Bibliometric analysis of COVID-19 publications shows the importance of telemedicine and equitable access to the internet during the pandemic and beyond.

BACKGROUND: Pandemics highlight the increasing role of information and communications technology for improving access to health care. This study aimed to present a bibliometric analysis of the concept of digital divide reported in the published articles concerning the coronavirus disease 2019 (COVID-19) pandemic. METHODS: To conduct this bibliometric analysis of research topics and trends, we used VOSviewer software. We developed a search strategy to retrieve peer-reviewed publications related to 'digital divide in the COVID-19 era' from the Scopus database. RESULTS: In total, 241 publications on the topic of digital divide and COVID-19 were retrieved from Scopus database between 2020 and 2021. The analysis of keywords co-occurrence of research topics revealed four main clusters including: 'telemedicine', 'Internet access and Internet use', 'e-learning' and 'epidemiology'. Seven characteristic categories were examined in these research topics, including: sociodemographic, economic, social, cultural, personal, material and motivational. CONCLUSION: 'Telemedicine' and 'Internet access and Internet use' as the largest clusters are connected to topics addressing inequalities in online health care access. Thus, policymakers should develop or modify policies in more egalitarian Internet access for all community members not only during a pandemic like the COVID-19 but also at regular times.

Exploring public opinion about telehealth during COVID-19 by social media analytics.

While COVID-19 catalyzed the acceptance and use of telehealth, our understanding of how it is perceived by multi-stakeholders such as patients, clinicians, and health authorities is limited. Drawing on social media analytics, this research examines social media discourses and users' opinions about telehealth during the COVID-19 pandemic. It applies natural language processing and deep learning to explore word of mouth on telehealth with a contextualized focus on the COVID-19 pandemic. We conducted topic modeling, sentiment analysis, and emotion analysis (fearful, happy, sad, surprised, and angry emotions). The topic modeling analysis led to the identification of 18 topics, representing 6 themes of digital health service delivery, pandemic response, communication and promotion, government action, health service domains (e.g. mental health, cancer, aged care), as well as pharma and drug. The sentiment analysis revealed that while most opinions expressed in tweets were positive, the public expressed mostly negative opinions about certain aspects of COVID-19 such as lockdowns and cyberattacks. Emotion analysis of tweets showed a dominant pattern of fearful and sad emotions in particular topics. The results of this study that inductively emerged from our social media analysis can aid public health authorities and health professionals to address the concerns of telehealth users and improve their experiences.

Assessing the online search behavior for COVID-19 outbreak: Evidence from Iran.

INTRODUCTION: Google Trends (GT) is an important free tool for online search behavior analysis, which provides access to Internet search patterns in Google. In recent decades, this database has been used for predicting the outbreak of epidemics and pandemics in different regions of the world. The present study aimed to evaluate Iranian users' COVID-19-related online search behavior. METHODS: This longitudinal study was conducted in 2021. The data of Iranian users' COVID-19-related online search behavior (trend) were collected from the GT website, and the epidemiological data of the COVID-19 outbreak in Iran from 16 February 2020 to 2 January 2021 were sourced from the Iranian ministry of health and medical education, as well as the World Health Organization. The data were analyzed in SPSS using descriptive and inferential statistics. RESULTS: All the COVID-19-related search terms in Iran gained their highest popularity value (relative search volume = 100) in the first 8 weeks of the pandemic, and then this value assumed a decreasing trend over time. Based on factor analysis, relative search volume (RSV) of factor 1 terms (related to corona [in Persian] and corona) have a low significance relationship with COVID-19 epidemiological data in one-, two-, and three-week time lags. Although, RSV of factor 2 terms (related to COVID [in Persian], COVID-19, and coronavirus) correlated with the total weekly number of COVID-19 cases in mentioned time lags. CONCLUSION: COVID-19-related search terms were popular among Iranian users at the beginning of the pandemic. The online search queries and the key terms searched by Iranian users varied during the COVID-19 pandemic. This study provides evidence in favor of the adoption of GT as an epidemiological surveillance tool but, it is necessary to consider that mass media and other confounders can significantly influence RSVs.

Cory COVID-Bot: An Evidence-Based Behavior Change Chatbot for COVID-19.

Cory COVID-Bot is an artificial intelligence chatbot designed and built by a multisector collaboration to help people safely step towards COVID normal. Achieving COVID normal and avoiding unnecessary adverse health outcomes requires effective communication to the public regarding COVID safe behaviors, but reaching young, culturally and linguistically diverse members of the community is challenging for government. Cory COVID-Bot was developed to directly engage with difficult to reach populations in English and Vietnamese. In order to resolve public ambiguity and uncertainty about public health guidelines, and to stimulate safe behavior, Cory COVID-Bot provides updated recommendations and behavior change interventions, which emphasize the importance of COVID safe behaviors.

Infodemic, Misinformation and Disinformation in Pandemics: Scientific Landscape and the Road Ahead for Public Health Informatics Research.

In response to epidemics and pandemics, access to authentic sources of information plays a critical role in informing public health practices. However, infodemic, i.e., an overabundance of health information, misinformation, and disinformation, impede implementing best public health policies during a public health crisis such as COVID-19. In this bibliometric study, we aim to report on concept mapping of infodemic literature, and in line with the World Health Organization (WHO)'s repeated calls for actions in managing infodemic, we highlight fruitful avenues for future directions. Through a visualization approach on a set of 414 records, a concept mapping was carried out. This map revealed 42 infodemic-related nodes in five clusters. We also propose an infodemic research platform in which a combination of the research nodes (e.g., COVID, pandemic, disinformation, fake news, post-truth, fact-checking, social networks, Facebook, WhatsApp, and lockdown) with impactful questions suggest future directions.

Health Data Privacy in the COVID-19 Pandemic Context: Discourses on HIPAA.

BACKGROUND: Considering the impacts of the COVID-19 pandemic on health service delivery, the US Office for Civil Rights (OCR) updated the policies on health data processing, and Health Insurance Portability and Accountability Act (HIPAA). OBJECTIVES: In this study, we investigated discourses on HIPAA in relation to COVID-19. METHODS: Through a search of media sources in the Factiva database, relevant texts were identified. We applied a text mining approach to identify concepts and themes in these texts. RESULTS: Our analysis revealed six central themes, namely, Health, HIPAA, Privacy, Security, Patients, and Need, as well as their associated concepts. Among these, Health was the most frequently discussed theme. It comprised concepts such as public, care, emergency, providers, telehealth, entity, use, discretion, OCR, Health and Human Services (HHS), enforcement, business, and services. CONCLUSION: Our discourse analysis of media outlets highlights the role of health data privacy law in the response to global public health emergencies and demonstrates how discourse analysis and computational methods can inform health data protection policymaking in the digital health era.

Health Pandemic and Social Media: A Content Analysis of COVID-Related Posts on a Telegram Channel With More Than One Million Subscribers.

BACKGROUND: Mobile-based social media play an important role in the dissemination of information during public health emergencies. OBJECTIVES: This study aimed to analyze the contents and trends of public messages posted on Telegram during Coronavirus Disease 2019 (COVID-19) pandemic. METHODS: A content analysis of the 1781 messages, posted in a public Telegram channel with more than one million subscribers performed over 9-weeks. The messages were categorized into seven categories. RESULTS: In total, 39% (n=703) of all messages were related to COVID-19. With the official confirmation of the case of COVID-19 in Iran, the number of COVID-related massages started to rise. Overall, the most frequent messages were of joke and humor (n=292, 41.5%), followed by educational messages (n=140, 19.9%). CONCLUSION: Our study showed that the most popular messages during first weeks of COVID pandemic were satirical, indicating that people may not had taken the risks of this pandemic seriously. It is crucial for health organizations to develop strategies for dissemination of reliable health information through social media.

A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS).

The expansion of mobile health apps for the management of COVID-19 grew exponentially in recent months. However, no study has evaluated these apps. The objective of this study was to develop a reliable measure and rate the quality of COVID-19 mobile health apps, to eventually provide a roadmap for future mHealth app development. In this study, we used COVID-related keywords to identify apps for iOS and Android devices. 13 apps (13.5% of the total number of apps identified) were selected for evaluation. App quality was assessed independently using MARS by two reviewers. Search queries yielded a total of 97 potentially relevant apps, of which 13 met our final inclusion criteria. Kendall's coefficient of concordance value for the inter-rater agreement was 0.93 (p = .03). COVID-19 GOV PK app had the highest average MARS score (4.7/5), and all of the apps had acceptable MARS scores (> 3.0). This study suggests that most COVID-related apps meet acceptable criteria for quality, content, or functionality, and they must highlight esthetic and interesting features for overall quality improvement to be welcomed by users.

COVID-19 on Instagram: A content analysis of selected accounts.

OBJECTIVE: This study aimed to characterize the representation of public health information related to COVID-19 posted on Instagram in 2020. METHODS: This qualitative content analysis study was conducted in Iran as one of the countries with the highest number of confirmed cases of COVID-19. Data were collected from the contents published from February 19 to April 3, 2020, on Instagram. The search feature of the Instagram app was used to find the posts related to Coronavirus or COVID-19. Overall, 1612 posts from 92 accounts were retrieved and analyzed using thematic analysis. RESULTS: A total of 23 themes emerged from the analysis of the retrieved posts. These themes include epidemiology and statistics, training and caring, general prevention guidelines, hygiene, healthy diet and lifestyle, patients, diagnosis and treatment, personal protective equipment, traditional medicine, psychology, children, cultural aspects, socio-cultural impacts, religious, misinformation, and wrong behaviors, animals, satire, condition of the healthcare system, politics, quarantine, operations of the Iranian National Disaster Management Organization (NDMO), economic impacts, and world news. CONCLUSION: The contents analysis of Instagram posts during a public health crisis can provide new and realistic insights into the crisis and identify the topics of interest or concern of the public. Furthermore, the information collected in this way can help policymakers identify the most critical issues from the public perspective and utilize the gained knowledge to manage the ongoing and future pandemics.

Telecardiology and Digital Health for Cardiac Care During COVID-19 Pandemic: Opportunities and Precautions

The COVID-19 pandemic has provided a substantial impetus for the rapid expansion of digital health services worldwide. With the rule of social distancing and quarantine following the outbreak of Coronavirus infection in many countries, special attention has been made to telecardiology as one of the best alternatives to traditional in-person cardiac care. The imposition of unprecedented restrictions on close encounters in almost all sectors, including health care necessitated the expansion of telemedicine and digital health in cardiology services (telecardiology). This paper highlights the benefits and potential risks of the rapid adoption of telecardiology and other digital health solutions for the management of patients with chronic cardiac conditions such as heart failure.

Role of Telehealth in the Management of COVID-19: Lessons Learned from Previous SARS, MERS, and Ebola Outbreaks.

Concerns about the prevention and management of COVID-19 are on the rise, as it is crucial in contagious epidemics that travel and transfer of the patients be minimal for diagnosis, treatment, and follow-ups. Telemedicine or telehealth can play an important role, especially with previous successful experiences in the management of acute infectious respiratory epidemics such as SARS and MERS. In order to better control the rapid spread of coronavirus and manage the COVID-19 crisis, both developed and developing countries can improve the efficiency of their health system by replacing a proportion of face-to-face clinical encounters with telehealth. Recent technological advancement facilitates this reform, but there is a need for national or state-wide rules and regulations to be adapted accordingly.