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The aim of the research. To conduct a cluster analysis of the assessment profile of students who participated in work of medical organisations providing care to COVID-19 patients to develop recommendations for its correction. Material and methods. The study was carried out at the premises of Prof. V.F. Voino-Yasenetsky Krasnoyarsk State Medical University (KrasSMU). The study group was constituted by 66 students in 3-6 years of study of the Medical and the Paediatric faculties of the University who took part in activities of medical organisations providing healthcare to patients with COVID-19. The items were presented in the form of binary questions and ranking scales. The analysis of qualitative attributes was carried out in the form of relative values with calculation of the standard error of the proportion. For ranking and nonparametric quantitative characteristics, the mode, median, centiles (Me [P25;P75]) and other nonparametric criteria for comparative statistics and communication statistics were used. For segmentation of respondents according to some criteria, depending on the answers, the method "two-step cluster analysis" and the method of "decision tree" were used. Results. The results of the study indicate a high motivational component related to practical medical activity of medical students during the difficult epidemiological situation since 94.1% of the respondents declared the readiness to support practical healthcare. Almost half of the surveyed 47.0% of students included in cluster 2, in contrast to students of clusters 1 and 3, are characterised by a high opinion on the degree of their contribution to the struggle against the COVID-19 epidemic and a high level of knowledge and skills, rating themselves at about 9.0 points out of 10 possible. In addition, the results of the study indicate an association between the level of students' self-esteem in regard to their contribution to the fight against COVID-19 with the level of the students' self-esteem of knowledge and skills and the duration of work in a medical organisation. Conclusion. The analysis performed has made it possible to formulate guidelines for support of medical students' professional attitudes within the framework of practice-oriented education, including distance learning.Copyright © 2021, Krasnoyarsk State Medical University. All rights reserved.
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Air pollution in India is a serious health issue. A countrywide lockdown was imposed in India in response to the COVID-19 pandemic, firstly for three weeks starting from March 24 to April 14, 2020, and then extended until May 3, 2020. Because of the restrictions imposed, pollution levels in cities all over the country have dropped dramatically in just a few days, raised questions among scientists about lockdown as the most effective alternative approach for reducing air pollution. Hyderabad was chosen for this study because it is India's 5th largest city by area and 4th largest city by population, as well as major industrial centre in South-East Asia with strong air quality statistics. In light of the recent COVID-19 outbreak around the country, a detailed analysis based on air quality parameters from six distinct air quality monitoring sites in Hyderabad, Telangana, has been performed. For simple interpretation of air quality data, establishing a correlation between different pollutants, identifying sources of pollution, and determining the most significant parameters, different multivariate statistical approaches such as Cluster analysis (CA), Principle component analysis (PCA), correlation analysis, and multiple linear regression analysis (MLR) were used. The aim of this study is to evaluate the major air pollution sources in Hyderabad and to identify the most significant air pollutants based on their individual contributions to the Air Quality Index (AQI). Variation in air quality parameters collected for six air quality monitoring stations were represented using box or whisker plots. The data set has been grouped into four major clusters depending on the similarities in the air quality data. Major sources of air pollution in each cluster were identified using PCA. MLR analysis was used to create models for predicting AQI for each cluster based on concentrations of important air contaminants. The findings revealed that PM10 and PM2.5 play a significant role in determining AQI levels. © 2023 Author(s).
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COVID-19 pandemic has resulted in a halt to the daily lifestyle of people around the world and bound them to abide by the lockdown measures enforced to prevent the disease from further spreading. In India also, lockdown has been enforced from March 2020. As a result, the level of air pollutants in the atmosphere goes on decreasing. To know the air quality pattern of Bangalore city, ten stations around the city were selected. Air quality data of these stations has been availed from the Central Pollution Control Board (CPCB) of India website. Box chart concept of graphical representation has been applied to show the range of temporal variation of the air pollutants selected (CO, NO2, Ozone, PM2.5, PM10 and SO2) for the study area over two distinct periods (pre-lockdown and post-lockdown). It has been observed that all the pollutants level were drastically or significantly reduced except for SO2 which showed mixed behavior during the entire study period probably due to no restriction on the operation of power plants. GIS based contour mapping is done for each pollutant over the entire study area and separately for two distinct periods (pre-lockdown and post-lockdown). It was found that, change in CO level over the entire study area was significant and the reason behind it was complete restriction on vehicular movement which is the primary reason for CO emission in atmosphere. Reduction in PMs and ozone was also noticeable, but change in SO2 over the entire study area was almost insignificant. To find out the probable sources of pollution during the lockdown and before the lockdown period and the most significant parameters statistical approach has been adopted. The whole data set has been grouped based on similarity and divided into three distinct clusters for both pre-lockdown and post-lockdown period separately using Hierarchical Agglomerative Cluster Analysis (HACA) concept. Principal Component Analysis (PCA) was done for each of the clusters and each time period considered. From the results of PCA it can be confirmed that the most significant parameters were PM10, PM2.5, ozone and SO2. Results suggest that the probable sources of pollution during pre-lockdown period were vehicular emissions, power plants, industrial activities etc. In contrast, during post-lockdown period the sources of pollution were power plants, construction sites and household pollution only. MLR (Multiple Linear Regression) models were developed to predict Air Quality Index (AQI). Most of the models showed good fit with adjusted R2 value more than 0.9. Regression coefficient (R2) values for PM10 followed PM2.5 were highest in each cluster. © 2023 Author(s).
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PurposeThe aim of this paper is to evaluate the influence of distance learning of the subject Operational Research in terms of the impact of the COVID-19 pandemic on the quality of teaching and the success of this course, to find out the satisfaction of students with the online learning, and the impact on the performance.Design/methodology/approachGrades of students from the subject were collected from the Faculty of Business and Economics of Mendel University in Brno between 2009 and 2021. A questionnaire concerning the views of students on online teaching of the subject and its comparison with face-to-face teaching was conducted, and the data obtained from 94 respondents were statistically processed by cluster analysis and the K-means method.FindingsA comparison of the results of examinations from the years taught in classical face-to-face form and from the period when teaching took place only online showed no significant effect on the final grades of the students. The results show that the students were basically divided into two-halves: one-half that preferred online teaching and the other that supported a more face-to-face form of teaching. Most of the students highly appreciated the tutorial videos provided because of the possibility of repeated viewing.Originality/valueThe paper shows that online teaching may be a suitable replacement for standard teaching. The paper answers the question whether some online elements can be integrated in the standard form of teaching.
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Adding to the already polarizing 2020 general election was the COVID-19 pandemic. One way in which this pandemic greatly affected the election was through an increased participation in by-mail, or mail-in, ballots. The state of North Carolina experienced a 316 percent increase in by-mail votes between 2016 and 2020, when approximately 977,186 votes were cast by mail. It is no surprise that this increase was due to the COVID-19 pandemic;however, these by-mail voting patterns are spatial in nature and vary across the state. This research measures to what degree COVID-19 rates affected by-mail voting rates. Using geographic information systems data developed from robust tabular files provided by the North Carolina State Board of Elections, by-mail votes were calculated and mapped at ZIP code scale and compared to COVID-19 rates measured at different dates. By-mail rates taken from final absentee tallies for the highest and lowest COVID-19 ZIP codes saw no significant differences across multiple dates (30 September 2020 and 31 October 2020) when COVID-19 data were collected. COVID-19 hot spots (high COVID-19 rates surrounded by other high COVID-19 rates) were extracted using geostatistical techniques and compared to COVID-19 cold spots (low COVID-19 rates surrounded by other low COVID-19 rates). It was found the lowest by-mail rates actually occurred in these COVID-19 hot spots across both dates, as well a metric that expressed percentage change in COVID-19 rates in the month before the 2020 election.Alternate :COVID-19使得已经两极分化的2020年美国大选, 变得更加雪上加霜。COVID-19影响选举的一种方式是邮寄选票的增加。2016年至2020年, 北卡罗来纳州的邮寄选票增加了316%, 共约977,186张。毫无疑问, COVID-19导致了邮寄选票的增加。然而, 邮寄选票在本质上是空间性的, 并且在北卡罗来纳州的各个地方具有差异性。本研究计算了COVID-19发病率对邮寄选票比例的影响程度。利用北卡罗来纳州选举委员会提供的准确的表格文件, 本文制作了地理信息系统数据, 在邮政编码尺度上对邮寄选票进行计算和制图, 并将这些邮寄选票与不同时间的COVID-19发病率进行了比较。在拥有最高和最低COVID-19发病率的邮政编码和不同时间（2020年9月30日和2020年10月31日）, 从缺失人数统计中得到的邮寄选票比例没有显著差异。利用地学统计方法提取COVID-19热点（COVID-19高发病率在空间上被其它高发病率所包围）, 并与COVID-19冷点（COVID-19低发病率在空间上被其它低发病率所包围）进行比较。结果发现, 在这两个时间内, 最低邮寄选票比例出现在COVID-19热点地区。本文还制定了一个指标, 可以表示2020年大选前一个月的COVID-19发病率百分比的变化。
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The COVID-19 pandemic has affected many organizations and the way work is performed, emphasizing the importance of human resource management (HRM). Although the HRM literature confirms the vital role of HR managers for firm recovery and survival during a crisis, knowledge remains scarce about what HR managers actually do in times of high disruptions, like a crisis. In this chapter, we explore the use of high-performance work system (HPWS) practices among 269 HR managers during the COVID-19 pandemic;a common set of HRM practices used to engender employee and organisational performance. Using cluster analysis, we identify two distinct groups of HR managers, engaging either in high or low levels of HPWS practices during the crisis. We then investigate how these two clusters relate to organizational and individual characteristics, as well as HR managers' perceptions of the pandemic. For instance, we find that those managers implementing HPWS to a high degree perceive more changes in their work context than their counterparts do. Our findings provide unique and new insights into group-specific differences associated with high and low levels of HPWS practices. We thereby contribute to the HR literature a fuller understanding of HRM system use in times of a crisis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
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BackgroundLupus is a heterogenous diseases which results in significant premature mortality. Most studies have evaluated risk factors for lupus mortality using regression models which considers the phenotype in isolation. Identifying clusters of patients on the other hand may help overcome the limitations of such analyses.ObjectivesThe objectives of this study were to describe the causes of mortality and to analyze survival across clusters based on clinical phenotype and autoantibodies in patients of the Indian SLE Inception cohort for Research (INSPIRE)MethodsOut of all patients, enrolled in the INSPIRE database till March 3st 2022, those who had <10% missing variables in the clustering variables were included in the study. The cause of mortality and duration between the recruitment into the cohort and mortality was calculated. Agglomerative unsupervised hierarchical cluster analysis was performed using 25 variables that define SLE phenotype in clinical practice. The number of clusters were fixed using the elbow and silhouette methods. Survival rates were examined using Cox proportional hazards models: unadjusted, adjusted for age at disease onset, socio-economic status, steroid pulse, CYC, MMF usage and cluster of the patients.ResultsIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting.Out of 2211 patients in the cohort, 2072 were included into the analysis. The median (IQR) age of the patients was 26 (20-33) years and 91.7% were females. There were 288 (13.1%) patients with juvenile onset lupus. The median (range) duration of follow up of the patients was 37 (6-42) months. There were 170 deaths, with only 77 deaths occurring in a health care setting. Death within 6 months of enrollment occured in in 80 (47.1%) patients. Majority (n=87) succumbed to disease activity, 23 to infections, 24 to coexisting disease activity and infection and 21 to other causes. Pneumonia was the leading cause of death (n=24). Pneumococcal infection led to death in 11 patients and SARS-COV2 infection in 7 patients. The hierarchical clustering resulted in 4 clusters and the characteristics of these clusters are represented in a heatmap (Figure-1A,B). The mean (95% confidence interval [95% CI] survival was 39.17 (38.45-39.90), 39.52 (38.71-40.34), 37.73 (36.77-38.70) and 35.80 (34.10-37.49) months (p<0.001) in clusters 1, 2, 3 and 4, respectively with an HR (95% CI) of 2.34 (1.56, 3.49) for cluster 4 with cluster 1 as reference(Figure 1C). The adjusted model showed an HR (95%CI) for cluster 4 of 2.22 (1.48, 3.22) with an HR(95%CI) of 1.78 (1.29, 2.45) for low socioeconomic status as opposed to a high socioeconomic status (Table 1).ConclusionIndian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting. Disease activity as determined by the traditional activity measures may not be sufficient to understand the true magnitude of organ involvement resulting in mortality. Clinically relevant clusters can help clinicians identify those at high risk for mortality with greater accuracy.Table 1.Univariate and multivariate Cox regression models predicting mortalityUnivariateMultivariateVariablesHazard ratio (95% Confidence interval)P valueHazard ratio (95% Confidence interval)P valueCluster1Reference-Reference-20.87 (0.57, 1.34)0.5320.89 (0.57, 1.38)0.59831.22 (0.81, 1.84)0.3371.15 (0.76, 1.73)0.51342.34 (1.56, 3.49)<0.0012.22(1.48, 3.22)<0.001Socioeconomic statusLower1.78 (1.29, 2.45)<0.001Pulse steroidYes1.6 (0.99, 2.58)0.051MMFYes0.71 (0.48, 1.05)0.083CYCYes1.42 (0.99, 2.02)0.052Proliferative LNYes0.99 (0.62, 1.56)0.952Date of birth age0.99 (0.98, 1.01)0.657CYC- cyclophosphamide, MMF- Mycophenolate mofetilFigure 1.A. Agglomerative clustering dendrogram depicting the formation of four clusters. B.Heatmap depicting distribution of variables used in clustering C. Kaplan-Meier curve showing the survival function across the 4 clusters[Figure omitted. See PDF]REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone eclared.
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Iron and zinc are important minerals in humans in sub Saharan Africa, whose deficiency is known as "hidden hunger" due to the lack of recognised symptoms in the early stages. Although iron deficiency is the most prevalent, zinc is also involved in inhibition of replication of viruses, including the corona virus (COVID-19). In North Kivu and South Kivu provinces where more than 50% of common bean is produced and consumed in Democratic Republic of Congo, 36% and 47% of preschool children are anemic due to iron deficiency. This paradox is mainly due to insufficiency of iron-rich foods. The aim of this study is to characterise 59 iron and zinc biofortified varieties together with six local varieties of common bean for a potential selection programme in Butembo town in the Democratic Republic of Congo. We focused on 15 qualitative and five quantitative parameters. The qualitative parameters were helpful to distinguish the different morphotypes and for cluster analysis. In addition to the descriptive statistics, the quantitative data were used for Pearson correlation and for principal component analysis, PCA. Qualitative parameters enabled grouping of the study genotypes into 14 morphotypes according to the aspect and colour of the seed coat, the colour around the hilum and the size of seeds. Clustering grouped the 65 genotypes into 12 clusters with the most similar genotypes grouped in the same cluster. Quantitative parameters showed that the study genotypes were dissimilar (P=0.00). A positive correlation was obtained between the days to flowering and the days to maturity (P<0.05) and between the number of pods per plant and the days to flowering. A strong correlation was found between the number of pods per plant and seeds per pod (P<0.01). In contrast, a negative correlation was observed between the 100 seed weight and the number of seeds per pod. The PCA represented on two perpendicular axes showed 64.1% of the total variance of which the 42.3% is explained by the first axis and 21.8% by the second axis. Overall, the study genotypes are morphologically and quantitatively different and thus can be used in a selection programme.
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Entrepreneurship can provide a creative, disruptive, problem-solving-oriented approach to the current economic, environmental, and social challenges of the world. This article aims to provide an analysis about the way universities can have an impact on developing entrepreneurial competence in students through extracurricular activities. The research relies on a questionnaire survey of students at the University of Petrosani, who participated in a range of entrepreneurial activities both online during the COVID-19 pandemic and face-to-face afterwards. The methodology consisted of applying principal component analysis to reduce the dimensionality of the indicators, followed by classification of the respondents through cluster analysis and training of a feedforward neural network. After finishing the network-training process, the error was minimized, resulting in three classes of respondents. Furthermore, based on the three classes, follow-up conclusions, policies, and decisions can be issued regarding the perception of entrepreneurship at the societal level, which is beneficial for academia and entrepreneurs, as well as for future research undertaken in this field. The key conclusion of our research is that entrepreneurship education is a real facilitator of the transition to sustainable entrepreneurship. Students perceived meeting successful entrepreneurs as being among the most effective extracurricular activities, assessing online activities as useful, and the field of study proved to be an important factor in their entrepreneurial intention.
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Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote learning/working and telemedicine has significantly increased. In this context, preserving high Quality of Service (QoS) and maintaining low-latency communication are of paramount importance. In cellular networks, the incorporation of unmanned aerial vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing Line of Sight (LoS) links. The UAV's limited battery life and its signal attenuation in indoor areas, however, make it inefficient to manage users' requests in indoor environments. Referred to as the cluster-centric and coded UAV-aided femtocaching (CCUF) framework, the network's coverage in both indoor and outdoor environments increases by considering a two-phase clustering framework for Femto access points (FAPs)' formation and UAVs' deployment. Our first objective is to increase the content diversity. In this context, we propose a coded content placement in a cluster-centric cellular network, which is integrated with the coordinated multipoint (CoMP) approach to mitigate the intercell interference in edge areas. Then, we compute, experimentally, the number of coded contents to be stored in each caching node to increase the cache-hit-ratio, signal-to-interference-plus-noise ratio (SINR), and cache diversity and decrease the users' access delay and cache redundancy for different content popularity profiles. Capitalizing on clustering, our second objective is to assign the best caching node to indoor/outdoor users for managing their requests. In this regard, we define the movement speed of ground users as the decision metric of the transmission scheme for serving outdoor users' requests to avoid frequent handovers between FAPs and increase the battery life of UAVs. Simulation results illustrate that the proposed CCUF implementation increases the cache-hit-ratio, SINR, and cache diversity and decrease the users' access delay, cache redundancy, and UAVs' energy consumption.
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The label "autoethnography” has been applied to a wide range of knowledge-producing practices, from what might be considered "normal” science to narrative-driven writing to performance. These debates highlight some of the most fundamental tensions about legitimate ways of knowing/ knowledge production in the contemporary world. Further, one strength of autoethnography as a method lies in situating personal experience within broader political, social, and cultural events, which can create new opportunities in academia for voices often silenced. With these elements of autoethnography in mind, and in response to the COVID-19 pandemic, the authors founded an interdisciplinary autoethnography course cluster and lab at Oberlin College and Conservatory. In this essay, we describe the course cluster, lab, and successes and challenges of each. We also discuss the strategies and innovations of introducing undergraduate students to autoethnography. We hope that our model will be instructive for colleagues with similar goals at their institutions. Through the cross-course workshops and collaborative exercises of the autoethnography lab, our students had the opportunity to use autoethnography not just to analyze their communities but also to build a community of practice. © 2023 by The Regents of the University of California. All rights reserved.
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BACKGROUND: Patients with functional neurological disorders (FND) often present with multiple motor, sensory, psychological and cognitive symptoms. In order to explore the relationship between these common symptoms, we performed a detailed clinical assessment of motor, non-motor symptoms, health-related quality of life (HRQoL) and disability in a large cohort of patients with motor FND. To understand the clinical heterogeneity, cluster analysis was used to search for subgroups within the cohort. METHODS: One hundred fifty-two patients with a clinically established diagnosis of motor FND were assessed for motor symptom severity using the Simplified Functional Movement Disorder Rating Scale (S-FMDRS), the number of different motor phenotypes (i.e. tremor, dystonia, gait disorder, myoclonus, and weakness), gait severity and postural instability. All patients then evaluated each motor symptom type severity on a Likert scale and completed questionnaires for depression, anxiety, pain, fatigue, cognitive complaints and HRQoL. RESULTS: Significant correlations were found among the self-reported and all objective motor symptoms severity measures. All self-reported measures including HRQoL correlated strongly with each other. S-FMDRS weakly correlated with HRQoL. Hierarchical cluster analysis supplemented with gap statistics revealed a homogenous patient sample which could not be separated into subgroups. CONCLUSIONS: We interpret the lack of evidence of clusters along with a high degree of correlation between all self-reported and objective measures of motor or non-motor symptoms and HRQoL within current neurobiological models as evidence to support a unified pathophysiology of 'functional' symptoms. Our results support the unification of functional and somatic syndromes in classification schemes and for future mechanistic and therapeutic research.
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Background: Enhance Access to Kidney Transplantation and Living Kidney Donation (EnAKT LKD) is a quality improvement intervention designed to enhance access to kidney transplantation and living kidney donation. We conducted a cluster-randomized clinical trial to evaluate the effect of the intervention versus usual care on completing key steps toward receiving a kidney transplant. Objective: To prespecify the statistical analysis plan for the EnAKT LKD trial. Design: The EnAKT LKD trial is a pragmatic, 2-arm, parallel-group, registry-based, open-label, cluster-randomized, superiority, clinical trial. Randomization was performed at the level of the chronic kidney disease (CKD) programs (the "clusters"). Setting: Twenty-six CKD programs in Ontario, Canada. Participants: More than 10 000 patients with advanced CKD (ie, patients approaching the need for dialysis or receiving maintenance dialysis) with no recorded contraindication to receiving a kidney transplant. Methods: The trial data (including patient characteristics and outcomes) will be obtained from linked administrative health care databases (the "registry"). Stratified covariate-constrained randomization was used to allocate the 26 CKD programs (1:1) to provide the intervention or usual care from November 1, 2017, to December 31, 2021 (4.17 years). CKD programs in the intervention arm received the following: (1) support for local quality improvement teams and administrative needs; (2) tailored education and resources for staff, patients, and living kidney donor candidates; (3) support from kidney transplant recipients and living kidney donors; and (4) program-level performance reports and oversight by program leaders. Outcomes: The primary outcome is completing key steps toward receiving a kidney transplant, where up to 4 unique steps per patient will be considered: (1) patient referred to a transplant center for evaluation, (2) a potential living kidney donor begins their evaluation at a transplant center to donate a kidney to the patient, (3) patient added to the deceased donor transplant waitlist, and (4) patient receives a kidney transplant from a living or deceased donor. Analysis plan: Using an intent-to-treat approach, the primary outcome will be analyzed using a patient-level constrained multistate model adjusting for the clustering in CKD programs. Trial Status: The EnAKT LKD trial period is November 1, 2017, to December 31, 2021. We expect to analyze and report the results once the data for the trial period is available in linked administrative health care databases. Trial Registration: The EnAKT LKD trial is registered with the U.S. National Institute of Health at clincaltrials.gov (NCT03329521 available at https://clinicaltrials.gov/ct2/show/NCT03329521). Statistical Analytic Plan: Version 1.0 August 26, 2022.
Contexte: EnAKT LKD est une intervention d'amélioration de la qualité visant à améliorer l'accès à la transplantation rénale et au don vivant de rein. Nous avons mené un essai clinique randomisé par grappes afin d'évaluer l'effet de l'intervention, par rapport aux soins habituels, sur le taux d'étapes clés réalisées dans le processus de réception d'une greffe de rein. Objectif: Exposer les grandes lignes du plan d'analyse statistique de l'essai EAKT LKD. Conception: EAKT LKD est un essai clinique pragmatique ouvert, à deux bras, en groupes parallèles, basé sur un registre, et randomisé en grappes. La randomisation a été réalisée au niveau des programmes d'insuffisance rénale chronique (IRC) (les « grappes ¼). Cadre: 26 programmes d'IRC en Ontario (Canada). Sujets: Plus de 10 000 patients atteints d'IRC de stade avancé (des patients approchant le besoin de dialyse ou recevant une hémodialyse d'entretien) sans contre-indication documentée à la greffe rénale. Méthodologie: Les données de l'essai (y compris les caractéristiques et les résultats des patients) seront obtenues à partir de bases de données administratives en santé (le « registre ¼). La randomisation stratifiée avec contraintes de covariables a servi à répartir les 26 programmes d'IRC (1:1) selon qu'ils allaient fournir l'intervention ou les soins habituels entre le 1er novembre 2017 et le 31 décembre 2021 (4,17 ans). Les programmes d'IRC du bras d'intervention ont eu droit au soutien suivant: (1) des équipes locales d'amélioration de la qualité et du soutien administratif; (2) de l'information et des ressources sur mesure pour le personnel, les patients et les donneurs vivants; (3) du soutien de la part de receveurs et de donneurs vivants; et (4) des rapports sur le rendement au niveau du programme et une surveillance assurée par les chefs de programme. Résultats: Le principal critère d'évaluation est le taux d'étapes clés accomplies vers la réception d'une greffe de rein, où jusqu'à quatre étapes uniques par patient seront comptabilisées: (1) le patient est aiguillé vers un centre de transplantation pour évaluation; (2) un possible donneur vivant de rein contacte un centre de transplantation pour un receveur en particulier et amorce son évaluation; (3) le patient est ajouté à la liste d'attente pour une transplantation d'un donneur décédé, et (4) le patient reçoit une greffe de rein d'un donneur vivant ou décédé. Plan d'analyse: Selon une approche fondée sur l'intention de traiter, le critère d'évaluation principal sera analysé au niveau du patient en utilisant un modèle multiétats contraint, corrigé dans les programmes d'IRC en fonction du regroupement. Statut de l'essai: L'essai EnAKT LKD s'est tenu du 1er novembre 2017 au 31 décembre 2021. Nous analyserons les résultats et en rendrons compte dès que les données seront disponibles dans les bases de données administratives couplées du système de santé.
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Introduction/Aim: Data visualisation is key to informing data-driven decision-making, yet this is an underexplored area of suicide surveillance. By way of enhancing a real-time suicide surveillance system model, an interactive dashboard prototype has been developed to facilitate emerging cluster detection, risk profiling and trend observation, as well as to establish a formal data sharing connection with key stakeholders via an intuitive interface. Materials and Methods: Individual-level demographic and circumstantial data on cases of confirmed suicide and open verdicts meeting the criteria for suicide in County Cork 2008-2017 were analysed to validate the model. The retrospective and prospective space-time scan statistics based on a discrete Poisson model were employed via the R software environment using the "rsatscan" and "shiny" packages to conduct the space-time cluster analysis and deliver the mapping and graphic components encompassing the dashboard interface. Results: Using the best-fit parameters, the retrospective scan statistic returned several emerging non-significant clusters detected during the 10-year period, while the prospective approach demonstrated the predictive ability of the model. The outputs of the investigations are visually displayed using a geographical map of the identified clusters and a timeline of cluster occurrence. Discussion: The challenges of designing and implementing visualizations for suspected suicide data are presented through a discussion of the development of the dashboard prototype and the potential it holds for supporting real-time decision-making. Conclusions: The results demonstrate that integration of a cluster detection approach involving geo-visualisation techniques, space-time scan statistics and predictive modelling would facilitate prospective early detection of emerging clusters, at-risk populations, and locations of concern. The prototype demonstrates real-world applicability as a proactive monitoring tool for timely action in suicide prevention by facilitating informed planning and preparedness to respond to emerging suicide clusters and other concerning trends.
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Objective: This study aimed to investigate COVID-19 vaccine acceptance and related factors in individuals with mental disorders in Korea. Methods: We surveyed 572 individuals with mental disorders about their attitudes toward COVID-19 vaccination using a 7-item self-rating questionnaire on vaccine acceptance and hesitancy. We categorized the respondents into groups based on their level of vaccine acceptance using hierarchical clustering. In addition, we evaluated the respondents' vaccination status and trust in sources of information regarding COVID-19 vaccines, and assessed their psychological characteristics using the Patient Health Questionnaire-9, Gratitude Questionnaire-6, and Big Five Inventory-10. Results: Clustering revealed three groups according to vaccine acceptance: 'totally accepting' (n= 246, 43.0%), 'somewhat accepting' (n= 184, 32.2%), and 'hesitant' (n= 142, 24.8%) groups. Three quarters of all participants, who belonged to the 'totally accepting' or 'somewhat accepting' groups, were willing to receive a COVID-19 vaccine despite concerns about its side effects. Individuals in the high vaccine acceptance group were older (F= 12.52, p< 0.001), more likely to receive the influenza vaccine regularly, and more likely to trust formal information sources. Additionally, they had higher levels of gratitude (F= 21.00, p< 0.001) and agreeableness (F= 4.50, p= 0.011), and lower levels of depression (χ2= 11.81, p= 0.003) and neuroticism (F= 3.71, p= 0.025). Conclusion: The present study demonstrated that individuals with mental disorders were generally willing to receive COVID-19 vaccination. However, they weighed its need and effectiveness against potential side effects before coming to a decision. It is important to understand the behavioral and psychological characteristics associated with vaccine acceptance, to effectively communicate its importance to individuals with mental disorders.
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INTRODUCTION: SARS-CoV-2, a severe acute respiratory illness virus that emerged in China in late 2019, continues to spread rapidly around the world, accumulating mutations and thus causing serious concern. Five virus variants of concern are currently known: Alpha (lineage B.1.1.7), Beta (lineage B.1.351), Gamma (lineage P.1), Delta (lineage B.1.617.2), and Omicron (lineage B.1.1.529). In this study, we conducted a molecular epidemiological analysis of the most prevalent genovariants in Moscow and the region. The aim of the study is to estimate the distribution of various variants of SARS-CoV-2 in Moscow city and the Moscow Region. MATERIALS AND METHODS: 227 SARS-CoV-2 sequences were used for analysis. Isolation of the SARS-CoV-2 virus was performed on Vero E6 cell culture. Sequencing was performed by the Sanger method. Bioinformatic analysis was carried out using software packages: MAFFT, IQ-TREE v1.6.12, jModelTest 2.1.7, Nextstrain, Auspice v2.34. RESULTS: As a result of phylogenetic analysis, we have identified the main variants of the virus circulating in Russia that have been of concern throughout the existence of the pandemic, namely: variant B.1.1.7, which accounted for 30% (9/30), AY.122, which accounted for 16.7% (5/30), BA.1.1 with 20% (6/30) and B.1.1 with 33.3% (10/30). When examining Moscow samples for the presence of mutations in SARS-CoV-2 structural proteins of different genovariants, a significant percentage of the most common substitutions was recorded: S protein D614G (86.7%), P681H/R (63.3%), E protein T9I (20.0%); M protein I82T (30.0%), D3G (20.0%), Q19E (20.0%) and finally N protein R203K/M (90.0%), G204R/P (73.3 %). CONCLUSION: The study of the frequency and impact of mutations, as well as the analysis of the predominant variants of the virus are important for the development and improvement of vaccines for the prevention of COVID-19. Therefore, ongoing molecular epidemiological studies are needed, as these data provide important information about changes in the genome of circulating SARS-CoV-2 variants.
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COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Moscow/epidemiology , COVID-19/epidemiology , PhylogenyABSTRACT
The present study investigated the effects of the first COVID-19 lockdown on the Cultural and Social Capitals in Italy in a large group of adults (n = 1125). The relationships between the COVID-19 spread and participants' Cultural Capital, Social Capital, educational level, occupational prestige, and age were studied using structural equation models. For women but not for men, pandemic spread was positively affected by occupational prestige and it had a positive relationship with their Social Capital (women: CFI = 0.949; RMSEA = 0.059 [CI = 0.045-0.075]; men: CFI = 0.959; RMSEA = 0.064 [CI = 0.039-0.087]). Moreover, the participants were divided into three validated clusters based on their Cultural and Social Capitals levels to investigate changes in the Capitals compared with the pre-lockdown period. It was found that the lockdown contributed to improving the gap among individuals increasing high levels and decreasing low levels of both the Capitals. People with high Cultural and Social Capitals seemed to have seized the opportunity given by COVID-19 restrictions to cultivate their cultural interests and become more involved within their networks. In contrast, individuals with low Cultural and Social Capitals paid the highest price for the social isolation. Given that the Capitals encourage healthy behavior and influence well-being and mental health, institutions should develop or improve their policies and practices to foster individual resources, and make fairer opportunities available during the pandemic. Supplementary Information: The online version contains supplementary material available at 10.1007/s11205-023-03140-7.
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This study aims a more thorough understanding of individuals' motivations and determinants of working from home (WFH) at various phases of the pandemic. To achieve this research goal, we analyze attitudes towards WFH, the profiles of various types of workers engaged in WFH, and the determinants of the current and future expected frequency of WFH among 816 workers in Hong Kong. We identify four types of teleworkers: (1) those with little employer support, (2) those distracted with tech problems, (3) those with good home office, and (4) those with substantial employer support. Separate latent-class choice models present that WFH frequencies in early phases of the pandemic (and at the moment), attitudes towards WFH, and certain constraining/facilitating factors affect the (expected) frequency of WFH. This study provides valuable insights into the types of teleworkers and the determinants of WFH, which will help policymakers create ways to encourage (or discourage) the future frequency of WFH.
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The refurbishment opportunities provided by climate policies require an adequate knowledge of the school building stock, characterised by an urgent need of maintenance. Nevertheless, empirical evidence on energy performance of school samples appears limited due to the difficulty in retrieving data, although field data analysis is crucial in the built environment management. This study aims to explore existing energy conditions of an educational building sample hosting pre-schools, primary and lower secondary schools, located in southern Italy (Apulia Region). Firstly, an overview of the schools based on data retrieved from the regional dataset was performed. Then, more than 1000 buildings were clustered based on two predictors (construction year and surface-to-volume ratio), identifying five clusters representing the majority Apulian schools. In addition, billed gas and electricity data collected for 47 schools over a five-year period (2017-2021) were analysed, identifying annual and monthly trends, benchmarks, and mean values, which account for 46.5 (gas consumption), 15.59 kWh/m2 (electricity consumption). On average, source total consumption in 2020 experienced a reduction of 20%, partly due to Covid-19 restrictive measures. Finally, factors affecting heating consumptions were explored, and a regression analysis was performed, identifying heating degree days, construction year and boiler power to be the most significant.
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Objective To analyze the epidemiological characteristics of COVID-19 cluster epidemic in Huizhou from January to February in 2020, and we provide experience and reference for the prevention and control of cluster epidemic. Methods Descriptive epidemiology was used to analyze the clusters of COVID-19 in Huizhou city. Results From January to February in 2020, a total of 19 COVID-19 cluster outbreaks were reported in Huizhou. The most common cluster outbreaks were in Huidong county (8 cases), Boluo county (3 cases) and Huiyang district (3 cases). There were 59 cases involved in 19 outbreaks, among which 46 were confirmed cases, and 13 were asymptomatic infected. The sex ratio of male to female was 0.84: 1, the age was 1-85 years old. The 19 cases of outbreaks were all caused by imported cases, among which 13 cases were imported from Wuhan (68.4%), 3 cases were imported from Hubei province except Wuhan (15.8%), and 3 cases were imported from other provinces and cities (15.8%). There were 13 cases (68.4%) in the first generation, and 6 cases (31.6%) in the second generation. Events exposed place were variety, including 3 (15.8%) simple family exposure, 13 (68.4%) joint exposure, exposure family, 1 (5.26%) of the joint exposure, family exposure, family dinners, 1 (5.26%) of the joint exposure, family exposure, exposure (hotel) exposed in public places, 1 (5.26%) of the collective unit (workplace) exposure. Conclusion All the COVID - 19 cluster outbreaks in Huizhou city were caused by imported cases, most of which occurred in the family and were caused by families living together and eating together. As the number of people returning to work, production and school increases, various prevention and control measures should be implemented in key areas, key populations and key places to prevent the outbreak from rebounding.Copyright © China Tropical Medicine 2021.