关键词： FGM   Nigeria   Social norms   COVID-19   Bayesian spatial modelling  

摘要： BackgroundDue to its economic burden and change of focus, there is no gainsaying of the potential impacts of the COVID-19 pandemic on the progress of several female genital mutilation (FGM) interventions across the various countries. However, the magnitude of the potential changes in likelihood and prevalence should be more accurately explored and quantified using a statistically robust comparative study. In this study, we examined the differences in the likelihood and prevalence of FGM among 15-49 years old women before and after the pandemic in *** used advanced Bayesian hierarchical models to analyse post-COVID-19 datasets provided by the Multiple Indicator Cluster Surveys (MICS 2021) and pre-COVID-19 data from the Demographic and Health Surveys (DHS 2018).ResultsResults indicated that although there was an overall decline in FGM prevalence nationally, heterogeneities exist at state level and at individual-/community-level characteristics. There was a 6.9% increase in prevalence among women who would like FGM to continue within the community. FGM prevalence increased by 18.9% in Nasarawa, while in Kaduna there was nearly 40% *** show that FGM is still a social norm issue in Nigeria and that it may have been exacerbated by the COVID-19 pandemic. The methods, data and outputs from this study would serve to provide accurate statistical evidence required by policymakers for complete eradication of FGM.

关键词： Normalisation of pandemic prevention and control   Cancer patients   Bed reservations   Operational efficiency   Nursing management  

摘要： BackgroundDuring the prolonged COVID-19 pandemic, hospitals became focal points for normalised prevention and control. In this study, we investigated the feasibility of an inpatient bed reservation system for cancer patients that was developed in the department?s public WeChat account. We also explored its role in improving operational efficiency and nursing quality management, as well as in optimising nursing workforce *** utilised WeChat to facilitate communication between cancer patients and health care professionals. Furthermore, we collected data on admissions, discharges, average number of hospitalisation days, bed utilisation rate, and the number of bed days occupied by hospitalised patients through the hospital information system and nurses? working hours and competency levels through the nurse scheduling system. The average nursing hours per patient per day were calculated. Through the inpatient bed reservation system, the number of accepted admissions, denied admissions, and cancelled admissions from the reservation system were collected. The impact of the bed reservation system on the department?s operational efficiency was analysed by comparing the number of hospitalisation discharges before and after reservations, as well as the average hospitalisation and bed utilisation rates. By comparing nurses? working hours per month and average nursing hours per patient per day, the system?s impact on nurses? working hours and nursing quality indicators was *** average hospitalisation length, bed utilisation rate, and nurses? working hours were significantly lower, and the average number of nursing hours per patient per day was significantly higher after the implementation of the reservation system. The full-cycle bed information management model for cancer patients did not affect the number of discharged ***? ability to reserve bed types from home in advance using the department?s official WeChat-based inp

关键词： COVID-19   Anxiety   Depression   Sedentary behavior   Physical inactivity   Students   ANXIETY  

摘要： BackgroundMovement behaviours, such as sedentary behavior (SB) and physical inactivity, have become a public health issue due to their implications for physical and mental health. The literature indicates that the university environment influences the movement behaviors of university students, and the strategies adopted during the pandemic may have favored a decrease in the practice of physical activity and an increase in the time dedicated to SB in this population. We aimed to evaluate the association of SB and moderate to vigorous leisure-time physical activity (MVPA) with presence of symptoms of mental disorders during the COVID-19 *** is a multicenter survey conducted with undergraduate students from eight Brazilian universities between October 2021 and February 2022 using an online questionnaire. The outcome variable was symptoms of anxiety and depression, assessed by the Depression, Anxiety, and Stress Scale-21. SB was assessed by total sitting time, being that individuals with >= 9 h/day were classified with high SB. The practice of MVPA was evaluated based on weekly frequency, duration, and type of exercise. Subsequently, the ratio between the time spent in MVPA (minutes/day) and the time spent in SB (hours/day) was calculated, being considered as cutoff point was the practice of 2.5 min of MVPA for each sedentary hour. To assess the association between the outcome and explanatory variables, multivariable logistic regression was *** total of 8,650 students participated in the study, with an average age of 23.9 years (SD: +/- 6.34). In the multivariate analysis, the odds of anxiety symptoms [OR: 1.37 (95% CI: 1.24-1.50)] and depression [OR: 1.61 (95% CI: 1.47-1.77)] were higher in individuals with >= 9 h of SB per day. In the analysis of the relationship between MVPA and SB, not engaging in 2.5 min of MVPA per hour of SB increases the odds of anxiety symptoms [OR: 1.44 (95% CI: 1.31-1.58)] and depression [OR: 1.74 (95% CI: 1.59

摘要： The COVID-19 pandemic has prompted an urgent need for reliable and efficient diagnostic tools to combat its spread. Since its origin in 2019, researchers have been trying to find out effective methods for identifying and classifying COVID-19 from other similar disease like pneumonia. This review paper gives a comparable overview of various diagnostic techniques employed by various experts. Artificial Intelligence (AI) based methods, like Machine Learning (ML) and Deep learning (DL) have widely been used for predicting COVID-19. These models usually generate good accuracy rates but still there is a scope of improvement. Hence, attention was shifted towards hybrid approaches which show better detection accuracy results then individual AI models. However, both AI and hybrid models overlook human social connections and migration patterns, which are diverse and not well-mixed in populations. COVID-19 modeling should consider the heterogeneity of individuals, especially as it disproportionately affects the elderly and those with underlying medical conditions like cancer, heart disease, diabetes, and hypertension. Furthermore, people’s mobility patterns and behaviors significantly influence virus spread dynamics. Therefore, role of multi-agent systems (MAS) comes into play, wherein each agent represents different data or information. However, not much work has been done in this filed and hence it needs to be explored more in future studies. Furthermore, it was noted that a significant proportion of researchers favored the utilization of CNN and its variants and SVM classifiers, while a minority opted for RF and regression models for the purpose of classification. Overall, this review provides insights into the strengths and limitations of each approach, emphasizing the need for a comprehensive strategy that harnesses multi-agent systems for COVID-19 detection.

关键词： Social Sciences   UK - Sociology  

ISBN: (纸本)9781032646824

摘要： This volume explores how researchers made innovative use of online technologies to innovate, define, and transform research methodologies in light of the varying impacts of the COVID-19 pandemic, especially those related to the ability to conduct qualitative research. The onset of the COVID-19 pandemic resulted in a radical shift in the way that people all over the world were/have been able to live, work, study, and conduct their daily lives. Academics and other professionals who routinely engage in research were no exception. The sudden, continued, and uneven need for health mandates calling for physical distancing added a particular layer of complexity for those who used research methods that typically required face-to-face interactions. Continued technological developments associated with the Internet had already given rise to ongoing debates on innovative methodological thinking and practices. The COVID-19 pandemic has further accentuated how indispensable the internet has become for the private and public lives of those with access to it, including for their employment, education, leisure, and social interactions. For those fortunate enough to have access to them, communication software such as Zoom and Google Meet have also become indispensable digital resources for researchers seeking to continue conducting research during lockdowns and quarantines, and beyond. More than ever, researchers are finding it useful, even necessary, to equip themselves with online research tools in order to be able to continue conducting their fieldwork. Drawing on research and case studies from around the world, this volume serves as a guidebook for those interested in attuning their own research methods to a world still struggling to grapple with the impacts of the COVID-19 pandemic.

关键词： monocytes   COVID-19   Gam-COVID-Vac vaccine   SARS-CoV-2 antigens   phenotype   cytokines   DENDRITIC CELLS   DR EXPRESSION   INFECTION  

摘要： Monocytes play a crucial role in the immune response against pathogens. Here, we sought to determine COVID-19 and the vaccine Gam-COVID-Vac induce long-term changes in the phenotype and cytokine production of circulating monocytes. Monocytes were purified from peripheral blood mononuclear cells of healthy donors who had not had COVID-19 or vaccination, who had received two doses of Gam-COVID-Vac, and who had mild/moderate COVID-19 in the last 6 months and evaluated by flow cytometry. To investigate the effect of SARS-CoV-2 proteins, monocytes were cultured for 2 days with or without stimulation with recombinant SARS-CoV-2 S1 and N peptides. Monocytes obtained from vaccinated and recovered individuals showed increased basal expression of HLA-DR, CD63, CXCR2, and TLR7. We also observed an increased frequency of CD63+ classical monocytes in both groups, as well as an increased frequency of HLA-DR+ non-classical monocytes in the COVID-19-recovered group compared to the control group. Monocytes from vaccinated and recovered donors produced higher basal levels of IL-6, IL-1 beta, and TNF-alpha cytokines. Ex vivo stimulation with SARS-CoV-2 antigens induced increased expression of HLA-DR and TLR7 on monocytes obtained from the control group. The challenge with SARS-CoV-2 antigens had no effect on the production of IL-6, IL-1 beta, and TNF-alpha cytokines by monocytes. The acquired data offer compelling evidence of enduring alterations in both the phenotype and functional status of circulating monocytes subsequent to vaccination with Gam-COVID-Vac and mild/moderate COVID-19 infection. At least some of these changes appear to be a consequence of exposure to SARS-CoV-2 S1 and N antigens.

关键词： Politics   Government   Policy  

摘要： Labour Prime Minister Keir Starmer has placed several experts who aren't politicians into government posts.

关键词： SURGERY   OUTCOMES   FAMILY   TIME  

摘要： Introduction The COVID-19 pandemic led to a significant reorganization of health services, potentially affecting the quality of care for major public health concerns such as proximal femoral fractures. This study aimed to investigate potential changes in the timing of various steps in the patient journey after a hip fracture during the pandemic in Piedmont, a region in Northern *** A retrospective study was conducted on the discharge records of patients aged 65 or older who were admitted for hip surgery following a femur fracture in 2019 and 2020. The study examined four-time steps: duration from hospital admission to surgery, length of hospital stay, interval between hospital discharge and admission to the rehabilitation facility, and duration of stay at the rehabilitation facility. To mitigate biases linked to sex and age factors, groups well-balanced across 2019 and 2020 were created using propensity score *** The dataset consisted of two cohorts of 583 patients each for the years 2019 and 2020. The average duration from admission to surgery was approximately 1.9 days in both years, with 75% of patients undergoing surgery within 2 days of hospital admission. The average hospital stay reduced from 13.49 days in 2019 to 11.34 days in 2020. The gap between hospital discharge and admission to rehabilitation was approximately 10-12 days, and the average duration of stay at the rehabilitation facility was about 31.6 *** The study indicates that healthcare systems can exhibit resilience and adaptability, even during a global pandemic, to ensure high-quality and safe standards of care. However, further long-term studies are needed to fully understand the pandemic's impact on primary health outcomes following hip replacement surgery and subsequent rehabilitation. The potential role of telemedicine in reducing the time between steps also warrants further investigation.

关键词： Fake detection  

摘要： Topic modeling is frequently being used for analysing large text corpora such as news articles or social media data. BERTopic, consisting of sentence embedding, dimension reduction, clustering, and topic extraction, is the newest and currently the SOTA topic modeling method. However, current topic modeling methods have room for improvement because, as unsupervised methods, they require careful tuning and selection of hyperparameters, e.g., for dimension reduction and clustering. This paper aims to analyse the technical application of BERTopic in practice. For this purpose, it compares and selects different methods and hyperparameters for each stage of BERTopic through density based clustering validation and six different topic coherence measures. Moreover, it also aims to analyse the results of topic modeling on real world data as a use case. For this purpose, the German fake news dataset (GermanFakeNCovid) on Covid-19 was created by us and in order to experiment with topic modeling in a multilingual (English and German) setting combined with the FakeCovid dataset. With the final results, we were able to determine thematic similarities between the United States and Germany. Whereas, distinguishing the topics of fake news from India proved to be more challenging. © 2024, CC BY-NC-ND.