Search Results (44,414)

Background/Objectives: Respiratory viruses, including Influenza, RSV, and COVID-19, cause various respiratory infections. Distinguishing these viruses relies on diagnostic methods such as PCR testing. Challenges stem from overlapping symptoms and the emergence of new strains. Advanced diagnostics are crucial for accurate detection and effective management. This study leveraged nasopharyngeal metabolome data to predict respiratory virus scenarios including control vs. RSV, control vs. Influenza A, control vs. COVID-19, control vs. all respiratory viruses, and COVID-19 vs. Influenza A/RSV. Method: We proposed a stacking-based ensemble technique, integrating the top three best-performing ML models from the initial results to enhance prediction accuracy by leveraging the strengths of multiple base learners. Key techniques such as feature ranking, standard scaling, and SMOTE were used to address class imbalances, thus enhancing model robustness. SHAP analysis identified crucial metabolites influencing positive predictions, thereby providing valuable insights into diagnostic markers. Results: Our approach not only outperformed existing methods but also revealed top dominant features for predicting COVID-19, including Lysophosphatidylcholine acyl C18:2, Kynurenine, Phenylalanine, Valine, Tyrosine, and Aspartic Acid (Asp). Conclusion: This study demonstrates the effectiveness of leveraging nasopharyngeal metabolome data and stacking-based ensemble techniques for predicting respiratory virus scenarios. The proposed approach enhances prediction accuracy, provides insights into key diagnostic markers, and offers a robust framework for managing respiratory infections. Full article

During the COVID-19 pandemic, a significant decline in Mycoplasma pneumoniae was observed; however, M. pneumoniae re-emerged globally in 2023. Here, we describe a current outbreak of M. pneumoniae infections in the United States (US). More than 287 million patient records from all 50 states in the US were reviewed to identify patients with a M. pneumoniae diagnosis between 1 January 2017 and 30 September 2024. A c-chart was created by calculating the mean and standard error (SE) of cases during the pre-COVID-19 pandemic period, with the upper control limit (UCL) set at 3 SE above the mean. The presence of an outbreak was defined as counts above the UCL. Cumulative excess cases were used to estimate the magnitude of the outbreak, and the fold increase was calculated. A US outbreak of M. pneumoniae began at the end of 2023, resulting in 9708 excess cases corresponding to a 9.0-fold increase over the baseline UCL. The outbreak is ongoing, affects both children and adults, and includes patients with M. pneumoniae community-acquired pneumonia requiring hospitalization. This US outbreak of M. pneumoniae has significant implications for the management of patients with respiratory infections during the current pneumonia season. Full article

Background: Age-related decline in musculoskeletal function is a significant concern, particularly in Western countries facing demographic shifts and increased healthcare demands. This review examines the typical trajectories of musculoskeletal deterioration with age and evaluates the effectiveness of various interventions in preventing or reversing these changes. Methods: The review analyzes documented rates of decline across multiple parameters, including muscle mass, Type II muscle fiber reduction, and decreased motor unit firing rates. It examines evidence from studies on targeted interventions aimed at reversing these trends or preventing further decline. Results: The evidence suggests that multimodal interventions, including strength training can effectively maintain or improve physical function in aging adults. These interventions have shown potential in altering the trajectory of age-related decline in musculoskeletal function. Conclusions. The findings of this review have important implications for healthcare providers and policymakers in addressing the challenges of an aging population. By providing a framework for understanding and addressing age-related physical decline through evidence-based interventions, this review offers potential strategies for reducing healthcare costs and improving the quality of life for older adults. Full article

Objective: This study aimed to evaluate the effects of an 8-week physiotherapy program on muscle strength, functional capacity, respiratory function, and quality of life in women recovering from COVID-19. Methods: A prospective cohort study was conducted with 42 women aged 18–65 who experienced muscle strength loss and functional impairments post-COVID-19. Participants underwent personalized physiotherapy interventions, including resistance training, respiratory therapy, and functional mobility exercises, for 8 weeks. Data were collected at baseline and post-intervention, including handgrip strength, 6-Minute Walk Test (6MWT), forced vital capacity (FVC), Fatigue Severity Scale (FSS), and SF-36 scores. Statistical analyses were performed using paired t-tests and Wilcoxon signed-rank tests. Results: Significant improvements were observed in muscle strength, with right-handgrip strength increasing from 18.5 ± 4.2 kg to 22.8 ± 4.6 kg (p < 0.001) and left-handgrip strength from 17.2 ± 4.1 kg to 21.1 ± 4.5 kg (p < 0.001). Functional capacity improved, as evidenced by a 6MWT distance increase from 382 ± 62 m to 438 ± 57 m (p < 0.001). Respiratory function parameters, including FVC and FEV1, also showed significant gains (p < 0.01). Quality of life scores improved significantly, particularly in physical functioning and vitality domains, while fatigue levels decreased markedly (p < 0.001). Conclusions: The results demonstrate the effectiveness of physiotherapy in addressing the physical and functional consequences of COVID-19 in women. These findings emphasize the importance of incorporating physiotherapy into post-COVID-19 rehabilitation protocols to enhance recovery and quality of life. Full article

This study aims to identify the common indices having an impact on the SPV of BRICS countries during crises. To address this, the monthly data retrieved from the database of the Global Economic Monitor (GEM), World Bank, IMF International Financial Statistics data, and OECD in the period of January 2000 to December 2023 are analyzed in two phases. In the first phase, DM classification techniques are applied to the data to identify the best common classification technique in order to use this technique in the second phase to compare the results with Multiple Linear Regression (MLR) results. In the second phase, to account for the global financial crisis and COVID-19 crisis, the sample period is divided into two sub-periods. For those sub-periods, MLR and the best classification technique that was found in the first phase are utilized to find the common indices that have an impact on the stock price volatility during individual and both crises. The findings indicate that the Random Tree method commonly classified the data among the seven classification techniques. Regarding MLR results, no common indices were identified during the global financial crisis or the COVID-19 crisis. However, based on Random Tree classifications, the CPI price percent, National Currency, and CPI index for all items were common during the global financial crisis, whereas only the CPI price percent was common during the COVID-19 crisis. While some common indices were observed in individual crises for specific countries, no indices were consistently found across both crises. This variation is attributed to the unique nature of each crisis and the diverse economic and socio-political structures of different countries. These findings provide valuable insights for financial institutions and investors to refine financial and policy decisions based on the specific characteristics of each crisis and the indices affecting each country. Full article

Background/Objectives: Food deserts are areas characterized by limited access to affordable and healthy food, often due to significant distances from supermarkets—exceeding 1.6 km in urban areas and 16 km in rural settings. These spatial limitations exacerbate health and socioeconomic disparities. This study aimed to assess diet quality and explore the barriers influencing dietary behaviors among individuals aged 60 and older residing in food deserts in Aragón, Spain. Methods: An exploratory qualitative study using a phenomenological approach was conducted, complemented by descriptive analyses of sociodemographic data and adherence to the Mediterranean diet, assessed through the PREDIMED questionnaire. Data were collected through in-depth interviews and a focus group with residents of food deserts. Results: Half of the participants showed high adherence to the Mediterranean diet, while the other half had moderate adherence. Despite the lack of access to supermarkets and higher food costs, many participants perceived their diet quality positively. Challenges, such as long distances to stores, limited public transport, and economic constraints, were mitigated through strategies like home gardening, hunting, and traditional cooking, which often reduced reliance on processed foods. However, participants also reported increased alcohol consumption as a means of socializing. Conclusions: Diet quality in Aragón’s food deserts reflects a balance between significant access barriers and community-driven resources. While participants leveraged local strategies to maintain diet quality, systemic issues remain. Public policies should focus on improving transportation, enhancing local food systems, and fostering community-based initiatives to reduce inequalities in food access and promote healthier dietary habits in rural areas. Full article

Background: Suicidal behavior (SB) and non-suicidal self-injury (NSSI) are significant public health concerns among adolescents. The COVID-19 pandemic may have exacerbated these issues. Methods: This retrospective cohort study analyzed data from 341 adolescents (aged 6–18 years) presenting to a Romanian pediatric psychiatry emergency department during the years 2019 (pre-pandemic) and 2022 (post-pandemic). All participants underwent a thorough psychiatric assessment, and, together with their caregivers, were questioned on a wide range of potentially relevant issues, such as family, social, school, and life history factors. Logistic regression and random forest models were used to identify predictors of SB and NSSI. Results: SB was significantly predicted in regression models based on a prior suicidal ideation (OR = 68.410; p < 0.001), having a parent living abroad (OR = 11.438; p = 0.020), depression (OR = 6.803; p < 0.001), and conflicts with peers (OR = 0.325, p = 0.042), teachers (OR = 0.119, p = 0.024), or both (OR = 0.166, p = 0.012). The random forest model featured a slightly different order of the main predictors and highlighted the importance of additional predictors, such as prior suicide attempts, gender, and past non-suicidal self-injury. NSSI was mainly predicted by a history of self-harm (OR = 52.437; p < 0.001), the number of comorbid psychiatric disorders (OR = 1.709; p = 0.003), and conduct disorder (OR = 0.184; p < 0.001), to which are added, according to random forest models, new predictors, such as borderline personality disorder, suicidal ideation, and school performance. Post-pandemic increases were observed in depression, suicidal ideation, and possible psycho-traumatic negative life event exposure. Conclusions: This study underscores the complex interplay of individual, familial, and societal factors influencing adolescent self-harm. Comprehensive interventions are needed, with early intervention crucial for those with a history of self-harm. Further research using prospective designs is recommended. Full article

In this work we analyze the evolution of productivity, in terms of the convergence of per capita income, of all the Spanish provinces, based on data from the previous decade. On the one hand, a cluster analysis allows us to group the Spanish provinces according to four income levels (low, medium-low, medium-high and high), which can be determined from the quartiles of the distribution, and, on the other hand, Markov chains make it possible to study the long-term evolution of productivity and convergence between the provinces, as well as the speed of convergence towards the equilibrium situation. Moreover, we can obtain the average time to return to an income level in which a province was previously. With the above, predictions of future income levels are made for the provinces, both in the current situation, and if the pandemic caused by COVID-19 had not existed, which leads us to evaluate the impact of the health emergency. Full article

Background/Objectives: The COVID-19 pandemic has had a profound impact on physical, mental, and social aspects of life worldwide. This study aimed to explore and compare differences in knowledge, awareness, behavior, and the psychological impact of the pandemic among students of biomedical faculties at the University of Zagreb. Methods: A cross-sectional study was conducted between 27 November 2020 and 19 January 2021 involving 518 students from the School of Dental Medicine, School of Medicine, Faculty of Pharmacy and Biochemistry, and Faculty of Veterinary Medicine. An anonymous online questionnaire was distributed, assessing participants’ knowledge about SARS-CoV-2, information sources, attitudes, and psychological responses. Data were analyzed using descriptive statistics and appropriate statistical tests. Results: The median knowledge score was 61.54%, with senior and female students demonstrating significantly more knowledge (p < 0.001 and p = 0.044, respectively). Students who consulted the scientific literature and official websites had higher knowledge levels (p < 0.001). Most participants used media and social networks for pandemic information, while scientific sources were underutilized. Psychological impacts were evident, with 46.3% expressing fear about the future and 25% reporting anxiety if they were to be infected. Additionally, those who engaged with the scientific literature were more likely to accept vaccination and showed lower levels of COVID-19 stigma. A majority (64.5%) believed that the media exaggerated the pandemic’s risks. Conclusions: Biomedical students demonstrated moderate knowledge about COVID-19, with a clear link between scientific literacy and more informed, less stigmatizing attitudes. This study underscores the importance of reliable information sources in shaping public health awareness and highlights the need for further education on COVID-19 symptoms and preventive measures. Full article

Background/Objectives: The COVID-19 pandemic has led to detrimental effects on diverse aspects of the mental and physical health of the general population worldwide. The elderly are more susceptible to COVID-19 infection compared to younger age groups. In this aspect, the purpose of the current survey is to evaluate the effect of the COVID-19 pandemic on the interrelationships among the sociodemographic and anthropometric characteristics, depressive behavior, quality of life, cognition status, physical activity and nutritional status of older adults. Methods: The present study constitutes a comparative, cross-sectional study of 4162 older adults (mean age ± standard deviation: 72.13 ± 8.1 years and 75.22 ± 8.2 years in the pre- and post-COVID-19 periods, respectively, and a male/female ratio of almost 1:1). We used validated questionnaires to assess depression, cognition function, quality of life, physical activity and nutritional status of the elderly in the pre-Covid and post-Covid periods. Relevant questionnaires were also used for collecting sociodemographic data, while anthropometric data were measured using standard protocols. Results: The present study finds that the COVID-19 pandemic influenced, in an independent manner, residence location, smoking status, overweight/obesity and abdominal obesity, depressive behavior, quality of life, cognition behavior, physical activity levels and nutritional status of the elderly. The COVID-19 pandemic was also related to employment and living status as well as family economic status. Nevertheless, the above three relationships were insignificant in the multivariate analysis. Conclusions: The COVID-19 pandemic exerted deleterious effects on several aspects of the mental and physical health of the elderly, which appeared to strongly persist in the post-Covid period. Future prospective population-based and well-organized surveys should be conducted to establish whether there is a causality long-term effect of the COVID-19 pandemic on diverse aspects of the mental and physical health of the elderly. Full article

This review offers a comprehensive and in-depth analysis of face mask detection and recognition technologies, emphasizing their critical role in both public health and technological advancements. Existing detection methods are systematically categorized into three primary classes: feaRture-extraction-and-classification-based approaches, object-detection-models-based methods and multi-sensor-fusion-based methods. Through a detailed comparison, their respective workflows, strengths, limitations, and applicability across different contexts are examined. The review underscores the paramount importance of accurate face mask detection, especially in response to global public health challenges such as pandemics. A central focus is placed on the role of datasets in driving algorithmic performance, addressing key factors, including dataset diversity, scale, annotation granularity, and modality. The integration of depth and infrared data is explored as a promising avenue for improving robustness in real-world conditions, highlighting the advantages of multimodal datasets in enhancing detection capabilities. Furthermore, the review discusses the synergistic use of real-world and synthetic datasets in overcoming challenges such as dataset bias, scalability, and resource scarcity. Emerging solutions, such as lightweight model optimization, domain adaptation, and privacy-preserving techniques, are also examined as means to improve both algorithmic efficiency and dataset quality. By synthesizing the current state of the field, identifying prevailing challenges, and outlining potential future research directions, this paper aims to contribute to the development of more effective, scalable, and robust face mask detection systems for diverse real-world applications. Full article

Background/Objectives: Rapid cycle analysis (RCA) is an established and efficient methodology that has been traditionally utilized by United States health authorities to monitor post-approval vaccine safety. Initially developed in the Vaccine Safety Datalink (VSD) in early 2000s, RCA has evolved into a valuable approach for timely post-approval signal detection. Due to the availability of additional near real-time data sources and enhanced analytic approaches, the use of RCA has expanded. This narrative review provides an in-depth assessment of studies that utilized RCA for safety surveillance to detect and evaluate safety signals in post-approval vaccine monitoring. Methods: Embase and Medline were searched on 8 August 2024 to identify post-approval non-interventional vaccine safety studies using RCA or other near real-time surveillance methods published from 1 January 2018 to 31 July 2024. Data on study characteristics (e.g., study population, data source, outcomes) and RCA methodological characteristics (e.g., type of comparator, sequential testing method, confounding control method) were extracted from the eligible RCA studies. Results: Of 1128 articles screened, 18 RCA vaccine safety studies were included, of which 17 (94.4%) were conducted in the United States (US). Twelve (67%) aimed at signal detection and six (33%) conducted further signal evaluation. Over 60% examined COVID-19 vaccine safety, with half using VSD. Over 80% conducted the RCA weekly or monthly and about 78% of the studies used a database-specific historical comparator group. Conclusions: This review indicates that most of the published articles on the application of the RCA methodology in vaccine safety studies are based on research conducted in the US. With increasing availability of near real-time data sources and advanced analytic methods capabilities, RCA is expected to be more widely deployed as an active surveillance tool to complement traditional pharmacovigilance. Future studies should explore the extension of vaccine RCA methodology for non-vaccine medicinal products. Full article

This article examines the ideological and spatial characteristics of neighborhoods built through the initiative of various states, particularly in Europe, in the post-World War II years, from 1945 to 1980. We argue that despite these neighborhoods being older and subject to economic, professional, and ideological criticism, they feature beneficial physical spaces that came to light, especially during the COVID-19 pandemic. These spaces provided opportunities for well-being, relaxation, and community building during times of lockdown and restricted human movement in the built environment. However, residents discovered these spaces, which we term here as “invisible spaces”, through a bottom-up process, and these spaces remain largely unknown to planners or other external stakeholders. In this article, we detail the ideological, economic, and professional approaches that informed the initial planning of these neighborhoods, the contemporary criticisms they face, and the methodology for objectively and comprehensively assessing the quality of their spaces to uncover the “invisible spaces”. We argue that examining urban location, human spatial diversity, intra-neighborhood visibility, and walkability can provide insights into the neighborhood’s qualities and human activity within it, particularly revealing the potential for the emergence of these beneficial “invisible spaces”. Full article

Background: Despite considerable research on pregnancy outcomes affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the consequences for infants exposed to the virus in utero remain unclear. Methods: A retrospective cohort study was conducted, encompassing 392 mother–infant pairs delivered between April 2020 and July 2021 at a community hospital network in northeastern Pennsylvania, USA. Of these, 198 mothers had a confirmed SARS-CoV-2 infection during pregnancy, while 194 did not. Infant outcomes were compared between the two groups. Results: Pregnant women with a SARS-CoV-2 infection during their gestation exhibited higher rates of obesity (p = 0.04) with higher body mass indices (BMI) (p = 0.01), were more likely to be of Hispanic ethnicity (p = 0.01), and had a history of chronic hypertension (p = 0.05), as well as higher occurrences of postpartum depression (p = 0.01), gestational diabetes (p = 0.05), cesarean section (CS) rates (p< 0.001), and preeclampsia (p = 0.04). Among the infants reviewed, there was no statistical significance difference in developmental milestones at 2, 4, 6, 9, and 12 months of age between infants of parturients who tested positive for coronavirus disease 2019 (COVID-19) and infants of parturients without a positive COVID-19 test result. There was no statistically significant difference between the two groups in developmental outcomes, as measured by Ages and Stages Questionnaire (ASQ) scores at 9 months (p = 0.76) and at 18 months (p = 0.89). Conclusions: This study corroborates the adverse impact of SARS-CoV-2 infection on pregnant women, characterized by increased maternal comorbidities and adverse birth outcomes. No significant disparities in neonatal developmental milestones or growth outcomes were observed at birth; first office visit, or at 1, 2, 4, 6, 9, and 12 months of age. Full article

Background/Objectives: The COVID-19 pandemic increased people’s reliance on masks and hand sanitizers, highlighting the critical role of health literacy (HL) in effectively using these preventive measures. This study aimed to assess how HL influences consumers’ comprehension of product labels for masks and hand sanitizers in post-pandemic Korea. Methods: A cross-sectional online survey was conducted in September 2023 among 500 Korean adults aged 20–69. The participants completed a questionnaire measuring HL and their knowledge of mask and hand sanitizer labels using the Korean Health Literacy Assessment Tool. The respondents were classified into high- and low-literacy groups, and statistical analyses (chi-squared tests, t-tests, and logistic regression analyses) were employed to compare label comprehension between the groups. Results: High HL was observed in 31.6% of participants, demonstrating significantly better label-reading habits, including greater recognition of quasi-drug designations, usage instructions, and safety precautions (p < 0.001). The logistic regression analysis revealed that high-HL participants were more likely to correctly identify mask-related information (OR 2.56, 95% CI: 1.69–3.89) and demonstrate hand sanitizer-related knowledge (OR 5.39, 95% CI: 3.31–8.77) than their counterparts. Demographic factors such as age, gender, or education showed no significant associations with label comprehension. Conclusions: Higher HL is strongly associated with better comprehension of mask and hand sanitizer labels, underscoring its importance in public health communication. Enhancing HL is essential in promoting the safe use of preventive products during health emergencies. Public health initiatives should prioritize improving health literacy to ensure more effective communication and safer practices during future health crises. Full article