Search Results (48,998)

COVID-19 and influenza A (FluA) cause severe respiratory infections in elderly patients, with cytokine dysregulation playing a central role. Direct comparative data in older adults remains limited. We aimed to characterize cytokine dynamics and their prognostic value in hospitalized elderly patients with COVID-19 vs. FluA. We performed a prospective cohort study including adults ≥ 60 years hospitalized with respiratory failure due to COVID-19 or FluA between March 2023 and March 2024. Serum IL-1β, IL-6, IL-10, IL-17A, IL-34, MCP-1, and CXCL10 were measured on Day 1 and Day 5 of hospitalization using Luminex^®. Cytokines and associations with non-invasive ventilation (NIV) were assessed by ROC analysis and multivariate logistic regression. 83 patients were included (39 COVID-19, median age 79 years; 44 FluA, median 77 years). At Day 1, COVID-19 exhibited significantly higher IL-6, IL-10, and CXCL10; FluA showed an attenuated cytokine response. At Day 5, cytokines declined in both groups. Baseline IL-6 independently predicted NIV (adjusted OR 3.02), whereas higher MCP-1 was associated with reduced NIV requirement. Early cytokine differences between COVID-19 and FluA are evident in elderly patients, but values converged by Day 5. IL-6 remains an informative early predictor of respiratory deterioration; MCP-1 may reflect a regulated innate response. Full article

Resource-limited settings continue to face challenges in the identification of COVID-19, bacterial pneumonia, viral pneumonia, and normal lung conditions because of the overlap of CT appearance and inter-observer variability. We justify a hybrid architecture of deep learning which combines hand-designed descriptors (Histogram of Oriented Gradients, Local Binary Patterns) and a 20-layer Convolutional Neural Network with dual self-attention. Handcrafted features were then trained with Support Vector Machines, and ensemble averaging was used to integrate the results with the CNN. The confidence level of 0.7 was used to mark suspicious cases to be reviewed manually. On a balanced dataset of 14,000 chest CT scans (3500 per class), the model was trained and cross-validated five-fold on a patient-wise basis. It had 97.43% test accuracy and a macro F1-score of 0.97, which was statistically significant compared to standalone CNN (92.0%), ResNet-50 (90.0%), multiscale CNN (94.5%), and ensemble CNN (96.0%). A further 2–3% enhancement was added by the self-attention module that targets the diagnostically salient lung regions. The predictions that were below the confidence limit amounted to only 5 percent, which indicated reliability and clinical usefulness. The framework provides an interpretable and scalable method of diagnosing multiclass lung disease, especially applicable to be deployed in healthcare settings with limited resources. The further development of the work will involve the multi-center validation, optimization of the model, and greater interpretability to be used in the real world. Full article

The rapid onset and progression of the COVID-19 pandemic highlighted the critical necessity for standardized, timely epidemiological investigations to generate actionable evidence for public health policy. The WHO Global Influenza Surveillance and Response System (GISRS) and Unity Studies and Investigations initiative (Unity Studies) provides the standardized framework to address these critical knowledge gaps. This manuscript reflects upon the Hamdard Institute of Medical Sciences and Research (HIMSR)’s experience as an active site implementing three WHO Unity protocols between 2020 and 2021. We synthesize key findings from the Household Transmission Investigation (HHTI) and the Health Facility Transmission (HCW cohort) studies, detail the operational and analytical complexities addressed through intensive collaboration with WHO HQ, SEARO, and WHO India, and outline the subsequent institutional capacity transmission. Building directly on this established expertise, HIMSR has been designated as the dedicated Nodal network site for the WHO SEARO Unity Network in India, coordinating administration activities of a vast network of national institutes for ongoing pandemic preparedness. This trajectory demonstrates the potential for low- and middle-income country (LMIC) institutions not only to contribute critical evidence during crises but also to transition into resilient national and regional research and surveillance platforms for future pan-respiratory pathogen threats. We detail the essential findings and operational lessons from the COVID-19 pandemic response and elaborate extensively on the strategic implementation plan for the proposed WHO Unity Nodal Network site in India, emphasizing capacity building, standardization, and the integration of research into public health policy. Full article

COVID-19 has been associated with an active immunothrombotic process. The involvement of endothelial cells (ECs) in the feedback loop of the inflammatory and thrombotic process characteristic of COVID-19, as well as its differences with other infectious inflammatory conditions, remains an area requiring further elucidation. This study aimed to assess the immunothrombotic phenotype induced by the SARS-CoV-2 Spike (S) protein and its receptor-binding domain (RBD) in endothelial-derived cell lines. HUVEC and EA.hy926 cell lines were exposed to S protein and to its RBD. Inflammatory, thrombotic, and fibrinolytic mediators were quantified. Molecular docking assays were conducted to identify potential EC receptors for S protein. EC activation was dependent on both protein concentration and stimulation time. An increased release of immunothrombotic biomarkers were observed in endothelial-derived cells exposed to the S protein and to its RBD. The RBD induced a stronger endothelial response. Molecular docking demonstrated high affinity and a possible interaction between the S protein and endothelial receptors: CD-141, CD-147, IL-6R, TLR 2, 4, and 7. These findings confirm that the S protein and its RBD can induce an immunothrombotic phenotype in EC-derived cell lines, potentially exacerbating the disease pathology. We propose possible endothelial receptors mediating this response. Full article

The COVID-19 pandemic created a natural experiment to assess air quality responses to emission reductions, yet evidence from Latin American coastal industrial cities remains scarce. This study examined how meteorological variability modulated the effects of COVID-19 restrictions on air quality in Ilo, a medium-sized coastal industrial city in southern Peru (~67,000 inhabitants). We analyzed daily concentrations of PM₁₀, PM_2.5, NO₂, O₃, and SO₂ across six pandemic phases (January–December 2020) using multiple linear regression, variance decomposition, and Random Forest models. A health impact assessment translated PM_2.5 changes into cardiovascular mortality estimates using Global Burden of Disease 2021 coefficients. Despite reduced anthropogenic activity, PM_2.5 increased by 34% during early reopening (May–June: 16.9 vs. 12.6 µg/m³ baseline), whereas NO₂ decreased consistently (13–19%), SO₂ declined up to 65%, and O₃ more than doubled (+108%) in austral winter. Variance decomposition revealed that O₃ variability was almost entirely meteorology-driven (98%), while PM_2.5 and NO₂ showed balanced contributions from meteorology and restrictions (~50% each). The PM_2.5 increase corresponded to approximately 3 additional cardiovascular deaths per 100,000 population annually. Coastal meteorology can counteract emission reductions, generating counterintuitive air quality responses and underscoring the need for meteorological normalization in policy evaluation. Full article

Background: Primary school teachers are experiencing unprecedented occupational stress due to technological demands, varied student needs, and the enduring psychological effects of the COVID-19 pandemic. Although burnout research is extensive globally, evidence regarding Greek primary educators remains scarce, particularly in post-pandemic contexts where Mediterranean cultural values, economic constraints, and centralized governance may yield unique patterns. Methods: This cross-sectional study examined professional burnout among 102 primary school teachers in Achaia prefecture, Greece, during autumn 2022. The Greek-validated Maslach Burnout Inventory-Educators Survey assessed emotional exhaustion, depersonalization, and personal accomplishment. The psychological impact of COVID-19 was evaluated alongside demographic and occupational factors. Analyses included descriptive statistics, nonparametric tests, correlation analyses, hierarchical clustering, and multiple regression models. Results: The sample exhibited mixed burnout profiles, with 42.2% indicating low emotional exhaustion (while 35.3% showed high levels) and 67.6% showing minimal depersonalization. Bivariate analysis revealed that the psychological burden of COVID-19 was significantly correlated with depersonalization (r = 0.339, p < 0.001) but not with emotional exhaustion (r = 0.078, ns) or personal achievement. However, multivariate regression controlling for demographic factors revealed a suppression effect: pandemic burden emerged as the strongest predictor of emotional exhaustion (β = 0.52, p < 0.001), while its association with depersonalization became non-significant. Cluster analysis identified four distinct profiles: Emotionally Strained (49.0%), Resilient (32.4%), Detached (15.7%), and At-Risk (2.9%). Gender significantly predicted emotional exhaustion (model R² = 0.136), while rural location and years of service predicted depersonalization (model R² = 0.225). Conclusions: Greek primary school teachers demonstrated remarkable resilience after the pandemic, maintaining professional effectiveness despite emotional challenges. The suppression effect observed for COVID-19 burden—significantly associated with depersonalization bivariately but with emotional exhaustion multivariately—highlights the importance of examining both direct and demographically mediated stress pathways. The dimensional independence observed, particularly personal achievement's resilience to external stressors, contests unified burnout models and indicates that targeted interventions addressing specific burnout dimensions may be more effective than holistic approaches. Full article

Despite South Africa being the epicentre of HIV, some progress was made in the fight against HIV, i.e., the implementation of HIV programmes, provision of antiretroviral therapy (ART), etc. However, little is known about the association between HIV testing modalities and ART initiation. This study aimed to determine the association between HIV testing modalities and ART initiation among men who have sex with men (MSM) in selected provinces of South Africa. Following a retrospective cohort design, this study analysed programme data on 3345 MSM aged 16 years and older who were living with HIV and eligible for ART initiation. Logistic regression assessed the association between HIV testing modalities and ART initiation, controlling for age group, location, and the COVID-19 period. All analyses were done using SPSS version 30. Significance was set at p < 0.05. Participants who tested for HIV using the social network strategy (SNS) (98.6%) or index testing (96.3%) showed the highest proportions of ART initiation. Logistic regression showed that MSM who tested for HIV using the SNS had over 12 times higher odds of initiating ART (aOR = 12.166; 95% CI: 7.617–19.430; p < 0.001), compared to those who used a rapid test. A significant association was observed between HIV testing modalities and ART initiation, with SNS and index testing demonstrating higher odds of ART initiation. Full article

This paper investigates whether intelligent workplace technologies improve firm-level productivity and, if so, under what conditions, with particular attention to their implications for the economic and social sustainability of firms. This investigation occurs in a context where firms increasingly combine automation, artificial intelligence (AI), and work-from-home (WFH) practices to sustain performance under structural shocks such as the COVID-19 pandemic. Despite evidence that firms adopt these technologies jointly and reorganize work accordingly, existing research typically examines them in isolation. We develop a micro-founded, task-based production model in which firms allocate tasks between on-site and remote labor and automated capital in an optimal manner. This model allows both automation technologies and remote work collaboration tools to affect productivity and coordination costs that are central to long-term organizational sustainability. Using firm-level survey data from nearly 4000 large firms across industries and countries (2018–2021), we show that working from home (WFH) exhibits diminishing productivity returns when scaled in isolation, reflecting rising coordination frictions. In contrast, firms that combine WFH with automation and digital collaboration tools experience significantly higher labor productivity growth. These integrated technology systems support sustainable productivity by enabling capital deepening, resilient task reallocation, and more efficient use of labor resources over time. Overall, the findings suggest that productivity gains—and by extension sustainable firm performance—stem from integrated workplace technology systems rather than isolated investments, highlighting the importance of coherent technology strategies for organizing work in the post-pandemic economy. Full article

Background: Endocrine disturbances are increasingly recognized as components of long COVID, yet long-term data remain limited. This study evaluated the prevalence of dysglycemia and thyroid autoimmunity four years after SARS-CoV-2 infection in adults without previously known endocrine disease. Methods: We conducted a retrospective longitudinal 4-year evaluation of adults hospitalized for COVID-19 between 2020 and 2021. Of 1009 eligible patients without prior diabetes or thyroid disease, 96 completed a standardized 4-year post-infection evaluation. Acute-phase data included COVID-19 severity, admission glucose, inflammatory markers, imaging findings, and treatments. The 4-year evaluation comprised fasting plasma glucose, thyroid function tests, anti-thyroid antibodies (anti-TPO, anti-Tg), and thyroid ultrasonography. Baseline HbA1c, thyroid autoantibodies, and thyroid imaging were not available. Results: At four years post-infection, 27.1% of patients exhibited dysglycemia compatible with type 2 diabetes mellitus, 41.6% showed thyroid autoimmunity, and 15.6% presented with both conditions. Overall, 47.9% developed at least one endocrine alteration. Admission hyperglycemia strongly predicted long-term dysglycemia (OR 6.67; 95% CI: 1.45–30.58), and diabetes prevalence increased with acute disease severity. Thyroid autoimmunity was frequent but not associated with initial COVID-19 severity. Conclusions: Four years after SARS-CoV-2 infection, a substantial proportion of patients exhibited persistent metabolic and autoimmune alterations, supporting a long COVID immunometabolic phenotype. In the absence of baseline endocrine data, the reported findings reflect long-term endocrine alterations identified at the 4-year evaluation, with a potential role of SARS-CoV-2 infection. These findings highlight the importance of baseline metabolic and thyroid assessment—including HbA1c and thyroid autoantibodies—in hospitalized COVID-19 patients and underscore the need for structured long-term endocrine monitoring. Full article

Digital mental health resources have expanded rapidly in the wake of the COVID-19 pandemic, offering new opportunities to improve access to mental healthcare through technologies such as AI chatbots, mobile apps, and online platforms. Despite this growth, significant challenges persist, including low user retention, limited digital literacy, unclear privacy regulations, and insufficient evidence of clinical effectiveness and safety. AI chatbots, which act as virtual therapists or companions, provide counseling and personalized support, but raise concerns about user dependence, emotional outcomes, privacy, ethical risks, and bias. User experiences are mixed: while some report enhanced social health and reduced loneliness, others question the safety, crisis response, and overall reliability of these tools, particularly in unregulated settings. Vulnerable and underserved populations may face heightened risks, highlighting the need for engagement with individuals with lived experience to define safe and supportive interactions. This review critically examines the empirical and grey literature on AI chatbot use in mental healthcare, evaluating their benefits and limitations in terms of access, user engagement, risk management, and clinical integration. Key findings indicate that AI chatbots can complement traditional care and bridge service gaps. However, current evidence is constrained by short-term studies and a lack of diverse, long-term outcome data. The review underscores the importance of transparent operations, ethical governance, and hybrid care models combining technological and human oversight. Recommendations include stakeholder-driven deployment approaches, rigorous evaluation standards, and ongoing real-world validation to ensure equitable, safe, and effective use of AI chatbots in mental healthcare. Full article

Objective: This study analyzes temporal trends in occupational cancer mortality in Brazil and its federative units from 1990 to 2023, focusing on regional and gender disparities. Methods: We conducted an ecological time-series analysis using data from the Global Burden of Disease (GBD) database. We included deaths from malignant neoplasms attributable to occupational exposures and calculated age-standardized mortality rates. We applied segmented regression with the Joinpoint Regression Program (version 5.4) to estimate the Annual Percent Change (APC) and Average Annual Percent Change (AAPC) for Brazil and its states, stratified by sex. Results: Occupational cancer mortality declined nationally (AAPC = −1.08; 95% CI: −1.37 to −0.85), with a more substantial decrease among men. Marked regional differences emerged: the South, Southeast, and Midwest regions showed consistent declines, while several states in the North and Northeast exhibited stable or rising rates, especially among women. Part of the observed recent decline coincided with the COVID-19 pandemic (2019–2023), suggesting potential underdiagnosis or underreporting. Conclusion: Brazil has experienced a national decline in occupational cancer mortality; however, regional and gender inequalities persist. Territorial, economic, and occupational contexts shape these differences. Strengthening surveillance systems, updating exposure registries, and developing policies sensitive to regional and gender disparities may contribute to improving occupational cancer prevention and control. Full article

Urban crises rarely occur in isolation but emerge as interconnected disruptions across space, time, and institutions. The COVID-19 pandemic intensified existing vulnerabilities and intersected with other crises, producing cascading effects. This paper asks how cascading effects analysis can be used as a planning-oriented method to map and govern compound urban crises, drawing on case studies from Cape Town, Dortmund, and São Paulo. In Cape Town, South Africa, the pandemic intersected with high HIV and tuberculosis rates and load shedding, straining health and social services. In Dortmund, Germany, COVID-19’s economic disruptions overlapped with an energy price crisis, while in São Paulo, Brazil, lockdowns coincided with increased gender-based violence and constrained access to support services. Together, these cases show how pre-existing socio-political and economic conditions shape the impacts of crises, exacerbating marginalization and deepening systemic inequalities. Cascading effects analysis is used to visualize and address interdependencies in compound crises, helping planners move beyond sectoral silos, identify key intervention points for crisis management, and support more resilient and equitable urban planning. The paper calls for a methodological shift in urban crisis research toward tools that better communicate systemic risk and bridge risk assessment, social vulnerability, and planning practice. Full article

COVID-19 exposed longstanding racial and ethnic inequities among underserved populations. This retrospective cohort study examined inequities across stages of the hospitalization continuum—from COVID-19 diagnosis at admission to in-hospital mortality, including mortality patterns among COVID-19 hospitalizations—among Medicaid beneficiaries in Kentucky during 2020–2021. Statewide hospitalizations were analyzed using multivariable regression models, with propensity score matching (PSM) used as a confirmatory approach. Non-Hispanic Black patients were more likely than non-Hispanic White patients to be hospitalized with COVID-19 (adjusted odds ratio [aOR] = 1.41; 95% confidence interval [CI] = 1.26–1.59). Across the full cohort, COVID-19 hospitalizations were associated with substantially higher in-hospital mortality compared with non-COVID-19 hospitalizations (adjusted hazard ratio [aHR] = 2.38; 95% CI = 2.09–2.70). Additionally, hospitalizations among non-Hispanic Black patients had a modestly lower hazard of in-hospital mortality compared with non-Hispanic White patients (aHR = 0.81; 95% CI = 0.70–0.94). However, in analyses restricted to COVID-19 hospitalizations, adjusted estimates showed no Black–White differences in in-hospital mortality, with consistent findings from PSM analyses. These results indicate that racial inequities were more pronounced at hospital admission than during inpatient care, underscoring the importance of prevention, early diagnosis, and timely outpatient care as COVID-19 enters an endemic phase. Full article

The COVID-19 pandemic has fundamentally transformed residential spaces, yet traditional survey-based approaches face limitations in objectively capturing these changes. This study investigates residential design trends in the Post-pandemic era, defined as the period in which pandemic-induced lifestyle changes have become institutionalized in everyday living environments. Residential interior images were collected from Pinterest and Instagram and analyzed using an image-based deep learning approach combined with expert evaluation. A pretrained convolutional neural network (ResNet50) was employed as a visual feature extractor to quantify three spatial attributes—openness and comfort, flexibility and diversity, and nature-friendliness—across four residential space types: balconies, living rooms, entrances, and bedrooms. The model-generated proportional scores were validated by experts and compared between pre-pandemic and post-pandemic periods. The results reveal dual transformation patterns of functional specialization and increased multifunctionality. Balconies evolved into well-being-oriented spaces with enhanced nature-related features, while living rooms emerged as multifunctional hubs with a substantial increase in spatial flexibility. In contrast, entrances exhibited reduced openness, functioning as hygienic buffer zones. These findings indicate a reconfiguration of spatial hierarchy in post-pandemic housing, where auxiliary spaces gain prominence and traditional primary spaces adopt flexible roles. This study demonstrates the value of image-based deep learning for objectively identifying residential design trends and provides practical implications for resilient housing design in the post-pandemic era. Full article

The COVID-19 pandemic has revealed profound social–psychological vulnerabilities and strengths across societies worldwide. Beyond its immediate health implications, the pandemic has triggered a wave of mental health issues, disrupted social cohesion, and challenged community resilience. This paper synthesizes the current literature, critically discusses five recent studies as part of the Special Issue “Mental Health Consequences of COVID-19: The Role of Social Determinants”, and articulates an agenda for future research within a social–psychological framework. Moving beyond mere negative effects such as anxiety, this review highlights the role of resilience, prosocial behavior, (digital) mental health interventions, and community social capital. Correspondingly, I advocate for interdisciplinary efforts to enhance awareness, preparedness, and adaptive capacity during health crises, emphasizing the need for a clearer focus on vulnerable social groups. In sum, recognizing the evolving global landscape, this work underscores the urgency of integrating psychological insights into public health policies to build resilient societies capable of confronting future pandemics and health emergencies. Full article