ABSTRACT Background Acute viral infections trigger overlapping but virus‐specific blood transcriptional responses; however, current analyses rarely quantify the mechanistic depth of activation across pathways, regulators, and immune cell compositions. Methods RNA‐seq data from GSE157240 were reanalyzed to infer transcription factor (TF) activity using DoRothEA/decoupleR, signaling pathway activity using PROGENy, and stress pathway and transcriptional perturbation breadth metrics. These four components were integrated into a viral host perturbation score (VHPS), a proof‐of‐concept framework designed to quantify the magnitude of host transcriptional perturbation. Differential expression analysis, Gene Ontology enrichment, module scoring, and CIBERSORTx‐based immune deconvolution were used to compare respiratory and systemic viral infections. Results VHPS‐stratified viruses along an axis of host transcriptional perturbation, with DNA viruses showing the highest median perturbation, followed by dengue and enterovirus/rhinovirus, whereas influenza A and other respiratory RNA viruses were intermediate and healthy controls were lowest. Upregulated genes revealed virus‐specific and shared signatures, and immune/stress GO terms showed stronger T cell and interferon enrichment for respiratory viruses. A 26‐gene “shared respiratory antiviral” module correlated with VHPS and TF/stress components but not PROGENy activity. Immune deconvolution revealed virus‐specific leukocyte remodeling, with marked Treg depletion and elevated neutrophils in respiratory viruses, monocyte skewing in dengue, and the lowest Treg fractions in DNA viruses. Conclusions Together, VHPS and immune deconvolution delineate shared and virus‐specific regulatory programs in acute viral infections, but the generalizability of VHPS requires evaluation in independent datasets.
ABSTRACT Background In Australia, non‐pharmaceutical interventions introduced early in 2020 to curtail the spread of COVID‐19 resulted in the temporary elimination of influenza. We used data from this influenza‐free period (2021) to validate influenza mortality burden predictions from time‐series models. Methods Time‐series models were parameterised with routinely collected health data from 2010 to 2019 (pre‐pandemic) and from 2010 to 2019 plus 2021 (pandemic‐inclusive). These models were used to predict influenza A‐ and influenza B‐associated mortality rates in Queensland between 2010 and 2019. Mortality estimates were made in persons < 65 and ≥ 65 years for pneumonia and influenza (P&I) and respiratory illnesses as contributory mortality causes and for all‐cause mortality. Results The models predicted consistent mortality rates for influenza B. However, the pandemic‐inclusive model for individuals ≥ 65 years predicted influenza A‐associated P&I mortality of 32.1 per 100,000 person‐years (95% prediction interval [PI]: 25.9, 39.6), significantly higher than the pre‐pandemic model estimate of 17.6 (95% PI: 13.4, 23.6). A similar, non‐significant difference occurred for respiratory mortality. Conclusions These results suggest that time‐series modelling may underestimate the true burden of influenza‐A mortality among the elderly. Further studies are needed to confirm this finding and establish the conditions under which the time‐series regression approach may be reliable.
ABSTRACT Background The COVID‐19 pandemic and associated nonpharmaceutical interventions caused unprecedented suppression of influenza circulation globally. Pakistan, with its high population density and evolving surveillance capacity, lacks long‐term data on post‐COVID‐19 influenza patterns, essential for guiding vaccine policy. Methods We extracted weekly virological data for Pakistan from the WHO FluNet platform (January 1, 2015, to December 31, 2024). The study period was divided into pre‐COVID‐19 (2015–2019), COVID‐19 disruption (2020–2021), and post‐COVID‐19 (2022–2024) phases. Outcomes included type A versus B proportion, subtype distribution (A[H1N1]pdm09 vs. A[H3]), positivity, peak intensity, and season duration (weeks with positivity ≥ 10%). Statistical comparisons used chi‐square for subtype distribution and Kruskal–Wallis for peak intensity. Results We analyzed 6522 positive specimens from 79,484 tested (10,781 pre‐COVID‐19; 14,687 during COVID‐19 disruption; 54,016 post‐COVID‐19). Influenza A declined from 94.2% to 71.7% then rose to 77.5%; influenza B increased from 5.7% to 28.3%, remaining at 22.5% ( p < 0.001). A(H3) dominated during the COVID‐19 disruption (98.8%); A(H1N1)pdm09 regained dominance post‐COVID‐19 (58.8%), though A(H3) remained higher than pre‐COVID‐19 (41.2% vs. 33.3%). Peak intensity differed ( p = 0.047): pre‐COVID‐19 33.3%–67.6%; COVID‐19 disruption 14.0%–17.6%; and post‐COVID‐19 19.8%–37.8%. Season duration was 1 week in 2020 and 3 non‐consecutive weeks in 2021, versus 10–16 weeks pre‐COVID‐19, recovering to 7–13 weeks post‐COVID‐19. Conclusion The COVID‐19 pandemic induced a lasting shift in Pakistan's influenza epidemiology, with persistently elevated influenza B and reshaped A subtype balance. These findings are consistent with the global disappearance of B/Yamagata and support consideration of trivalent vaccine formulations, though antigenic and genetic data remain necessary to confirm vaccine match.
ABSTRACT Background Respiratory syncytial virus (RSV) is a leading cause of pediatric hospitalization, yet data on children hospitalized with RSV in their second year of life are limited. Objective To compare clinical characteristics and management practices of children hospitalized with RSV during their second versus first year of life. Methods This retrospective multicenter study included children aged 0–23 months hospitalized with RSV infection across 11 medical centers between 2017 and 2021. We compared demographics, outcomes (length of stay [LOS] > 3 days, and pediatric intensive care unit [PICU] admission), and systemic corticosteroid and antibiotic use between the second and first years of life, adjusting for prematurity, comorbidities, and the COVID‐19 pandemic. Results Among 6260 children hospitalized with laboratory‐confirmed RSV infection, 1321 (21%) were hospitalized during their second year of life. Compared with first‐year admissions, second‐year patients had higher rates of prematurity (18.0% vs. 13.4%) and comorbidities (6.3% vs. 2.6%) (both p < 0.001). They more frequently received corticosteroids (53.5% vs. 23.2%) and antibiotics (63.4% vs. 45.9%) (both p < 0.001) and had lower PICU admission rates (4.6% vs. 7.0%; p < 0 0.001) and similar rates of prolonged LOS (35.0% vs. 35.6%; p = 0.64). In adjusted analyses, second‐year hospitalization was associated with increased corticosteroid use (adjusted odds ratio [aOR], 4.28; 95% CI, 3.67–4.99) and antibiotic use (aOR, 2.09; 95% CI, 1.80–2.43), and lower odds of PICU admission (aOR, 0.56; 95% CI, 0.40–0.79). Conclusions RSV hospitalization in the second year of life carries a significant burden, with higher antibiotic and corticosteroid use despite lower PICU rates and similar LOS. These findings highlight the need for better characterization of this age group to optimize future immunoprophylaxis strategies.
ABSTRACT Background In 2024, a severe outbreak caused by human adenovirus type 7d (HAdV‐7) occurred in Finnish military garrisons. Molecular typing was implemented to support outbreak control. The aim of this study was to determine adenovirus types circulating in Finnish garrisons during 2013–2023 by retrospective surveillance and to review earlier findings to better understand factors contributing to the 2024 outbreak. Methods Adenovirus‐positive respiratory samples collected through routine surveillance (2013–2023) and enhanced surveillance (2024–2025) were typed using type‐specific PCR assays targeting types 3, 4, 7, 11, 14, 16, and 21. Whole‐genome sequencing was performed on 11 selected samples. Index case interviews were conducted among conscripts infected with HAdV‐7 in late 2023. Results During 2013–2023, among 497 typed samples, HAdV‐4 was most common ( n = 446; 89.7%), followed by HAdV‐3 ( n = 25; 5%). Other types detected were HAdV‐21 ( n = 11; 2.2%), HAdV‐7 ( n = 6; 1.2%), and HAdV‐11 ( n = 1; 0.2%). HAdV‐4 was predominant in 2013–2017 and HAdV‐3 in 2018–2019. Between February 2024 and June 2025, 1692 adenovirus‐positive respiratory samples were typed. The adenovirus types detected were HAdV‐4 ( n = 1133; 67%), HAdV‐7 ( n = 440; 26%), co‐detection of HAdV‐4 and ‐7 ( n = 70; 4.1%), and HAdV‐14 ( n = 1; 0.1%). Epidemiological investigation and whole‐genome sequencing data revealed that the adenovirus associated with the 2024 outbreak (HAdV‐7d) was already circulating in Finnish garrisons in 2023. Conclusion The severity of the 2024 outbreak may reflect limited prior circulation of HAdV‐7 in Finland. Although HAdV‐7 continued to circulate among conscripts in 2025, the severity of the epidemic subsided, possibly due to effective preventative measures guided by active surveillance.
