Commemoration and Emotional Sustenance: A Text Analysis of Students' Motivations Behind Online Mourning of Dr Li Wenliang.

As one of the first doctors issued a protective warning to the public, Dr. Li Wenliang was known as "whistleblower" of COVID-19 pandemic. After his death of COVID-19, students entered to his Sina Weibo to display their condolences and sorrow. We conduct text analysis and sentiment classification to investigate the motivation behind online mourning for Dr. Li among students on Sina Weibo. Our results indicate that, a) there always more than one motivation behind online mourning exists in each time period. b) continuing connection and semi-interaction with the deceased is the main motivation when students mourn online. c) there exists positive correlation between the influence of the deceased and the motivation--sharing information with the community of fans and creating social support in a time of loss and social support. d) the motivation--honoring the dead and expressing sadness and resentment can gradually lose over time.

Psychological state and its correlates of local college students in Wuhan during COVID-19 pandemic.

In 2020, the lockdown of Wuhan due to the outbreak of COVID-19 impacted various aspects of local college students' life and may further negatively affect their psychological state. This study was conducted among 652 Wuhan local college students during the quarantine of this city. We assessed their psychological state using Depression-Anxiety-Stress Scale 21 and evaluated their living condition including diet, schedule, recreational activities, social contact, academic life, and attention paid to pandemic news. Results showed that 16.87% of the students reported stress, 28.68% with anxiety, and 35.12% had depression. According to multivariate logistic regression analysis, having a medical background was associated with higher stress levels; students who had an irregular diet and schedule were more likely to develop stress, anxiety, and depression; students with their academic life affected had a higher prevalence of anxiety and depression. By studying local students in the hardest-hit area during the pandemic, our findings can provide references for the improvement of college students' mental health in the long term.

A cross-sectional study on the mental health of patients with COVID-19 1 year after discharge in Huanggang, China.

OBJECTIVE: This study is aimed to investigate the mental health status of COVID-19 survivors 1 year after discharge from hospital and reveal the related risk factors. METHODS: From April 11 to May 11, 2021, 566 COVID-19 survivors in Huanggang city were recruited through their primary doctors. A total of 535 participants (94.5%) admitted to participate in the survey and completed the questionnaires. Five scales were applied including 7-Items Generalized Anxiety Disorder Scale, Patient Health Questionnaire-9, Impact of Event Scale-Revised, Pittsburgh Sleep Quality Index, and Fatigue Scale-14. The chi-square and the Fisher's exact test were used to evaluate the classification data, multivariate logistic regression was used to explore the related factors of sleep quality, fatigue, anxiety, depression, and post-traumatic stress disorder (PTSD). RESULTS: One year after being discharged, of the 535 COVID-19 survivors, 252 (47.1%) had poor sleep quality; 157 (29.3%) had the symptoms of fatigue; 84 (15.7%),112 (20.9%), and 130 (24.3%) suffered from symptoms of anxiety, depression, and PTSD, respectively. The logistic regression analysis showed that history of chronic disease was risk factor for poor sleep quality (OR 2.501; 95% CI, 1.618-3.866), fatigue (OR 3.284; 95% CI 2.143-5.033), PTSD (OR 2.323; 95% CI 1.431-3.773) and depression (OR 1.950; 95% CI 1.106-3.436) in COVID-19 survivors. Smoking contributed to the poor sleep quality (OR 2.005; 95% CI 1.044-3.850), anxiety (OR 4.491; 95% CI 2.276-8.861) and depression (OR 5.459; 95% CI 2.651-11.239) in survivors. Drinking influenced fatigue (OR 2.783; 95% CI 1.331-5.819) and PTSD (OR 4.419; 95% CI 1.990-9.814) in survivors. Compared with college-educated survivors, survivors with high school education were at higher risk for poor sleep quality (OR 1.828; 95% CI 1.050-3.181) and PTSD (OR 2.521; 95% CI 1.316-4.830), and survivors with junior high school education were at higher risk for PTSD (OR 2.078; 95% CI 1.039-4.155). Compared with overweight survivors (BMI ≥ 23.0), survivors with normal BMI (18.5-22.9) (OR 0.600; 95% CI 0.405-0.889) were at lower risk for fatigue. While being housewife (OR 0.390; 95% CI 0.189-0.803) was protective factor for fatigue and having more family members was protective factor for PTSD (OR 0.404 95% CI 0.250-0.653) in survivors. CONCLUSIONS: One year after infection, poor sleep quality, fatigue, anxiety, depression, and PTSD, still existed in a relatively high proportion of COVID-19 survivors. Chronic disease history was an independent risk factor for poor sleep quality, fatigue, depression, and PTSD. Participants with low education levels were more likely to have mental problems than the others. We should focus on the long-term psychological impact of COVID-19 on survivors, and the government should apply appropriate mental health services to offer psychiatric support.

Corrigendum: What "family affair?" domestic violence awareness in China.

[This corrects the article DOI: 10.3389/fpubh.2022.795841.].

Technology-based interventions for health challenges older women face amid COVID-19: a systematic review protocol.

BACKGROUND: Pandemics, such as COVID-19, are dangerous and socially disruptive. Though no one is immune to COVID-19, older persons often bear the brunt of its consequences. This is particularly true for older women, as they often face more pronounced health challenges relative to other segments in society, including complex care needs, insufficient care provisions, mental illness, neglect, and increased domestic abuse. To further compound the situation, because protective measures like lockdowns can result in unintended consequences, many health services older women depend on can become disrupted or discontinued amid pandemics. While technology-based interventions have the potential to provide near-time, location-free, and virtually accessible care, there is a dearth of systematic insights into this mode of care in the literature. To bridge the research gaps, this investigation aims to examine the characteristics and effectiveness of technology-based interventions that could address health challenges older women face amid COVID-19. METHODS: A systematic review of randomized trials reporting on technology-based interventions for older women (≥65 years) during COVID-19 will be conducted. The databases of Web of Science, ScienceDirect, PubMed/MEDLINE, PsycINFO, CINAHL, and Scopus will be searched. Retrieved citations will be screened independently by at least two reviewers against the eligibility criteria. Included studies will be assessed using the Cochrane ROB-2 tool. Data will be extracted independently by the reviewers. Where possible, meta-analyses will be performed on relevant study outcomes and analysed via odds ratios on the dichotomized outcomes. Where applicable, heterogeneity will be measured using the Cochrane Q test, and publication bias will be assessed via funnel plots and Egger's regression test. DISCUSSION: Technology has the potential to transform healthcare for the better. To help society better safeguard vulnerable populations' health and quality of life, this investigation sets out to gauge the state-of-the-art development of technology-based interventions tailored to the health challenges older women face amid COVID-19. In light of the growing prevalence of population ageing and the inevitability of infectious disease outbreaks, greater research efforts are needed to ensure the timely inception and effective implementation of technology-based health solutions for vulnerable populations like older women, amid public health crises like COVID-19 and beyond. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020194003.

The relationship between oxygen therapy, drug therapy, and COVID-19 mortality.

Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19). We conducted a retrospective study of COVID-19 inpatients in Wuhan Pulmonary Hospital (Wuhan, China) from January 1 to February 29, 2020. The subjects were divided into four groups due to different treatment regimes. We used the Kaplan-Meier method to determine the cumulative rates of in-hospital death and the Cox proportional hazard model to calculate the risk factors and corresponding hazard ratios. A total of 185 patients were included in this study. The median age of the patients was 62 years, including 94 men and 91 women. Kaplan-Meier analysis demonstrated that mortality was higher in older patients, higher in men, and lower in the low-flow oxygen therapy group. Body mass index (BMI) had no influence on mortality, as well as high flow oxygen therapy, Lopinavir-ritonavir (LPV/r) therapy, and the interferon-alpha add LPV/r therapy. Cox proportional hazard regression confirmed that the low flow oxygen therapy was independent protective factor for in-hospital death after adjusting for age, gender, and BMI. In conclusion, the mortality was higher in older patients, higher in men, and lower in the low-flow oxygen therapy group. BMI had no influence on mortality, as well as high flow oxygen therapy, LPV/r therapy, and interferon-alpha add LPV/r therapy.

Subjective wellbeing and emotion regulation strategies: How are they associated with student engagement in online learning during Covid-19?

BACKGROUND: The COVID-19 pandemic has brought unprecedented challenges to the world, creating significant impact on people's lives and subjective wellbeing. While previous studies have shown that students' wellbeing and how they manage their emotions are critical to students' learning, less research has considered their specific impacts on student engagement in online learning. AIMS: The aim of this study is to examine how students' subjective wellbeing and emotion regulation strategies (viz cognitive reappraisal and expressive suppression) are associated with student engagement in online learning during the pandemic. SAMPLE: A total of 965 students from a university in China participated in the study. METHODS: The data were collected online during the COVID-19 from March to July 2020, which included measures of wellbeing, emotion regulation strategie, and online learning engagement. RESULTS: Structural equation modelling results showed that wellbeing was positively associated with both the use of reappraisal and suppression. Moreover, mediation analysis showed that reappraisal partially mediated the relationship between wellbeing and all types of online learning engagement (including cognitive, emotional and behavioural engagements). Conversely, suppression was found to have a small mediating effect between wellbeing and behavioural engagement of online learning only. No such effect was found on cognitive and emotional engagements. CONCLUSIONS: The findings provide evidence on the positive relationship between wellbeing and both the strategies of suppression and reappraisal during the pandemic. However, only reappraisal has positive impact on learning, suggesting the importance of effective regulation strategies on students' online engagement. Theoretical and practical implications of the findings are discussed.

What "Family Affair?" Domestic Violence Awareness in China.

Introduction: Domestic violence is toxic to society. With approximately one in three women on average falling victim to domestic violence, systematic solutions are needed. To further complicate the issue, mounting research shows that COVID-19 has further exacerbated domestic violence across the world. Situations could be even more pronounced in countries like China, where though domestic violence is prevalent, there is a dearth of research, such as intervention studies, to address the issue. This study investigates key barriers to domestic violence research development in China, with a close focus on salient cultural influences. Methods: A review of the literature on domestic violence in China in PubMed, PsycINFO, and Scopus was conducted to answer the research question. The search was focused on three themes, domestic violence, China, research, and cultural influences. Results: The study findings show that categorizing domestic violence as a "family affair" is a key barrier to domestic violence research development in China-an incremental hindrance that prevents the public and policymakers from understanding the full scale and scope of domestic violence in China. In addition to abusers, witnesses, and victims, even law enforcement in China often dismisses domestic violence crimes as "family affairs" that resides outside the reach and realm of the law. The results indicated that mistreating domestic violence crimes as "family affairs" is a vital manifestation of the deep-rooted cultural influences in China, ranging from traditional Confucian beliefs in social harmony to the assumed social norms of not interfering with other people's businesses. Conclusion: Domestic violence corrupts public health and social stability. Our study found that dismissing domestic violence cases as "family affairs" is an incremental reason why China's domestic violence research is scarce and awareness is low. In light of the government's voiced support for women's rights, we call for the Chinese government to develop effective interventions to timely and effectively address the domestic violence epidemic in China.

Disinformation of text mining online about tobacco and the COVID-19 discussed on Sina Weibo.

INTRODUCTION: During the COVID-19 pandemic, various types of disinformation have emerged from the media. This study focuses on the online disinformation about tobacco and the COVID-19 on the Sina Weibo, the Chinese largest new media microblog platform. METHODS: The related posts from the beginning of the epidemic in December 2019 to 19 January 2021 were searched. Text mining technology was applied on these posts to identify content on 'smoking can prevent COVID-19'. Descriptive research was used to analyze the dataset. RESULTS: Among the 912 original posts, 508 informative posts were selected after artificial recognition, including 112 posts of spreading disinformation and 396 which dispel the disinformation. Of the disinformation posts, 74% (83/112) cited the results of scientific research, and 17% (19/112) mentioned that smog from burning Asian wormwood could prevent COVID-19. By analyzing the public's comments on these 112 disinformation posts, it was suggested that about 12% of the comments were in support, and 88% of the posts were opposed or invalid. The proportion of supportive comments on pseudo-scientific information was higher than on plain disinformation, 21% and 9%, respectively. CONCLUSIONS: The disinformation of promoting smoking as a way to prevent COVID-19 has the typical feature of using pseudo-scientific arguments to package disinformation, making it very difficult for readers without professional knowledge to identify. Such actions harm both tobacco control and COVID-19 prevention.

Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan.

BACKGROUND: Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. METHODS: A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. RESULTS: The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. CONCLUSIONS: The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. KEYORDS: COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

Three phases of COVID-19: theoretical thinking on epidemic prevention and control.

The response to the COVID-19 outbreak was evaluated by analyzing the literature published after the outbreak. By reviewing and summarizing the different stages, nodes and measures during the occurrence and development of COVID-19, other countries can draw on their experience and reference for the fight against COVID-19 in China. In December 2019, the COVID-19 was first reported in Wuhan, China, and then the whole world continued to pay close attention to the development of the COVID-19 in China. Until now, the outbreak and development of the COVID-19 has lasted for more than a year. Looking back on the process of the COVID-19, several key stages and events have had a profound impact on the development of the COVID-19. We divided the evolution of the outbreak since its origin into different phases. The policy changes of the Chinese government in different periods of the COVID-19 pandemic were evaluated, and the transformation nodes of the policies and differences in each stage were determined. We divided the evolution of the outbreak into three stages of the outbreak are initial outbreak stage, the carrying of the virus (people or goods) stage, and the non-direct contact transmission (goods transmission) stage. This paper reviews the three stages of the evolution of responses by the Chinese government to COVID-19 using a phase analysis method to examine different policy starting points, changes to policy, and reasons for policy change. The study provides a resource for COVID-19 policy review and includes image of the three-phase shift in policy as the epidemic progressed. By summarizing and describing the policy changes in the three phases of the response to COVID-19 in China, this paper provides a resource for others in formulating their response to the pandemic. The commentary is also designed to provoke scholarly dialog among the readers of the journal.

Mental health consequences of COVID-19 media coverage: the need for effective crisis communication practices.

During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading "Chinese virus" narrative, and the use of disinfectants to "cure" COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.

Epidemic characteristics of coronavirus disease 2019 in northwest and northeast border areas of China

Objective: To analyze the epidemic characteristics of coronavirus disease 2019 (COVID-19) in the northwest and northeast border areas of China (as of April 20, 2020) and provide scientific basis for prevention and control of COVID-19 epidemic situation.

Identification of COVID-19 Clinical Phenotypes by Principal Component Analysis-Based Cluster Analysis.

Background: COVID-19 has been quickly spreading, making it a serious public health threat. It is important to identify phenotypes to predict the severity of disease and design an individualized treatment. Methods: We collected data from 213 COVID-19 patients in Wuhan Pulmonary Hospital from January 1 to March 30, 2020. Principal component analysis (PCA) and cluster analysis were used to classify patients. Results: We identified three distinct subgroups of COVID-19. Cluster 1 was the largest group (52.6%) and characterized by oldest age, lowest cellular immune function, and albumin levels. 38.5% of subjects were grouped into Cluster 2. Most of the lab results in Cluster 2 fell between those of Clusters 1 and 3. Cluster 3 was the smallest cluster (8.9%), characterized by youngest age and highest cellular immune function. The incidence of respiratory failure, acute respiratory distress syndrome (ARDS), heart failure, and usage of non-invasive mechanical ventilation in Cluster 1 was significantly higher than others (P < 0.05). Cluster 1 had the highest death rate of 30.4% (P = 0.005). Although there were significant differences in age between Clusters 2 and 3 (P < 0.001), we found that there was no difference in demand for medical resources. Conclusions: We identified three distinct clusters of the COVID-19 patients. The results show that age alone could not be used to assess a patient's condition. Specifically, management of albumin, and immune function are important in reducing the severity of disease.

COVID-19 in Shanghai: IPC Policy Exploration in Support of Work Resumption Through System Dynamics Modeling.

PURPOSE: It is unclear how and to what extent various infection prevention and control (IPC) policies affect the spread of an epidemic during work resumption. In order to assess the impact of IPC policies, this research addresses the results of a policy simulation in Shanghai, China, which estimates the transmission dynamics of COVID-19 under various IPC policies and offers evidence-based outcomes of work resumption policies for the world. MATERIALS AND METHODS: This simulation research is based on a system dynamics (SD) model that integrates IPC work resumption policies implemented in Shanghai into the classical susceptible-exposed-infected-removed (SEIR) epidemiological model. Input data were obtained from official websites, the Baidu migration index and published literature. The SD model was validated by comparing results with real-world data. RESULTS: The simulations show that a non-quarantined and non-staged approach to work resumption (Policy 1) would bring a small secondary outbreak of COVID-19. The quarantined but non-staged approach (Policy 2) and the non-quarantined but staged approach (Policy 3) would not bring a secondary outbreak of COVID-19. However, they both would generate more newly confirmed cases than the staged and quarantined approach (Policy 4). Moreover, the 14-day quarantine policy alone appears to be more effective in reducing transmission risk than the staged work resumption policy alone. The combined staged and quarantined IPC policy led to the fewest confirmed cases caused by work resumption in Shanghai, and the spread of COVID-19 stopped (ie, the number of newly confirmed cases reduced to zero) at the earliest date. CONCLUSION: Conservative IPC policies can prevent a second outbreak of COVID-19 during work resumption. The dynamic systems model designed in this study can serve as a tool to test various IPC work resumption policies, facilitating decision-making in responses to combating the COVID-19 pandemic.

A race for a better understanding of COVID-19 vaccine non-adopters.

In this paper, we aim to underscore the need for a more nuanced understanding of vaccine non-adopters. As the availability of vaccines does not translate into their de facto adoption-a phenomenon that may be more pronounced amid "Operation Warp Speed"-it is important for public health professionals to thoroughly understand their "customers" (i.e., end users of COVID-19 vaccines) to ensure satisfactory vaccination rates and to safeguard society at large.

Dynamic changes of D-dimer and neutrophil-lymphocyte count ratio as prognostic biomarkers in COVID-19.

BACKGROUND: Since December 2019, the outbreak of COVID-19 caused a large number of hospital admissions in China. Many patients with COVID-19 have symptoms of acute respiratory distress syndrome, even are in danger of death. This is the first study to evaluate dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio (NLR) as a prognostic utility in patients with COVID-19 for clinical use. METHODS: In a retrospective study, we collected data from 349 hospitalized patients who diagnosed as the infection of the COVID-19 in Wuhan Pulmonary Hospital. We used ROC curves and Cox regression analysis to explore critical value (optimal cut-off point associated with Youden index) and prognostic role of dynamic changes of D-Dimer and NLR. RESULTS: Three hundred forty-nine participants were enrolled in this study and the mortality rate of the patients with laboratory diagnosed COVID-19 was 14.9%. The initial and peak value of D-Dimer and NLR in deceased patients were higher statistically compared with survivors (P < 0.001). There was a more significant upward trend of D-Dimer and NLR during hospitalization in the deceased patients, initial D-Dimer and NLR were lower than the peak tests (MD) -25.23, 95% CI: - 31.81- -18.64, P < 0.001; (MD) -43.73, 95% CI:-59.28- -31.17, P < 0.001. The test showed a stronger correlation between hospitalization days, PCT and peak D-Dimer than initial D-Dimer. The areas under the ROC curves of peak D-Dimer and peak NLR tests were higher than the initial tests (0.94(95%CI: 0.90-0.98) vs. 0.80 (95% CI: 0.73-0.87); 0.93 (95%CI:0.90-0.96) vs. 0.86 (95%CI:0.82-0.91). The critical value of initial D-Dimer, peak D-Dimer, initial NLR and peak NLR was 0.73 mg/L, 3.78 mg/L,7.13 and 14.31 respectively. 35 (10.03%) patients were intubated. In the intubated patients, initial and peak D-Dimer and NLR were much higher than non-intubated patients (P < 0.001). The critical value of initial D-Dimer, peak D-Dimer, initial NLR and peak NLR in prognosticate of intubation was 0.73 mg/L, 12.75 mg/L,7.28 and 27.55. The multivariable Cox regression analysis showed that age (HR 1.04, 95% CI 1.00-1.07, P = 0.01), the peak D-Dimer (HR 1.03, 95% CI 1.01-1.04, P < 0.001) were prognostic factors for COVID-19 patients' death. CONCLUSIONS: To dynamically observe the ratio of D-Dimer and NLR was more valuable during the prognosis of COVID-19. The rising trend in D-Dimer and NLR, or the test results higher than the critical values may indicate a risk of death for participants with COVID-19.