Academic Emotion Classification Using FER: A Systematic Review

Facial emotion expressions are among the most potent, natural, and powerful means of human communication. Due to the COVID-19 pandemic, educational institutions worldwide are forced to switch rapidly to remote and online learning. Students are currently in an emergency state and must adapt to various and readily accessible learning methods, such as mobile learning applications or an e-learning system. A systematic literature review (SLR) is conducted to extract and synthesize information such as the emotion classifier used in the facial expression recognition (FER) system, the dataset used, the preprocessing technique applied, the feature extraction approach used, and the strength and limitation of the previous studies. Based on the search criteria, 701 publications were initially retrieved from five different digital databases, of which 48 studies have been chosen as primary studies for further analysis. Based on the findings of this study, the deep learning approach is the most frequently adopted approach in classifying student emotions during online learning. FER-2013 is the most commonly used FER dataset in FER studies, while DAiSEE is the most used academic emotion dataset. Moreover, support vector machine (SVM) is the conventional learning emotion classifier that is widely used in the FER systems, while convolutional neural network (CNN) is the most frequently used deep learning classifier. Next, it was found that the number of real-time FER systems is less than that of non-real-time FER systems. Finally, the top-1 accuracy of 94.6% was achieved by the long-term recurrent convolutional network on the academic emotion dataset, and the limitation is that it has low illumination and a lack of frontal pose. [ FROM AUTHOR] Copyright of Human Behavior & Emerging Technologies is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Assessment of COVID-19 Positive Rates Amongst COVID-19 Close Contacts Through the Health Risk Warning System.

From 6 Jan 22 to 17 Feb 22, a total of 729,367 close contacts classified into four distinct groups (i.e., household, social, school and nursing/ welfare home contacts) were managed by the Health Risk Warning system. High COVID-19-positive rates were demonstrated amongst household contacts, i.e., 10.9% (37,220/342,302) were detected via antigen rapid test kits and 56.5% (4,952/8,767) were detected via polymerase chain reaction testing. Household contacts represent the highest risk of being infected by virtue of the sustained close-proximity interactions in the household setting. Social, school and nursing/ welfare home contacts continue to remain at-risk groups for close monitoring. At a population level, household and symptomatic close contacts should be the groups of focus in the early phases of the pandemic, including future potential waves involving COVID-19 variants of concern.

Predictive performance of emergency department-specific variables on COVID-19 pneumonia.

INTRODUCTION: The majority of patients with COVID-19 infection do not progress to pneumonia. We report emergency department (ED)-specific variables and evaluate their predictive performance on diagnosis of pneumonia, intensive care unit (ICU) admission and death. METHODS: This was a retrospective, single-centre cohort study of confirmed COVID-19 patients admitted to a Singapore tertiary hospital. Primary outcome was diagnosis of COVID-19 pneumonia. Secondary outcomes were ICU admission and/or death. Multivariate logistic regression was used to analyse the predictive performance of ED-specific variables. Accuracy of continuous variables was measured by area under receiver operating characteristic (ROC) curve. RESULTS: 294 patients were included. Patients with pneumonia were older (52.0 years, p < 0.001) and had higher C-reactive protein (CRP; 33.8 mg/L, p < 0.001). Patients with indeterminate chest radiograph (CRX) findings were at risk of pneumonia vs. patients with normal CRX (37.5% vs. 4.3%, p < 0.001). Patients admitted to ICU were older (60.0 years, p < 0.001) and had higher CRP (40.0 mg/L, p < 0.001). Diagnosis of COVID-19 pneumonia was associated with ICU admission and death (30.0% vs 0.39%, p < 0.001). Multivariate logistic regression analysis showed that age (aOR 1.07, p = 0.049), CRP (aOR 1.05, p = 0.006) and CRX findings (aOR 50.00, p < 0.001) had increased odds of pneumonia. ROC curve analysis showed that CRP of 23.3 mg/L was the optimal cut-off for predicting pneumonia. CONCLUSION: Older age, higher CRP and CRX findings are associated with COVID-19 pneumonia, ICU admission and death. Prospective studies should be undertaken to validate these findings.

The monkeypox diagnosis, treatments and prevention: A review.

The world is currently dealing with a second viral outbreak, monkeypox, which has the potential to become an epidemic after the COVID-19 pandemic. People who reside in or close to forest might be exposed indirectly or at a low level, resulting in subclinical disease. However, the disease has lately emerged in shipped African wild mice in the United States. Smallpox can cause similar signs and symptoms to monkeypox, such as malaise, fever, flu-like signs, headache, distinctive rash, and back pain. Because Smallpox has been eliminated, similar symptoms in a monkeypox endemic zone should be treated cautiously. Monkeypox is transmitted to humans primarily via interaction with diseased animals. Infection through inoculation via interaction with skin or scratches and mucosal lesions on the animals is conceivable significantly once the skin barrier is disrupted by scratches, bites, or other disturbances or trauma. Even though it is clinically unclear from other pox-like infections, laboratory diagnosis is essential. There is no approved treatment for human monkeypox virus infection, however, smallpox vaccination can defend counter to the disease. Human sensitivity to monkeypox virus infection has grown after mass vaccination was discontinued in the 1980s. Infection may be prevented by reducing interaction with sick patients or animals and reducing respiratory exposure among people who are infected.

MESTrans: Multi-scale embedding spatial transformer for medical image segmentation.

BACKGROUND AND OBJECTIVE: Transformers profiting from global information modeling derived from the self-attention mechanism have recently achieved remarkable performance in computer vision. In this study, a novel transformer-based medical image segmentation network called the multi-scale embedding spatial transformer (MESTrans) was proposed for medical image segmentation. METHODS: First, a dataset called COVID-DS36 was created from 4369 computed tomography (CT) images of 36 patients from a partner hospital, of which 18 had COVID-19 and 18 did not. Subsequently, a novel medical image segmentation network was proposed, which introduced a self-attention mechanism to improve the inherent limitation of convolutional neural networks (CNNs) and was capable of adaptively extracting discriminative information in both global and local content. Specifically, based on U-Net, a multi-scale embedding block (MEB) and multi-layer spatial attention transformer (SATrans) structure were designed, which can dynamically adjust the receptive field in accordance with the input content. The spatial relationship between multi-level and multi-scale image patches was modeled, and the global context information was captured effectively. To make the network concentrate on the salient feature region, a feature fusion module (FFM) was established, which performed global learning and soft selection between shallow and deep features, adaptively combining the encoder and decoder features. Four datasets comprising CT images, magnetic resonance (MR) images, and H&E-stained slide images were used to assess the performance of the proposed network. RESULTS: Experiments were performed using four different types of medical image datasets. For the COVID-DS36 dataset, our method achieved a Dice similarity coefficient (DSC) of 81.23%. For the GlaS dataset, 89.95% DSC and 82.39% intersection over union (IoU) were obtained. On the Synapse dataset, the average DSC was 77.48% and the average Hausdorff distance (HD) was 31.69 mm. For the I2CVB dataset, 92.3% DSC and 85.8% IoU were obtained. CONCLUSIONS: The experimental results demonstrate that the proposed model has an excellent generalization ability and outperforms other state-of-the-art methods. It is expected to be a potent tool to assist clinicians in auxiliary diagnosis and to promote the development of medical intelligence technology.

COVID-19 Close Contact Management: An Evolution of Operations Harnessing the Digital Edge.

Singapore, like many other nations globally, had to contend with significant caseloads arising from the Coronavirus disease (COVID-19) pandemic. This paper focuses on using technology as an intervention for pandemic management. With scant scientific evidence on effective medications and vaccinations (i.e., pharmaceutical interventions) initially, disease containment strategies predominated during the early phases. Non-pharmaceutical interventions were critical in slowing disease transmission and preventing public healthcare institutions from being overwhelmed. Such interventions could be broadly divided into case-based interventions (e.g., contact tracing and quarantining of close contacts) and population-based measures (e.g., mask use and social distancing). The paper describes Singapore's experience in the operational implementation of contact-based interventions, and illustrates how harnessing the digital edge enabled fast, accurate, resource-efficient, and flexible execution of ground operations. Singapore applied digital technology and developed an integrated system to facilitate issuance and acknowledgement of quarantine orders, submission of COVID-19 test results, and collection of antigen rapid test kits at the population level. Data was obtained from this proprietary centralised, automated platform. The paper demonstrates how such simple, yet elegant systems could have a direct impact on disease transmission in an outbreak setting and on population health. Moving forward, it is recommended that technology and digital solutions feature prominently in work process designs beyond COVID-19 such as in the management of emerging infectious diseases and non-communicable diseases.

The Effect of Servant Leadership on Work Resilience: Evidence from the Hospitality Industry during the COVID-19 Period.

The COVID-19 pandemic is a tremendous crisis for public health, which also has a profound impact on business and social activities because many countries restrict travel and social gatherings to avoid the spread of COVID-19. Workers suffer from mental health problems including depression and anxiety due to the uncertain work environment. Hence, psychological resilience, a positive psychological response to these challenges, is essential to the success of employees and companies. Drawing on the conservation of resources theory (COR), this paper investigates how the leadership style (i.e., servant leadership) enhances the work resilience of hospitality employees through two time-lagged empirical studies. Specifically, study 1 demonstrates a positive relationship between servant leadership and employees' work resilience. Study 2 replicates study 1's result and further demonstrates that emotional exhaustion mediates the relationship between servant leadership and employees' work resilience. Furthermore, study 2 finds a significant moderating effect of job complexity. The findings of this paper provide empirical evidence for practitioners to manage employees' resilience and psychological resources.

A Nomogram-Based Study: A Way Forward to Predict the Anxiety Status in Medical Staff During the COVID-19 Pandemic.

Background and Objective: Anxiety influences job burnout and health. This study aimed to establish a nomogram to predict the anxiety status of medical staff during the coronavirus disease (COVID-19) pandemic. Methods: A total of 600 medical members were randomized 7:3 and divided into training and validation sets. The data was collected using a questionnaire. Logistic regression analysis and Akaike information criterion (AIC) were applied to investigate the risk factors for anxiety. Odds ratio (OR) and 95% confidence interval (95% CI) were calculated to establish a nomogram. Results: Participation time (OR=44.28, 95% CI=13.13~149.32), rest time (OR=38.50, 95% CI=10.43~142.19), epidemic prevention area (OR=10.16, 95% CI=3.51~29.40), epidemic prevention equipment (OR=15.24, 95% CI=5.73~40.55), family support (OR=9.63, 95% CI=3.55~26.11), colleague infection (OR=6.25, 95% CI=2.18~19.11), and gender (OR=3.30, 95% CI=1.15~9.47) were the independent risk factors (P<0.05) for anxiety in medical staff. The areas under the receiver operating characteristic (ROC) curves of the training and validation sets were 0.987 and 0.946, respectively. The decision curve's net benefit shows the nomogram's clinical utility. Conclusion: The nomogram established in this study exhibited an excellent ability to predict anxiety status with sufficient discriminatory power and calibration. Our findings provide a protocol for predicting and identifying anxiety status in medical staff during the COVID-19 pandemic.

Assessment of Attitudes and Intentions towards COVID-19 Vaccines and Associated Factors among General Populations of Pakistan: A Cross-Sectional Study.

OBJECTIVE: The goal of public health in combatting COVID-19 is to increase herd immunity. However, vaccine reluctance makes attaining herd immunity a worldwide challenge. This investigation aimed to identify negative and positive attitudes and intentions about COVID-19 vaccinations. METHODS: A cross-sectional online survey was conducted once free COVID-19 vaccines became available in Pakistan in 2021. 4392 Pakistanis aged 18 and older were surveyed from seven administrative units between 1 July and 30 August 2021. Online structured questionnaires were utilized to collect data using a simple sampling procedure. The questionnaires were divided into three major sections: sociodemographic, health factors, and attitudes toward COVID-19. RESULTS: The survey link was shared with approximately 4500 participants. 97.6%(4392) completed the survey once begun. Frequency, percentage and Chi-square tests were used to analyze statistical data. Most of the participants in the research were men (2703 (61.54%)), 3277 (74.61%) were aged 18-29 years, and 1824 (41.53%) were residents of the Khyber Pakhtunkhwa province. (18.69%) Respondents expressed COVID-19 vaccine hesitancy, whereas 36.66% of participants liked getting the Sinopharm and Sinovac vaccines and (35.84%) of participants preferred the Pfizer vaccine. A significant number of participants (38.05%) were concerned about the vaccine's unexpected side effects Thus, it is essential to realize that many participants were concerned about the vaccine's unexpected side effects. CONCLUSIONS: The overall high level of concern about the unforeseen side effects of COVID-19 vaccines, as well as widespread vaccine hesitancy among Pakistani populations and its predictors, should be taken into account if public health intervention campaigns in Pakistan are changing negative attitudes and improving compliance with regard to COVID-19 vaccines.

Knowledge, Attitude, and Perception of Cancer Patients towards COVID-19 in Pakistan: A Cross-Sectional Study.

BACKGROUND: Cancer patients, being immunocompromised, are at higher risk of coronavirus disease (COVID-19). The current study determines cancer patients' knowledge, attitude, perception, and impact of the COVID-19 pandemic. METHOD: A cross-sectional online survey was conducted in Pakistan from 1 April 2020 to 1 May 2020. The study respondents were cancer patients with ages equal to or greater than 18 years. Following a request for participation, the URL for the survey was distributed on numerous channels. Other social media platforms, including WeChat, WhatsApp, Facebook, Twitter, Instagram, Messenger, and LinkedIn, were used to increase cancer patient interaction. The questionnaire comprised five different sections such as: (1) sociodemographic information, (2) knowledge, (3) attitude, (4) perception, and (5) impact of COVID-19 on cancer patients. Descriptive medical statistics such as frequency, percentage, mean, and standard deviation were used to illustrate the demographic characteristics of the study participants. To compare mean knowledge scores with selected demographic variables, independent sample t-tests and one-way analysis of variance (ANOVA) were used, which are also practical methods in epidemiological, public health and medical research. The cut-off point for statistical significance was set at a p-value of 0.05. RESULTS: More than 300 cancer patients were invited, of which 208 agreed to take part. The response rate was 69.33% (208/300). Gender, marital status, and employment status had a significant association with knowledge scores. Of the total recruited participants, 96% (n = 200) (p < 0.01) knew about COVID-19, and 90% were aware of general symptoms of COVID-19 disease, such as route of transmission and preventive measurements. In total, 94.5% (n = 197) (p < 0.01) were willing to accept isolation if they were infected with COVID-19, and 98% (n = 204) (p < 0.01) had reduced their use of public transportation. More than 90% (n = 188) (p < 0.01) of cancer patients were found to be practicing preventative measures such as using a face mask, keeping social distance, and avoiding handshaking and hugging. Around 94.4% (n = 196) (p < 0.01) of cancer patients had been impacted by, stopped or had changed cancer treatment during this pandemic, resulting in COVID-related anxiety and depression. CONCLUSION: The included cancer patients exhibited a good level of COVID-19 knowledge, awareness, positive attitude, and perception. Large-scale studies and efforts are needed to raise COVID-19 awareness among less educated and high-risk populations. The present survey indicates that mass-level effective health education initiatives are required for developing countries to improve and reduce the gap between KAP and COVID-19.

Influence factors analysis of COVID-19 Prevention behavior of chinese Citizens: a path analysis based on the hypothetical model.

BACKGROUND: Under the outbreak of Coronavirus disease 2019 (COVID-19), a structural equation model was established to determine the causality of important factors that affect Chinese citizens' COVID-19 prevention behavior. METHODS: The survey in Qingdao covered several communities in 10 districts and used the method of cluster random sampling. The research instrument used in this study is a self-compiled Chinese version of the questionnaire. Of the 1215 questionnaires, 1188 were included in our analysis. We use the rank sum test, which is a non-parametric test, to test the influence of citizens'basic sociodemographic variables on prevention behavior, and the rank correlation test to analyze the influencing factors of prevention behavior. IBM AMOS 24.0 was used for path analysis, including estimating regression coefficients and evaluating the statistical fits of the structural model, to further explore the causal relationships between variables. RESULTS: The result showed that the score in the prevention behavior of all citizens is a median of 5 and a quartile spacing of 0.31. The final structural equation model showed that the external support for fighting the epidemic, the demand level of health information, the cognition of (COVID-19) and the negative emotions after the outbreak had direct effects on the COVID-19 prevention behavior, and that negative emotions and information needs served as mediating variables. CONCLUSIONS: The study provided a basis for relevant departments to further adopt epidemic prevention and control strategies.

Association Between Passive Smoking and Health Among Chinese Nurses: A Cross-Sectional Study.

This study aimed to investigate the association between passive smoking and physical and psychological health in Chinese nurses. Participants of this cross-sectional study comprised 2,484 non-smoking nurses. Passive smoking and demographic information were assessed using a self-administered questionnaire. Physical, psychological, and overall health status of nurses were measured using the Cornell Medical Index (CMI) health questionnaire. Multivariate-adjusted odds ratio (OR) and 95% confidence interval (CI) for nurses' health were estimated by exposure to passive smoking using unconditional logistic regression models. A total of 1,219 nurses (49.07%) were exposed to passive smoking. Of these, 609 (24.52%), 160 (6.44%), and 587 (23.63%) nurses had poorer physical, mental, and overall health, respectively. After adjusting for other confounding factors, compared with the non-passive smoking group, passive smoking was associated with poor physical (OR = 1.51, 95% CI: 1.25-1.83), mental (OR = 1.48, 95% CI: 1.07-2.07), and overall (OR = 1.58, 95% CI: 1.30-1.93) health of nurses, respectively. We also carried out subgroup analyses stratified by age, department, and professional title, which showed that most findings supported the main results. This study demonstrated that exposure to passive smoking was a risk factor for overall decreased physical and mental health status among Chinese nurses.

Assessment of General Populations Knowledge, Attitude, and Perceptions Toward the Coronavirus Disease (COVID-19): A Cross-Sectional Study From Pakistan.

Background: Coronavirus disease 2019 (COVID-19) is a global health threat and caused a universal psychosocial impact on the general population. Therefore, the knowledge, attitude, and perceptions (KAPs) of the general population are critical for the development and effective implementation of standard operating procedures (SOP) to contain the contagion and minimize the losses. Therefore, the current study was conducted to understand and evaluate the KAPs of Pakistani populations toward the COVID-19. Methods: An online cross-sectional study was carried out among participants from 1 May to 30 July 2020 in different areas of Pakistan. The respondents of the study were the general population with age ≥ 18 years. The poll URL was posted on several channels after a call for participation. Other social media platforms such as WeChat, WhatsApp, Facebook, Twitter, Instagram, Messenger, and LinkedIn were engaged to maximize general population engagement. The questionnaire included details about sociodemographic, knowledge about COVID-19, perceptions toward universal safety precautions of COVID-19, and beliefs attitude toward the COVID-19. The obtained data were exported into a Microsoft Excel spreadsheet and SPSS software version 21 for windows. The descriptive statistics values were presented in frequencies and percentages. Binary logistic regression, Chi-square test, and one-way ANOVA were applied to analyze the participants' socio-demographic characteristics and variables related to KAPs. P-value < 0.05 was recorded as significant. Results: A total of 1,000 participants were invited of which 734 participated in this study. The response rate was 73.4% (734/1,000). The gender, marital status, education, and residence showed a significant association with the knowledge score. The majority of the study participants were thinking that COVID-19 may be more dangerous in elderly individuals 94.5% (n = 700), and individuals with chronic diseases or severe complications 96.7% (n = 710) (p = 0.00). More than half of the participants 52.5% (n = 385) showed their concern that either they or their family members might get the infection. More than 98% (n = 703), (P-value = 0.00) of the participants held that COVID-19 would be successfully controlled in Pakistan by following the standard SOPs and government guidelines. Conclusion: This study showed that the general population of Pakistan has good awareness and reasonable attitudes and perceptions toward the full features of the COVID-19. The current study suggests that mass-level effective health education programs are necessary for developing countries to improve and limit the gap between KAP toward COVID-19.

Secondary hypogonadism following hand, foot, and mouth disease in an adult: a case report and review of literature.

BACKGROUND: Previous reports have described hypogonadism associated with virus infection such as hantavirus, human immunodeficiency virus (HIV) or severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). However, to our best knowledge there has been no case report of secondary hypogonadism following hand, foot, and mouth disease (HFMD). CASE PRESENTATION: A previously healthy 28-year-old man with no history of major physical and psychological trauma, presented with bilateral gynecomastia and erectile dysfunction 2 weeks after HFMD. Laboratory testament showed the level of gonadotropin hormones declined. Imaging examination demonstrated no major abnormal change in pituitary or reproductive system. The diagnosis of hypogonadism was established. Then the patient was ordered to maintain mental health outward of hospital without drug intervention. One month after presentation, his gonadotropin hormone level and sexual desire had recovered, while bilateral gynecomastia and erectile dysfunction symptoms disappeared. CONCLUSIONS: Physicians should notice the possibility for hypogonadism in adult patients with a recent history of HFMD.

Genome-Wide Analysis of Codon Usage Patterns of SARS-CoV-2 Virus Reveals Global Heterogeneity of COVID-19.

The ongoing outbreak of coronavirus disease COVID-19 is significantly implicated by global heterogeneity in the genome organization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The causative agents of global heterogeneity in the whole genome of SARS-CoV-2 are not well characterized due to the lack of comparative study of a large enough sample size from around the globe to reduce the standard deviation to the acceptable margin of error. To better understand the SARS-CoV-2 genome architecture, we have performed a comprehensive analysis of codon usage bias of sixty (60) strains to get a snapshot of its global heterogeneity. Our study shows a relatively low codon usage bias in the SARS-CoV-2 viral genome globally, with nearly all the over-preferred codons' A.U. ended. We concluded that the SARS-CoV-2 genome is primarily shaped by mutation pressure; however, marginal selection pressure cannot be overlooked. Within the A/U rich virus genomes of SARS-CoV-2, the standard deviation in G.C. (42.91% ± 5.84%) and the GC3 value (30.14% ± 6.93%) points towards global heterogeneity of the virus. Several SARS-CoV-2 viral strains were originated from different viral lineages at the exact geographic location also supports this fact. Taking all together, these findings suggest that the general root ancestry of the global genomes are different with different genome's level adaptation to host. This research may provide new insights into the codon patterns, host adaptation, and global heterogeneity of SARS-CoV-2.

A multi-class COVID-19 segmentation network with pyramid attention and edge loss in CT images.

At the end of 2019, a novel coronavirus COVID-19 broke out. Due to its high contagiousness, more than 74 million people have been infected worldwide. Automatic segmentation of the COVID-19 lesion area in CT images is an effective auxiliary medical technology which can quantitatively diagnose and judge the severity of the disease. In this paper, a multi-class COVID-19 CT image segmentation network is proposed, which includes a pyramid attention module to extract multi-scale contextual attention information, and a residual convolution module to improve the discriminative ability of the network. A wavelet edge loss function is also proposed to extract edge features of the lesion area to improve the segmentation accuracy. For the experiment, a dataset of 4369 CT slices is constructed, including three symptoms: ground glass opacities, interstitial infiltrates, and lung consolidation. The dice similarity coefficients of three symptoms of the model achieve 0.7704, 0.7900, 0.8241 respectively. The performance of the proposed network on public dataset COVID-SemiSeg is also evaluated. The results demonstrate that this model outperforms other state-of-the-art methods and can be a powerful tool to assist in the diagnosis of positive infection cases, and promote the development of intelligent technology in the medical field.

The interplay between anxiety, fear, protective behaviors, compassion, and resilience among older adults during a COVID-19 lockdown: a structural equation modeling study.

The implementation of lockdown measures to curb the transmission of Coronavirus disease-2019 (COVID-19) has brought about significant psychological impacts and older adults have been identified as one of the vulnerable groups. In the current COVID-19 context among older adults in the community, the fear of COVID-19, anxiety symptoms, compassion, resilience, and the practice of protective behaviors are possibly related to each other in several ways. How these factors relate to each other would have important implications in managing the spread of the disease and its mental health consequences. To this end, we modeled their interrelationships using a structural equation model. Older adults (N = 421), aged 60 and above completed various questionnaires-COVID-19 Fear Inventory, Short form of the Geriatric Anxiety Inventory, COVID-19 Risky and Protective Behaviours, Resilience Appraisals Scale, and Compassion Scale during a COVID-19 lockdown. The relationships between these variables were assessed within a structural equation model. The findings showed that older adults who are more compassionate engage in protective behaviors more frequently. Additionally, frequent practice of protective behaviors and greater resilience predicted lower anxiety among older adults. Greater fear predicted higher anxiety levels but did not significantly influence an individual's engagement in protective behaviors. Mental health services are crucial in fostering resilience and supporting older adults psychologically. Social services are also necessary in maintaining and enhancing social support for older adults. Importantly, these findings suggest that public health communications could promote compassion and avoid using a fear-based approach to increase engagement in protective behaviors.

This study focused on the interrelations between various psychosocial factors (i.e., fear of COVID-19, compassion, and resilience) and the behavioral (i.e., engagement in protective health behaviors) and psychological responses (i.e., anxiety) to COVID-19 among community-dwelling older adults. The study analyzed self-reported data from 421 older adults who are aged 60 and above. The findings showed that older adults who are more compassionate engage in protective behaviors more frequently. Additionally, older adults who showed greater resilience and engage in protective health behaviors more frequently reported lower anxiety levels. Lastly, greater fear of COVID-19 predicted greater anxiety among older adults but did not significantly influence their engagement in protective health behaviors.

Progress in Research on SARS-CoV-2 Infection Causing Neurological Diseases and Its Infection Mechanism.

COVID-19 has spread rapidly worldwide since its outbreak and has now become a major public health problem. More and more evidence indicates that SARS-CoV-2 may not only affect the respiratory system but also cause great harm to the central nervous system. Therefore, it is extremely important to explore in-depth the impact of SARS-CoV-2 infection on the nervous system. In this paper, the possible mechanisms of SARS-CoV-2 invading the central nervous system during COVID-19, and the neurological complications caused by SARS-CoV-2 infection were reviewed.

Advances and challenges in the prevention and treatment of COVID-19.

Since the end of 2019, a new type of coronavirus pneumonia (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been spreading rapidly throughout the world. Previously, there were two outbreaks of severe coronavirus caused by different coronaviruses worldwide, namely Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). This article introduced the origin, virological characteristics and epidemiological overview of SARS-CoV-2, reviewed the currently known drugs that may prevent and treat coronavirus, explained the characteristics of the new coronavirus and provided novel information for the prevention and treatment of COVID-19.

Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study.

BACKGROUND: Since December 2019, the 2019 coronavirus disease (COVID-19) has expanded to cause a worldwide outbreak that more than 600,000 people infected and tens of thousands died. To date, the clinical characteristics of COVID-19 patients in the non-Wuhan areas of Hubei Province in China have not been described. METHODS: We retrospectively analyzed the clinical characteristics and treatment progress of 91 patients diagnosed with COVID-19 in Jingzhou Central Hospital. RESULTS: Of the 91 patients diagnosed with COVID-19, 30 cases (33.0%) were severe and two patients (2.2%) died. The severe disease group tended to be older (50.5 vs. 42.0 years; p = 0.049) and have more chronic disease (40% vs. 14.8%; p = 0.009) relative to mild disease group. Only 73.6% of the patients were quantitative polymerase chain reaction (qPCR)-positive on their first tests, while typical chest computed tomography images were obtained for each patient. The most common complaints were cough (n = 75; 82.4%), fever (n = 59; 64.8%), fatigue (n = 35; 38.5%), and diarrhea (n = 14; 15.4%). Non-respiratory injury was identified by elevated levels of aspartate aminotransferase (n = 18; 19.8%), creatinine (n = 5; 5.5%), and creatine kinase (n = 14; 15.4%) in laboratory tests. Twenty-eight cases (30.8%) suffered non-respiratory injury, including 50% of the critically ill patients and 21.3% of the mild patients. CONCLUSIONS: Overall, the mortality rate of patients in Jingzhou was lower than that of Wuhan. Importantly, we found liver, kidney, digestive tract, and heart injuries in COVID-19 cases besides respiratory problems. Combining chest computed tomography images with the qPCR analysis of throat swab samples can improve the accuracy of COVID-19 diagnosis.