonstrated strong training potential but are limited in short-term forecasting due to timeliness constraints. Additionally, laboratory-based surveillance performs a useful role in bridging community and hospital datasets.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>A set of key attributes is useful for assessing which influenza surveillance systems are best aligned with AI/ML training and short-term forecasting requirements. These attributes distinguished systems that are likely to be the most suitable for modeling future short-term disease scenarios for influenza at the community and hospital levels in New Zealand. Integrating these data sources could enhance influenza forecasts to improve public health responses and intervention planning.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 8","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal Incidence of Human Metapneumovirus in High-Risk Adults With Medically Attended Acute Respiratory Illness in a Rural US Community","authors":"Maria E. Sundaram,&nbsp;David L. McClure,&nbsp;Oluwakemi D. Alonge,&nbsp;Jennifer P. King,&nbsp;Jennifer K. Meece,&nbsp;Huong Q. Nguyen","doi":"10.1111/irv.70119","DOIUrl":"https://doi.org/10.1111/irv.70119","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The burden of human metapneumovirus (hMPV) among community-dwelling high-risk adults is understudied. We calculate the cumulative incidence of outpatient hMPV in high-risk adults, over five consecutive winter respiratory virus seasons (2015–2016 through 2019–2020), and describe clinical characteristics of their illnesses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a retrospective analysis of data and respiratory specimens from adults ≥ 18 years old originally participating in a test-negative study of influenza vaccine effectiveness. We included adults with ≥ 1 high-risk condition in 2015–2016 through 2019–2020 seasons. Residual respiratory specimens were retested for hMPV using a multiplex viral panel. We calculated seasonal incidence using Poisson regression and population weighting, with the sum of observed and extrapolated hMPV cases in the study cohort divided by the number of adults with high-risk conditions in the underlying source population.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We tested 3601 respiratory samples; the mean (SD) age of individuals contributing samples was 53 (19) years. We identified 289 individuals (8.0%) with a respiratory sample positive for human metapneumovirus. The estimated seasonal incidence of outpatient hMPV-associated acute respiratory illness was 95.6 (95% CI: 80.5–113.4) cases per 10,000 high-risk adults. These values varied by season, with the highest incidence in 2015–2016 (276.8 cases per 10,000; 95% CI: 210.7–363.5) and lowest in 2016–17 (55.0 cases per 10,000; 95% CI: 31.2–97.0).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We identified substantial seasonal incidence of hMPV cases in community-dwelling high-risk adults in a Wisconsin population cohort.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 7","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transmission and Pathologic Findings of Divergent Human Seasonal H1N1pdm09 Influenza A Viruses Following Spillover Into Pigs in the United States","authors":"Giovana Ciacci Zanella,&nbsp;Alexey Markin,&nbsp;Megan Neveau Thomas,&nbsp;Celeste A. Snyder,&nbsp;Carine K. Souza,&nbsp;Bailey Arruda,&nbsp;Tavis K. Anderson,&nbsp;Amy L. Baker","doi":"10.1111/irv.70128","DOIUrl":"https://doi.org/10.1111/irv.70128","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The H1N1 pandemic (H1N1pdm09) lineage of influenza A viruses (IAV) emerged in North America in 2009. It spread rapidly due to efficient transmission and the limited immunity in humans, replacing the previous human seasonal H1. Human-to-swine transmission of H1N1pdm09 IAV has since contributed to genetic diversity in pigs. While most were not sustained, approximately 160 spillovers persisted in pigs in the United States for at least 1 year and reassorted with other endemic swine IAVs in most cases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We sought to identify how transmission and reassortment with endemic IAV in swine impact virus traits and zoonotic risk in this study. We conducted a swine pathogenesis and transmission study using four swine H1N1pdm09 viruses derived from different human influenza seasons that had acquired different gene segment combinations after spillovers into swine. To assess antigenic evolution, we compared the selected swine H1N1pdm09 strains against each other and to five human seasonal H1 vaccine strains.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Ongoing circulation and reassortment resulted in viruses with variable virulence, shedding, and transmission kinetics. The H1N1pdm09 viruses retained antigenic similarities with the human vaccine strain of the same season of incursion but showed increasing antigenic distances with human seasonal H1N1 vaccine strains from other seasons.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Human seasonal H1N1 viruses are capable of replicating and transmitting in swine, and there is potential for these human-to-swine spillovers to reassort with endemic swine IAV. Controlling IAV at the human-swine interface has the benefit of reducing IAV burden in swine and subsequent zoonotic risk.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 7","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influenza Vaccine Effectiveness in Australia During 2017–2019","authors":"Tanya Diefenbach-Elstob,&nbsp;Monique B. Chilver,&nbsp;Violeta Spirkoska,&nbsp;Kylie S. Carville,&nbsp;Clyde Dapat,&nbsp;Mark Turra,&nbsp;Thomas Tran,&nbsp;Yi-Mo Deng,&nbsp;Heidi Peck,&nbsp;Ian G. Barr,&nbsp;Nigel Stocks,&nbsp;Sheena G. Sullivan","doi":"10.1111/irv.70137","DOIUrl":"https://doi.org/10.1111/irv.70137","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Vaccine effectiveness (VE) estimates provide important post-marketing assessment of how well seasonal influenza vaccines prevent medically attended influenza disease. We present VE estimates for primary care in Australia for the 2017–2019 seasons.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study used a test-negative design. Influenza VE was estimated from adjusted logistic regression models comparing the odds of vaccination among influenza-test-positive cases and test-negative non-cases. Estimates were made overall and separately by influenza type, subtype, lineage and clade and stratified by age group. Antigenic similarity of influenza viruses to vaccine strains was assessed using the haemagglutination inhibition assay, and phylogenetic analysis was performed on sequenced viruses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study included 2879, 1973 and 3371 general practice patients with swabs collected during 2017, 2018 and 2019 respectively. Influenza A(H3N2) was predominant in 2017 and 2019, while influenza A(H1N1)pdm09 predominated in 2018. VE was estimated at 37% (95% CI 22, 48) for the 2017 season, 53% (95% CI 33, 67) for 2018 and 50% (95% CI 40, 58) for 2019. In general, estimates were higher against A(H1N1)pdm09 and influenza B viruses and lower against A(H3N2) viruses. Across the three seasons, antigenic data identified a greater proportion of A(H1N1)pdm09 and influenza B viruses than A(H3N2) viruses as antigenically similar to the cell-propagated reference viruses. VE estimates by clade generally indicated higher VE among viruses in the same clade as the vaccine viruses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Influenza VE varied across influenza seasons and by influenza type/subtype. Given the ongoing evolution of circulating influenza viruses, vaccine improvements are needed, especially for influenza A(H3N2).</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 7","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of K-12 School District Nonpharmaceutical Interventions on Community-Level Prevalence of Acute Respiratory Infection During the COVID-19 Pandemic","authors":"C. He,&nbsp;M. D. Goss,&nbsp;D. Norton,&nbsp;G. Chen,&nbsp;A. Uzicanin,&nbsp;J. L. Temte","doi":"10.1111/irv.70139","DOIUrl":"https://doi.org/10.1111/irv.70139","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Responding to the COVID-19 pandemic, kindergarten through 12th grade schools implemented nonpharmaceutical interventions (NPIs). The effects of school-based NPIs on broader community levels of acute respiratory infection (ARI) have not been defined. We utilized an existing longitudinal cohort of households reporting weekly ARI cases to evaluate the effects of evolving school districtwide NPIs on ARI activity at eight transition points from December 2019 through October 2022.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Household ARI data were reported through the GReat Oregon Child Absenteeism due to Respiratory Disease Study (ORCHARDS) Vaccine Effectiveness Study—a prospective cohort study based in the Oregon School District (OSD) (GROVES). Participating GROVES families completed weekly online surveys with respiratory illness updates. Mixed effects logistic regression was used to examine the association between eight school-related transition events during the COVID-19 pandemic and changes in the trajectory of ARI risk for GROVES family members, while accounting for family clusters. Transition events were assessed using a ±4-week window of community data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Opening schools with maximal NPIs (mandated masking and physical distancing, with hybrid education) was not associated with increased community ARI activity. The four transition events associated with significant ARI risk trajectory increases included summer breaks (June 2020, <i>p</i> = 0.001; June 2021, <i>p</i> = 0.002), and the start of school with mandatory masking only (September 2021, <i>p</i> &lt; 0.001) or without NPIs (September 2022, <i>p</i> &lt; 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>School-based NPI implementation was associated with reduced risks for community ARI activity. Enhanced surveillance platforms such as the weekly online surveys used in this study are valuable tools for better understanding and monitoring SARS-CoV-2 and respiratory virus transmission in schools and surrounding communities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":13544,"journal":{"name":"Influenza and Other Respiratory Viruses","volume":"19 7","pages":""},"PeriodicalIF":4.3,"publicationDate":"2025-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.70139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}