Search Results (200)

Artificial intelligence (AI) techniques—ranging from hybrid mechanistic–machine learning (ML) ensembles to gradient-boosted decision trees, support-vector machines, and deep neural networks—are transforming the management of seasonal influenza, respiratory syncytial virus (RSV), human immunodeficiency virus (HIV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Symptom-based triage models using eXtreme Gradient Boosting (XGBoost) and Random Forests, as well as imaging classifiers built on convolutional neural networks (CNNs), have improved diagnostic accuracy across respiratory infections. Transformer-based architectures and social media surveillance pipelines have enabled real-time monitoring of COVID-19. In HIV research, support-vector machines (SVMs), logistic regression, and deep neural network (DNN) frameworks advance viral-protein classification and drug-resistance mapping, accelerating antiviral and vaccine discovery. Despite these successes, persistent challenges remain—data heterogeneity, limited model interpretability, hallucinations in large language models (LLMs), and infrastructure gaps in low-resource settings. We recommend standardized open-access data pipelines and integration of explainable-AI methodologies to ensure safe, equitable deployment of AI-driven interventions in future viral-outbreak responses. Full article

Objectives: This study aimed to describe the profile and identify the clinical and sociodemographic factors associated with emergency department (ED) use among patients aged ≥65 years. Methods: This was a retrospective cross-sectional study of patients aged ≥65 years who were seen in the emergency department of the Hospital de Mérida (Spain) in 2019, the year before the Coronavirus Disease 2019 (COVID-19) pandemic. Descriptive statistics were calculated for dependent variables such as hours of ED stay, total number of visits, reasons for discharge, and diagnostic specialty, disaggregated by gender, season, age group, day type (work or holiday), shift, and population area (rural or urban). Results: Significant differences in ED hours were found according to gender (p < 0.001), season (p = 0.024), age group (p < 0.001), attention shift (p < 0.001), and population area (p = 0.003). Discharge to home was the most common destination (63.5%), followed by hospital admission (25.7%). Admissions for gastrointestinal surgery and neurology were predominant in men, and admissions for internal medicine and trauma were predominant in women. Patients aged 65–79 years were admitted to internal medicine, and those over 80 years were admitted to cardiology. Among patients who presented to the hospital’s emergency department and required admission, 51.5% were men aged ≥ 75 years, rising to 53.3% among those aged 65 to 74 years. The clinical areas were related to cardiology (27.67%) and pneumology (20.63%). Conclusions: Demands for ED care in those over 65 years of age are associated with sociodemographic and clinical characteristics, which can be used to better plan and manage resources and improve user satisfaction. Full article

Viral lung infections are a never-ending threat to public health due to the emergence of new variants and their seasonal nature. While vaccines offer some protection, the need for effective antiviral drugs remains high. The existing research methods using 2D cell culture and animal models have their limitations. Human cell-based tissue engineering approaches hold great promise for bridging this gap. Here, we describe a microextrusion bioprinting approach to generate three-dimensional (3D) lung models composed of four cell types: endothelial cells, primary fibroblasts, macrophage cells, and epithelial cells. A549 and Calu-3 cells were selected as epithelial cells to simulate the cells of the lower and upper respiratory tract, respectively. Cells were bioprinted in a hydrogel consisting of alginate, gelatin, hyaluronic acid, collagen, and laminin-521. The models were cultured under air–liquid interface (ALI) conditions to further enhance their physiological relevance as lung cells. Their viability, metabolic activity, and expression of specific cell markers were analyzed during long-term culture for 21 days. The constructs were successfully infected with both a seasonal influenza A virus (IAV) and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant, demonstrating their potential for studying diverse viral infections. Full article

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the zoonotic virus responsible for the COVID-19 pandemic, has caused global health and economic disruption. American mink (Neovison vison) are highly susceptible to SARS-CoV-2 and capable of transmitting it to both mink and humans. We previously reported the first detection of SARS-CoV-2 in feral mink, with two positive cases among 13 animals in the upper courses of two rivers in the Valencian Community, eastern Spain. Here, we expand that study with 60 additional feral mink sampled from November 2020 to May 2022. Four new positives were identified by two-step RT-PCR assay on necropsy samples, including nasal and rectal swabs, lung tissue, lymph nodes, and fetuses from three pregnant females. In total, six of 73 mink tested positive, all with low viral loads. Sanger sequencing confirmed infection and revealed clustering with the B.1.177 and Alpha variants. Body weight and reproductive status analyses indicated seasonal breeding and high population turnover, consistent with other wild mink populations. Our findings reveal that SARS-CoV-2 circulation is limited in feral mink, at least in this region. They underscore the key importance of wildlife surveillance as an element of the One Health strategy, which encompasses humans, animals, and the environment. Full article

Influenza poses a significant global health burden due to its high transmissibility, antigenic variability, and substantial morbidity. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has further complicated influenza dynamics, highlighting the need for rapid, accurate, and accessible diagnostics. This review comprehensively summarized the advancements in influenza virus (IFV) detection, from conventional methods like viral culture and serology to modern molecular techniques, including CRISPR-based systems, next-generation sequencing (NGS), and biosensors. We analyze the sensitivity, specificity, and applicability of these methods and emphasize their roles in clinical and public health settings. While traditional techniques remain valuable for strain characterization, novel technologies like CRISPR and portable biosensors offer rapid, low-resource solutions. This review provides a comprehensive insight into the development of integrated diagnostic strategies for seasonal IFV epidemics and future pandemics. Full article

Background and Objectives: Group A Streptococcus (GAS) is a leading cause of acute pharyngitis with seasonal outbreaks. The coronavirus disease 2019 (COVID-19) pandemic significantly altered respiratory infection trends; however, its impact on GAS pharyngitis (GAS-P) incidence remains unclear. Additionally, data on co-infections with GAS and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are limited. In this study, temporal trends in GAS-P incidence and characteristics of GAS–SARS-CoV-2 co-infections in Japan were examined. Materials and Methods: In this observational study, data from patients who visited the Tokyo Shinagawa Hospital between January 2019 and December 2024 were retrospectively analyzed. Data on GAS and SARS-CoV-2 test results and patient demographics were extracted from medical records. The study period was categorized based on COVID-19-related public health measures as follows: pre-COVID-19 social period (January 2019–April 2020), restricted social period (May 2020–April 2023), and post-restriction period (May 2023–December 2024). GAS incidence stratified by sex, age, and period was calculated. Clinical characteristics of patients co-infected with GAS and SARS-CoV-2 were analyzed. Results: Among 4837 GAS tests, 463 (9.6%) were positive. GAS positivity rates varied significantly: 11.4% (pre-COVID-19), 7.1% (restricted social period), and 12.6% (post-restriction period; p < 0.001). The proportion of pediatric cases decreased significantly during the restricted social period (24.8–5.3%) before rising sharply in the post-restriction period (47.1%, p < 0.001). Among 151 patients tested for GAS and SARS-CoV-2, 14 (9.3%) had co-infections, which were identified exclusively after July 2022. Most patients exhibited mild symptoms, primarily fever and sore throat, with decreased lymphocyte counts despite normal white blood cell counts. Conclusions: In our cohort, the incidence of GAS pharyngitis temporarily declined during COVID-19-related public health measures and subsequently increased, particularly among children, after restrictions were lifted. Limited testing may contribute to the underdiagnosis of GAS–SARS-CoV-2 co-infections. Further large-scale studies are warranted to assess microbial interactions, disease severity, and long-term outcomes. Full article

Background/Objectives: Allergic rhinitis (AR) significantly affects patients’ quality of life and poses a substantial burden on healthcare systems worldwide, with its prevalence rising among pediatric populations. This study aimed to investigate the factors associated with the use of combination therapy involving traditional Korean medicine (KM) and conventional medicine in pediatric AR patients using large-scale health insurance data from South Korea. Methods: Data from 696,182 pediatric patients diagnosed with AR between 2018 and 2021 were analyzed. Multivariate logistic regression was employed to identify factors influencing KM therapy utilization. Results: Among these, 61,745 patients received KM combination therapy. The key predictors of KM combination therapy utilization included school-age children, the winter season, and comorbidities such as rhinitis and atopic dermatitis. Patients receiving KM combination therapy had longer treatment durations and incurred higher healthcare costs compared to those on conventional therapy alone. Additionally, seasonal variations and demographic factors, including a decline in KM use during the Coronavirus Disease 2019 (COVID-19) pandemic, were observed. Conclusions: The findings suggest that integrating KM into pediatric AR treatment may offer potential benefits, especially for children with comorbidities or during the winter months. These insights could guide the development of targeted healthcare policies and strategies to optimize treatment outcomes for pediatric AR patients. Full article

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underwent significant mutations, resulting in the Omicron variant. Methods: In this study, we analyzed blood samples from 98 patients with acute coronavirus disease 19 (COVID-19) hospitalized during the initial SARS-CoV-2 wave and the onset of Omicron in 2021. High-resolution melting (HRM) analysis of PCR products was used to analyze RNA extracted from clinical samples collected in July and November 2021 from patients infected with SARS-CoV-2. Results: HRM analysis revealed a characteristic deletion in the N protein RNA of the virus isolated in November 2021, associated with the Omicron variant. Elevated levels of inflammatory markers and interleukin-6 (IL-6) were observed in both waves of COVID-19. Complement levels and IgG and IgM antibodies to SARS-CoV-2 were detected more often during the second wave. An increase in hemagglutinin-inhibiting (HI) antibodies against influenza viruses was observed in paired blood specimens from moderate to severe COVID-19 patients during both outbreaks. Conclusions: Patients admitted during both waves of COVID-19 showed a significant rise in inflammatory markers, suggesting that Omicron triggers inflammatory responses. The rapid formation of IgM and IgG in Omicron may indicate a faster immune response. Seasonal flu may negatively impact the clinical course of coronavirus infections. Full article

The global outbreak of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) and the strategies adopted by different nations have affected and altered the transmission of different respiratory pathogens around the world. We examined the impact of SARS-CoV-2 on the spread of respiratory viruses in the period between 2021 and 2024 in patients with severe influenza-like symptoms in the Lazio region using multiplex PCR tests for the identification of common seasonal respiratory viruses. Our data reveal a change in the transmission of respiratory viruses from 2021 to 2024, with a sharp decline in the transmission of SARS-CoV-2 and a rise in the transmission of other respiratory viruses, especially influenza viruses, and human rhinovirus/enterovirus in 2024. Moreover, viral co-infections, both those involving two viruses and those involving three viruses, have also increased. This work shows how the spread of SARS-CoV-2 influenced the spread of other respiratory viruses over four years in patients with severe influenza-like symptoms in the Lazio region. In conclusion, the resurgence and fluctuation of various respiratory viruses emphasize the dynamic nature of viral epidemiology in the post-pandemic context and highlight the ongoing need for vigilant public health monitoring and intervention strategies. Full article

The recent success of emission reduction policies in China has significantly lowered sulfur dioxide (SO₂) levels. However, accurately forecasting these concentrations remains challenging due to their inherent non-stationary tendency. This study introduces an innovative hybrid deep learning model, RF-VMD-Seq2Seq, combining the Random Forest (RF) algorithm, Variational Mode Decomposition (VMD), and the Sequence-to-Sequence (Seq2Seq) framework to improve SO₂ concentration forecasting in five coastal cities of northern China. Our results show that the predicted SO₂ concentrations closely align with observed values, effectively capturing fluctuations, outliers, and extreme events—such as sharp declines the Novel Coronavirus Pneumonia (COVID-19) pandemic in 2020—along with the upper 5% of SO₂ levels. The model achieved high coefficients of determination (>0.91) and Pearson’s correlation (>0.96), with low prediction errors (RMSE < 1.35 μg/m³, MAE < 0.94 μg/m³, MAPE < 15%). The low-frequency band decomposing from VMD showed a notable long-term decrease in SO₂ concentrations from 2013 to 2020, with a sharp decline since 2018 during heating seasons, probably due to the ‘Coal-to-Natural Gas’ policy in northern China. The input sequence length of seven steps was recommended for the prediction model, based on high-frequency periodicities extracted through VMD, which significantly improved our model performance. This highlights the critical role of weekly-cycle variations in SO₂ levels, driven by anthropogenic activities, in enhancing the accuracy of one-day-ahead SO₂ predictions across northern China’s coastal regions. The results of the RF model further reveal that CO and NO₂, sharing common anthropogenic sources with SO₂, contribute over 50% to predicting SO₂ concentrations, while meteorological factors—relative humidity (RH) and air temperature—contribute less than 20%. Additionally, the integration of VMD outperformed both the standard Seq2Seq and Ensemble Empirical Mode Decomposition (EEMD)-enhanced Seq2Seq models, showcasing the advantages of VMD in predicting SO₂ decline. This research highlights the potential of the RF-VMD-Seq2Seq model for non-stationary SO₂ prediction and its relevance for environmental protection and public health management. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel human coronavirus, emerged in late 2019 and rapidly evolved into a pandemic around the world. The coronavirus disease (COVID-19) pandemic has dramatically changed the epidemiology and seasonality of other traditional respiratory viruses, e.g., influenza, respiratory syncytial virus, enterovirus, etc. These traditional respiratory viruses have transmission mode and clinical symptoms similar to SARS-CoV-2 but may differ in clinical outcomes and management. Co-infection between SARS-CoV-2 and one or more traditional respiratory viruses have been reported in the literature but have shown mixed evidence in clinical outcomes. With SARS-CoV-2 evolving into mild Omicron variants, it is believed that SARS-CoV-2 co-circulates with other respiratory viruses, which in turn affect the epidemiology and clinical course of respiratory viral infections. In response to these changes, multiplex molecular tests for SARS-CoV-2 and one or more traditional respiratory viruses are attracting more attention in the field and have been developed into a variety of testing modalities. In this review, we describe the seasonality (i.e., in the Northern Hemisphere), epidemiology, and clinical significance of traditional respiratory viruses and their co-infection with SARS-CoV-2 in the post-COVID era. Furthermore, we review commonly used multiplex molecular tests and their applications for the detection of respiratory viruses and their co-infections. Altogether, this review not only sheds light on the epidemiology and clinical significance of respiratory viral infections and co-infections in the post-COVID era, and but also provides insights into the laboratory-based diagnoses of respiratory viral infections using multiplex molecular testing. Full article

Background/Objectives: mRNA vaccines have demonstrated strong immunogenicity and efficacy against SARS-CoV-2. However, the extent of antibody cross-reactivity against human seasonal coronaviruses, such as NL63, remains unclear. Furthermore, it is unknown whether pre-existing antibody responses against NL63 might influence the outcome of SARS-CoV-2 mRNA vaccination. Methods: We used a flow cytometry-based serological assay and an in vitro neutralization assay to analyze NL63 antibody responses in sera from SARS-CoV-2 mRNA-vaccinated mice and plasma samples from a vaccinated human cohort. Results: We found that the Moderna mRNA-1273 vaccine can generate cross-reactive antibodies against NL63. Importantly, SARS-CoV-2 mRNA vaccination did not boost pre-existing anti-NL63 responses in humans, and pre-existing NL63 antibody levels did not affect the antibody response induced by SARS-CoV-2 mRNA vaccination. Conclusions: These findings suggest that while SARS-CoV-2 mRNA vaccination can induce cross-reactive antibodies against NL63, pre-existing immunity to this seasonal coronavirus does not appear to significantly impact vaccine immunogenicity. These findings contribute to our understanding of the complex interplay between pre-existing immunity to seasonal coronaviruses and the immune response generated by SARS-CoV-2 mRNA vaccines. Full article

Background/Objectives: The impact of the coronavirus disease 2019 (COVID-19) pandemic on health was significant worldwide. The measures adopted to limit the spread of the virus had an indirect effect on the epidemiology of other infectious diseases with similar mechanisms of inter-human transmission. The present literature review analyzed the scenario of pediatric acute respiratory infections in the post-lockdown period compared to the pre-pandemic and lockdown periods. The different patterns of viruses’ outbreaks were evaluated according to the type of local COVID-19 restrictive measures and to the type of pathogen. Methods: Relevant scientific literature published between March 2020 and November 2024 was identified by means of electronic keyword searches in the PubMed, Scopus, and Cochrane Library databases. Results: Worldwide implementation of non-pharmacological public health interventions aimed at limiting the COVID-19 pandemic resulted in a measurable effect on the circulation of other common respiratory viruses, significantly affecting their usual seasonality. Most viruses significantly reduced their activity during the lockdown period but returned to or exceeded historical levels after discontinuation of preventive non-pharmacological measures. For many respiratory viruses, particularly respiratory syncytial virus, an off-season increase was reported. Conclusions: The non-pharmacological interventions, which effectively helped limit the COVID-19 pandemic, resulted in relevant epidemiologic changes in most common respiratory viruses. Given the different seasonality and clinical severity observed for some pathogens after lockdown, possible future off-season or more severe epidemics should be expected. Full article

A historical perspective of more than one hundred years of influenza surveillance in New York State demonstrates the progression from anecdotes and case counts to next-generation sequencing and electronic database management, greatly improving pandemic preparedness and response. Here, we determined if influenza virologic surveillance at the New York State public health laboratory (NYS PHL) tests sufficient specimen numbers within preferred confidence limits to assess situational awareness and detect novel viruses that pose a pandemic risk. To this end, we analyzed retrospective electronic data on laboratory test results for the influenza seasons 1997–1998 to 2021–2022 according to sample sizes recommended in the Influenza Virologic Surveillance Right Size Roadmap issued by the Association of Public Health Laboratories and Centers for Disease Control and Prevention. Although data solely from specimens submitted to the NYS PHL were insufficient to meet surveillance goals, when supplemented with testing data from clinical laboratories participating in surveillance programs, the recommended surveillance goals were achieved. Despite the sudden decline in influenza cases in 2020–2021, impacted by the COVID-19 mitigation measures, the dramatic increases in influenza cases surrounding the coronavirus pandemic reveal that influenza remains a national and international public health threat. Sample submissions to public health laboratories must be encouraged to facilitate monitoring for emerging viruses and preparedness for another pandemic. Full article

The coronavirus disease 2019 (COVID-19) pandemic profoundly disrupted the epidemiology of respiratory viruses, driven primarily by widespread non-pharmaceutical interventions (NPIs) such as social distancing and masking. This eight-year retrospective study examines the seasonal patterns and incidence of influenza virus, respiratory syncytial virus (RSV), and other respiratory viruses across pre-pandemic, pandemic, and post-pandemic phases in Jalisco, Mexico. Weekly case counts were analyzed using an interrupted time series (ITS) model, segmenting the timeline into these three distinct phases. Significant reductions in respiratory virus circulation were observed during the pandemic, followed by atypical resurgences as NPIs were relaxed. Influenza displayed alternating subtype dominance, with influenza A H3 prevailing in 2022, influenza B surging in 2023, and influenza A H1N1 increasing thereafter, reflecting potential immunity gaps. RSV activity was marked by earlier onset and higher intensity post-pandemic. Other viruses, including human rhinovirus/enterovirus (HRV/HEV) and parainfluenza virus (HPIV), showed altered dynamics, with some failing to return to pre-pandemic seasonality. These findings underscore the need for adaptive surveillance systems and vaccination strategies to address evolving viral patterns. Future research should investigate the long-term public health implications, focusing on vaccination, clinical outcomes, and healthcare preparedness. Full article