Analysis of Outbreak and Global Impacts of the COVID-19

Self-reported Changes in Use of and Attitudes Toward ICT in Three Generations in Sweden During the Early Phase of the COVID-19 Pandemic

COVID-19 has affected the daily activities of people worldwide. Recommendations introduced to reduce the spread of the virus led to increased use of Information and Communication Technologies (ICT) to meet everyday needs. Such rapid digitalization had not been seen previously and not been possible to study before. Hence, this study aimed to identify and describe self-reported changes in usage of and attitudes toward ICT among three generations in Sweden during the early phase of the COVID-19 pandemic. Additionally, it aimed to identify whether and how belonging to a specific generation was related to these changes. A national cross-sectional survey was conducted in June 2020 with a final sample of N = 3,000, stratified into three generations (30-39, 50-59, and 70-79-year-old persons). A majority reported using digital technology more often than before the pandemic. Compared to the youngest generation, the oldest and middle-aged generations reported that they used digital technology more often than before the pandemic. Our results show which technologies were considered essential for different generations during the early phase of the pandemic. This information can be used to guide policy makers based on knowledge concerning the needs and demands for digital technologies in everyday life among people of different ages.

Experiences of environmental services workers in a tertiary hospital in Asia during the COVID-19 pandemic: a qualitative study

Background

The Coronavirus Disease 2019 (COVID-19) pandemic has had a significant impact on all walks of life, in particular, environmental services workers in healthcare settings had higher workload, increased stress and greater susceptibility to COVID-19 infections during the pandemic. Despite extensive literature describing the impact of the pandemic on healthcare workers such as doctors and nurses, studies on the lived experiences of environmental services workers in healthcare settings are sparse and none has been conducted in the Asian context. This qualitative study thus aimed to examine the experiences of those who worked for a year of the COVID-19 pandemic.

Methods

A purposive sample of environmental services workers was recruited from a major tertiary hospital in Singapore. Semi-structured interviews were conducted in-person, lasting around 30min, and included open-ended questions pertaining to five main domains: work experiences during COVID-19, training and education needs, resource and supplies availability, communication with management and other healthcare staff, and perceived stressors and support. These domains were identified based on team discussions and literature review. The interviews were recorded and transcribed for thematic analysis, as guided by Braun and Clarke.

Results

A total of 12 environmental services workers were interviewed. After the first seven interviews, no new themes emerged but an additional five interviews were done to ensure data saturation. The analysis yielded three main themes and nine subthemes, including (1) practical and health concerns, (2) coping and resilience, and (3) occupational adaptations during the pandemic. Many expressed confidence in the preventive efficacy of proper PPE, infection control practice and COVID-19 vaccination in protecting them against COVID-19 and severe illness. Having prior experience with infectious disease outbreaks and previous training in infection control and prevention appeared to be useful as well for these workers. Despite the various challenges presented by the pandemic, they could still find meaning in their everyday work by positively impacting the wellbeing of patients and other healthcare workers in the hospital.

Conclusion

Besides uncovering the concerns shared by these workers, we identified helpful coping strategies, resilience factors and certain occupational adaptations, which have implications for future pandemic planning and readiness.

Monkeypox Outbreak Analysis: An Extensive Study Using Machine Learning Models and Time Series Analysis

The sudden unexpected rise in monkeypox cases worldwide has become an increasing concern. The zoonotic disease characterized by smallpox-like symptoms has already spread to nearly twenty countries and several continents and is labeled a potential pandemic by experts. monkeypox infections do not have specific treatments. However, since smallpox viruses are similar to monkeypox viruses administering antiviral drugs and vaccines against smallpox could be used to prevent and treat monkeypox. Since the disease is becoming a global concern, it is necessary to analyze its impact and population health. Analyzing key outcomes, such as the number of people infected, deaths, medical visits, hospitalizations, etc., could play a significant role in preventing the spread. In this study, we analyze the spread of the monkeypox virus across different countries using machine learning techniques such as linear regression (LR), decision trees (DT), random forests (RF), elastic net regression (EN), artificial neural networks (ANN), and convolutional neural networks (CNN). Our study shows that CNNs perform the best, and the performance of these models is evaluated using statistical parameters such as mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and R-squared error (R2). The study also presents a time-series-based analysis using autoregressive integrated moving averages (ARIMA) and seasonal auto-regressive integrated moving averages (SARIMA) models for measuring the events over time. Comprehending the spread can lead to understanding the risk, which may be used to prevent further spread and may enable timely and effective treatment.

Exploring restaurant and customer needs, barriers, interests, and food choices induced by the COVID-19 pandemic in Tarragona Province (Catalonia, Spain): A cross-sectional study

Background

COVID-19 has harmed restaurants, but customer preferences remain unknown. This study aims to determine the needs, barriers, interests, and food choice changes in restaurants and customers before and during the COVID-19 pandemic in Tarragona Province (Spain).

Methods

An observational cross-sectional study conducted in spring 2021 collected Mediterranean offerings, food safety, and hygiene information about the pandemic through online surveys and focus group interviews with restaurateurs and customers about the changes in their needs and new barriers.

Results

Fifty-one restaurateurs (44 survey, 7 focus group) and 138 customers (132 survey, 6 focus group) were included. In relation to the economic, emotional, and uncertainty restaurateurs' barriers detected, they implemented measures to tackle it: buy less and more often, reduce restaurant staff and reduce the restaurants offer, among others. Some customers reported changes in their restaurant orders, specifically increasing their takeaway orders. The Mediterranean diet offer (AMed criteria) remained without noticeable changes in any of the criteria. After lockdown, compared to before lockdown, restaurateurs increased their takeaway offerings by 34.1% (p < 0.001) and their use of digital menus by 27.3% (p < 0.001) because of customer demand. The use of local products in the menus remained high. The cleaning and disinfection tasks increased by 21.1% (p = 0.022), and the use of hydroalcoholic solutions increased by 13.7% (p = 0.031).

Conclusion

In restaurants, the first COVID-19 lockdown increased takeaway orders, sanitation, and digital communication. This study provides valuable information for adapting gastronomic offerings during challenging situations.

Synthesis of Potential Antiviral Agents for SARS-CoV-2 Using Molecular Hybridization Approach

We synthesized a set of small molecules using a molecular hybridization approach with good yields. The antiviral properties of the synthesized conjugates against the SAR-CoV-2 virus were investigated and their cytotoxicity was also determined. Among all the synthesized conjugates, compound 9f showed potential against SARS-CoV-2 and low cytotoxicity. The conjugates’ selectivity indexes (SIs) were determined to correlate the antiviral properties and cytotoxicity. The observed biological data were further validated using computational studies.

Exploring time evolution characteristics of the collaborative mode in emergency information release of public health emergencies: A network analysis of response to COVID-19 from the central government of China

Emergency information release during public health emergencies is a governance measure to slow down the spread of the epidemic and guide the public in scientific protection. Because of the uncertainty and life-cycle characteristics of public health emergencies, emergency information release represents the process of time dynamics. At present, it is an inevitable trend to establish a collaborative mechanism for emergency information release of public health emergencies to improve the release efficiency and respond to public demand. To determine time evolution characteristics of organizational collaboration in emergency information release, this study took the response to COVID-19 from the central government of China as an example and conducted research based on social network analysis. Based on information from COVID-19-related press conferences held by China's central government, the emergency information release collaborative networks (EIRCNs), and Emergency Organizations-Emergency Information Release Matters (EOs-EIRMs) 2-mode network were constructed. With the time evolution, the tightness, convergence, stability, and connectivity of EIRCNs in public health emergencies presented the process of lowering and then raising. At different stages, the core emergency organization (EO) nodes in EIRCNs continued to maintain a certain degree of activity. Their dynamic processes showed the characteristics of diversification rather than homogeneity. The time evolution of emergency information release matters (EIRMs) reflected the dynamic adjustment of the government's prevention and control measures and responded to the diversification of the public's understanding and protection needs during different stages of the COVID-19 pandemic. The study further examined the driving factors and implementation mechanism of the time evolution characteristics of the collaborative mode of emergency information release. The implementation of EIRMs at different stages had different resource requirements, which were usually achieved by introducing new EOs (Adding resource increment) or increasing the collaborative frequencies among EOs (Activating resource stock). In addition, further research prospects and feasibility interpretation were proposed.

Revalidation of an ultra-short scale for the measurement of perceived job security in Latin America

Introduction Due to the measures imposed by governments to reduce the spread of this new virus, the economic sector was one of the most affected during the COVID-19 pandemic. Several labor sectors had to undergo a virtual adaptation process resulting in job instability and job loss. The objective of this study was to revalidate an ultra-short scale for measuring perceived job security in Latin America. Methods A revalidation study was done on a short scale that measures worker’s perceived security about losing or keeping their job in the near future. Results The four items remained on the revalidated scale, where all four explained a single factor. The goodness-of-fit measures confirmed the single-factor model (χ: 7.06; df: 2; p = 0.29; mean square error: 0.015; goodness-of-fit index: 0.998; adjusted goodness-of-fit index: 0.991; comparative fit index: 0.999; Tucker-Lewis index: 0.997; normalized fit index: 0.998; incremental fit index: 0.999; and root mean square error of approximation: 0.036). The scale’s reliability was calculated using McDonald’s omega coefficient, obtaining an overall result of ω = 0.72. Conclusions The scale was correctly revalidated in Latin America, and the four items were kept in a single reliable factor.

The Relationship Between Meaning in Life and Health Behaviors in Adults Aged 55 Years and Over During the COVID-19 Pandemic: the Mediating Role of Risk Perception and the Moderating Role of Powerful Others Health Locus of Control

BACKGROUND

Coronavirus disease 2019 (COVID-19) has impacted many people's meaning in life and health behaviors. This study aimed to verify the relationship among meaning in life (MIL), epidemic risk perception, health locus of control (HLC), and preventive health behaviors among older adults after the COVID-19 outbreak was declared a pandemic.

METHOD

In this longitudinal study, 164 participants aged 55 years and above completed the following measures at time 1 (February 19, 2021) and one month later at time 2 (March 19, 2021): Meaning in Life in the Epidemic Questionnaire, Epidemic Risk Perception Questionnaire, Multidimensional Health Locus of Control Scale, and Health Behaviors Before and After the Epidemic Survey. Hayes' SPSS Process Macro was used to analyze the mediating effect of epidemic risk perception (model 4) and the moderating role of powerful others HLC in the mediation model (model 14).

RESULTS

The results showed that after controlling for gender, age, education level, and health behaviors at the baseline, risk perception had a significant mediating effect on the relationship between MIL and preventive health behaviors (β = .02, SE = .01, 95% CI [.00, .04]). In addition, powerful others HLC had a moderating effect on the second half of the mediating effect (β = .02, p = .02, 95% CI [.00, .03]). Specifically, compared to the older adults with low powerful others HLC, the risk perception of older adults with high powerful others HLC increased preventive health behaviors.

CONCLUSION

Practitioners should adequately cultivate older adults' risk awareness and reinforce the importance of advice from doctors and professionals, thereby effectively enhancing the preventive health behaviors of older adults in China during the COVID-19 pandemic.

The Impact of Consumers' Loneliness and Boredom on Purchase Intention in Live Commerce During COVID-19: Telepresence as a Mediator

This paper examines the relationship between consumer loneliness, boredom, telepresence, influencer-brand image congruence and purchase intention by investigating consumers of live commerce during the COVID-19 period. With the help of an online survey website, survey data was gathered on 550 Chinese customers who experienced live commerce shopping in China. Although previous studies have shown that consumer boredom and loneliness have an impact on purchase intention, the mechanism of influence remains unclear. As a result, additional research is needed to study the link between boredom and loneliness and customer purchase intention. Consumers' purchase intention was influenced by their feelings of loneliness and boredom. Telepresence played a mediating role in the impact of loneliness and boredom on purchase intention. Influencer-brand image congruence played a moderating role in the impact of consumers' boredom on purchase intention. The study results contribute to the research of factors impacting consumers' purchase intention. In addition, this study can help live commerce merchants better understand the impact factors of consumers' purchase intention and contribute to the development of live commerce.

COVID-19-Related Vaccine Hesitancy among Community Hospitals’ Healthcare Workers in Singapore

COVID-19 has culminated in widespread infections and increased deaths over the last 3 years. In addition, it has also resulted in collateral economic and geopolitical tensions. Vaccination remains one of the cornerstones in the fight against COVID-19. Vaccine hesitancy must be critically evaluated in individual countries to promote vaccine uptake. We describe a survey conducted in three Singapore community hospitals looking at healthcare workers’ vaccine hesitancy and the barriers for its uptake. The online anonymous survey was conducted from March to July 2021 on all staff across three community hospital sites in SingHealth Singapore. The questionnaire was developed following a scoping review and was pilot tested and finalized into a 58-item instrument capturing data on demographics, contextual features, knowledge, attitudes, perceptions, and other vaccine-related factors in the vaccine hesitancy matrix. Logistic regression analysis was employed for all co-variates that are significant in univariate analysis. The response rate was 23.9%, and the vaccine hesitancy prevalence was 48.5% in the initial phase of the pandemic. On logistic regression analysis, only being female, a younger age, not having had a loved one or friend infected with COVID-19 and obtaining information from newspapers were associated with vaccine hesitancy in healthcare workers in Singapore community hospitals.

Regression Analysis for COVID-19 Infections and Deaths Based on Food Access and Health Issues

COVID-19, or SARS-CoV-2, is considered as one of the greatest pandemics in our modern time. It affected people’s health, education, employment, the economy, tourism, and transportation systems. It will take a long time to recover from these effects and return people’s lives back to normal. The main objective of this study is to investigate the various factors in health and food access, and their spatial correlation and statistical association with COVID-19 spread. The minor aim is to explore regression models on examining COVID-19 spread with these variables. To address these objectives, we are studying the interrelation of various socio-economic factors that would help all humans to better prepare for the next pandemic. One of these critical factors is food access and food distribution as it could be high-risk population density places that are spreading the virus infections. More variables, such as income and people density, would influence the pandemic spread. In this study, we produced the spatial extent of COVID-19 cases with food outlets by using the spatial analysis method of geographic information systems. The methodology consisted of clustering techniques and overlaying the spatial extent mapping of the clusters of food outlets and the infected cases. Post-mapping, we analyzed these clusters’ proximity for any spatial variability, correlations between them, and their causal relationships. The quantitative analyses of the health issues and food access areas against COVID-19 infections and deaths were performed using machine learning regression techniques to understand the multi-variate factors. The results indicate a correlation between the dependent variables and independent variables with a Pearson correlation R²-score = 0.44% for COVID-19 cases and R² = 60% for COVID-19 deaths. The regression model with an R²-score of 0.60 would be useful to show the goodness of fit for COVID-19 deaths and the health issues and food access factors.

Self-organizing Maps and Bayesian Regularized Neural Network for Analyzing Gasoline and Diesel Price Drifts

Any nation’s growth depends on the trend of the price of fuel. The fuel price drifts have both direct and indirect impacts on a nation’s economy. Nation’s growth will be hampered due to the higher level of inflation prevailing in the oil industry. This paper proposed a method of analyzing Gasoline and Diesel Price Drifts based on Self-organizing Maps and Bayesian regularized neural networks. The US gasoline and diesel price timeline dataset is used to validate the proposed approach. In the dataset, all grades, regular, medium, and premium with conventional, reformulated, all formulation of gasoline combinations, and diesel pricing per gallon weekly from 1995 to January 2021, are considered. For the data visualization purpose, we have used self-organizing maps and analyzed them with a neural network algorithm. The nonlinear autoregressive neural network is adopted because of the time series dataset. Three training algorithms are adopted to train the neural networks: Levenberg-Marquard, scaled conjugate gradient, and Bayesian regularization. The results are hopeful and reveal the robustness of the proposed model. In the proposed approach, we have found Levenberg-Marquard error falls from − 0.1074 to 0.1424, scaled conjugate gradient error falls from − 0.1476 to 0.1618, and similarly, Bayesian regularization error falls in − 0.09854 to 0.09871, which showed that out of the three approaches considered, the Bayesian regularization gives better results.

Analysing deaths and confirmed cases of COVID-19 pandemic by analytical approaches

In this work, the time series of growth rates regarding confirmed cases and deaths of COVID-19 for several sampled countries are investigated via an introduction of an orthonormal basis. This basis, which is served as the feature benchmark, reveals the hidden features of COVID-19 via the magnitude of Fourier coefficients. These coefficients are ranked in the form of ranking vectors for all the sampled countries. Based on these and Manhattan metric, we then perform spectral clustering to categorise the countries. Unlike the classical cosine similarity analysis which, relatively speaking, is a composite index and hard to identify the features of the categorised countries, spectral analysis delves into the internal structures or dynamical trend of the time series. This research shows there is no single feature that dominates the trend of the growth rates. It also reveals that results from the spectral analysis are different from the ones of cosine similarity. In the end, some approximated values of the confirmed cases and deaths are also calculated by the spectral analysis.

A cross-sectional study of COVID-19 pandemic-related organizational aspects in health care

Aim

This study explores how healthcare professionals included in the COVID‐19 contingency plan experienced organizational changes, and explores factors associated with the experiences. Additionally, the study aimed to identify learning points for future similar scenarios.

Design

A cross‐sectional study.

Methods

A questionnaire survey of healthcare professionals at three Danish hospitals, June 2020.

Results

A total of 1,448 healthcare professionals completed the questionnaire. Hereof, 813 (57%) were relocated to new settings/new jobs. The majority experienced that their relocation was totally (49%) or partially (31%) imposed, and 51% reported that the overall experience of the new job function was satisfactory. Type of profession and whether relocation to the new job function was imposed were the main variables associated with the overall experience of being part of the contingency plan. Suggestions for future scenarios included training adjusted to individual competencies, more targeted information, voluntariness with consideration of individual needs and clarification of expectations.

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

Neutrophil-to-lymphocyte ratio (NLR) is an accessible and widely used biomarker. NLR may be used as an early marker of poor prognosis in patients with COVID-19.

OBJECTIVE

To evaluate the prognostic value of the NLR in patients diagnosed with COVID-19.

METHODS

We conducted a systematic review and meta-analysis. Observational studies that reported the association between baseline NLR values (ie, at hospital admission) and severity or all-cause mortality in COVID-19 patients were included. The quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS). Random effects models and inverse variance method were used for meta-analyses. The effects were expressed as odds ratios (ORs) and their 95% confidence intervals (CIs). Small study effects were assessed with the Egger's test.

RESULTS

We analysed 61 studies (n = 15 522 patients), 58 cohorts, and 3 case-control studies. An increase of one unit of NLR was associated with higher odds of severity (OR 6.22; 95%CI 4.93 to 7.84; P < .001) and higher odds of all-cause mortality (OR 12.6; 95%CI 6.88 to 23.06; P < .001). In our sensitivity analysis, we found that 41 studies with low risk of bias and moderate heterogeneity (I2  = 53% and 58%) maintained strong association between NLR values and both outcomes (severity: OR 5.36; 95% CI 4.45 to 6.45; P < .001; mortality: OR 10.42 95% CI 7.73 to 14.06; P = .005).

CONCLUSIONS

Higher values of NLR were associated with severity and all-cause mortality in hospitalised COVID-19 patients.

The Similarities and Distances of Growth Rates Related to COVID-19 Between Different Countries Based on Spectral Analysis

The COVID-19 pandemic has taken more than 1.78 million of lives across the globe. Identifying the underlying evolutive patterns between different countries would help us single out the mutated paths and behavior of this virus. I devise an orthonormal basis which would serve as the features to relate the evolution of one country's cases and deaths to others another's via coefficients from the inner product. Then I rank the coefficients measured by the inner product via the featured frequencies. The distances between these ranked vectors are evaluated by Manhattan metric. Afterwards, I associate each country with its nearest neighbor which shares the evolutive pattern via the distance matrix. Our research shows such patterns is are not random at all, i.e., the underlying pattern could be contributed to by some factors. In the end, I perform the typical cosine similarity on the time-series data. The comparison shows our mechanism differs from the typical one, but is also related to each it in some way. These findings reveal the underlying interaction between countries with respect to cases and deaths of COVID-19.

Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia

This observational study aims to investigate the early disease patterns of coronavirus disease 2019 (COVID-19) in Southeast Asia, consequently providing historical experience for further interventions. Data were extracted from official websites of the WHO and health authorities of relevant countries. A total of 1346 confirmed cases of COVID-19, with 217 recoveries and 18 deaths, were reported in Southeast Asia as of 16 March 2020. The basic reproductive number (R0) of COVID-19 in the region was estimated as 2.51 (95% CI:2.31 to 2.73), and there were significant geographical variations at the subregional level. Early transmission dynamics were examined with an exponential regression model: y = 0.30e0.13x (p < 0.01, R2 = 0.96), which could help predict short-term incidence. Country-level disease burden was positively correlated with Human Development Index (r = 0.86, p < 0.01). A potential early shift in spatial diffusion patterns and a spatiotemporal cluster occurring in Malaysia and Singapore were detected. Demographic analyses of 925 confirmed cases indicated a median age of 44 years and a sex ratio (male/female) of 1.25. Age may play a significant role in both susceptibilities and outcomes. The COVID-19 situation in Southeast Asia is challenging and unevenly geographically distributed. Hence, enhanced real-time surveillance and more efficient resource allocation are urgently needed.

Community engagement in the prevention and control of COVID-19: Insights from Vietnam

Introduction

Community engagement (CE) is an effective public health strategy for improving health outcomes. There is limited published knowledge about effective approaches to CE in ensuring effective responses to COVID-19 throughout lockdowns, travel restrictions and social distancing. In this paper, we contribute to bridging this gap by highlighting experience of CE in Vietnam, specifically focusing on migrant workers in Vietnam.

Methods

A cross-sectional qualitative study design was used with qualitative data collection was carried out during August-October 2020. Two districts were purposefully selected from two large industrial zones. Data was collected using in-depth interviews (n = 36) with individuals and households, migrants and owners of dormitories, industrial zone factory representatives, community representatives and health authorities. Data was analyzed using thematic analysis approach. The study received ethics approval from the Hanoi University Institutional Review Board.

Results

The government’s response to COVID-19 was spearheaded by the multi-sectoral National Steering Committee for the Prevention and Control of COVID-19, chaired by the Vice Prime Minister and comprised different members from 23 ministries. This structure was replicated throughout the province and local levels and all public and private organizations. Different activities were carried out by local communities, following four key principles of infection control: early detection, isolation, quarantine and hospitalization. We found three key determinants of engagement of migrant workers with COVID-19 prevention and control: availability of resources, appropriate capacity strengthening, transparent and continuous communication and a sense of trust in government legitimacy.

Discussion and conclusion

Our results support the current literature on CE in infection control which highlights the importance of context and suggests that future CE should consider five key components: multi-sectoral collaboration with a whole-of-community approach to strengthen governance structures with context-specific partnerships; mobilization of resources and decentralization of decision making to encourage self-reliance and building of local capacity; capacity building through training and supervision to local institutions; transparent and clear communication of health risks and sensitization of local communities to improve compliance and foster trust in the government measures; and understanding the urgent needs ensuring of social security and engaging all parts of the community, specifically the vulnerable groups.

A study on the sentiments and psychology of twitter users during COVID-19 lockdown period

The outbreak of the novel Coronavirus in late 2019 brought severe devastation to the world. The pandemic spread across the globe, infecting more than ten million people and disrupting several businesses. Although social distancing and the use of protective masks were suggested all over the world, the cases seem to rise, which led to worldwide lockdown in different phases. The rampant escalation in the number of cases, the global effects, and the lockdown may have a severe effect on the psychology of people. The emergency protocols implemented by the authorities also lead to increased use in the number of multimedia devices. Excessive use of such devices may also contribute to psychological disorders. Hence, hence it is necessary to analyze the state of mind of people during the lockdown. In this paper, we perform a sentiment analysis of Twitter data during the pandemic lockdown, i.e., two weeks and four weeks after the lockdown was imposed. Investigating the sentiments of people in the form of positive, negative, and neutral tweets would assist us in determining how people are dealing with the pandemic and its effects on a psychological level. Our study shows that the lockdown witnessed more number positive tweets globally on multiple datasets. This is indicative of the positivity and optimism based on the sentiments and psychology of Twitter users worldwide. The study will be effective in determining people's mental well-being and will also be useful in devising appropriate lockdown strategies and crisis management in the future.

Bibliometric Evaluation of Global Tai Chi Research from 1980-2020

While studies on the health benefits of Tai Chi have sprung up over the past four decades, few have engaged in collecting global data, estimating the developing trends, and conducting reviews from the perspective of visualization and bibliometric analysis. This study aimed to provide a summary of the global scientific outputs on Tai Chi research from 1980 to 2020, explore the frontiers, identify cooperation networks, track research trends and highlight emerging hotspots. Relevant publications were downloaded from the Web of Science Core Collection (WoSCC) database between 1980 and 2020. Bibliometric visualization and comparative analysis of authors, cited authors, journals, co-cited journals, institutions, countries, references, and keywords were systematically conducted using CiteSpace software. A total of 1078 publications satisfied the search criteria, and the trend of annual related publications was generally in an upward trend, although with some fluctuations. China (503) and Harvard University (74) were the most prolific country and institution, respectively. Most of the related researches were published in the journals with a focus on sport sciences, alternative medicine, geriatrics gerontology, and rehabilitation. Our results indicated that the current concerns and difficulties of Tai Chi research are “Intervention method”, “Targeted therapy”, “Applicable population”, “Risk factors”, and “Research quality”. The frontiers and promising domains of Tai Chi exercise in the health science field are preventions and rehabilitations of “Fall risk”, “Cardiorespiratory related disease”, “Stroke”, “Parkinson’s disease”, and “Depression”, which should receive more attention in the future.

Influence of life intervention on anxiety, depression, and quality of life of COVID-19 patients: A protocol for systematic review and meta-analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) patients suffer from anxiety, depression, and sleep disorder due to isolation treatment and other reasons. Whether life interventions can be an alternative therapy for COVID-19 patients, accompanied with anxiety, depression, and sleep disorder, is controversial. Therefore, we conducted a meta-analysis and systematic review to evaluate the effects of life interventions on anxiety, depression, and sleep disorder in COVID-19 patients to provide some guidance for clinical application.

METHODS

The randomized controlled trials related to the life intervention and COVID-19 from inception to February 2021 will be searched. The following databases are our focused areas: the Cochrane Central Register of Controlled Trials, PubMed, MEDLINE, EMBASE, Web of Science, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and Wan Fang Database. Two investigators would independently screen the literature according to the inclusion and exclusion criteria, extract data, and evaluate the risk of bias in the included studies. Meta-analysis was performed with RevMan 5.3 software.

RESULTS

The results will provide a high-quality synthesis of current evidence for researchers in this subject area.

CONCLUSION

The conclusion of our study will provide evidence for the judgment of whether life intervention is an effective intervention on COVID-19 patients.

PROSPERO REGISTRATION NUMBER

CRD42020199802.

A novel LSTM-CNN-grid search-based deep neural network for sentiment analysis

As the number of users getting acquainted with the Internet is escalating rapidly, there is more user-generated content on the web. Comprehending hidden opinions, sentiments, and emotions in emails, tweets, reviews, and comments is a challenge and equally crucial for social media monitoring, brand monitoring, customer services, and market research. Sentiment analysis determines the emotional tone behind a series of words may essentially be used to understand the attitude, opinions, and emotions of users. We propose a novel long short-term memory (LSTM)-convolutional neural networks (CNN)-grid search-based deep neural network model for sentiment analysis. The study considers baseline algorithms like convolutional neural networks, K-nearest neighbor, LSTM, neural networks, LSTM-CNN, and CNN-LSTM which have been evaluated using accuracy, precision, sensitivity, specificity, and F-1 score, on multiple datasets. Our results show that the proposed model based on hyperparameter optimization outperforms other baseline models with an overall accuracy greater than 96%.

Life in lockdown: Social isolation, loneliness and quality of life in the elderly during the COVİD-19 pandemic: A scoping review

Coronavirus disease-2019 (COVID-19) had an unprecedented effect all over the world, especially in older individuals. The aim is to evaluate the social isolation, loneliness and quality of life of elderly individuals during the COVID-19 pandemic and to map suggestions to reveal and improve the current situation. This was a scoping review. Articles since December 2019 to March 2021 published on PubMed, Scopus, ProQuest, Cochrane Library, CINAHL databases with the following MeSh terms (‘COVID-19’, ‘coronavirus’, ‘quality of life’ ‘aging’, ‘older people’, ‘elderly’, ‘loneliness’ and ‘social isolation) in English were included. The research, by consensus, resulted in seven studies selected for full reading, including three descriptive and cross-sectional studies, a quasi-experimental study, a pre-post pilot program, an editorial note and a correspondence. In generally, these recommendations were grouped as evaluating the current state of loneliness and isolation in elderly people, making more use of technology opportunities, using cognitive behavioral therapies and different individual intervention components.

The effect of Tai Chi on the quality of life in the elderly patients recovering from coronavirus disease 2019: A protocol for systematic review and meta-analysis

BACKGROUND

coronavirus disease 2019 (COVID-19) is spreading fast starting late 2019. As their cardiopulmonary and immune functions gradually decline, elderly people are prone to COVID-19. Tai Chi has a positive impact on heart function, blood pressure, lung function, blood circulation, and so on, and it's suitable for the elderly. Quality of life (QoL)can reflect of individuals' physical and mental health, it can also reflects their ability to participate in society. This systematic review and meta-analysis will summarize the current evidence that Tai Chi improve the QoL in the elderly patients recovering from COVID-19.

METHODS

We will search PubMed, EMBASE, MEDLINE, the Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Biomedical Literature Database, Chinese Science and Technology Periodical Database, Wanfang Database, Clinical Trials and Chinese Clinical Trial Registry. The complete process will include study selection, data extraction, risk of bias assessment and meta-analyses. Endnote X9.3 will be used to manage data screening. The statistical analysis will be completed by Stata/SE 15.1 software.

RESULTS

This proposed study will evaluate the effectiveness and safety of Tai Chi for the improvement of QoL in elderly COVID-19 patients during the recovery period.

CONCLUSION

The conclusion of this study will provide evidence to prove the safety and effectiveness of Tai Chi on elderly COVID-19 patients during the recovery period.

ETHICS AND DISSEMINATION

This protocol will not evaluate individual patient information or infringe patient rights and therefore does not require ethical approval.

REGISTRATION

PEROSPERO CRD42020206875.

Global Forecasting Confirmed and Fatal Cases of COVID-19 Outbreak Using Autoregressive Integrated Moving Average Model

The world health organization (WHO) formally proclaimed the novel coronavirus, called COVID-19, a worldwide pandemic on March 11 2020. In December 2019, COVID-19 was first identified in Wuhan city, China, and now coronavirus has spread across various nations infecting more than 198 countries. As the cities around China started getting contaminated, the number of cases increased exponentially. As of March 18 2020, the number of confirmed cases worldwide was more than 250,000, and Asia alone had more than 81,000 cases. The proposed model uses time series analysis to forecast the outbreak of COVID-19 around the world in the upcoming days by using an autoregressive integrated moving average (ARIMA). We analyze data from February 1 2020 to April 1 2020. The result shows that 120,000 confirmed fatal cases are forecasted using ARIMA by April 1 2020. Moreover, we have also evaluated the total confirmed cases, the total fatal cases, autocorrelation function, and white noise time-series for both confirmed cases and fatalities in the COVID-19 outbreak.