Search Results (14,903)

In this paper we aimed to compare seasonality, clinical characteristics, and outcomes of Influenza A and COVID-19 in the context of influenza reemergence and ongoing Omicron circulation. We performed a retrospective comparative analysis at the Teaching Hospital of Infectious Diseases in Cluj-Napoca, Romania. We included adult patients hospitalized with Influenza A or COVID-19 between 1 November 2022 and 31 March 2024. Data were collected on demographics, clinical presentation, complications, and in-hospital mortality. We included 899 COVID-19 and 423 Influenza A patients. The median age was 74 years for COVID-19 and 65 for Influenza A (p < 0.001). The age-adjusted Charlson comorbidity index was higher in COVID-19 patients (5 vs. 3, p < 0.001). Despite this age gap, acute respiratory failure was more common in Influenza A (62.8% vs. 55.7%, p = 0.014), but ventilation rates did not differ significantly. Multivariate models showed Influenza A was associated with increased risk of intensive-care unit (ICU) admission or ventilation, whereas older COVID-19 patients had higher in-hospital mortality (5.67% vs. 3.3%, p = 0.064). Omicron COVID-19 disproportionately affected older patients with comorbidities, contributing to higher in-hospital mortality. However, Influenza A remained a significant driver of respiratory failure and ICU admission, underscoring the importance of preventive measures in high-risk groups. Full article

Background: Coronavirus disease 2019 (COVID-19) has led to the expansion of the spectrum of invasive fungal infections beyond traditional immunocompromised populations. Although COVID-19-associated pulmonary aspergillosis is increasingly being recognised, COVID-19-associated mucormycosis remains rare, particularly in non-endemic regions. Concurrent COVID-19-associated invasive tracheobronchial aspergillosis and pulmonary mucormycosis with histopathological confirmation is exceedingly uncommon and poses significant diagnostic and therapeutic challenges. Case presentation: We report the case of a 57-year-old female with myelodysplastic syndrome who underwent haploidentical allogeneic haematopoietic stem cell transplantation. During post-transplant recovery, she developed COVID-19 pneumonia, complicated by respiratory deterioration and radiological findings, including a reverse halo sign. Bronchoscopy revealed multiple whitish plaques in the right main bronchus. Despite negative serum and bronchoalveolar lavage fluid galactomannan assay results, cytopathological examination revealed septate hyphae and Aspergillus fumigatus was subsequently identified. Given the patient’s risk factors and clinical features, liposomal amphotericin B therapy was initiated. Subsequent surgical resection and histopathological analysis confirmed the presence of Rhizopus microsporus. Following antifungal therapy and surgical intervention, the patient recovered and was discharged in stable condition. Conclusions: This case highlights the critical need for heightened clinical suspicion of combined invasive fungal infections in severely immunocompromised patients with COVID-19, even in non-endemic regions for mucormycosis. Early tissue-based diagnostic interventions and prompt initiation of optimal antifungal therapy are essential for obtaining ideal outcomes when co-infection is suspected. Full article

The emergence of SARS-CoV-2 variants highlights the urgent need for novel therapeutic strategies, particularly entry inhibitors that could efficiently prevent viral infection. Medicinal herbs and herbal combination formulas have long been recognized for their effects in treating infectious diseases and their antiviral properties, thus providing abundant resources for the discovery of antiviral candidates. While many candidates have been suggested to have antiviral activity against SARS-CoV-2 infection, few have been validated for their mechanisms, including possible effects on viral entry. This study aimed to identify SARS-CoV-2 entry inhibitors from medicinal herbs and herbal formulas that are known for heat-clearing and detoxifying properties and/or antiviral activities. A SARS-CoV-2 pseudoparticle (SARS-CoV-2pp) system was used to assess mechanism-specific entry inhibition. Our results showed that the methanol extract of Anemarrhena asphodeloides rhizome, as well as the water extracts of Cimicifuga foetida rhizome, Xiao Chai Hu Tang (XCHT), and Sheng Ma Ge Gen Tang (SMGGT), have substantial inhibitory effects on the entry of SARS-CoV-2pps into host cells. Given the observation that Cimicifuga foetida exhibited the most potent inhibition and is a constituent of SMGGT, we further investigated the major compounds of the herb and identified caffeic acid as a bioactive component for blocking SARS-CoV-2pp entry. Entry inhibition of Cimicifuga foetida and caffeic acid was validated on both wild-type and the currently dominant JN.1 strain SARS-CoV-2pp systems. Moreover, caffeic acid was able to both inactivate the pseudoparticles and prevent their entry into pretreated host cells. The results support the traditional use of these herbal medicines and underscore their potential as valuable resources for identifying active compounds and developing therapeutic entry inhibitors for the management of COVID-19. Full article

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

The P1104A variant in the TYK2 gene is recognized as the first common monogenic cause of tuberculosis, and recent studies also suggest a potential role in COVID-19 severity. However, its frequency and impact in admixed Latin American populations remain underexplored. Therefore, we investigated the P1104A/TYK2 variant in a cohort comprising 1826 RT-PCR-confirmed COVID-19 patients from Southern Brazil. Cases were stratified by severity into non-severe (n = 1190) and severe (n = 636). Three homozygous individuals were identified—one non-severe and two severe cases—although no statistically significant association with disease severity was observed. The frequency of the C allele in the COVID-19 cohort (2.85%) was significantly higher than in Brazilian population databases, including “DNA do Brasil” (1.81%, p < 0.001) and ABraOM (2.34%, p = 0.03), but lower than in the multi-ancestry gnomAD database (3.71%, p = 0.01), possibly reflecting ancestry bias. We also observed associations between COVID-19 severity and sex (p = 0.003), age (p < 0.001), obesity (p < 0.001), diabetes (p < 0.001), and hypertension (p < 0.001). Future studies in larger and more diverse cohorts are needed to characterize the prevalence of the variant in admixed populations and assess its contribution to COVID-19 susceptibility. Full article

Background/Objective: The COVID-19 pandemic profoundly transformed social life worldwide, indiscriminately affecting individuals across all age groups. Children have not been exempted from the risk of severe illness and death caused by COVID-19. Objective: This paper sought to describe the clinical findings, laboratory and imaging results, and hospital care provided for severe and critical cases of COVID-19 in unvaccinated children, with or without severe asthma, hospitalized in a public referral service for COVID-19 treatment in the Brazilian state of Pernambuco. Methods: This was a case series study of severe and critical COVID-19 in hospitalized, unvaccinated children, with or without severe asthma, conducted in a public referral hospital between March 2020 and June 2021. Results: The case series included 80 children, aged from 1 month to 11 years, with the highest frequency among those under 2 years old (58.8%) and a predominance of males (65%). Respiratory diseases, including severe asthma, were present in 73.8% of the cases. Pediatric multisystem inflammatory syndrome occurred in 15% of the children, some of whom presented with cardiac involvement. Oxygen therapy was required in 65% of the cases, mechanical ventilation in 15%, and 33.7% of the children required intensive care in a pediatric intensive care unit. Pulmonary infiltrates and ground-glass opacities were common findings on chest X-rays and CT scans; inflammatory markers were elevated, and the most commonly used medications were antibiotics, bronchodilators, and corticosteroids. Conclusions: This case series has identified key characteristics of children with severe and critical COVID-19 during a period when vaccines were not yet available in Brazil for the study age group. However, the persistence of low vaccination coverage, largely due to parental vaccine hesitancy, continues to leave children vulnerable to potentially severe illness from COVID-19. These findings may inform the development of public health emergency contingency plans, as well as clinical protocols and care pathways, which can guide decision-making in pediatric care and ensure appropriate clinical management, ultimately improving the quality of care provided. Full article

This study presents an extended approach to compartmental modeling of infectious disease spread, focusing on regional heterogeneity within affected areas. Using classical SIS, SIR, and SEIR frameworks, we simulate the dynamics of COVID-19 across two major regions of Ukraine—Dnipropetrovsk and Kharkiv—during the period 2020–2024. The proposed mathematical model incorporates regionally distributed subpopulations and applies a system of differential equations solved using the classical fourth-order Runge–Kutta method. The simulations are validated against real-world epidemiological data from national and international sources. The SEIR model demonstrated superior performance, achieving maximum relative errors of 4.81% and 5.60% in the Kharkiv and Dnipropetrovsk regions, respectively, outperforming the SIS and SIR models. Despite limited mobility and social contact data, the regionally adapted models achieved acceptable accuracy for medium-term forecasting. This validates the practical applicability of extended compartmental models in public health planning, particularly in settings with constrained data availability. The results further support the use of these models for estimating critical epidemiological indicators such as infection peaks and hospital resource demands. The proposed framework offers a scalable and computationally efficient tool for regional epidemic forecasting, with potential applications to future outbreaks in geographically heterogeneous environments. Full article

With the popularization of social media, information related to public health events has seen explosive growth online, making it essential to accurately identify informative tweets with decision-making and management value for public health emergency response and risk monitoring. However, existing methods often suffer performance degradation during cross-event transfer due to differences in data distribution, and research specifically targeting public health events remains limited. To address this, we propose the Label Confusion Domain Adversarial Network (LCDAN), which innovatively integrates label confusion with domain adaptation to enhance the detection of informative tweets across different public health events. First, LCDAN employs an adversarial domain adaptation model to learn cross-domain feature representation. Second, it dynamically evaluates the importance of different source domain samples to the target domain through label confusion to optimize the migration effect. Experiments were conducted on datasets related to COVID-19, Ebola disease, and Middle East Respiratory Syndrome public health events. The results demonstrate that LCDAN significantly outperforms existing methods across all tasks. This research provides an effective tool for information detection during public health emergencies, with substantial theoretical and practical implications. Full article

Background: The surge in COVID-19 cases during the pandemic created a disease burden. An epidemiological study on COVID-19 is required as not much is known about the impact of containment and mitigation on health. We aimed to compare the epidemiological features during the years of the COVID-19 pandemic in the Vidarbha region in Maharashtra, India, to understand the epidemiology changes throughout the pandemic’s progression. Method: All of the cases reported at our testing centers in Nagpur and its periphery during the three years of the pandemic (i.e., from February 2020 to December 2022) were included. Descriptive analyses of variables of interest and statistical measures were compared. Results: There were 537,320 tests recorded during the study period. Of these, 13,035 (13.29%), 42,909 (13.70%), and 19,936 (15.91%) tested positive in 2020, 2021, and 2022, respectively. Hospitalization decreased from 2020 to 2022. An age group shift from 45 to 16–30 years over the pandemic was noticed. Seasonally, positivity peaked in September (27.04%) in 2020, in April (43.4%) in 2021, and in January in 2022 (35.30%). The estimated case fatality ratio was highest in 2021 (36.68%) over the three years in the hospital setting. Conclusion: Understanding the changing epidemiology of SARS-CoV-2 strengthens our perceptive of this disease, which will aid in improving the healthcare system in terms of both controlling and preventing the spread of COVID-19. Full article

Secukinumab (SEC) is a recombinant, fully human monoclonal antibody that is selective for interleukin-17A (IL-17A). SEC may increase the risk of developing infections such as oral herpes and oral candidiasis. The aim of this case report and literature review was to describe chronic hyperplastic candidiasis (CHC) in a patient with psoriasis (PsO) and psoriatic arthritis (PsA) treated with SEC. CHC is a rare and atypical clinical entity. A definitive diagnosis requires biopsy of the oral mucosa for histopathological diagnosis (PHD). The differential diagnosis includes hairy tongue, hairy leukoplakia, oral lichen planus (OLP), oral lichenoid reaction (OLR), leukoplakia, frictional keratosis, morsication, oral psoriasis, syphilis, and oral lesions associated with coronavirus disease (COVID-19). In addition to the usual factors (xerostomia, smoking, antibiotics, vitamin deficiency, immunosuppression, comorbidities), the new biological therapies/immunotherapies are a predisposing factor for oral candidiasis. The therapeutic approach must be multidisciplinary and in consultation with a clinical immunologist. Dentists and specialists (oral medicine, dermatologists, rheumatologists) must be familiar with the oral adverse events of the new biological therapies. Simultaneous monitoring of patients by clinical immunology and oral medicine specialists is crucial for timely diagnosis and therapeutic intervention to avoid possible adverse events and improve quality of life (QoL). Full article

A multilayer linear response model (MLRM) is proposed to generate time-series data based on linear response theory. The proposed MLRM is designed to generate data for anomalous dynamics by extending the conventional single-layer linear response model (SLRM) into multiple layers. While the SLRM is a linear equation with respect to external forces, the MLRM introduces nonlinear interactions, enabling the generation of a wider range of dynamics. The MLRM is applicable to various fields, such as finance, as it does not rely on machine learning techniques and maintains interpretability. We investigated whether the MLRM could generate anomalous dynamics, such as those observed during the coronavirus disease 2019 (COVID-19) pandemic, using pre-pandemic data. Furthermore, an analysis of the log returns and realized volatility derived from the MLRM-generated data demonstrated that both exhibited heavy-tailed characteristics, consistent with empirical observations. These results indicate that the MLRM can effectively reproduce the extreme fluctuations and tail behavior seen during high-volatility periods. Full article

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the etiologic agent that causes the coronavirus disease (COVID-19) identified in Wuhan, in 2019. Men are more prone to developing severe manifestations than women, suggesting a possible crucial role of sex hormones. 17,β-Estradiol (E2) and 1,25 α dihydroxyvitamin D₃ (calcitriol) act upon gene pathways as immunomodulators in several infectious respiratory diseases. In this study, we aimed to evaluate the influence of E2 and calcitriol on the VSV-based pseudovirus SARS-CoV-2 and SARS-CoV-2 infection in vitro. We infected Vero E6 cells with the recombinant VSV-based pseudovirus SARS-CoV-2 and the SARS-CoV-2 viruses according to the pre-treatment and pre–post-treatment models. The Angiotensin-Converting Enzyme 2 (ACE2) and Vitamin D Receptor (VDR) gene expression did not change under different treatments. The VSV-based pseudovirus SARS-CoV-2 infection showed a significant decrease in the focus-forming unit count in the presence of E2 and calcitriol (either alone or in combination) in the pre-treatment model, while in the pre–post-treatment model, the infection was inhibited only in the presence of E2. Th SARS-CoV-2 infection highlighted a decrease in viral titres in the presence of E2 and calcitriol only in the pre–post-treatment model. 17,β-Estradiol and calcitriol can exert an inhibitory effect on SARS-CoV-2 infections, demonstrating their protective role against viral infections. Full article

Nasal irrigation (NI) is an effective, safe, low-cost strategy for treating and preventing upper respiratory tract diseases. High-volume, low-pressure saline irrigations are the most efficient method for removing infectious agents, allergens, and inflammatory mediators. This article reviews clinical evidence supporting NI use in various conditions: nasal congestion in infants, recurrent respiratory infections, acute and chronic rhinosinusitis, allergic and gestational rhinitis, empty nose syndrome, and post-endoscopic sinus surgery care. NI improves symptoms, reduces recurrence, enhances the efficacy of topical drugs, and decreases the need for antibiotics and decongestants. During the COVID-19 pandemic, NI has also been explored as a complementary measure to reduce viral load. Due to the safe profile and mechanical cleansing action on inflammatory mucus, nasal irrigations represent a valuable adjunctive treatment across a wide range of sinonasal conditions. Full article

Non-polio enteroviruses continue to cause numerous epidemics world-wide that range from mild to severe disease, including acute flaccid paralysis, meningitis, severe respiratory infections and encephalitis. Using publicly available data we present a comprehensive global and regional temporal distribution of non-polio enteroviruses, with a focus on highly prevalent genotypes. We found that regional distribution did vary compared to global prevalence where the top prevalent genotypes included CVA6 and EV-A71 in Asia, EV-D68 in North America and CVA13 in Africa, while E-30 was prevalent in Europe, South America and Oceania. In 2020, the COVID-19 pandemic did interrupt non-polio enterovirus detections globally, and cases rebounded in subsequent years, albeit at lower prevalence and with decreased genotype diversity. Environmental surveillance for non-polio enteroviruses does occur and has been used in some regions as an early-warning system; however, further development is needed to effectively supplement potential gaps in clinical surveillance data. Overall, monitoring for non-polio enteroviruses is critical to identify true incidence, improve understanding of genotype circulation, provide an early warning system for emerging/re-emerging genotypes and allow for better outbreak control. Full article

The COVID-19 pandemic catalyzed the rapid adoption of remote patient monitoring (RPM) technologies such as telemedicine and wearable devices (WDs), significantly transforming healthcare delivery. Telemedicine made virtual consultations possible, reducing in-person visits and infection risks, particularly for the management of chronic diseases. Wearable devices enabled the real-time continuous monitoring of health that assisted in condition prediction and management, such as for COVID-19. This narrative review addresses these transformations by uniquely synthesizing findings from 13 diverse studies (sourced from PubMed and Google Scholar, 2020–2024) to analyze the parallel evolution of telemedicine and WDs as interconnected RPM components. It highlights the pandemic’s dual impact, as follows: accelerating RPM innovation and adoption while simultaneously unmasking systemic challenges such as inequities in access and a need for robust integration approaches; while telemedicine usage soared during the pandemic, consumption post-pandemic, as indicated by the reviewed studies, suggests continued barriers to adoption among older adults. Likewise, wearable devices demonstrated significant potential in early disease detection and long-term health management, with promising applications extending beyond COVID-19, including long COVID conditions. Addressing the identified challenges is crucial for healthcare providers and systems to fully embrace these technologies and this would improve efficiency and patient outcomes. Full article