The college students' anxiety during the Coronavirus disease 2019 (COVID-19) epidemic remains unclear. We aimed to evaluate the college students' anxiety after returning to school during the COVID-19 ...epidemic, to provide reference for the management and nursing care of college students. We conducted a survey from September 15, 2021 to September 30, 2021 investigate the anxiety level of college students. The Self-rating Anxiety Scale was used for anxiety assessment. The Spearman correlation analysis was conducted to evaluate the correlation between students' anxiety and characteristics. Logistic regression analysis was used to explore the influencing factors of concurrent anxiety among college students. A total of 2168 college students were included, the incidence of anxiety was 30.07% in college students during the COVID-19 epidemic. Pearson correlation analyses showed that grade (R = 0.715), main use of computer and mobile phone (R = 0.622), daily exercise (R = 0.735), whether relatives or friends are infected with COVID-19 (R = 0.735) are associated with the anxiety level of college students (all P < .05). Logistic regression analysis indicated that senior year (Odds ratio OR = 2.064, 95% confidence interval CI: 1.355-3.001), online game (OR = 3.122, 95% CI: 2.562-3.899), relatives or friends are infected with COVID-19 (OR = 2.987, 95% CI: 1.901-3.451) are the independent risk factors of anxiety in college students (all P < .05). Daily exercise (OR = 0.514, 95% CI: 0.205-0.814) was the independent protective factors of anxiety in college students (P = .008). During the COVID-19 epidemic, college students have increased anxiety and there are many influencing factors. Administrators and educators should especially pay attention to the mental health of students with those risk factors to maintain students' physical and mental health.
Novel coronavirus (COVID‐19), a global threat whose source is not correctly yet known, was firstly recognised in the city of Wuhan, China, in December 2019. Now, this disease has been spread out to ...many countries in all over the world. In this paper, we solved a time delay fractional COVID‐19 SEIR epidemic model via Caputo fractional derivatives using a predictor–corrector method. We provided numerical simulations to show the nature of the diseases for different classes. We derived existence of unique global solutions to the given time delay fractional differential equations (DFDEs) under a mild Lipschitz condition using properties of a weighted norm, Mittag–Leffler functions and the Banach fixed point theorem. For the graphical simulations, we used real numerical data based on a case study of Wuhan, China, to show the nature of the projected model with respect to time variable. We performed various plots for different values of time delay and fractional order. We observed that the proposed scheme is highly emphatic and easy to implementation for the system of DFDEs.
INTRODUCTION: Post COVID -19 epidemics is in a critical situation which has to be properly managed with right preventive and curative measures to protect the economy and welfare of the Human beings.
...OBJECTIVES: Effective management of this terrific situation may be possible through the help of contact tracing and its application of AI mechanism. Here the authors as taken the available data for the testing of the significance of AI approach for contract tracing proper management of the post COVID epidemic situation.
METHODS: Here contact tracing data are collected analysed interpreted and validity is tested with the help of statistical tools like egression, coefficient and Annova for the testing of the available data with its further application.
R ESULTS: AI application creates more awareness, vaccination, self-testing, isolation and intake medicine
CONCLUSION: Artificial Intelligence &social media plays a vital role for the creation of social awareness and proper manage of post COVID-19 epidemics.
In this paper, we analyse effects of the first wave of the COVID-19 epidemic on employment in Slovenia in the light of some theories on the destandardisation and segmentation of employment. We ...consider statistical databases, state measures and policies, along with union strategies before and during the epidemic. The epidemic has caused a sharp decline in employment and hit hardest those workers holding non-standard forms of employment (especially students and temporary workers). Given the decline in service turnover/production volume, particular service industries (e.g. retail, exports) have been more affected by export-oriented manufacturing that has invested less in employee skills and shifted the effects of the shock to labour and the state. We also note the trade unions have not deepened the splits in labour market divisions, while segmentation has been strengthened by both pre- and post-epidemic state policies.
This study aimed to explore the psychological needs of nurses caring for patients with coronavirus disease 2019(COVID-19) and to propose corresponding interventions.
In-depth interviews were ...conducted with 10 nurses who cared for patients with COVID-19. Interview data were analyzed by category analysis from the perspective of the existence, relatedness, and growth theory (ERG).
The existence needs were mainly reflected in health and security needs, whereas the relatedness needs consisting mainly of interpersonal needs, humanistic concern needs, and family needs; further, the growth needs were mainly reflected as a strong need for knowledge. Existence needs were the main needs during the epidemic, with health and security needs influencing each other. Humanistic concern needs were the most important of the relatedness needs; interpersonal and family needs were also growing.
It is found that the existence, relatedness, and growth needs coexist in clinical nurses. It is helpful to take effective interventions to meet their needs if the needs of nurses caring for COVID-19 patients could be perceived well.
The fight against the COVID-19 epidemic significantly raises the global demand for personal protective equipment, especially disposable face masks (DFMs). The discarded DFMs may become a potential ...source of microplastics (MPs), which has attracted much attention. In this work, we identified the detailed source of MPs released from DFMs with laser direct infrared spectroscopy. Polypropylene (PP) and polyurethane (PU) accounted for 24.5% and 57.1% of released MPs, respectively. The melt-blown fabric was a dominant MPs source, however, previous studies underestimated the contribution of mask rope. The captured polyethylene terephthalate (PET), polyamide (PA), polyethylene (PE), and polystyrene (PS) in airborne only shared 18.4% of released MPs. To deepen the understanding of MPs release from medical mask into the aquatic environment, we investigated the effects of environmental factors on MPs release. Based on regression analysis, the effects of temperature, incubation time, and wearing time significantly affect the release of MPs. Besides, acidity, alkalinity, sodium chloride, and humic acid also contributed to the MPs release through corroding, swelling, or repulsion of fibers. Based on the exposure of medical mask to simulated environments, the number of released MPs followed the order: seawater > simulated gut-fluid > freshwater > pure water. Considering the risk of MPs released from DFMs to the environment, we innovatively established a novel flotation removal system combined with cocoamidopropyl betaine, achieving 86% removal efficiency of MPs in water. This work shed the light on the MPs release from DFMs and proposed a removal strategy for the control of MPs pollution.
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•Mask rope was identified as a dominant source of microplastics.•Temperature, wearing time, and incubation time promoted microplastics release.•The release of microplastics was affected by pH, sodium chloride, and humic acid.•Disposable face mask released more microplastics in seawater and gut-fluid.•Froth flotation with cocoamidopropyl betaine removed microplastics efficiently.
The COVID-19 pandemic has had a significant impact on global mental health, affecting individuals of all age groups and various demographic backgrounds including athletes. Anxiety disorders have ...become more prevalent during the pandemic, attributed to factors such as quarantine, social isolation, fear of the virus, job insecurity, and the psychological impact of a pandemic. This narrative review aims to summarize the existing literature addressing mental health issues related to the COVID-19 pandemic, as well as the associated risk factors and potential interventions. Additionally, the review explores the impact of COVID-19 on specific populations, including athletes, frontline healthcare workers, children and adolescents, and individuals with pre-existing mental health conditions. In addition, the review explores the long-term consequences of the pandemic on mental health, including the potential for a surge in post-traumatic stress disorder (PTSD) and other trauma-related disorders. Overall, this review underscores the urgent need for comprehensive mental health support and resources in response to the COVID-19 pandemic.
As the new coronavirus pandemic enters its third year, its long-term impact on the urban environment cannot be ignored, especially in megacities with more than millions of people. Here, we analyzed ...the changes in the concentration levels, emission sources, temporal variations and holiday effects of ambient fine particulate matter (PM2.5) and its chemical components in the pre- and post-epidemic eras based on high-resolution, long time-series datasets of PM2.5 and its chemical components in Chengdu. In the post-epidemic era, the PM2.5 concentration in Chengdu decreased by 7.4%, with the components of PM2.5 decreasing to varying degrees. The positive matrix factorization (PMF) results indicated that the emissions from soil dust and industrial production were significantly lower during the COVID-19 lockdown period and post-epidemic era than those in the pre-epidemic era. In contrast, the contribution of secondary aerosols to PM2.5 during these two periods increased by 2.7% and 6.6%, respectively. Notably, we found that PM2.5 and its components substantially decreased on workdays and holidays in the post-epidemic era due to the reduced traffic volume and outdoor activities. This provides direct evidence that changes in the habitual behavior patterns of urban residents in the post-epidemic era could exert an evident positive impact on the urban environment. However, the higher PM2.5 concentration was observed due to the increased consumption of regular (As4S4, Xionghuang in Chinese) and “sulfur incense” during the Dragon Boat Festival holiday in the post-epidemic era. Finally, we examined the potential effects of sporadic COVID-19 outbreaks on the PM2.5 concentration in Chengdu, and there was no decrease in PM2.5 during two local COVID-19 outbreak events due to the strong influence of secondary pollution processes.
•Long-term impacts of the COVID-19 epidemic on urban PM2.5 were analyzed.•Emissions from transportation and industry reduced in the post-epidemic era.•PM2.5 concentration significantly dropped over workdays and holidays in the post-epidemic era.•PM2.5 concentration conversely increased during the Dragon Boat Festival in the post-epidemic era.
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 is challenging the dental community to an unprecedented degree. Knowledge of the increased ...risk of infection in dental settings has been disseminated to the public and guidelines have been formulated to assist dental attendance decision-making. However, dental attendance behaviors incompatible with treatment need is not uncommon in clinical settings. Important gaps remain in the knowledge about how psychological factors are affecting dental attendance behaviors during the COVID-19 epidemic. In this cross-sectional study, a questionnaire survey was performed during February and March 2020. A total of 342 and 294 dental patients who attended and avoided dental visits, respectively, were included. The participants were classified into four groups based on dental attendance behavior and emergent/urgent dental treatment need. Bivariate analysis was performed to investigate factors associated with dental attendance. Multivariable logistic regression based on principal component scores was performed to identify major psychological constructs associated with unnecessary dental avoidance and attendance. Among all the factors explored, inability to wear masks during dental treatment (
P
< 0.001; effect size: 0.32) was most closely associated with the overall pattern of dental attendance among participants. Multivariable regression suggested that unnecessary dental avoidance was associated with perceived risk of infection in general and in dental settings (odds ratio 95% CI: 0.62 0.53, 0.72;
p
< 0.001), perceived impact of COVID-19 and dental problems on general health (0.79 0.65, 0.97; 0.021), and personal traits such as trust and anxiety (0.77 0.61, 0.98; 0.038). Unnecessary dental attendance was associated with optimism toward the epidemic (1.68 1.42, 2.01; <0.001) and trust (1.39 1.13, 1.74; 0.002). Multidisciplinary efforts involving dental and medical professionals as well as psychologists are warranted to promote more widespread adoption, among the general public, of dental attendance behaviors compatible with dental treatment need during the COVID-19 epidemic.
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response ...to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM2.5 with adverse health effects. In this study, by using PM2.5 observations from 1388 monitoring stations nationwide in China, we examine the PM2.5 variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015–2019, and find that the national average of PM2.5 decreases by 18 μg/m3, and mean PM2.5 for most sites (about 75%) decrease by 30%–60%. The anthropogenic and meteorological contributions to these PM2.5 variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov–Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM2.5 reductions, and meteorological conditions have the negative influence on PM2.5 reductions for some regions, such as Beijing–Tianjin–Hebei (BTH). Additionally, the avoided premature death due to PM2.5 reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM2.5 are 24.1, 24.3, 13.5 and 29.5 μg/m3, with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.
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