关键词： Artificial intelligence   Inflation   Machine learning   Neural network   Russia-Ukraine war   West Africa   ECOWAS COMMON CURRENCY   TIME-SERIES   INFLATION   FORECASTS   MACHINE  

摘要： The accuracy of predicting Consumer Price Index (CPI) in West African economies is a complex issue influenced by various factors, including COVID-19 and ongoing Russia-Ukraine war. The current study examined the effectiveness of three different models, including Autoregressive Integrated Moving Average (ARIMA), Extreme Learning Machine (ELM), and Evidential Neural Network with Gaussian Random Fuzzy Numbers (EVNNGRFN), in predicting the CPI for four West African nations: Ghana, Guinea Bissau, Nigeria, and Togo. The study use dummy variables to capture the periods of COVID-19 and Russia-Ukraine war. The EVNN-GRFN model demonstrated superior performance compared to the ARIMA model in terms of prediction accuracy. However, the incorporation of information about COVID-19 and the Russo-Ukrainian war had a varying impact on the performance of the EVNN-GRFN model, depending on the country. EVNN-GRFN significantly enhanced prediction accuracy by 12.93%, 7.14%, and 16.96% for Guinea Bissau, Nigeria, and Togo, respectively, compared to ARIMA. While incorporating information about COVID-19 and the Russo-Ukrainian war worsened the predictive accuracy for Guinea Bissau and Nigeria for the EVNN-GRFN model, it improved the accuracy by 7.70% for Ghana and 1.12% for Togo. This information only improved the accuracy of ELM for Guinea Bissau by 6.51%, but it worsened accuracy for Ghana, Nigeria, and Togo. Overall, the findings suggest that the EVNN-GRFN model is a promising tool for predicting CPI in West African economies and can be used to inform policy decisions regarding economic integration, monetary policy, and investment.

关键词： COVID-19   Coronaphobia   Phobias   Fears   Factor analysis   QUESTION  

摘要： Coronaphobia represents the fears and phobias attributed to the COVID-19 virus and pandemic. The COVID-19 Phobia Scale, previously validated as a four-factor structure, is a widely used multidimensional measure to assess coronaphobia. The current study scrutinized various competing factor structures of this instrument to identify the optimal psychometric representation of coronaphobia. Adults (N = 412) ranging in age from 19 to 84 years completed the COVID-19 Phobia Scale. Several theoretically plausible factor structures of coronaphobia were tested and compared using confirmatory factor analysis: four-factor structure, one-factor structure, higher-order factor structure, and five-factor bifactor structure. The one-factor structure showing an overarching factor of COVID-19 phobia revealed the poorest fit to the data. The five-factor bifactor structure that allowed every item to double-load on the COVID-19 general phobia factor alongside one of the COVID-19 specific phobia factors (psychological phobia, psycho-somatic phobia, economic phobia, or social phobia) produced the strongest fit indices and was superior to the widely accepted four-factor structure. The five-factor bifactor structure demonstrated multi-group measurement invariance across gender, race, age, and state urbanization. Furthermore, the general phobia factor and the psycho-somatic phobia factor from the five-factor bifactor structure uniquely predicted present moment state anxiety using structural equation modeling. This psychometric investigation underscores that coronaphobia is experienced as a general pandemic fear that is simultaneously experienced with specific domains of pandemic fears. Theoretical and methodological insights are offered for conceptualizing and measuring coronaphobia and understanding how pandemic phobias differ from traditional phobias.

关键词： COVID-19   Child mental health   Parenting   Person-centred methodology   Latent transition analysis   DIFFICULTIES QUESTIONNAIRE   EXTERNALIZING PROBLEMS   DEPRESSION   STRENGTHS   PERCEPTIONS   BEHAVIORS   STRESS   SAMPLE  

摘要： BackgroundThe COVID-19 pandemic has had a substantial impact on children and families worldwide. Children's mental health has been at the forefront of pandemic research, with several observational studies documenting its decline. Limited person-centred research exists, however, investigating the diverse mental health responses of vulnerable children during *** purpose of this study is to examine the profiles of 289 low-income children's mental health transitions from pre-COVID-19 to during ***' reports of children's mental health using the Strengths and Difficulties Questionnaire from before (X over bar \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{X }$$\end{document}= 2.73 years, SD = 0.23) and during (X over bar \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{X }$$\end{document}= 5.31 years, SD = 0.59) COVID-19 were *** comparable profile solutions were identified pre- and early during the pandemic. Latent transition analysis revealed diverse patterns of children's mental health trajectory from prior to during COVID-19. Based on transition probabilities, the majority of children in the Average Levels of Internalizing/Externalizing Problems and Externalizing Problems profiles pre-pandemic showed stability in profile membership. Interestingly, most children in the high levels of Internalizing/Externalizing Problems profile pre-pandemic experienced some improvement in their mental health. Pre-pandemic maternal mental health and parenting had significant associations with children's profile membership at both time *** fi

关键词： Aggression   Violence   Healthcare workers   COVID-19 pandemic   Meta-analysis   Women's rights   HETEROGENEITY   NURSES  

摘要： Objectives: Despite the critical value of healthcare workers (HCWs) demonstrated during the COVID-19 pandemic, there remains a noted global surge in violence against this population. The present meta-analysis aimed to gather data on the prevalence of workplace violence (WPV) against HCWs and to determine if there is any difference based on gender. Study design: This was a systematic review and meta-analysis. Methods: A thorough search of PubMed/MEDLINE, Lilacs, and Cochrane Collaboration databases was conducted from the start of the COVID-19 pandemic until March 8, 2023. Two authors independently carried out screening, data extraction, and quality assessment, followed by statistical analysis using random-effects meta-analysis and subgroup analysis to assess heterogeneity. Results: We included 22 studies with 44,357 participants, of which 79.37% were women. The analysis revealed an overall prevalence of WPV similar in both women (51.86%, 95% confidence interval [CI]: 41.39-62.33) and men (51.45%, 95% CI: 40.95-61.95). There were considerable differences in gender-based WPV across geographic regions. Aggressions tend to be higher toward men in Asia (odds ratio [OR] 0.79, 95% CI 0.74-0.85, P < 0.001). Conversely, in Latin America, WPV prevalence was higher in women (OR 1.20, 95% CI 1.01-1.4, P = 0.035). HCWs from low- middle-income-level countries suffered a higher incidence of violence irrespective of gender compared with high- and upper-middle-income countries (72.36% vs 47.35%). Conclusions: Our data indicate that more than half of HCWs experienced WPV during the COVID-19 pandemic. In addition, women and HCWs in low-middle-income countries were notably vulnerable to WPV. A deeper understanding of the nuances behind violence against HCWs will help to facilitate tailored strategies for different demographical contexts. Registration: PROSPERO ID: CRD42023403970. (c) 2024 The Royal Society for Public Health. Published by Elsevier Ltd. All rights are reserved, including

关键词： Cognitive complaints   Fatigue   Functional connectivity   Post-COVID syndrome   White matter   FUNCTIONAL CONNECTIVITY   DEPRESSION   IMPAIRMENT   DAMAGE  

摘要： The main objective was to evaluate structural and functional connectivity correlates of fatigue in post-COVID syndrome, and to investigate the relationships with an objective measure of mental fatigue and with subjective cognitive complaints. One-hundred and twenty-nine patients were recruited after 14.79 +/- 7.17 months. Patients were evaluated with fatigue, neuropsychological, and subjective cognitive complaints assessments. Structural and functional magnetic resonance imaging were acquired, and functional connectivity, white matter diffusivity and grey matter volume were evaluated. Fatigue was present in 86 % of patients, and was highly correlated to subjective cognitive complaints. Fatigue was associated with structural and functional connectivity mostly in frontal areas but also temporal, and cerebellar areas, showing mental fatigue different pattern of functional connectivity correlates compared to physical fatigue. White matter diffusivity correlates were similar in fatigue and subjective cognitive complaints, located in the forceps minor, anterior corona radiata and anterior cingulum. Findings confirm that fatigue in post-COVID syndrome is related to cerebral connectivity patterns, evidencing its brain substrates. Moreover, results highlight the relationship between fatigue and subjective cognitive complaints. These findings point out the relevance of the multidisciplinary assessment of post-COVID syndrome patients with subjective cognitive complaints, in order to unravel the symptomatology beneath the patient's complaints.

关键词： Available online xxxx   Nurse staffing   Nurse work environment   Mortality   Covid-19 pandemic   Hospital   PATIENT MORTALITY   OUTCOMES   ENVIRONMENTS   LEGISLATION   EDUCATION  

摘要： Background: During the Covid-19 pandemic, Covid-19 mortality varied depending on the hospital where patients were admitted, but it is unknown what aspects of hospitals were important for mitigating preventable deaths. Objective: To determine whether hospital differences in pre-pandemic and during pandemic nursing resources- average patient-to-registered nurse (RN) staffing ratios, proportion of bachelor-qualified RNs, nurse work environments, Magnet recognition-explain differences in risk-adjusted Covid-19 mortality; and to estimate how many deaths may have been prevented if nurses were better resourced prior to and during the pandemic. Methods: This is a cross-sectional study of 87,936 Medicare beneficiaries (65-99 years old) hospitalized with Covid-19 and discharged (or died) between April 1 and December 31, 2020, in 237 general acute care hospitals in New York and Illinois. Measures of hospital nursing resources (i.e. patient-to-RN staffing ratios, proportion of bachelor-qualified RNs, nurse work environments, Magnet recognition) in the pre-pandemic period (December 2019 to February 2020) and during (April to June 2021) were used to predict in-hospital and 30-day mortality using adjusted logistic regression models. Results: The mean age of patients was 78 years (8.6 SD); 51 % were male (n = 44,998). 23 % of patients admitted to the hospital with Covid-19 died during the hospitalization (n = 20,243); 31.5 % died within 30-days of admission (n = 27,719). Patients admitted with Covid-19 to hospitals with better nursing resources pre-pandemic and during the pandemic were statistically significantly less likely to die. For example, each additional patient in the average nurses' workload pre-pandemic was associated with 20 % higher odds of in-hospital mortality (OR 1.20, 95% CI [1.12-1.28], p < 0.001) and 15% higher odds of 30-day mortality (OR 1.15, 95 % CI [1.09-1.21], p < 0.001). Hospitals with greater proportions of BSN-qualified RNs, better quality nurse work envi

关键词： Remaining burden   Potential deaths   COVID-19   Statistical model   Vaccination  

摘要： Background: Stringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures. Methods: Immune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained. Results: Accounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged >= 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older. Conclusions: Our estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.

关键词： Risk preferences   Time preferences   COVID-19   RISK ATTITUDES   IMPACT   STABILITY   BEHAVIOR   TIME  

摘要： This paper studies the impact of the COVID-19 pandemic on risk and time preferences. Using a longitudinal dataset from a survey of cab drivers in Lima (Peru), we document a significant increase in risk tolerance and patience. The changes are heterogeneous and monotonic by age: older cohorts become more risk-taking while younger ones become more patient. Our findings suggest that the pandemic could have affected individuals' behavior and socioeconomic outcomes via another channel, namely, changes in economic preferences.

关键词： Covid-19   Deep learning   DenseNet   Computed tomography images   Evaluation metrics   CLASSIFICATION   SOCIETY  

摘要： The novel coronavirus disease in human was detected in Wuhan, China and spread rapidly across countries each time mutating itself as a new variant. It has impacted not only the patients but also medical infrastructure a lot. Several artificial intelligence-based systems for detection of covid-19 in chest images have been proposed. This study aims to develop a deep learning-based approach that efficiently detect Covid-19 using chest Computed Tomography (CT) images. In this work, we propose an efficient and lightweight deep-learning architecture based on the concept of a densely connected network for Covid-19 detection. The proposed architecture is designed by stacking dense modules in which each layer is directly connected to the other layers, with very fewer number of neurons at each layer. The dense connection is used to improve the learning capability of the proposed model and the fewer number of neurons make network computationally efficient. CT images for covid-19 detection are effectively used for the detection of Covid-19 patients. We train and test our model on SARS-CoV-2 CT-scan datasets. The experimental results are evaluated on accuracy, sensitivity and F1 score. The Adam optimizer with binary cross entropy loss function gives 97.2% accuracy with 0.98 sensitivity, 0.97 precision and 0.97 F1 score. The model achieves maximum accuracy of 88% at precision 0.97%, specificity 0.82 and F1 score 0.89 with CovidCT dataset. The proposed model is compared with other state-of-the-art methods. The results of the proposed methods and its comparison shows acceptable level of performance on chest CT images.

关键词： advance care planning   group medical visits   shared medical appointments   telehealth   goals of care conversations   COVID-19   DOCUMENTATION  

摘要： Background The COVID-19 pandemic necessitated the transition from in person to virtual advance care planning (ACP) engagement efforts. This pilot initiative evaluated virtual group visits (GVs) and in-person GVs for ACP to determine their feasibility and *** Participants included patients in a Geriatric Medicine clinic who were referred by their primary care physician to an ACP GVs intervention. The ACP GVs had 2 sessions, led by clinicians with ACP expertise who facilitated a discussion on patients' values, goals, and preferences. Participants were provided with technical assistance to support use of the virtual platform. Evaluation included an ACP readiness survey, post-session feedback, GV observations, and electronic health record review at baseline and a 6 month follow-up for goals of care documentation and advance *** Seventy patients attended 46 ACP GVs from August 2019 to February 2022, including 16 in-person GVs and 54 virtual GVs. At a 6 month follow-up, for virtual GVs participants (n = 54), goals of care documentation increased from 31% to 93%, and advance directives increased from 22% to 30%. For in-person GVs participants (n = 16), goals of care documentation increased from 25% to 100%, and advance directives increased from 69% to 75%. All surveyed patients in both formats would recommend ACP *** ACP GVs are feasible and effective for supporting ACP, demonstrating an increase in both goals of care conversations and advance directives completion.