Corona Virus (COVID-19) "Infodemic" and Emerging Issues through a Data Lens: The Case of China

Trust in Acquaintances, Strangers and Institutions among Individuals of Different Socioeconomic Statuses during Public Health Emergencies: The Moderation of Family Structure and Policy Perception

Trust plays a crucial role in effectively responding to public health emergencies. Drawing on COVID-19 survey data conducted in Hubei, China, during August 2020 with a sample size of 5494, this study investigated the influence of individuals' socioeconomic status on trust in acquaintances, strangers and institutions, and how this relationship is moderated by epidemic prevention, policy perception and family structure. The findings showed that individuals with higher socioeconomic status tend to have higher levels of trust. Those with higher income but being married demonstrate higher trust. When perceiving epidemic prevention policies as stringent, those with higher income display increased trust in acquaintances and institutions; similarly, those with lower education levels exhibit heightened trust in acquaintances and strangers. Individuals working in social organizations express higher trust in strangers; however, their trust is compromised under stringent epidemic prevention policies due to potentially heavier work burdens.

The coronavirus disease 2019 infodemic: a concept analysis

Aim

This study aimed to analyze the coronavirus disease 2019 (COVID-19) infodemic phenomenon in the medical field, providing essential data to help healthcare professionals understand it.

Methods

This study utilized a hybrid model for concept analysis. In the theoretical phase (first phase), a literature review was conducted using ScienceDirect, PubMed, CINAHL, ProQuest, Scopus, Web of Science, DBpia, RISS, and KISS. Semi-structured interviews, involving eight physicians and six nurses, were used in the fieldwork phase (second phase). In the final analysis phase (third phase), the results of the preceding phases were combined.

Results

Based on the findings of these phases, the COVID-19 infodemic can be defined as "the phenomenon of information flood, reproduction, dissemination, and asymmetry, which occurred during the pandemic through social networks among the public lacking essential knowledge of infectious disease, and is associated with negative and positive effects."

Conclusion

Our findings can help the Ministry of Health and Welfare and healthcare professionals to understand the phenomenon of the infodemic and prepare necessary strategies and education programs for the public. Therefore, the provision of basic data is important for developing influential roles for healthcare professionals during infectious disease outbreaks.

Scenario-based assessment of emergency management of urban infectious disease outbreaks

Infectious diseases pose a severe threat to human health and are accompanied by significant economic losses. Studies of urban outbreaks of infectious diseases are diverse. However, previous studies have neglected the identification of critical events and the evaluation of scenario-based modeling of urban infectious disease outbreak emergency management mechanisms. In this paper, we aim to conduct an empirical analysis and scenario extrapolation using a questionnaire survey of 18 experts, based on the CIA-ISM method and scenario theory, to identify the key factors influencing urban infectious disease outbreaks. Subsequently, we evaluate the effectiveness of urban infectious disease outbreak emergency management mechanisms. Finally, we compare and verify the actual situation of COVID-19 in China, drawing the following conclusions and recommendations. (1) The scenario-based urban infectious disease emergency management model can effectively replicate the development of urban infectious diseases. (2) The establishment of an emergency command center and the isolation and observation of individuals exposed to infectious diseases are crucial factors in the emergency management of urban outbreaks of infectious disease.

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 μg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 μg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

COVID-19 vaccine literacy: A scoping review

To address vaccine hesitancy, specific self-rated tools have been developed to assess vaccine literacy (VL) related to COVID-19, including additional variables, such as beliefs, behavior, and willingness to be vaccinated. To explore the recent literature a search was performed selecting articles published between January 2020 and October 2022: 26 papers were identified using these tools in the context of COVID-19. Descriptive analysis showed that the levels of VL observed in the studies were generally in agreement, with functional VL score often lower than the interactive-critical dimension, as if the latter was stimulated by the COVID-19-related infodemic. Factors associated with VL included vaccination status, age, educational level, and, possibly, gender. Effective communication based on VL when promoting vaccination is critical to sustaining immunization against COVID-19 and other communicable diseases. The VL scales developed to date have shown good consistency. However, further research is needed to improve these tools and develop new ones.

Structural Validation and Measurement Invariance Testing of the Chinese Version of the eHealth Literacy Scale Among Undergraduates: Cross-Sectional Study

BACKGROUND

The eHealth Literacy Scale (eHEALS) was introduced in China in 2013 as one of the most important electronic health literacy measurement instruments. After a decade of development in China, it has received widespread attention, although its theoretical underpinnings have been challenged, thus demanding more robust research evidence of factorial validity and multigroup measurement properties.

OBJECTIVE

This study aimed to evaluate the Chinese version of the eHEALS in terms of its measurement properties.

METHODS

A cross-sectional survey was conducted in a university setting in China. Item statistics were checked for response distributions and floor and ceiling effects. Internal consistency reliability was confirmed with Cronbach α, split-half reliability, Cronbach α if an item was deleted, and item-total correlation. A total of 5 representative eHEALS factor structures were examined and contrasted using confirmatory factor analysis. The study used the item-level content validity index (I-CVI) and the average of the I-CVI scores of all items on the scale to assess the content validity of the dominance model. Furthermore, the validated dominance model was subsequently used to evaluate the relevance and representation of elements in the instrument and to assess measurement invariance across genders.

RESULTS

A total of 972 respondents were identified, with a Cronbach α of .92, split-half reliability of 0.88, and item-total score correlation coefficients ranging from 0.715 to 0.781. Cronbach α if an item was deleted showed that all items should be retained. Acceptable content validity was supported by I-CVIs ≥0.80. The confirmatory factor analysis confirmed that the 3-factor model was acceptable. The measurement model met all relevant fit indices: average variance extracted from 0.663 to 0.680, composite reliability from 0.810 to 0.857, chi-square divided by the df of 4.768, root mean square error of approximation of 0.062, standardized root mean squared residual of 0.020, comparative fit index (CFI) of 0.987, and Tucker-Lewis index of 0.979. In addition, the scale demonstrated error variance invariance (Δnormed fit index=-0.016, Δincremental fit index=-0.012, ΔTucker-Lewis index=0.005, Δcomparative fit index=-0.012, Δrelative fit index=0.005, and Δroot mean square error of approximation=0.005).

CONCLUSIONS

A 3-factor model of the Chinese version of the eHEALS fits best, and our findings provide evidence for the strict measurement invariance of the instrument regarding gender.

Assessing the health, social, educational and economic impact of the COVID-19 pandemic on adolescents in low- and middle-income countries: a rapid review of the literature

COVID-19 has caused profound health, social, educational and economic devastation around the world, especially among the lives of adolescents in low- and middle-income countries. This paper looks at a wide array of outcomes impacting adolescents' daily lives including health (mental, physical, sexual and reproductive health, vaccine perceptions and overlap between these topics), social relationships (family and peer), education and socio-economic disparities. Both scientific and grey literature between December 2019 and February 2022 were sought from PubMed, Google Scholar and organisations conducting research among adolescents, and coded. A total of 89 articles were included, 73% of which were peer-reviewed; 37% of the articles were from WHO's Western Pacific region; 62% of the articles were cross-sectional; 75% were quantitative. Three major topics emerged in more than half the articles: mental health (72%), education (61%) and socio-economic ramifications (55%). However, there were regional differences in topics and many of them overlapped. The results indicate that, where there has been research, almost all findings have been linked to worse mental health during the pandemic. Overall, remote education was seen as a negative experience. The ramification of school closures on future aspirations, in particular early school leaving, highlights the importance of prioritising education during future pandemics based on the situation within the country. Gender and other disparities have made marginalised adolescents vulnerable to the economic ramifications of containment measures. Given the risks identified, there is a pressing need to put adolescents at the centre of establishing priorities for their health agenda for post-pandemic recovery.

Factors associated with COVID-19 misinformation rebuttal among college students: a descriptive study

Background

The deluge of COVID-19 misinformation makes people confused, and acting on such misinformation can kill, leading to the tragic outcome of death. This makes it necessary to identify significant factors associated with college students' susceptibility.

Objective

This descriptive study sought to ascertain factors significantly associated with college students' susceptibility to online COVID-19 misinformation.

Methods

To assess college students' susceptibility to COVID-19 misinformation, we first chose as independent variables some demographic information, some well-developed, validated literacy tools, and the Patient Health Questionnaire-9 Items. Second, we selected as the dependent variable COVID-19 myths from some authoritative, official websites. Third, we integrated the independent and dependent variables into an online questionnaire. Fourth, we recruited students from Nantong University in China to participate in an online questionnaire survey. Finally, based on the data collected, we conducted quantitative and qualitative analyses to relate the independent variables to the dependent variable.

Results

Five hundred forty-six students participated in the survey voluntarily, and all questionnaires they answered were valid. The participants had an average of 2.32 (SD = 0.99) years of higher education. They have a mean age of 20.44 (SD = 1.52) years. 434 (79.5%) of the 546 participants were females. The frequency of their Internet use averaged 3.91 (SD = 0.41), indicating that they logged onto the Internet almost every day. Their self-reported Internet skill was rated 3.79 (SD = 1.07), indicating that the participants rated their Internet skills as basically "good." The mean scores of the sub-constructs in the AAHLS were 6.14 (SD = 1.37) for functional health literacy, 5.10 (SD = 1.65) for communicative health literacy, and 11.13 (SD = 2.65) for critical health literacy. These mean scores indicated that the participants needed help to read health-related materials "sometimes," the frequency that they knew how to communicate effectively with professional health providers was between "often" and "sometimes," and the frequency that they were critical about health information was between "often" and "sometimes," respectively. The sum of their scores for eHealth literacy averaged 28.29 (SD = 5.31), showing that they had a relatively high eHealth literacy level. The mean score for each question in the GHNT was determined at 1.31 (SD = 0.46), 1.36 (SD = 0.48), 1.41 (SD = 0.49), 1.77 (SD = 0.42), 1.51 (SD = 0.50), and 1.54 (SD = 0.50), respectively. These mean scores showed that a high percentage of the participants answered the 6 questions wrongly, especially Questions 4-6. Similarly, participants performed unsatisfactorily in answering the 3 questions in the CRT, with a mean score of 1.75 (SD = 0.43), 1.55 (SD = 0.50), and 1.59 (SD = 0.49) for each question, respectively. In the PHQ-9, the participants reported that they never felt depressed or felt depressed only for 1-3 days in the past week. The mean score for myths 1-6 and 9-10 ranged from 1.15 (SD = 0.36) to 1.29 (SD = 0.46). This meant that the participants rated these myths false. However, most of the participants rated myths 7-8 true (1.54, SD = 0.50; 1.49, SD = 0.50), showing that they were highly susceptible to these 2 pieces of misinformation. Through data analysis via Logistic Regression (forward stepwise), we found that (1) at an average threshold of 0.5, Internet use frequency, functional health literacy, general health numeracy, reflective thinking tendency, and depression severity were significant predictors of susceptibility to misinformation for both male and female students, (2) at a higher threshold of 0.8, aggregated general health numeracy scores and functional health literacy scores, as well as depression severity were predictors of susceptibility to misinformation for both male and female students, (3) functional health literacy, general health literacy, and depression predicted resistance to misinformation for female students, and (4) internet use frequency and self-reported digital health literacy predicted resistance to misinformation for male students.

Conclusion

We revealed the complexity, dynamics, and differences in age, gender, education, Internet exposure, communicative health literacy, and cognitive skills concerning college students' susceptibility to online COVID-19 misinformation. Hopefully, this study can provide valuable implications for counteracting COVID-19 misinformation among Chinese college students.

The Role of Social Media in Health Misinformation and Disinformation During the COVID-19 Pandemic: Bibliometric Analysis

BACKGROUND

The use of social media platforms to seek information continues to increase. Social media platforms can be used to disseminate important information to people worldwide instantaneously. However, their viral nature also makes it easy to share misinformation, disinformation, unverified information, and fake news. The unprecedented reliance on social media platforms to seek information during the COVID-19 pandemic was accompanied by increased incidents of misinformation and disinformation. Consequently, there was an increase in the number of scientific publications related to the role of social media in disseminating health misinformation and disinformation at the height of the COVID-19 pandemic. Health misinformation and disinformation, especially in periods of global public health disasters, can lead to the erosion of trust in policy makers at best and fatal consequences at worst.

OBJECTIVE

This paper reports a bibliometric analysis aimed at investigating the evolution of research publications related to the role of social media as a driver of health misinformation and disinformation since the start of the COVID-19 pandemic. Additionally, this study aimed to identify the top trending keywords, niche topics, authors, and publishers for publishing papers related to the current research, as well as the global collaboration between authors on topics related to the role of social media in health misinformation and disinformation since the start of the COVID-19 pandemic.

METHODS

The Scopus database was accessed on June 8, 2023, using a combination of Medical Subject Heading and author-defined terms to create the following search phrases that targeted the title, abstract, and keyword fields: ("Health*" OR "Medical") AND ("Misinformation" OR "Disinformation" OR "Fake News") AND ("Social media" OR "Twitter" OR "Facebook" OR "YouTube" OR "WhatsApp" OR "Instagram" OR "TikTok") AND ("Pandemic*" OR "Corona*" OR "Covid*"). A total of 943 research papers published between 2020 and June 2023 were analyzed using Microsoft Excel (Microsoft Corporation), VOSviewer (Centre for Science and Technology Studies, Leiden University), and the Biblioshiny package in Bibliometrix (K-Synth Srl) for RStudio (Posit, PBC).

RESULTS

The highest number of publications was from 2022 (387/943, 41%). Most publications (725/943, 76.9%) were articles. JMIR published the most research papers (54/943, 5.7%). Authors from the United States collaborated the most, with 311 coauthored research papers. The keywords "Covid-19," "social media," and "misinformation" were the top 3 trending keywords, whereas "learning systems," "learning models," and "learning algorithms" were revealed as the niche topics on the role of social media in health misinformation and disinformation during the COVID-19 outbreak.

CONCLUSIONS

Collaborations between authors can increase their productivity and citation counts. Niche topics such as "learning systems," "learning models," and "learning algorithms" could be exploited by researchers in future studies to analyze the influence of social media on health misinformation and disinformation during periods of global public health emergencies.

Telemedicine in Heart Failure in the COVID-19 and Post-Pandemic Era: What Have We Learned?

Numerous studies showed that patients with heart failure (HF) and COVID-19 are at high risk of in-hospital complications and long-term mortality. Changes in the organisation of the medical system during the pandemic also worsened access to standard procedures, increasing the general mortality in HF and forcing the systems to be reorganised with the implementation and development of telemedical technologies. The main challenges for HF patients during the pandemic could be solved with new technologies aimed to limit the risk of SARS-CoV-2 transmission, optimise and titrate the therapy, prevent the progression and worsening of HF, and monitor patients with acute HF events in the course of and after COVID-19. Dedicated platforms, phone calls or video conferencing and consultation, and remote non-invasive and invasive cardiac monitoring became potential tools used to meet the aforementioned challenges. These solutions showed to be effective in the model of care for patients with HF and undoubtedly will be developed after the experience of the pandemic. However, the multitude of possibilities requires central coordination and collaboration between institutes with data protection and cost reimbursement to create effective mechanisms in HF management. It is crucial that lessons be learned from the pandemic experience to improve the quality of care for HF patients.

Investigating the Psychological, Social, Cultural, and Religious Predictors of COVID-19 Vaccine Uptake Intention in Digital Age: A Media Dependency Theory Perspective

Media exposure to health communication contents related to the COVID-19 pandemic alone is inadequate to measure the influence of media on individuals in adopting precautionary behaviors against COVID-19, such as vaccine uptake. Certain individuals may pay attention to and be influenced by communication content. However, literature has suggested other instrumental determinants in developing and adopting health precautionary measures, such as culture or religion, especially regarding vaccination. In times of crisis, such as the COVID-19 pandemic, it is valuable to examine the interrelationships among psychological, sociocultural, and informational factors. This can provide valuable insights for policymakers in developing effective communication strategies. Drawing an analogy between the Media dependency theory (MDT) and the Theory of Planned Behavior (TPB) model, this study unravels the factors underpinning the COVID-19 vaccine uptake intention among Pakistanis. The study utilized a cross-sectional research design and employed a survey method to gather data from a sample of 993 participants. The findings obtained from the PLS-SEM analysis confirmed that individuals relied on both traditional and social media to cope with the COVID-19 pandemic. The findings show that individuals rely more on the informational content disseminated through conventional media channels. The findings also suggest that individuals from Asian countries, such as Pakistan, tend to be more inclined toward collectivism. The findings about the moderating role of religiosity suggest that religious beliefs significantly shape individuals' reliance on traditional media. Hence, this study has uniquely contributed to public health and media management by providing a strategy for managers to address disseminating misinformation related to religion and its impact on vaccination-related health issues. The study has theoretically confirmed the principles of media dependency theory. As a result, it is recommended that various information sources be utilized to cultivate resilience among individuals to manage health crises effectively.

Health risk communication and infodemic management in Iran: development and validation of a conceptual framework

OBJECTIVE

The COVID-19 pandemic exposed significant gaps in Iran's and other health systems' risk communication. The accompanying infodemic undermined policy responses, amplified distrust in government and reduced adherence to public health recommendations among the Iranian population. This study aimed to develop a conceptual framework for health risk communication and infodemic management (RCIM) during epidemics and health emergencies in Iran that could have potential applications in other contexts.

DESIGN

This study was designed in two phases. Phase 1 involved semistructured qualitative interviews with key informants to explore effective RCIM strategies across public health settings in Iran and to develop a conceptual framework. Phase 2 involved revising the framework based on feedback from an online expert panel regarding its comprehensiveness and validity.

SETTING

Provincial/national public health settings in Iran.

PARTICIPANTS

Twenty key informants from provincial and national public health authorities who contributed to COVID-19 response programmes participated in interviews. Nine experts from diverse academic disciplines, provincial and national settings, and geographical locations participated in an online expert panel.

RESULTS

The conceptual model was created based on qualitative interviews and expert panel discussions and was structured according to six pillars of the WHO health system framework: leadership and governance, information, health workforce and financial resources, along with media and community. Leadership and governance, including trustworthy leaders, were recommended as the foundation for developing RCIM in Iran. Developing an official strategy with information infrastructures, including high-quality surveillance systems, identified personnel and training for specialists among the health workforce, financial resources, communication channels and community engagement were recognised as other dimensions for developing health risk communication in Iran.

CONCLUSION

The proposed framework represents a step toward establishing a national RCIM strategy in Iran. Further validation of the conceptual framework and experiments on how it could potentially influence policy and practice is recommended. This model has the potential to be applied in other contexts in its current form or as the foundation for customised local versions.

The Impact of Meso-Level Factors on SARS-CoV-2 Vaccine Early Hesitancy in the United States

The extant literature on the U.S. SARS-CoV-2 virus indicates that the vaccination campaign was lagging, insufficient, and uncoordinated. This study uses the spatial model to identify the drivers of vaccine hesitancy (in the middle of the pandemic), one of the critical steps in creating impactful and effective interventions to influence behavioral changes now and in the future. The applied technique accounted for observed and unobserved homogeneity and heterogeneity among counties. The results indicated that political and religious beliefs, quantified by Cook's political bipartisan index and the percentage of the population affiliated with the main Christian groups, were the main drivers of the SARS-CoV-2 vaccine hesitancy. The past vaccination experience and other variables determining the demand and supply of vaccines were also crucial in influencing hesitancy. The results imply that vaccination campaigns require engaging community leaders at all levels rather than depending on politicians alone and eliminating barriers to the supply and demand of vaccines at all levels. Coordination among religious and community leaders would build a practical institutional arrangement to facilitate (rather than frustrate) the vaccination drives.

COVID-19 and Sinophobia: Detecting Warning Signs of Radicalization on Twitter and Reddit

Hate crimes and hateful rhetoric targeting individuals of Asian descent have increased since the outbreak of COVID-19. These troubling trends have heightened concerns about the role of the Internet in facilitating radicalization. This article explores the existence of three warning signs of radicalization-fixation, group identification, and energy bursts-using data from Twitter and Reddit. Data were collected before and after the outbreak of COVID-19 to assess the role of the pandemic in affecting social media behavior. Using computational social science and Natural Language Processing techniques, we looked for signs of radicalization targeting China or Chinese individuals. Results show that fixation on the terms China and Chinese increased on Twitter and Reddit after the pandemic began. Moreover, tweets and posts containing either of these terms became more hateful, offensive, and negative after the outbreak. We also found evidence of individuals identifying more closely with a particular group, or adopting an "us vs. them" mentality, after the outbreak of COVID-19. These findings were especially prominent in subreddits catering to self-identified Republicans and Conservatives. Finally, we detected bursts of activity on Twitter and Reddit following the start of the pandemic. These warning signs suggest COVID-19 may have had a radicalizing effect on some social media users. This work is important because it not only shows the potential radicalizing effect of the pandemic, but also demonstrates the ability to detect warning signs of radicalization on social media. This is critical, as detecting warning signs of radicalization can potentially help curb hate-fueled violence.

Lived experiences and meanings of the COVID-19 pandemic: A case of the elderly survivors

The extent of risk brought about by the COVID-19 pandemic on the well-being of the elderly has emphasized the need to investigate their experiences during these challenging times. This study was conducted to explore the elderly's lived experiences as COVID-19 patients and to understand how they make sense of and cope with what happened to them when infected with COVID-19. Using Husserl's descriptive phenomenology, 13 elderly from Naval, Biliran Province, Philippines were chosen as participants using purposive sampling. The total number of participants was determined through theoretical saturation. In-depth interviews and the writing of field notes were done to collect information on the participants' experiences. The transcripts were analyzed following Colaizzi's steps in descriptive phenomenological method of analysis. Four general themes emerged for the elderly's lived experiences during the pandemic. These included discrimination, social isolation, anxiety and stress, and fear. Findings revealed that despite the challenges the elderly encountered during the pandemic and when they tested positive for COVID-19, they had seen it as an opportunity to improve and change their practices. The strategies that the elderly employed to cope with the pandemic were all adaptive and have resulted in positive outcomes. Results of the study emphasize the need for more programs and policies to enhance the care and support provided to the elderly during a health crisis.

Clinical Study on the Emotional Intervention of Patients with Asymptomatic and Mild Novel Coronavirus (COVID-19)

Background and Objectives: The aim was to explore the interventional effect of the traditional Chinese medicine (TCM) exercise of Tian Dan Shugan Tiaoxi on the emotions of patients with mild novel coronavirus (COVID-19). Materials and Methods: A total of 110 asymptomatic and mildly symptomatic COVID-19 patients from Hongkou Memorial Road Temporary Cabin Hospital and South Renji Hospital were selected between April 2022 and June 2022, and randomly divided into two groups: a control group and an intervention group. There were 55 participants in each group. The control group was treated with Lianhua Qingwen granules, and members of the intervention group were made to practice Tian Dan Shugan Tiaoxi (an exercise that soothes the liver and regulates emotions) every day for 5 days. The Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder questionnaire (GAD-7), and the Symptom Checklist 90 (SCL-90) were used to evaluate the data collected before and after the trial. Results: The incidence of anxiety and depression was high in the patients included in this study, at 73.64% and 69.09%, respectively. After intervention, the scores of the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder questionnaire (GAD-7) in the two groups had decreased in comparison with those recorded before intervention (p < 0.05). The PHQ-9 and GAD-7 scores in the intervention group were significantly better than those of the control group (p < 0.05). The factors of somatization, depression, anxiety, hostility, and fear in the SCL-90 in the intervention group were significantly improved after intervention, and generally, better than those in the control group (p < 0.05). Conclusions: Patients infected with novel coronavirus in shelter hospitals have different degrees of emotional abnormalities. Tian Dan Shugan Tiaoxi can reduce the anxiety and depression of people with mild novel coronavirus, and it can be practiced clinically to improve the recovery rate among infected people.

Ensemble deep honey architecture for COVID-19 prediction using CT scan and chest X-ray images

Recently, the infectious disease COVID-19 remains to have a catastrophic effect on the lives of human beings all over the world. To combat this deadliest disease, it is essential to screen the affected people quickly and least inexpensively. Radiological examination is considered the most feasible step toward attaining this objective; however, chest X-ray (CXR) and computed tomography (CT) are the most easily accessible and inexpensive options. This paper proposes a novel ensemble deep learning-based solution to predict the COVID-19-positive patients using CXR and CT images. The main aim of the proposed model is to provide an effective COVID-19 prediction model with a robust diagnosis and increase the prediction performance. Initially, pre-processing, like image resizing and noise removal, is employed using image scaling and median filtering techniques to enhance the input data for further processing. Various data augmentation styles, such as flipping and rotation, are applied to capable the model to learn the variations during training and attain better results on a small dataset. Finally, a new ensemble deep honey architecture (EDHA) model is introduced to effectively classify the COVID-19-positive and -negative cases. EDHA combines three pre-trained architectures like ShuffleNet, SqueezeNet, and DenseNet-201, to detect the class value. Moreover, a new optimization algorithm, the honey badger algorithm (HBA), is adapted in EDHA to determine the best values for the hyper-parameters of the proposed model. The proposed EDHA is implemented in the Python platform and evaluates the performance in terms of accuracy, sensitivity, specificity, precision, f1-score, AUC, and MCC. The proposed model has utilized the publicly available CXR and CT datasets to test the solution's efficiency. As a result, the simulated outcomes showed that the proposed EDHA had achieved better performance than the existing techniques in terms of Accuracy, Sensitivity, Specificity, Precision, F1-Score, MCC, AUC, and Computation time are 99.1%, 99%, 98.6%, 99.6%, 98.9%, 99.2%, 0.98, and 820 s using the CXR dataset.

Effectiveness of online teaching and learning in Indian universities during the COVID-19 pandemic

Purpose

This study aims to analyze the effectiveness of online teaching and learning in the higher education sector during the COVID-19 pandemic and thereby design and formulate strategies to overcome the lacunas, if any, to enhance teaching effectiveness.

Design/methodology/approach

A survey was conducted to analyze how far students were able to adapt to online teaching and learning, access teaching platforms and afford it. It was also studied whether they were able to grasp and apply the concepts learned. A total of 600 questionnaires were given, and 372 complete responses were received. Structural equation modeling is employed to test the hypothesis. Confirmatory factor analysis (CFA) was conducted to test the model fit and measurement model.

Findings

This study is first of its kind in India which aims to analyze the effectiveness of online teaching and learning environments. This research model is designed to identify the determinants of effective online learning and to overcome the lacunas existing in the prevailing online teaching methods. It can be applied not just during crises like the pandemic but also during normal times to make teaching and learning more economical, innovative and impactful. The present study examined the impact of five major determinants—adaptability, affordability, bandwidth, grasping and interaction—on online learning and its effectiveness during COVID-19. It was observed that all the determinants positively influence online learning effectiveness.

Research limitations/implications

The scope of the study was restricted to three centrally funded Indian Universities. Other institutions were not part of the study.

Originality/value

This study is the first of its kind done in the current COVID-19 scenario, and the outcome would help overcome the lacunas in the prevailing online teaching scenario across the globe and make it more effective.

Tailoring of neurosurgical practice during COVID-19 in a developing country: Insights gained and a way forward

Background:

The coronavirus disease-19 pandemic has aggravated the already neglected neurosurgical specialty in developing countries with a mounting shortage of specialists, long queues of operative patients, and a lack of adequate critical care units.

Methods:

We have reviewed the innovative strategies adopted for maintaining an optimal surgical practice while ensuring team safety at the Aga Khan University Hospital, Karachi Pakistan.

Results:

There is already a scarcity of resources in developing countries. The international guidelines had to be tailored to the context of the developing world. A multimodal strategy that focused on infection control, continuum of care, and the well-being of staff was adopted at Aga Khan University. Patients were screened and seen either in person or through telemedicine, depending on the severity of the disease. All educational activities for residents were shifted online, and this helped in preventing overcrowding.

Conclusion:

Optimal surgical practice while ensuring team safety can be achieved through a multimodal strategy focusing on infection control, continuum of care, and the well-being of staff.

Quantified multidimensional public sentiment characteristics on social media for public opinion management: Evidence from the COVID-19 pandemic

Background

Public sentiments arising from public opinion communication pose a serious psychological risk to public and interfere the communication of nonpharmacological intervention information during the COVID-19 pandemic. Problems caused by public sentiments need to be timely addressed and resolved to support public opinion management.

Objective

This study aims to investigate the quantified multidimensional public sentiments characteristics for helping solve the public sentiments issues and strengthen public opinion management.

Methods

This study collected the user interaction data from the Weibo platform, including 73,604 Weibo posts and 1,811,703 Weibo comments. Deep learning based on pretraining model, topics clustering and correlation analysis were used to conduct quantitative analysis on time series characteristics, content-based characteristics and audience response characteristics of public sentiments in public opinion during the pandemic.

Results

The research findings were as follows: first, public sentiments erupted after priming, and the time series of public sentiments had window periods. Second, public sentiments were related to public discussion topics. The more negative the audience sentiments were, the more deeply the public participated in public discussions. Third, audience sentiments were independent of Weibo posts and user attributes, the steering role of opinion leaders was invalid in changing audience sentiments.

Discussion

Since the COVID-19 pandemic, there has been an increasing demand for public opinion management on social media. Our study on the quantified multidimensional public sentiments characteristics is one of the methodological contributions to reinforce public opinion management from a practical perspective.

Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data

With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same.

Smartphone-based corona virus detection using saliva: A mini-review

During the ongoing worldwide epidemic, SARS-CoV-2 has infected millions of individuals and taken the lives of numerous victims. It is clear that early detection of infected individuals, especially asymptomatic carriers, is possible with the development of innovative analytical tools for rapid identification of COVID-19 present in nasopharyngeal swabs, serum, and saliva. The saliva, as a diagnostic sample, can be easily collected by the patient with almost no discomfort and needs specialized healthcare personnel to manage, which reduces the risks for the operator. Moreover, smartphone-based sensing systems are one of the most attractive techniques that can speed up the detection time of COVID-19 agents without the need for professional staff and clinical centers. In this review, recent advances in precise salivary-based SARS-CoV-2 diagnosis using smartphones via viral RNA detection, antibody identification, and viral antigen identification were summarized. Finally, the conclusion and future perspective of this field are described in brief.

Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace

In recent years, there has been a growing amount of discussion on the use of big data to prevent and treat pandemics. The current research aimed to use CiteSpace (CS) visual analysis to uncover research and development trends, to help academics decide on future research and to create a framework for enterprises and organizations in order to plan for the growth of big data-based epidemic control. First, a total of 202 original papers were retrieved from Web of Science (WOS) using a complete list and analyzed using CS scientometric software. The CS parameters included the date range (from 2011 to 2022, a 1-year slice for co-authorship as well as for the co-accordance assessment), visualization (to show the fully integrated networks), specific selection criteria (the top 20 percent), node form (author, institution, region, reference cited, referred author, journal, and keywords), and pruning (pathfinder, slicing network). Lastly, the correlation of data was explored and the findings of the visualization analysis of big data pandemic control research were presented. According to the findings, "COVID-19 infection" was the hottest cluster with 31 references in 2020, while "Internet of things (IoT) platform and unified health algorithm" was the emerging research topic with 15 citations. "Influenza, internet, China, human mobility, and province" were the emerging keywords in the year 2021-2022 with strength of 1.61 to 1.2. The Chinese Academy of Sciences was the top institution, which collaborated with 15 other organizations. Qadri and Wilson were the top authors in this field. The Lancet journal accepted the most papers in this field, while the United States, China, and Europe accounted for the bulk of articles in this research. The research showed how big data may help us to better understand and control pandemics.

Virtual screening of bioactive anti-SARS-CoV natural products and identification of 3β,12-diacetoxyabieta-6,8,11,13-tetraene as a potential inhibitor of SARS-CoV-2 virus and its infection related pathways by MD simulation and network pharmacology

Since the first prevalence of COVID-19 in 2019, it still remains the most devastating pandemic throughout the world. The current research aimed to find potential natural products to inhibit the novel coronavirus and associated infection by MD simulation and network pharmacology approach. Molecular docking was performed for 39 natural products having potent anti-SARS-CoV activity. Five natural products showed high binding interaction with the viral main protease for the SARS-CoV-2 virus, where 3β,12-diacetoxyabieta-6,8,11,13 tetraene showed stable binding in MD simulation until 100 ns. Both 3β,12-diacetoxyabieta-6,8,11,13 tetraene and tomentin A targeted 11 common genes that are related to COVID-19 and interact with each other. Gene ontology development analysis further showed that all these 11 genes are attached to various biological processes. The KEGG pathway analysis also showed that the proteins that are targeted by 3β,12-diacetoxyabieta-6,8,11,13 tetraene and tomentin A are associated with multiple pathways related to COVID-19 infection. Furthermore, the ADMET and MDS studies reveals 3β,12-diacetoxyabieta-6,8,11,13 as the best-suited compound for oral drug delivery.Communicated by Ramaswamy H. Sarma.

A Statistical Synopsis of COVID-19 Components and Descriptive Analysis of Their Socio-Economic and Healthcare Aspects in Bangladesh Perspective

The aim of the work is to analyze the socio-economic and healthcare aspects that arise in the contemporary COVID-19 situation from Bangladesh perspective. We elaborately discuss the successive COVID-19 occurrences in Bangladesh with consequential information. The components associated with the COVID-19 commencement and treatment policy with corresponding features and their consequences are patently delineated. The effect of troublesome issues related to the treatment is detailed with supporting real-time data. We elucidate the applications of modern technologies advancement in epidemiological aspects and their existent compatibility in Bangladesh. We statistically analyze the real-time data through figurative and tabular approaches. Some relevant measures of central tendency and dispersion are utilized to explore the data structure and its observable specifications. For a clear manifestation, Z- scores of the COVID-19 components are analyzed through the Box-Whisker plot. We have discovered that the gathered data exhibit features that are unsatisfactory for the normal distribution, are highly positively skewed, and are predominated by the earliest occurrences. Infections and deaths were initially lower than the global average, but they drastically rose in the first quarter of 2021 and persisted for the remainder of the year. Substantial preventive results were produced by the region-wisetime-worthy moves. In the fourth quarter of 2021, the infections and deaths noticeably decreased, and the number of recoveries was highly significant. In the middle of 2022, a lethal rise in infections was observed in Bangladesh and that was quickly stabilized, and the pandemic ingredients were under control. According to our assessment, some concluding remarks are made at the end of this work.

COVID-19 and Dr. Google: Parents' changing experience using online health information about their children's health during the pandemic

AIMS

To identify how the COVID-19 pandemic influences parents' use of the internet, including social media, when seeking health-related information about the pandemic relevant to their children.

METHODS

This study employed semi-structured interviews to explore the factors affecting parents of young children when information-seeking online about their children's health related to the COVID-19 pandemic. Parents of children with and without chronic health conditions were interviewed in July and August 2020. Interviews were audio-recorded and transcribed verbatim, then analysed using theoretical thematic analysis, based on Social Cognitive Theory.

RESULTS

Through interviews with 13 parents, we identified a myriad of factors that affected parents' internet searching. The decision to access online health information and the regulation of its usage was multifaceted and relied upon the interactions between environmental triggers and parents' information needs, personal attitudes, and circumstances. Overall, parents felt supported by online health information during the COVID-19 pandemic, and the majority were confident in their ability to navigate the plethora of online health information. However, parents of children with chronic conditions had unmet information needs in relation to COVID-19 and their children's condition.

CONCLUSIONS

Understanding parents' attitudes and behaviours when seeking online health information that is relevant to their children during a global pandemic can inform the optimisation of online health content delivery to parents.

Corporate ESG performance as good insurance in times of crisis: lessons from US stock market during COVID-19 pandemic

Purpose

The COVID-19 outbreak and its confinement resulted in an unexpected stock market crash, hence the interest in environmental, social and governance (hereafter, ESG) policies. This paper aims to examine the association between ESG performance and stock market volatility before and after the COVID-19 pandemic.

Design/methodology/approach

This paper examined 500 US companies listed in the S&P 500. The window period volatility refers to March 18, 2020, when the US President signed into law the Families First Coronavirus Response Act. Here, the Thomson Reuters database was used to collect ESG data and daily market information.

Findings

The findings suggest that companies with high ESG performance have lower stock price volatility than companies with poor ESG performance. In other words, strong ESG performance reduces stock price volatility resulting from the COVID-19 shock and promotes resilience and stock price stability.

Practical implications

This research contributes to current debates on emerging pandemics and unexpected risks and highlights the need to invest more in improving corporate sustainability.

Originality/value

The results have substantial implications for managers and investors, as it highlights the relevance of customer and investor loyalty to the durability of ESG stocks.

Limitations of COVID-19 testing and case data for evidence-informed health policy and practice

BACKGROUND

Coronavirus disease 2019 (COVID-19) became a pandemic within a matter of months. Analysing the first year of the pandemic, data and surveillance gaps have subsequently surfaced. Yet, policy decisions and public trust in their country's strategies in combating COVID-19 rely on case numbers, death numbers and other unfamiliar metrics. There are many limitations on COVID-19 case counts internationally, which make cross-country comparisons of raw data and policy responses difficult.

PURPOSE AND CONCLUSIONS

This paper presents and describes steps in the testing and reporting process, with examples from a number of countries of barriers encountered in each step, all of which create an undercount of COVID-19 cases. This work raises factors to consider in COVID-19 data and provides recommendations to inform the current situation with COVID-19 as well as issues to be aware of in future pandemics.

Protecting public's wellbeing against COVID-19 infodemic: The role of trust in information sources and rapid dissemination and transparency of information over time

Objectives

This study examined how trust in the information about COVID-19 from social media and official media as well as how the information was disseminated affect public's wellbeing directly and indirectly through perceived safety over time.

Methods

Two online surveys were conducted in China, with the first survey (Time1, N = 22,718) being at the early stage of the pandemic outbreak and the second one (Time 2, N = 2,901) two and a half years later during the zero-COVID policy lockdown period. Key measured variables include trust in official media and social media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, and emotional responses toward the pandemic. Data analysis includes descriptive statistical analysis, independent samples t-test, Pearson correlations, and structural equation modeling.

Results

Trust in official media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, as well as positive emotional response toward COVID-19 increased over time, while trust in social media and depressive response decreased over time. Trust in social media and official media played different roles in affecting public's wellbeing over time. Trust in social media was positively associated with depressive emotions and negatively associated with positive emotion directly and indirectly through decreased perceived safety at Time 1. However, the negative effect of trust in social media on public's wellbeing was largely decreased at Time 2. In contrast, trust in official media was linked to reduced depressive response and increased positive response directly and indirectly through perceived safety at both times. Rapid dissemination and transparency of COVID-19 information contributed to enhanced trust in official media at both times.

Conclusion

The findings highlight the important role of fostering public trust in official media through rapid dissemination and transparency of information in mitigating the negative impact of COVID-19 infodemic on public's wellbeing over time.

An investigation on information quality, media richness, and social media fatigue during the disruptions of COVID-19 pandemic

Mobile social platforms have become a valuable information source by which users gain information about the COVID-19 pandemic. However, little is known about whether users have experienced increased daily fatigue as a result of the disruptions caused by pandemic. Drawing on the cognitive activation theory of stress (CATS), this study proposed that two typical characteristics of social media platforms (SMP), information quality and media richness, are associated with event disruptions of the COVID-19 pandemic (EDC), and then induce social media fatigue. To address this, this study used the experience sampling method (ESM), collecting 550 matched cases from 110 users of the WeChat application in mainland China over five consecutive days. Through multilevel structural equation modeling (MSEM), this study discovered three main findings: (1) daily information quality is negatively related to event disruptions of the COVID-19 pandemic, which in turn decreases daily social media fatigue; (2) daily media richness is positively associated with such event disruptions, which ultimately increases daily social media fatigue; (3) these effects were stronger for users who reported higher (vs. lower) levels of health consciousness. The implications of these results for the COVID-19 pandemic and beyond are discussed.

The lived experience of hospitalized and non-hospitalized health care providers of COVID-19 pandemic: a qualitative study

This paper explores the lived experience and any mental health issues of COVID-19 survivors throughout the disease crisis using a qualitative method. The semi-structured interviewing method was conducted with COVID-19 patients who were admitted and non-admitted to hospitals in Kurdistan, Iraq. The patients had positive and negative perceptions of the COVID-19 pandemic and disease, including beliefs and thoughts about COVID-19, conspiracy thinking, and concerns toward the family and their children. The patients were affected by the disease in different ways including physical consequences of COVID-19 infection, social isolation, life changes, and mental wellbeing. But they had some coping strategies to overcome the disease, such as seeking help, preventive measures, and coping techniques. The patients had some concerns about health settings and therapeutic procedures, including lack of sufficient care, receptiveness, hospital environment, and infection guidelines. This study showed that the COVID-19 disease had devastating effects on patients either physically or psychologically.

Towards a soft three-level voting model (Soft T-LVM) for fake news detection

Fake news has a worldwide impact and the potential to change political scenarios and human behavior, especially in a critical time like the COVID-19 pandemic. This work suggests a Soft Three-Level Voting Model (Soft T-LVM) for automatically classifying COVID-19 fake news. We train different individual machine learning algorithms and different ensemble methods in order to overcome the weakness of individual models. This novel model is based on the soft-voting technique to calculate the class with the majority of votes and to choose the classifiers to merge and apply at every level. We use the Grid search method to tune the hyper-parameters during the process of classification and voting. The experimental evaluation confirms that our proposed model approach has superior performance compared to the other classifiers.

COVID-19-related fear, stress and depression in school principals: impacts of symptoms like COVID-19, information confusion, health-related activity limitations, working hours, sense of coherence and health literacy

BACKGROUND

School principals have been reported to have a higher prevalence of burnout and psychological problems than their colleagues. During the pandemic, extra workload and pressure from unprecedented situations potentially cause fear, stress and depression. Therefore, we aimed to explore associated factors of stress, fear of COVID-19 (F-CoV-19S) and depressive symptoms among school principals.

METHODS

A cross-sectional online survey was conducted in Taiwan from 23 June to 16 July 2021. Data of 413 school principals were collected, including socio-demographic factors, COVID-19-related factors, work-related information, health status, sense of coherence (SoC), health literacy (HL), F-CoV-19S, stress and depression. Multiple linear and logistic regression models were utilized to explore associations.

RESULTS

School principals with symptoms like COVID-19 (S-COVID-19-S), or with health-related activity limitations had a higher score of stress (B = 0.92; p = .039) (B = 1.52; p < .001) and a higher depression likelihood (OR = 3.38; p < .001) (OR = 3.06; p < .001), whereas those with a better SoC had a lower stress score (B = -1.39; p < .001) and a lower depression likelihood (OR = 0.76; p = .020). School principals confusing about COVID-19-related information had a higher score of stress (B = 2.47; p < .001) and fear (B = 3.77; p < .001). The longer working time was associated with a higher fear score (B = 1.69; p = .006). Additionally, school principals with a higher HL score had a lower stress score (B = -1.76; p < .001), a lower fear score (B = -1.85; p < .001) and a lower depression likelihood (OR = 0.53; p = .043).

CONCLUSIONS

Health-related activity limitations, S-COVID-19-S, COVID-19-related information confusion and longer working hours were positively associated with at least one mental health problem (e.g. stress, fear and depression), whereas better SoC and HL showed the benefits to mitigate fear, stress and depressive symptoms in school principals. Our study provides evidence for appropriate strategies to improve principals' mental health during the pandemic.Key messages:School principals with health-related activity limitations or with symptoms like COVID-19 were more likely to be stressed and depressed.Higher levels of stress and fear were observed in school principals who confused about COVID-19-related information, and who had longer working time than before the pandemic.Better sense of coherence and higher health literacy could potentially mitigate the fear, stress and depressive symptoms in school principals.

Study on the communication effect of the social livestream of cabin hospitals' construction process during the COVID-19 outbreak

When the world is recovering from the chaos that COVID-19 creates, the epidemic is still posing challenges to the public health system and communication. However, a case of information communication during the COVID-19 outbreak can provide a reference for the current information promulgate strategy in China. In January 2020, CCTV broadcasted the construction of two cabin hospitals on a 24-h Livestream (24H-LS), creating a remarkable viewing effect. We conducted a quantitative analysis based on the number of views, social media communication, and internet search index. We collected posts and comment data of the 24H-LS audience and related topics on Weibo, using sentiment classification and word frequency analysis to study the communication effect of 24H-LS from three perspectives: perception effect, psychology, and subject issue. The results show that, first, 24H-LS has attracted extensive public attention on the Internet and social media after its launch. Second, the public's perception of the risks of the COVID-19 outbreak and its uncertainty has decreased after watching the 24H-LS. At the same time, the positive emotions of the public have been enhanced to a certain extent. Third, through subject analysis, we found that the public had high participation and strong interaction in 24H-LS, which produced collective symbols and emotions. The study shows that through 24H-LS, a new information form, the media can effectively convey important information and resolve the public's fear and anxiety.

The impact of the COVID-19 pandemic on individuals with generalized anxiety disorder: assessing COVID-19 media source exposure and behaviour changes

Background

The COVID-19 pandemic that has resulted in social distancing, lockdowns, and increase in media posts has taken a toll on the mental health of many people especially those living with Generalized Anxiety Disorder (GAD). The main objective of this study is to understand whether the source of information people use to receive information about COVID-19 and increase or decrease in personal weekly habits during the pandemic were associated with severity of GAD. 

Methods

This study was a cross sectional design and was based on data from Canada. The Canadian Perspective Survey Series (CPSS) 4, 2020: Information Sourced Consulted During the Pandemic was used for the study. The outcome variable was severity of GAD. Multivariate logistic regression was carried out using STATA IC 13.

Results

Severity of GAD was significantly associated with being a female, the type of information source used to find out about COVID-19 and change in weekly habits (consuming alcohol, consuming cannabis spending time on the internet and eating junk foods or sweets).

Conclusion

The results indicate that getting information from credible sources about the pandemic, staying connected with family and friends, seeking virtual mental health services, and learning positive coping strategies can help reduce the severity of GAD.

Web search behaviors and infodemic attitudes regarding COVID-19 in Turkey: A framework study for improving response and informing policy on the COVID-19 infodemic

Objective

This study aimed to develop a framework regarding COVID-19 infodemic response and policy informing through focusing on infodemic concepts circulating on the online search engine in Turkey in relation to the COVID-19 outbreak and comparing the contents of these concepts with Maslow's hierarchy of needs and disaster stages.

Materials and methods

The universe of this descriptive epidemiological research consists of internet search activities on COVID-19 circulating online on Google Trends between March 10, 2020, when the first case was seen in Turkey, and June 01, 2020, when the lockdown restrictions were lifted.

Findings

There was no internet trend regarding a misinformed attitude within the given date range. While an infodemic attitude toward superficial attitude and racist attitude in the internet environment was detected for 1 week, an infodemic attitude toward definitive attitude was detected for 2 weeks. The non-infodemic concepts were more common than the other infodemic attitudes. The infodemic concepts were able to reach Maslow's physiological, safety, and social need levels. With the infodemic concepts obtained, a COVID-19 development process framework was developed. The framework consists of three domains (COVID-19, applications and outcomes), including disaster phases and health/social impacts, built on seven public health epochs.

Results

A systematized COVID-19 development process framework was modeled in order to conceptualize COVID-19 internet searches and to reveal the development processes and outcomes.

COVID‐digital health literacy and subjective well‐being of students in Ghana: Mediation‐moderation analyses

Background

Previous research has established a strong association between COVID‐19 digital health literacy (DHL) and subjective well‐being among several populations, including students. With the growing misinformation and heightened fear of COVID‐19 among persons with an underlying medical condition, several scholars have questioned the direct relationship between DHL and well‐being. This study assessed the moderating roles of information accuracy concerns and the existence of an underlying medical condition among students.

Methods

Using a cross‐sectional design, a multi‐stage sampling approach was used to select 1392 students from senior high schools in Northern Ghana who completed a questionnaire containing information on DHL, information accuracy, subjective well‐being, and underlying health condition, with reported internal consistency coefficients above 0.70. The data which was processed with SPSS version 25, was analyzed using correlation (Pearson and biserial), and Hayes' PROCESS for the moderation and mediation analyses.

Results

A significant positive relationship was found between (a) DHL and subjective well‐being, (b) DHL and information accuracy concerns, and (c) information accuracy concerns and subjective well‐being. However, the prevalence of underlying health condition was negatively associated with information accuracy, DHL, and subjective well‐being. Information accuracy concerns and the existence of an underlying medical condition significantly regulated the relationship between DHL and subjective well‐being.

Conclusions

Demonstrating satisfactory levels of DHL does not necessarily result in improved subjective well‐being. However, emphasis should be placed on whether individuals attach much importance to the accuracy of information retrieved as well as having or not an underlying health condition.

We collaborated with head teachers, teachers and students before and during the administration of the survey instrument across selected public secondary schools in the Northern and Upper Regions of Ghana.

Current Status and Associated Factors of Health Information Literacy Among the Community Elderly in Central China in the COVID-19 Pandemic: A Cross-Sectional Study

Purpose

COVID-19 posed a threat to the public’s physical and mental health, and under outbreak control, the opportunities to go outside of the elderly have been reduced and making it more difficult to access health information and detrimental to their health management. This study aims to assess the current status of health information literacy (HIL) among older adults in the community in the context of COVID-19 and to identify its associated factors.

Methods

A cross-sectional survey was conducted from April to July, 2021, for which 617 community elderly members were recruited in Chenzhou, China. Data were collected through a general information questionnaire, The Chinese residents’ HIL self-rated scale and a reliability evaluation form.

Results

The average score of HIL was 75.87 ± 9.85, and after processed by the 100-point system, we found 84.12% (519/617) of the participants scored less than 60 points, which indicates that the overall level of HIL among the community elderly is low. Multiple linear regression showed that age, gender, education, annual family Income, living arrangement, and chronic disease status (β = –0.341, –0.296, 0.384, 0.327, 0.296, 0.356, respectively; all P < 0.001) were significantly associated with the level of HIL found among the community elderly, out of which education was the most important associated factor.

Conclusion

The overall HIL level among the community elderly was low in Central China during the COVID-19 pandemic. Our results further prove the need for tailor-made health education programs for this group, with particular attention paid to the low-educated and low-income among them. Those measures must highlight on three aspects of health information search, evaluation, and application skills to offer useful experiences that improve the HIL level of the elderly and strengthen their ability to cope with emerging public health events.

Digital humanitarianism and crisis management: an empirical study of antecedents and consequences

Purpose

This study proposes a digital humanitarianism dynamic capability (DHDC) paradigm that explores the direct effects of DHDC on disaster risk reduction (DRR) and the mediating effects of process-oriented dynamic capabilities (PODC) on the relationship between DHDC and DRR.

Design/methodology/approach

To validate the proposed model, the authors used an offline survey to gather data from 260 district magistrates in India managing the COVID-19 pandemic.

Findings

The results affirm the importance of the DHDC system for DRR. The findings depict that the impact of PODC on DRR in the DHDC system is negligible. This study can help policymakers in planning during emergencies.

Research limitations/implications

Technological innovation has reshaped the way humanitarian organizations (HOs) respond to humanitarian crises. These organizations are able to provide immediate aid to affected communities through digital humanitarianism (DH), which involves significant innovations to match the specific needs of people in real-time through online platforms. Despite the growing need for DH, there is still limited know-how regarding how to leverage such technological concepts into disaster management. Moreover, the impact of DH on DRR is rarely examined.

Originality/value

The present study examines the impact of the dynamic capabilities of HOs on DRR by applying the resource-based view (RBV) and dynamic capability theory (DCT).

COVID-19 related information seeking: The impact of media on parental concerns

The expansion of information sources and their use has accelerated since the beginning of the COVID-19 pandemic, sometimes provoking significant concern in the daily lives of parents. The objective of this study was to investigate the association between COVID-19 related information sources and the level of concern about COVID-19 among parents of school-aged children. Using factor analysis and hierarchical ascending classification, we constructed groups according to the information sources they used. We performed ANOVA analysis and then binomial logistic regression to compare concern levels among the groups created. Overall, the 3,459 participants were mainly women (79.2%) and 59.5% reported being between 35 and 44 years old. The mean concern score in our sample was 9.5/15 (s.d. = 3.87). The whole sample fell into three groups: (1) Traditional Media (n = 1,610), who mainly used newspapers; (2) Online Social Networks and Entourage (n = 776), who mostly consulted online social media as well as friends and family; and (3) the Unplugged (n = 1,073), who consulted few or no information sources. Compared to the Unplugged, individuals in the other two groups had a higher risk of being concerned (Traditional Media, OR = 2.2; p < 0.001; Social Networks and Entourage, OR = 3.1; p < 0.001). Communication about pandemic risk should be conveyed based on reliable information and at moderate intervals to safeguard the mental health of individuals.

An Improved Epidemiological Model for the Underprivileged People in the Contemporary Pandemics

In this work, we introduce an improved form of the basic SEIRD model based on Python simulation for the troublesome people who are oblivious about the contemporary pandemics due to diverse social impediments, especially those economically underprivileged. In the extant epidemiological models, some unorthodox issues are yet to be considered, such as poverty, illiteracy, and carelessness towards health issues, significantly influencing the data modeling. Our focus is to overcome these issues by adding two more branches, for instance, uncovered and apathetic people, which significantly influence the practical purposes. For the data simulation, we have used the Python-based algorithm that trains the desired system based on a set of real-time data with the proposed model and provides predicted data with a certain level of accuracy. Comparative discussions, statistical error analysis, and correlation-regression analysis have been introduced to validate the proposed epidemiological model. To show the numerical evidence, the investigation comprised the figurative and tabular modes for both real-time and predicted data. Finally, we discussed some concluding remarks based on our findings.

Lessons Learned During the COVID-19 Pandemic in Central India: Overlooked Psychological and Social Determinants of Health

Background: The coronavirus disease 2019 (COVID-19) pandemic, which started in 2019, has created unprecedented public health problems, mental health crises, and economic and social problems. These effects have been studied by numerous researchers on the general population but none on hospitalized and discharged COVID-19 patients.

Aim: To assess psychological and social problems among hospitalized and discharged COVID-19 patients.

Methods: During lockdown and post-lockdown in India, we interviewed 500 COVID-19 patients admitted at our tertiary care center during their hospitalization and post-discharge period for psychological and social problems.

Results: The common psychological issues in hospitalized patients during lockdown were anxiety and misconceptions about COVID-19, while insomnia, anxiety, and frustration were common during the post-lockdown period. The typical social problems in hospitalized patients during the lockdown were containment-related issues, discrimination, longer wait for repeat COVID-19 tests, and boredom; whereas issues related to employment and financial matters were common during post-lockdown. Psychological problems comparatively decreased whereas social problems increased after discharge.

Conclusion: Unrehearsed mitigation strategies at the beginning of the pandemic unknowingly led to various psychological and social problems. It was further aggravated by a lack of information and miscommunication.

Infodemic Preparedness and COVID-19: Searching about Public Health and Social Measures Is Associated with Digital Health Literacy in University Students

We aimed to evaluate the associations between information searching about public health and social measures (PHSM) and university students' digital health literacy (DHL) related to the new coronavirus (SARS-CoV-2) and COVID-19.

METHODS

This cross-sectional study included 3,084 Portuguese university students (75.7% females), with an average age of 24.2 (SD = 7.5). Sociodemographic data, DHL questionnaire and online information concerning PHSM were gathered. Cox proportional hazards models were performed.

RESULTS

Students who searched for personal protective measures achieved in shorter time sufficient "evaluating reliability" (HR = 1.4; 95% CI = 1.1; 1.7) and "determining relevance" (HR = 1.5; 95% CI = 1.2; 1.8). Searching for surveillance and response measures was associated with sufficient "determining relevance" (HR = 1.4; 95% CI = 1.1; 1.9). Finally, those students who searched for environmental, economic and psychosocial measures achieved in shorter time "determining relevance" (HR = 1.2; 95% CI = 1.0; 1.4).

CONCLUSIONS

Searching for PHSM was significantly associated with an increased likelihood of achieving sufficient DHL subscales in a shorter time. Further studies are needed, including developing strategies to increase the availability of high-quality information concerning public health and social measures and to improve (digital) health literacy.

The persuasive role of the past: Policy feedback and citizens' acceptance of information communication technologies during the COVID-19 pandemic in China

How can the enforcement of policies in the past influence a society's future adoption of information communication technologies (ICTs)? In this paper, we tackle this question by exploring how past e-governance policies influence citizens' willingness to use the health QR code, which is a COVID-19 tracing app widely used in China's pandemic control. Past policies regarding smart-city development in China involve two aspects: the construction of electronic infrastructure and the applications of specific technologies. Empirical analysis based on a nationwide dataset in China suggests that past policies exhibit persuasive effects and influence citizens' acceptance of the health QR code. Specifically, e-governance applications in cities significantly enhance citizens' acceptance through the demonstration of their usefulness. However, the construction of e-governance infrastructure per se does not have the same impact on citizens' acceptance. By connecting citizens' acceptance of new technology with past e-governance policies, the study illustrates a nuanced policy feedback mechanism through which past policies can substantially reshape public opinion by policy outcomes.

Assessing the validity of digital health literacy instrument for secondary school students in Ghana: The polychoric factor analytic approach

The emergence of the coronavirus pandemic resulted in the heightened need for digital health literacy among the youth of school-going age. Despite the relevance of digital health literacy among the general public (including students), it appears the measurement of digital health literacy is still a challenge among researchers. Recently, Dadackinski and colleagues adapted existing digital health literacy measures to fit the COVID-19 situation. Since this development, the instrument has been widely used with few validation studies with none in Africa and specifically, in Ghana. The purpose of the study was to assess the validity of the digital health literacy instrument (DHLI) for secondary school students in Ghana using the polychoric factor analysis. We sampled 1,392 students from secondary schools in Ghana. The digital health literacy instrument was administered to the respondents, thereof. The study confirmed the four latent structure of the DHLI. Further, sufficient validity evidence was found regarding the construct validity of the DHLI. The findings from the study support the validity of the DHLI and its utility within the Ghanaian context. With the growing need for digital health literacy among younger people globally, the DHLI provides sufficient grounds for scaling them based on their level of literacy. There is a need for the instrument to be adapted and re-validated in Ghana and among different populations to widen its reproducibility.

The Complex Media Effects on Civic Participation Intention Amid COVID-19 Pandemic: Empirical Evidence from Wuhan College Students

In the context of the COVID-19 pandemic, media exposure is crucial to motivate public action for the combat with COVID-19 pandemic. However, media effects on civic participation intention are understudied. This study applied the Differential Susceptibility to Media effects Model (DSMM) to explore the relations among Wuhan college students' media use, their pandemic-relevant beliefs, and civic participation intention, with a focus on the possible mediation of pandemic-relevant beliefs. Data of 4355 students from a large-scale cross-sectional survey were analyzed. Results show that traditional media use and online media interaction both directly and indirectly affect civic participation intention via pandemic-relevant beliefs. Pandemic-relevant beliefs distort the relations that direct and indirect effects of new media use on civic participation intention are significant but in opposite directions. The influence of pandemic news on civic participation intention is entirely mediated by pandemic-relevant beliefs. To conclude, during pandemic, the role of traditional media use is unreplaceable in its direct and indirect impact on civic participation intention. Pandemic-relevant beliefs play as a distorter variable. The balance between overexposure and insufficiency of pandemic-relevant news is vital. Online media interaction, as a main trait of new media use, plays a crucial role in civic participation intention, directly and indirectly.

Impact of COVID-19 pandemic on screening and diagnosis of patients with prostate cancer: a systematic review protocol

INTRODUCTION

With the exponential progress of patients with COVID-19, unexpected restrictions were directed to limit SARS-CoV-2 dissemination and imposed health-system an entire reformation to diminish transmission risk. These changes likely have caused the full range of cancer screenings and diagnosis gaps. Regardless of the recommendations, prostate cancer (PCa) screening/diagnosis programmes were momentarily postponed. Prostate-specific antigen (PSA) testing has been an inexpensive, low-invasive and relatively precise means of detection for PCa screening that would improve the uncovering of any type of PCa. Unfortunately, a decrease in PSA screening would significantly decrease PCa detection, with non-negligible growth in PCa-specific death. This review is designed to improve our understanding of the impact of the COVID-19 pandemic on the screening and diagnosis of patients with PCa.

METHODS AND ANALYSIS

This systematic review will be reported in accordant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. A comprehensive search has been executed through five main electronic databases: PubMed/MEDLINE, Web of Science, Scopus, Embase and ProQuest until 1 March 2022. Besides, grey literature, preprint studies and references of included studies will be searched. The main keywords have been used to perform the search strategy: COVID-19, prostatic neoplasms. All the relevant studies that met the inclusion criteria will be screened, selected and then extracted data by two independent authors. The quality assessment of the included studies will be performed by the Newcastle-Ottawa Scale. In case of any disagreement between the two authors in selecting, extracting data and assessing the quality of included studies, it will be resolved via consensus and checked by the third author.

ETHICS AND DISSEMINATION

As this study will be a systematic review without human participants' involvement, there will be no requirement for ethics approval. Findings will be presented at conferences and in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42021291656.

Risk management and communication plans from SARS to COVID-19 and beyond

Objective

Nowadays, due to globalisation, the likelihood that infectious diseases spread rapidly is extraordinarily high. SARS and COVID‐19 are two diseases of the Coronavirus family, which developed in China and then spread internationally, causing global public health emergencies. This study investigates the role that risk management and communication systems played in mitigating these emergencies, to establish how they should be improved in the future.

Methods

A narrative review was carried out to investigate different knowledge domains, such as risk management and communication, risk assessment and indicators, epidemiological and clinical data, diagnostic methods, vaccines, public health and social measures.

Results

On one side, risk management systems assess the main data, knowledge, and indicators on epidemiology, diagnostics, and vaccines (science‐based); on the other side, they apply public health and social measures (socially‐based). Decision‐makers, in fact, implement their actions by constantly balancing these two sides (policy‐based).

Conclusions

A correct crisis management approach should support the governance of pandemics, by harmonising the actual risks assessed by experts with those perceived by the general population. It should incorporate not only the biological, but even the environmental, social and economic aspects of virus emergencies, towards establishing a suitable framework to deal with possible future pandemics.

COVID‐19 and SARS enhanced rapid research on specific diagnostics and vaccines.

Public health and social measures remain the primary response to virus outbreaks.

Risk perception affects people's behaviour and public health measures' application.

Risk management and communication plans are crucial to cope with pandemics.

SARS and COVID‐19 experiences should help to deal with future virus emergencie.