Introduction: Influenza infection poses a significant public health threat. The core for disease prevention and control relies on strengthened surveillance activities, particularly in Saudi Arabia, the country that hosts the largest annual mass gathering event worldwide. This study aimed to assess the molecular and seasonal pattern of influenza virus subtypes in western Saudi Arabia to inform policy decisions on influenza vaccine.
Methods: This cross-sectional study was conducted at King Abdulaziz Medical City, western Saudi Arabia. Medical records and surveillance database of laboratory-confirmed influenza cases were reviewed from October 2015 to 2019. A panel of real-time polymerase chain reactions was performed to detect influenza A and B. Extracted RNA from a subset of positive samples was used to determine influenza A subtypes and influenza B lineages.
Results: This study included a total of 1928 patients with laboratory-confirmed influenza infections. Influenza peaks were observed in October each season, with variant predominant strains. Influenza virus subtypes co-circulate with no reports of co-infection. Influenza A(H3N2) was reported in 42% of the cases, then influenza B (30.7%) and influenza A(H1N1)pdm09 (27.3%). Healthcare workers represented 9.4% of the cases. One-third of the cases (30.4%) were admitted to the hospital with a median admission duration of 4 days. The influenza B viruses were subtyped in 218 cases. Victoria lineage was predominant (64.1%) in 2015 and 2016; however, Yamagata was predominant in the next two consecutive seasons (94.4% and 85.4%, respectively).
Conclusion: The burden due to influenza B may be underestimated with an observed vaccine mismatch. A quadrivalent influenza vaccine is recommended to reduce the health impact associated with influenza B infections. Molecular surveillance of the influenza viruses should be enhanced continuously for a better understanding of the influenza activity and assessment of vaccine effectiveness.
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http://dx.doi.org/10.2991/jegh.k.210427.001 | DOI Listing |
BMC Infect Dis
January 2025
Department of Emergency Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 212001, China.
Background: In China many respiratory pathogens stayed low activities amid the COVID-19 pandemic due to strict measures and controls. We here aimed to study the epidemiological and clinical characteristics of pediatric inpatients with Mycoplasma pneumoniae pneumonia (MPP) after the mandatory COVID-19 restrictions were lifted, in comparison to those before the COVID-19 pandemic.
Methods: We here included 4,296 pediatric patients with MPP, hospitalized by two medical centers in Jiangsu Province, China, from January 2015 to March 2024.
Nat Nanotechnol
January 2025
Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, USA.
The forward design of biosensors that implement Boolean logic to improve detection precision primarily relies on programming genetic components to control transcriptional responses. However, cell- and gene-free nanomaterials programmed with logical functions may present lower barriers for clinical translation. Here we report the design of activity-based nanosensors that implement AND-gate logic without genetic parts via bi-labile cyclic peptides.
View Article and Find Full Text PDFSci Rep
January 2025
Chemistry of Natural and Microbial Products Department, Pharmaceutical and Drug Industries Research Institute, National Research Centre, 33 El Buhouth St, Dokki-Giza, Egypt.
The COVID-19 pandemic has caused significant mortality and morbidity for millions of people. Severe Acute Respiratory Syndrome-2 (SARS-CoV-2) virus is capable of causing severe and fatal diseases. We evaluated the antiviral properties of Aspergillus tamarii SP73-EGY isolate extract against low pathogenic coronavirus (229E), Adeno-7- and Herpes-2 viruses.
View Article and Find Full Text PDFTalanta
December 2024
State Key Laboratory of NBC Protection for Civilian, Beijing, 102205, China. Electronic address:
Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple analysis. In this study, we utilized fluorescence excitation-emission matrix (EEM) spectroscopy as a rapid and specific tool with high sensitivity, employing a straightforward methodological approach to identify spectral differences between samples of respiratory infection viruses. To achieve this goal, the fluorescence EEM spectral data from eight virus samples was divided into training and test sets, which were then analyzed using random forest and support vector machine classification models.
View Article and Find Full Text PDFVaccine
January 2025
Health and Biotechnology (SaBio), Instituto de Investigación en Recursos Cinegéticos, IREC (CSIC, UCLM, JCCM), Ronda de Toledo 12, 13005 Ciudad Real, Spain.; Center for Veterinary Health Sciences, Department of Veterinary Pathobiology, Oklahoma State University, Stillwater, OK, USA.
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