The COVID-19 social media infodemic

The Disruption of the Cystic Fibrosis Community’s Experiences and Concerns during the COVID-19 Pandemic: Topic Modeling and Time Series Analysis of Reddit Comments (Preprint)

BACKGROUND

The COVID-19 pandemic disrupted the needs and concerns of the cystic fibrosis community. Patients with cystic fibrosis were particularly vulnerable during the pandemic due to overlapping symptoms in addition to the challenges patients with rare diseases face, such as the need for constant medical aid and limited information regarding their disease or treatments. Even before the pandemic, patients vocalized these concerns on social media platforms like Reddit and formed communities and networks to share insight and information. This data can be used as a quick and efficient source of information about the experiences and concerns of patients with cystic fibrosis in contrast to traditional survey- or clinical-based methods.

OBJECTIVE

This study applies topic modeling and time series analysis to identify the disruption caused by the COVID-19 pandemic and its impact on the cystic fibrosis community's experiences and concerns. This study illustrates the utility of social media data in gaining insight into the experiences and concerns of patients with rare diseases.

METHODS

We collected comments from the subreddit r/CysticFibrosis to represent the experiences and concerns of the cystic fibrosis community. The comments were preprocessed before being used to train the BERTopic model to assign each comment to a topic. The number of comments and active users for each data set was aggregated monthly per topic and then fitted with an autoregressive integrated moving average (ARIMA) model to study the trends in activity. To verify the disruption in trends during the COVID-19 pandemic, we assigned a dummy variable in the model where a value of "1" was assigned to months in 2020 and "0" otherwise and tested for its statistical significance.

RESULTS

A total of 120,738 comments from 5827 users were collected from March 24, 2011, until August 31, 2022. We found 22 topics representing the cystic fibrosis community's experiences and concerns. Our time series analysis showed that for 9 topics, the COVID-19 pandemic was a statistically significant event that disrupted the trends in user activity. Of the 9 topics, only 1 showed significantly increased activity during this period, while the other 8 showed decreased activity. This mixture of increased and decreased activity for these topics indicates a shift in attention or focus on discussion topics during this period.

CONCLUSIONS

There was a disruption in the experiences and concerns the cystic fibrosis community faced during the COVID-19 pandemic. By studying social media data, we were able to quickly and efficiently study the impact on the lived experiences and daily struggles of patients with cystic fibrosis. This study shows how social media data can be used as an alternative source of information to gain insight into the needs of patients with rare diseases and how external factors disrupt them.

People with High Perceived Infectability Are More Likely to Spread Rumors in the Context of COVID-19: A Behavioral Immune System Perspective

Since the outbreak of COVID-19, many studies have explored the influencing factors of rumor spreading, such as anxiety, risk perception and information source credibility, but few studies have focused on the impact of individual differences. Based on the theory of behavioral immune systems, we investigated the impact of perceived infectability on rumor spreading and the mediating role of rumor trust in the context of COVID-19. Two studies were investigated using the scale and recall-report task of rumor spreading. The results show that perceived infectability was a significant positive predictor of rumor spreading. However, the impact of perceived infectability on rumor spreading was not direct, and it mainly indirectly affected rumor spreading through the mediating role of rumor trust. Overall, the findings suggest that individuals with high perceived infectability are more likely to believe rumors and then spread rumors during the epidemic. This study advances the literature on rumor spreading and behavioral immune systems and provides practical implications to anti-rumor campaigns.

COVID-19 Public Opinion: A Twitter Healthcare Data Processing Using Machine Learning Methodologies

The COVID-19 pandemic has shattered the whole world, and due to this, millions of people have posted their sentiments toward the pandemic on different social media platforms. This resulted in a huge information flow on social media and attracted many research studies aimed at extracting useful information to understand the sentiments. This paper analyses data imported from the Twitter API for the healthcare sector, emphasizing sub-domains, such as vaccines, post-COVID-19 health issues and healthcare service providers. The main objective of this research is to analyze machine learning models for classifying the sentiments of people and analyzing the direction of polarity by considering the views of the majority of people. The inferences drawn from this analysis may be useful for concerned authorities as they work to make appropriate policy decisions and strategic decisions. Various machine learning models were developed to extract the actual emotions, and results show that the support vector machine model outperforms with an average accuracy of 82.67% compared with the logistic regression, random forest, multinomial naïve Bayes and long short-term memory models, which present 78%, 77%, 68.67% and 75% accuracy, respectively.

Social Media for Public Health: Framework for Social Media-Based Public Health Campaigns

The pervasiveness of social media is irrefutable, with 72% of adults reporting using at least one social media platform and an average daily usage of 2 hours. Social media has been shown to influence health-related behaviors, and it offers a powerful tool through which we can rapidly reach large segments of the population with tailored health messaging. However, despite increasing interest in using social media for dissemination of public health messaging and research exploring the dangers of misinformation on social media, the specifics of how public health practitioners can effectively use social media for health promotion are not well described. In this viewpoint, we propose a novel framework with the following 5 key principles to guide the use of social media for public health campaigns: (1) tailoring messages and targeting them to specific populations-this may include targeting messages to specific populations based on age, sex, or language spoken; interests; or geotargeting messages at state, city, or zip code level; (2) including members of the target population in message development-messages should be designed with and approved by members of the community they are designed to reach, to ensure cultural sensitivity and trust-building; (3) identifying and addressing misinformation-public health practitioners can directly address misinformation through myth-busting messages, in which false claims are highlighted and explained and accurate information reiterated; (4) leveraging information sharing-when designing messages for social media, it is crucial to consider their "shareability," and consider partnering with social media influencers who are trusted messengers among their online followers; and (5) evaluating impact by measuring real-world outcomes, for example measuring foot traffic data. Leveraging social media to deliver public health campaigns enables us to capitalize on sophisticated for-profit advertising techniques to disseminate tailored messaging directly to communities that need it most, with a precision far beyond the reaches of conventional mass media. We call for the Centers for Disease Control and Prevention as well as state and local public health agencies to continue to optimize and rigorously evaluate the use of social media for health promotion.

Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Social media is not only an essential platform for the dissemination of public health-related information, but also an important channel for people to communicate during the COVID-19 pandemic. However, social bots can interfere with the social media topics that humans follow. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

Examining COVID-19 vaccine attitude using SEM-Artificial Neural Networks approach: a case from Reddit community

As new coronavirus variants continue to emerge, in order to better address vaccine-related concerns and promote vaccine uptake in the next few years, the role played by online communities in shaping individuals’ vaccine attitudes has become an important lesson for public health practitioners and policymakers to learn. Examining the mechanism that underpins the impact of participating in online communities on the attitude toward COVID-19 vaccines, this study adopted a two-stage hybrid structural equation modeling (SEM)-artificial neural networks (ANN) approach to analyze the survey responses from 1037 Reddit community members. Findings from SEM demonstrated that in leading up to positive COVID-19 vaccine attitudes, sense of online community mediates the positive effects of perceived emotional support and social media usage, and perceived social norm mediates the positive effect of sense of online community as well as the negative effect of political conservatism. Health self-efficacy plays a moderating role between perceived emotional support and perceived social norm of COVID-19 vaccination. Results from the ANN model showed that online community members’ perceived social norm of COVID-19 vaccination acts as the most important predictor of positive COVID-19 vaccine attitudes. This study highlights the importance of harnessing online communities in designing COVID-related public health interventions and accelerating normative change in relation to vaccination.

A novel approach based on rough set theory for analyzing information disorder

The paper presents and evaluates an approach based on Rough Set Theory, and some variants and extensions of this theory, to analyze phenomena related to Information Disorder. The main concepts and constructs of Rough Set Theory, such as lower and upper approximations of a target set, indiscernibility and neighborhood binary relations, are used to model and reason on groups of social media users and sets of information that circulate in the social media. Information theoretic measures, such as roughness and entropy, are used to evaluate two concepts, Complexity and Milestone, that have been borrowed by system theory and contextualized for Information Disorder. The novelty of the results presented in this paper relates to the adoption of Rough Set Theory constructs and operators in this new and unexplored field of investigation and, specifically, to model key elements of Information Disorder, such as the message and the interpreters, and reason on the evolutionary dynamics of these elements. The added value of using these measures is an increase in the ability to interpret the effects of Information Disorder, due to the circulation of news, as the ratio between the cardinality of lower and upper approximations of a Rough Set, cardinality variations of parts, increase in their fragmentation or cohesion. Such improved interpretative ability can be beneficial to social media analysts and providers. Four algorithms based on Rough Set Theory and some variants or extensions are used to evaluate the results in a case study built with real data used to contrast disinformation for COVID-19. The achieved results allow to understand the superiority of the approaches based on Fuzzy Rough Sets for the interpretation of our phenomenon.

Political polarization on Twitter during the COVID-19 pandemic: a case study in Brazil

The debate over the COVID-19 pandemic is constantly trending at online conversations since its beginning in 2019. The discussions in many social media platforms is related not only to health aspects of the disease, but also public policies and non-pharmacological measures to mitigate the spreading of the virus and propose alternative treatments. Divergent opinions regarding these measures are leading to heated discussions and polarization. Particularly in highly politically polarized countries, users tend to be divided in those in-favor or against government policies. In this work we present a computational method to analyze Twitter data and: (i) identify users with a high probability of being bots using only COVID-19 related messages; (ii) quantify the political polarization of the Brazilian general public in the context of the COVID-19 pandemic; (iii) analyze how bots tweet and affect political polarization. We collected over 100 million tweets from 26 April 2020 to 3 January 2021, and observed in general a highly polarized population (with polarization index varying from 0.57 to 0.86), which focuses on very different topics of discussions over the most polarized weeks–but all related to government and health-related events.

Adolescent sleep myths: Identifying false beliefs that impact adolescent sleep and well-being

OBJECTIVE

Commonly held beliefs about sleep unsupported by scientific evidence (ie, myths) among adolescents and their parents/caregivers may adversely influence sleep-related attitudes and behaviors among adolescents. Thus, identifying such myths with the goal of developing effective evidence-based counter-messages has the potential to improve sleep health in adolescents.

METHOD

We identified myths with a panel of adolescent sleep health experts (n = 12) using the Delphi method in three sequential steps: (1) focus groups; (2) online discussion; and (3) closed-ended questionnaires with which the experts rated myths on: (1) falseness and (2) public health significance using 5-point Likert scales ranging from 1 (not at all false/important for public health) to 5 (extremely false/important for public health). Next, we explored the prevalence of the myths among a demographically diverse sample of parents/caregivers of adolescents in the United States. Finally, we report the counterevidence to refute each myth.

RESULTS

Ten myths about adolescent sleep were identified by the experts using the Delphi method. The most prevalent myths were the beliefs that (1) "Going to bed and waking up late on the weekends is no big deal for adolescents, as long as they get enough sleep during that time," reported by 74% of parents/caregivers; (2) "If school starts later, adolescents will stay up that much later," reported by 69% of parents/caregivers; and (3) "Melatonin supplements are safe for adolescents because they are natural," reported by 66% of parents/caregivers.

CONCLUSION

Parents/caregivers have the potential to serve as sleep health advocates for their adolescent and support their adolescent's sleep health behaviors. Our study found that many parents/caregivers endorse myths about adolescent sleep that may hinder their ability to support their adolescent's sleep health. Future research may explore methods for promoting evidence-based beliefs about adolescent sleep among parents/caregivers.

In Science We Trust: The Effects of Information Sources on COVID-19 Risk Perceptions

The goal of this study was to investigate the effects of sources of information on COVID-19 risk perceptions. Using data from a representative sample of the Portuguese population (N = 1,411) collected early in the pandemic, we find that while media sources were more frequently used, scientific sources played a more important role on perceived personal and societal-level risks; higher trust in scientific sources associated with increased risk perceptions (i.e., amplified perceived risk), trust in social media associated with dismissing personal threat (i.e., attenuated perceived risk). These findings suggest that people's relations with science were determinant factors in risk perceptions, and dimensions that measure these deserve further investigation.

Predicting social media rumours in the context of public health emergencies

The spread of rumours on social media in the context of public health emergencies often distorts perceptions of public events and obstructs crisis management. Microblog entries about 28 rumour cases are collected on Sina Weibo during the COVID-19 outbreak. The Modality–Agency–Interactivity–Navigability model is used to identify the key factors of rumour prediction. To investigate the relationship among information modality, information content, information source and rumour identification, the binary logistic regression model is established based on the features of users and microblog entries. In addition, we propose a multi-feature rumour prediction model based on the Bidirectional Encoder Representations from Transformers (BERT) and Extreme Gradient Boosting (XGBoost) models. The proposed rumour prediction model has the best performance compared with other models. The feature importance is then calculated by the SHapley Additive exPlanations (SHAP), which can also explain the XGBoost results. It is shown that the likelihood that microblog entries are rumours decreases as the values of variables such as user influence and the positive sentiment of comments rise. Microblog entries posted on Thursdays or at noon are more probably to be rumours than those posted at other time. The proposed model can assist emergency management departments in establishing a feasible rumour prediction mechanism to guide public opinion against rumours.

Use of social media platforms by migrant and ethnic minority populations during the COVID-19 pandemic: a systematic review

OBJECTIVE

Migrants and ethnic minority groups have been disproportionately impacted by COVID-19 and have lower levels of vaccine uptake in some contexts. We aimed to determine the extent and nature of social media use in migrant and ethnic minority communities for COVID-19 information, and implications for preventative health measures including vaccination intent and uptake.

DESIGN

A systematic review of published and grey literature following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched databases including Embase, Web of Science, PubMed NIH, CINAHL, facilitated through the WHO Global Research on COVID-19 database from 31 December 2019 to 9 June 2021.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Research reporting the use of social media by migrants and/or ethnic minority groups in relation to COVID-19.

DATA EXTRACTION

We extracted data on key outcomes, study design, country, population under study and sample size.

RESULTS

1849 unique records were screened, and 21 data sources were included, including populations in the UK, USA, China, Jordan, Qatar and Turkey. We found evidence of consistent use of a range of social media platforms for COVID-19 information in some migrant and ethnic minority populations (including WeChat, Facebook, WhatsApp, Instagram, Twitter, YouTube), which may stem from difficulty in accessing COVID-19 information in their native languages or from trusted sources. Some evidence suggested circulating misinformation and social media use may be associated with lower participation in preventative health measures, including vaccine intent and uptake, findings which are likely relevant to multiple population groups.

CONCLUSIONS

Social media platforms are an important source of information about COVID-19 for some migrant and ethnic minority populations. Urgent actions and further research are now needed to better understand effective approaches to tackling circulating misinformation, and to seize on opportunities to better use social media platforms to support public health communication and improve vaccine uptake.

REGISTRATION

This study has been registered with PROSPERO (CRD42021259190).

The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges

The COVID-19 pandemic is the most devastating public health crisis in at least a century and has affected the lives of billions of people worldwide in unprecedented ways. Compared to pandemics of this scale in the past, societies are now equipped with advanced technologies that can mitigate the impacts of pandemics if utilized appropriately. However, opportunities are currently not fully utilized, particularly at the intersection of data science and health. Health-related big data and technological advances have the potential to significantly aid the fight against such pandemics, including the current pandemic's ongoing and long-term impacts. Specifically, the field of natural language processing (NLP) has enormous potential at a time when vast amounts of text-based data are continuously generated from a multitude of sources, such as health/hospital systems, published medical literature, and social media. Effectively mitigating the impacts of the pandemic requires tackling challenges associated with the application and deployment of NLP systems. In this paper, we review the applications of NLP to address diverse aspects of the COVID-19 pandemic. We outline key NLP-related advances on a chosen set of topics reported in the literature and discuss the opportunities and challenges associated with applying NLP during the current pandemic and future ones. These opportunities and challenges can guide future research aimed at improving the current health and social response systems and pandemic preparedness.

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.

Should I trust or should I go? How people perceive and assess the quality of science communication to avoid fake news

This paper investigates how citizens of five European countries (Italy, Poland, Portugal, Slovakia, and Spain) enquire about scientific issues, how they rate scientific information on climate change and vaccines in terms of quantity and quality, and their strategies for overcoming perceived defects. We conducted a public consultation involving almost 500 citizens and addressed controversial science-related topics. Discussions were qualitatively content analyzed. The public consultations revealed the prevalence of traditional media as a source of scientific information, and the results presented a general perception of inadequate, imprecise, and insufficient scientific communication. Finally, we show how traditional media are still the most frequently used channels and that personal criteria prevail in the evaluation of the reliability of information sources.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11135-022-01569-5.

Impact of the eHealth literacy, knowledge and attitudes on COVID-19 prevention behavior among residents in the second year of the COVID-19 pandemic: A cross-sectional study in Anhui Province, China

Objective

The pandemic of COVID-19 continues to challenge people's health worldwide. In the second year of the pandemic, adherence to COVID-19 preventive behavior is key to continuing efforts to overcome the epidemic. This study aims to assess the COVID-19-related knowledge, attitude, and prevention behavior (KAP) and electronic health literacy (eHealth literacy) among Anhui residents in China.

Methods

From January 30 to March 27, 2021, the cross-sectional study was performed among Anhui residents in China, including 16 cities. An online survey was adopted to assess KAP regarding COVID-19, and eHealth, involving a total of 2,122 citizens. Following informed consent, residents were recruited by convenience sampling. Frequencies and proportions were calculated. Additionally, Mann-Whitney U tests were used to analyze the variables. Independent predictors of preventive behavior of COVID-19 were ascertained using a multivariable logistic regression model.

Result

Residents demonstrated good knowledge, positive attitudes, acceptable practices, and good eHealth literacy. Online news and WeChat are the main health information resources. Citizens who had good knowledge, a positive attitude, good eHealth, and did not participate in the online lectures or training COVID-19 were more likely to take preventive measures. Those with poor health, who were male, did not have family members working in health care facilities, and did not work in a face-to-face environment were less likely to take precautions. Compared with a master's degree and above, participants with middle school education level and below took preventive behavior sometimes. Residents who browse the COVID-19 webpage <15 min weekly seldom took preventive actions.

Conclusion

The study showed that in the second year of the COVID-19 pandemic, Chinese residents had adequate knowledge of COVID-19, positive attitudes, appropriate preventive practices, and basic eHealth literacy. To prevent the rebound of the COVID-19 epidemic, the government and health agencies should inform citizens concerning which information channels or websites to use and assist the underprivileged population who lacks basic infrastructure. In addition, increasing the level of knowledge and attitude, enhancing eHealth literacy and the Health Belief Model (HBM), and implementing the Health Code were seen as ways to reinforce adherence to preventive behavior. Targeting men, implementing public awareness campaigns, community engagement strategies, and health education programs are recommended.

Disentangling crucial factors of the pandemic in Brazil: Effect of lockdown restrictions on mental health

Quarantine and social distance restrictions have been enforced worldwide to reduce the spread of coronavirus disease 2019 (COVID-19). The effects of these measures on mental health are recognised, but remaining unclear, is whether these effects are a consequence of the virus itself or policies that are enforced to prevent it. The present study investigated the impact of lockdown restrictions on anxiety and depression at two different times in 2020. Data were collected from 118 participants from all regions of Brazil. After easing quarantine restrictions in the second half of 2020, two natural groups were formed. One group included participants who voluntarily remained at home (n = 73). The other group consisted of those who decided to leave home (n = 45). A linear mixed model was used to determine the effects of group and time and their interaction. The McNemar test was used to determine intragroup differences in perceptions and concerns about COVID-19. Logistic regression identified predictors of high and stable depression and anxiety. None of the factors or their interactions was significant. Indicators of depression and anxiety remained stable over time, regardless of whether the participants left home or remained at home. Significantly, a strong and stable agreement with quarantine was found. The participants agreed that COVID-19 was a threat to public health. Political orientation was a predictor of high and stable levels of depression but not anxiety. Participants who self-identified as liberal politically were at a greater risk of developing depression. The results suggest that the lockdown policy did not contribute to disruptions of mental health, which instead was a consequence of the pandemic and virus itself. We also found wide and strong support amongst the participants for lockdown and mandatory stay-at-home policies.

How to Promote Public Engagement and Enhance Sentiment Through Government Social Media During the COVID-19 Crisis

In the period of public health crisis, effective and efficient transmission of crisis information to the public through social media is an important support for achieving social stability and orderly online public engagement. From the perspective of public value management, this study systematically investigated how local government agencies in China used social media to promote public engagement and raise public sentiment during the COVID-19 crisis. Using data captured from the “Wuhan Release” Sina Weibo account, the authors studied the factors that influence public engagement, including information sources, language styles, and media types. Further, it explores the influence of the interactive effects of public value with information sources, language styles, and media types on public engagement and public sentiment. The results show that the consistency of government response content and public value promotes public engagement and raises public sentiment. This research provides enlightenment and ideas for cognition, understanding and governance of public opinion in practice.

Science, health, and human rights

A solid knowledge base is one of the necessary conditions to assure health as a human right. The contemporary source of such knowledge are the sciences at large, which however presents a problem, since the scientific enterprise can - and has been - a source of human rights violations as well. The field of social studies of science (STS) takes an iconoclast approach to the science, providing much needed criticism of its claims of authority. Recently, however, when attacks from multiple sources attempt to undermine perfectly reasonable scientific developments, the STS approach may not provide the adequate tools to deal with such challenge, especially with regard to health issues. This essay explores, with examples, ways in which the critical stance of STS may be compatible with a defense of proper scientific knowledge - in fact, helping to define what that actually means - without falling in the trap of scientism.

Online health information seeking and digital health literacy among information and learning resources undergraduate students

Background

During the COVID-19 pandemic, students have trouble coping with the available health information regarding the coronavirus in their daily lives because of misinformation.

Objectives

The aim of this study was to evaluate online health information seeking and digital health literacy among information and learning resources undergraduate students at Taibah University during the COVID-19 pandemic.

Methods

To investigate the primary goal, this study used a simultaneous exploratory mixed methods design. Seventeen students participated in phone interviews, and 306 were invited to complete an online survey.

Analysis

The collected data was analyzed using both quantitative (SPSS) and qualitative (NVivo 10) methods.

Results

Search engines, social media, and YouTube were most often used by the respondents as sources to search for COVID-19-related information. COVID-19 symptoms, restrictions, and the current spread of COVID-19 were the most searched topics by the respondents. Significant and relevant differences emerged for the digital health literacy subscales “information search” and “adding self-generated content”. However, there were no significant differences in the digital health literacy subscale “determining relevance”.

Conclusion

Using the internet to provide health information tailored to the needs and interests of students to seek health information online and thereby improve their health literacy.

Differential impacts of COVID-19 and associated responses on the health, social well-being and food security of users of supportive social and health programs during the COVID-19 pandemic: A qualitative study

The effects of the coronavirus disease-2019 (COVID-19) pandemic on the lives of underserved populations are underexplored. This study aimed to identify the impacts of the COVID-19 pandemic and associated public health responses on the health and social well-being, and food security of users of Housing First (HF) services in Toronto (Canada) during the first wave of the COVID-19 pandemic. This qualitative descriptive study was conducted from July to October 2020 in a subsample of 20 adults with a history of homelessness and serious mental disorders who were receiving HF services in Toronto. A semi-structured interview guide was used to collect narrative data regarding health and social well-being, food security and access to health, social and preventive services. A thematic analysis framework guided analyses and interpretation of the data. The COVID-19 pandemic and response measures had a variable impact on the health, social well-being and food security of participants. Around 40% of participants were minimally impacted by the COVID-19 pandemic. Conversely, among the remaining participants (impacted group), some experienced onset of new mental health problems (anxiety, stress, paranoia) or exacerbation of pre-existing mental disorders (depression, post-traumatic stress disorder and obsessive-compulsive disorder). They also struggled with isolation and loneliness and had limited leisure activities and access to food goods. The pandemic also contributed to disparities in accessing and receiving healthcare services and treatment continuity for non-COVID-19 health issues for the negatively impacted participants. Overall, most participants were able to adhere to COVID-19 public health measures and get reliable information on COVID-19 preventive measures facilitated by having access to the phone, internet and media devices and services. In conclusion, the COVID-19 pandemic and associated response measures impacted the health, social well-being, leisure and food security of people with experiences of homelessness and mental disorders who use supportive social and housing services in diverse ways.

Advanced sanitation products infused with silver nanoparticles for viral protection and their ecological and environmental consequences

The outbreak of coronavirus ailments (COVID-19) in 2019 resulted in public health crisis leading to global pandemonium. In response to the high prevalence of disease transmission, governments all around the globe implemented emergency measures in various routes (e.g., social distancing, personal hygiene, and disinfection of public/private places) to curb/contain COVID-19 infections. The social media infodemic, released as uncensored publishing and/or views/recommendations, also triggered large-scale behavior changes such as the overuse of advanced sanitation products (ASPs) containing nanomaterials. The majority of these ASPs contain silver nanoparticles (AgNPs) as an active ingredient to enhance their antimicrobial potential. Ecotoxicological concerns such as the transformation and degradation of these AgNP-infused products in terrestrial or aquatic environments are under the jurisdiction of the EPA. However, they are not considered in the FDA approval process. In light of excessive consumption of ASPs, it is time to consider their ecotoxicological screening prior to market approval jointly by the FDA and EPA, along with the implementation of post-market surveillance strategies. At the same time, efforts should be put into running awareness programs to prevent the overuse of ASPs.

Early detection of fraudulent COVID-19 products from Twitter chatter: a dataset and a baseline approach using anomaly detection (Preprint)

Background

Social media has served as a lucrative platform for spreading misinformation and for promoting fraudulent products for the treatment, testing, and prevention of COVID-19. This has resulted in the issuance of many warning letters by the US Food and Drug Administration (FDA). While social media continues to serve as the primary platform for the promotion of such fraudulent products, it also presents the opportunity to identify these products early by using effective social media mining methods.

Objective

Our objectives were to (1) create a data set of fraudulent COVID-19 products that can be used for future research and (2) propose a method using data from Twitter for automatically detecting heavily promoted COVID-19 products early.

Methods

We created a data set from FDA-issued warnings during the early months of the COVID-19 pandemic. We used natural language processing and time-series anomaly detection methods for automatically detecting fraudulent COVID-19 products early from Twitter. Our approach is based on the intuition that increases in the popularity of fraudulent products lead to corresponding anomalous increases in the volume of chatter regarding them. We compared the anomaly signal generation date for each product with the corresponding FDA letter issuance date. We also performed a brief manual analysis of chatter associated with 2 products to characterize their contents.

Results

FDA warning issue dates ranged from March 6, 2020, to June 22, 2021, and 44 key phrases representing fraudulent products were included. From 577,872,350 posts made between February 19 and December 31, 2020, which are all publicly available, our unsupervised approach detected 34 out of 44 (77.3%) signals about fraudulent products earlier than the FDA letter issuance dates, and an additional 6 (13.6%) within a week following the corresponding FDA letters. Content analysis revealed misinformation, information, political, and conspiracy theories to be prominent topics.

Conclusions

Our proposed method is simple, effective, easy to deploy, and does not require high-performance computing machinery unlike deep neural network-based methods. The method can be easily extended to other types of signal detection from social media data. The data set may be used for future research and the development of more advanced methods.

Analysis of government agencies and stakeholders’ twitter communications during the first surge of COVID-19 in Brazil

BACKGROUND: Official authorities are in charge of communicating with the public in a consistent and coherent manner. The impact of social media on managing the coronavirus 2019 (COVID-19) pandemic potentially influenced social behavior in Brazil. OBJECTIVE: Using Twitter, this study analyzes communications about the COVID-19 pandemic from official agencies of the Brazilian government and key public sector decision-makers. METHOD: We captured public Twitter messages about COVID-19 exchanged between authorities at the federal, state, and municipal levels of government. These messages were further classified into guidance and information messages or disinformation messages. Finally, through analysis of tweets and their frequency, we evidenced the level of information generated by the three levels of government. RESULTS: Our analyses show an underestimation of the magnitude of the pandemic by Brazilian government authorities. None of the spheres of government anticipated the imminent health crisis, did not issue good recommendations and guidelines, and did not take preventive actions. CONCLUSION: The lack of governmental actions and adequate guidance in Brazil has led to an explosive increase in infected people and deaths. Surprisingly, this was not due to technical or structural reasons. It resulted from conflicting communication strategies implemented by the federal, state, and municipal governments in attempts to minimize the effects of COVID-19 on their local health structures.

Trust in social media and COVID-19 beliefs and behaviours

The study investigates the relationship between trust in social media and beliefs and preventive behaviours in the context of the COVID-19 pandemic. We surveyed 1008 respondents in South Africa to study how trust in social media relative to other information sources predicts perceived risk and adoption of preventive behaviours. Although engagement with and trust in social media do not predict less adoption of preventive behaviours, trusting information from social media more than information from mass media or scientists is associated with less risk perception from COVID-19 and reduces the adoption of preventive behaviours (including vaccines).

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.

COVID-19 related conspiracy beliefs and their relationship with defense strategies, emotions, powerlessness, attitudes, and time perspective

The COVID-19 pandemic has greatly impacted individual's life and society, and such an emergency has increased the likelihood of recurring conspiratorial thinking. There is much research on broader conspiratorial thinking and studies on COVID-19-related conspiratorial thinking has been growing worldwide, moreover, the negative consequences of COVID-19 specific conspiratorial beliefs for people's health are clear. However, person-centered research aiming at identify groups of individuals who share patterns of relations between COVID-19 specific conspiratorial beliefs and other psychological features is still scarce. A sample of 1.002 people (18-40 years old, M = 23; SD = 5.19) responded to a questionnaire administered online. The aim was to identify groups of individuals based on their beliefs about COVID-19 conspiracy theories and to compare the groups identified in terms of psychological characteristics associated such as automatic defense mechanisms, coping strategies, powerlessness, emotions, emotional regulation, attitudes toward the COVID-19, social distancing discontent, perceptions of COVID-19 severity and temporal perspective. A k-mean cluster analysis identified the groups of Believers (22.26%), Ambivalent believers (34.3%), and Non-believers (43.21%). The three groups differ particularly in terms of defense mechanisms, and time perspective. Results suggested the need to tailor interventions for individuals believing in COVID-19 conspiratorial theories based on differences in the psychological characteristics among the three groups.

False memories for true and false vaccination information form in line with pre-existing vaccine opinions

Misinformation continually threatens efforts to control the COVID-19 pandemic, with vaccine misinformation now a key concern. False memories for misinformation can influence behavioural intentions, yet little is known about the factors affecting (false) memories for vaccine-related news items. Across two experiments (total n = 1481), this paper explores the effects of pre-existing vaccine opinions on reported memories for true and false news items. In Study 1, participants (n = 817) were exposed to fabricated pro- or anti-vaccine news items, and then asked if they have a memory of this news event having occurred. In Study 2, participants (n = 646) viewed true pro- or anti-vaccine news items. News items were more likely to be remembered when they aligned with participants' pre-existing vaccine beliefs, with stronger effects for pro-vaccine information. We conclude by encouraging researchers to consider the role of attitudinal bias when developing interventions to reduce susceptibility to misinformation.

The digital rainbow: Digital determinants of health inequities

The widely used socioecological rainbow model from Dahlgren and Whitehead specifies determinants of health inequity on multiple hierarchical levels and suggests that these determinants may interact both within and between levels. At the time of its inception, digital determinants only played a minor role in tackling inequities in public health and were therefore not specifically considered. This has dramatically changed: From today's perspective, health inequities increasingly depend on digital determinants. In this article, we suggest adapting the Dahlgren-Whitehead model to reflect these developments. We propose a model that allows formulating testable hypotheses, interpreting research findings, and developing policy implications against the background of the global spread of digital technologies. This may facilitate the development of a new line of research and logic models for public health interventions in the digital age. Using the COVID-19 pandemic as a case study, we illustrate how the digitization of all aspects of life affects the different levels of determinants of health inequities in the Dahlgren-Whitehead model. In doing so, we deliberately argue for not introducing a separate digital sphere in its own right, but for understanding digitization as a phenomenon that permeates all levels of determinants of health inequities. As a result, we present a digital rainbow model that integrates Dahlgren and Whitehead's 1991 model with digital environments to identify current health promotion and research issues without changing the rainbow model's initial structure.

COVID-19 Conspiracy Theories Discussion on Twitter

The coronavirus disease 2019 (COVID-19) pandemic was an unexpected event and resulted in catastrophic consequences with long-lasting behavioral effects. People began to seek explanations for different aspects of COVID-19 and resorted to conspiracy narratives. The objective of this article is to analyze the changes on the discussion of different COVID-19 conspiracy theories throughout the pandemic on Twitter. We have collected a data set of 1.269 million tweets associated with the discussion on conspiracy theories between January 2020 and November 2021. The data set includes tweets related to eight conspiracy theories: the 5G, Big Pharma, Bill Gates, biological weapon, exaggeration, FilmYourHospital, genetically modified organism (GMO), and the vaccines conspiracy. The analysis highlights several behaviors in the discussion of conspiracy theories and allows categorizing them into four groups. The first group are conspiracy theories that peaked at the beginning of the pandemic and sharply declined afterwards, including the 5G and FilmYourHospital conspiracies. The second group associated with the Big Pharma and vaccination-related conspiracy whose role increased as the pandemic progressed. The third are conspiracies that remained persistent throughout the pandemic such as exaggeration and Bill Gates conspiracies. The fourth are those that had multiple peaks at different times of the pandemic including the GMO and biological weapon conspiracies. In addition, the number of COVID-19 new cases was found to be a significant predictor for the next week tweet frequency for most of the conspiracies.

Health Equity, History, and a New Presidential Bioethics Commission: Lessons from the "Lost" Reports

Convening a national bioethics commission has historically been one of the most powerful bioethical legacies a US presidential administration can undertake. The Biden Administration has not yet created such a commission; here we argue that centering health equity and healthcare access would provide a vital framework for a new commission's legacy. Moreover, we demonstrate two crucial historical episodes when American presidents appointed commissions to examine the practical and ethical implications of these very issues. We turn first to the 1952 President's Commission report on "Building America's Health," a lofty vision of universal healthcare access stymied by both political conflict and unaddressed problems of racism in the era's legislation. Its rich yet incomplete account of American health inequities serves as a valuable forerunner to questions of justice in bioethics. We then explore the President's Commission's 1983 report "Securing Access to Healthcare: A Report on the Ethical Implications of Differences in the Availability of Health Services." This report took up the mantle of equity in healthcare access, again with mixed results. Only by understanding the checkered history of these overlooked, practically "lost" reports can a new era in American bioethics successfully re-center the goal of equitable health for all.

Personal Narrative under Nationalism: Chinese COVID-19 Vaccination Expressions on Douyin

Scholars are divided over whether narrative/storytelling occupies a central position in health-related behaviour or in the health-related issues discussed on social media platforms. This study explored Chinese COVID-19 vaccination expressions on Douyin, China's biggest short-video sharing social media platform, and found that narration is still the most important tool employed by Chinese users when talking about COVID-19 vaccinations on Douyin, emphasizing nationalism and widespread optimism. Most of the narratives employed by Chinese users come from a first-person perspective. Nationalism, as manifested in the support expressed for national policies, rather than the external platform characteristics of memetics, makes the Chinese users' expressions about COVID-19 vaccinations similar on Douyin. Douyin seems to have become a 'pilgrimage platform' for the Chinese public to express their patriotic sentiment and their trust in the country and the government.

A Thin Line Between Helpful and Harmful Internet Usage: Embodied Research on Internet Experiences Among Adolescent and Young Adult Cancer Patients

Purpose: The purpose of this study was to expand upon findings from a prior Delphi study of adolescent and young adults' (AYAs') preferences for cancer resources. Utilizing an embodied approach, this study intended to elucidate a deeper and nuanced understanding of the expressed benefits and risks of engaging in cancer-related online interactions. Methods: Using Gale et al.'s framework method for qualitative, multidisciplinary health research and Thanem and Knights's embodied research methods for the social sciences, an investigative team of embodied researchers (AYA cancer patients turned researchers) conducted semistructured in-depth interviews with AYA cancer patients (n = 10) diagnosed between ages 15 and 39 years. To generate themes, researchers identified commonalities and differences within the qualitative data, and indexed codes according to the agreed analytic framework. Furthermore, by fully engaging with personal reflexivity, bracketing, and analytic memos across data collection and analysis, the investigative team elucidated benefits and risks of embodied research. Results: Findings impart evidence on AYAs' needs for internet-based content at the time of cancer diagnosis, use of the internet to fulfill cancer-related needs, perception of gaps in online cancer resources, and advice to other AYA cancer patients accessing internet-based information and support. Content analysis of interview data on participants' descriptions of personal engagement with the internet revealed beneficial themes of empowerment and harmful themes of fear-inducing consequences. Conclusions: In our rapidly evolving context of postpandemic internet reliance, developers of online cancer content should prioritize and respond to the nuanced vulnerabilities of AYAs. Future research must include socioeconomically disadvantaged participants to better understand practical challenges and promote health equity.

Théories du complot et COVID-19 : comment naissent les croyances complotistes ?

La pandémie COVID-19 causée par le nouveau coronavirus SARS-CoV-2 a provoqué une crise mondiale sans précédent, associée à une prolifération de théories du complot. La prévalence de ces croyances complotistes a participé à affaiblir la crédibilité des mesures gouvernementales de santé publique, limiter l'accès des citoyens aux sources d’information fiables, et perturber la réponse des systèmes de santé face à la crise sanitaire. Plusieurs hypothèses ont été proposées en psychologie et en sciences sociales pour comprendre la genèse de ces croyances dans des contextes épidémiques, associant l’implication conjointe de facteurs psychologiques (comme la volonté de préserver sa sécurité, de maintenir une image de soi positive, ou encore de renforcer son rôle social) et sociodémographiques (comme les caractéristiques générationnelles, socioculturelles et politiques des individus). Toutefois, les découvertes récentes en sciences cognitives à propos des mécanismes élémentaires de traitement de l'information offrent un nouvel éclairage sur la génération des croyances conspirationnistes à travers les époques et les cultures. Dans cet article, nous proposons une définition de la théorie du complot et une classification des croyances complotistes pendant la pandémie de COVID-19. Nous montrons comment les mécanismes de génération et de mise à jour des croyances permettent d'expliquer la genèse des théories du complot, et nous proposons plusieurs hypothèses étayées par les recherches contemporaines en sciences cognitives et en sciences sociales à propos des théories du complot.

Measuring the effects of misinformation exposure and beliefs on behavioural intentions: a COVID-19 vaccination study

Misinformation has been a pressing issue since the beginning of the COVID-19 pandemic, threatening our ability to effectively act on the crisis. Nevertheless, little is known about the actual effects of fake news on behavioural intentions. Does exposure to or belief in misinformation about COVID-19 vaccines affect people's intentions to receive such a vaccine? This paper attempts to address this question via three preregistered experiments (N = 3463). In Study 1, participants (n = 1269) were exposed to fabricated pro- or anti-vaccine information or to neutral true information, and then asked about their intentions to get vaccinated. In Study 2, participants (n = 646) were exposed to true pro- and anti-vaccine information, while Study 3 (n = 1548) experimentally manipulated beliefs in novel misinformation about COVID-19 vaccines by increasing exposure to the information. The results of these three studies showed that exposure to false information about the vaccines had little effect on participants' intentions to get vaccinated, even when multiple exposures led them to believe the headlines to be more accurate. An exploratory meta-analysis of studies 1 and 3, with a combined sample size of 2683, showed that exposure to false information both supporting and opposing COVID-19 vaccines actually increased vaccination intentions, though the effect size was very small. We conclude by cautioning researchers against equating exposure to misinformation or perceived accuracy of false news with actual behaviours.

Depression, reduced education, and bias perceptions as risk factors of beliefs in misinformation

The spread of misinformation and conspiracy theories related to COVID‐19 has represented one of the several undesirable effects of the current pandemic. In understanding why people can be more or less at risk to believe in misinformation, emotional distress and education could play a crucial role. The present study aims to analyze the relationship among depressive symptoms, education, and beliefs in misinformation about COVID-19 during the early phase of the pandemic. We do this through a cross-sectional study carried out on a random and representative sample of the Italian population that allows us to go and verify the co-evolution of many factors: i.e., beliefs in misinformation, symptoms of depression, perceptions about COVID-19, ways in which citizens got informed about the pandemic, and sociodemographic characteristics (e.g., age, gender, education). The results show that the relationship between depression and beliefs in misinformation exists and is more complex than hypothesized because it is mediated by individual perceptions. In particular, the most at-risk people to believe in misinformation show higher bias perceptions, higher depression, and lower education. Practical implications are discussed suggesting a supportive intervention at both individual and social levels.

Losing the battle over best-science guidance early in a crisis: COVID-19 and beyond

Ensuring widespread public exposure to best-science guidance is crucial in any crisis, e.g., coronavirus disease 2019 (COVID-19), monkeypox, abortion misinformation, climate change, and beyond. We show how this battle got lost on Facebook very early during the COVID-19 pandemic and why the mainstream majority, including many parenting communities, had already moved closer to more extreme communities by the time vaccines arrived. Hidden heterogeneities in terms of who was talking and listening to whom explain why Facebook's own promotion of best-science guidance also appears to have missed key audience segments. A simple mathematical model reproduces the exposure dynamics at the system level. Our findings could be used to tailor guidance at scale while accounting for individual diversity and to help predict tipping point behavior and system-level responses to interventions in future crises.

The use of social media at work place and its influence on the productivity of the employees in the era of COVID-19

As per Internet world stats, with 560 million Internet users, India is the second largest online market in the world, ranked only behind China. Out of these 560 million Internet users in India, almost 375 million people use social media. These facts are enough to highlight the deep penetration of Internet and social media in Indian society. This deep penetration of social media among the Indian workers has further more deepened in the era of COVID-19. The employees are working from home, so they are more prone to use mobile and social media platforms for non-work-related purposes. It is a proven fact that social media has not only impacted our personal lives but also professional lives in more than one ways. Despite the previously mentioned staggering figures which show the deep penetration of Internet and social media in our Indian society, sufficient studies/researches have not been conducted to study the impact of social media on our professional lives. Keeping in mind these things, the purpose of this study is to understand the impact of social media on one of the most crucial aspects of our professional lives, i.e., labour productivity which is quite crucial not only for the success of individuals and business organizations but also for the economic growth of any country. This study also tries to highlight the other related aspects of social media usage at workplace like the perception of the employees regarding use of social media at workplace, purpose for which social media is being used by the employees and other such related issues. Primary data have been used in this study; collected through a survey from the professionals/employees who hail from different sectors/industries. The authors have used convenient sampling method to collect data to examine the impact of social media usage on the productivity of the employees in the era of COVID-19. The findings of this study offer practical insights about the various impacts of social media on work life of the employees and how their working lives have changed while working from home in the era of COVID-19. This study also offers suggestions about harnessing the benefits and minimizing the side-effects of social media usage at workplace. Both the employees and the organizations can equally take advantage of this report.

Determining Anxiety Disorder in Health Workers who have received COVID-19 Vaccines: A Cross-Sectional Study at Public Health Centers in Tegal District, Indonesia

BACKGROUND: The COVID-19 pandemic has a major impact on health workers’ mental health. Health workers in Indonesia have received COVID-19 vaccines to get protection against COVID-19 infection and reduce anxiety while on duty. AIM: This study aims to determine anxiety disorder in health workers at public health centers who have received COVID-19 vaccines. METHODS: A cross-sectional study was conducted at six public health centers in Tegal district, Indonesia. Data were collected using questionnaire that given to health workers who had vaccinated COVID-19. Anxiety disorder was determined with generalized anxiety disorder-7 (GAD-7) questionnaire. RESULTS: There were 137 samples who participated in this study, consisted of 83.2% of women and 16.8% of men. The majority of the samples were 30−39 years old (41.6%), married (93.4%), and midwife (44.5%). There were 6.6% of samples had mild anxiety and others were normal (93.4%). CONCLUSION: COVID-19 vaccination program for health workers can reduce anxiety when providing health services. However, assistance is still needed for health workers who have mild anxiety disorder to prevent prolonged symptoms and more severe mental health condition.

Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia

Background

Since COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020, the disease has had an unprecedented impact worldwide. Social media such as Reddit can serve as a resource for enhancing situational awareness, particularly regarding monitoring public attitudes and behavior during the crisis. Insights gained can then be utilized to better understand public attitudes and behaviors during the COVID-19 crisis, and to support communication and health-promotion messaging.

Objective

The aim of this study was to compare public attitudes toward the 2020-2021 COVID-19 pandemic across four predominantly English-speaking countries (the United States, the United Kingdom, Canada, and Australia) using data derived from the social media platform Reddit.

Methods

We utilized a topic modeling natural language processing method (more specifically latent Dirichlet allocation). Topic modeling is a popular unsupervised learning technique that can be used to automatically infer topics (ie, semantically related categories) from a large corpus of text. We derived our data from six country-specific, COVID-19–related subreddits (r/CoronavirusAustralia, r/CoronavirusDownunder, r/CoronavirusCanada, r/CanadaCoronavirus, r/CoronavirusUK, and r/coronavirusus). We used topic modeling methods to investigate and compare topics of concern for each country.

Results

Our consolidated Reddit data set consisted of 84,229 initiating posts and 1,094,853 associated comments collected between February and November 2020 for the United States, the United Kingdom, Canada, and Australia. The volume of posting in COVID-19–related subreddits declined consistently across all four countries during the study period (February 2020 to November 2020). During lockdown events, the volume of posts peaked. The UK and Australian subreddits contained much more evidence-based policy discussion than the US or Canadian subreddits.

Conclusions

This study provides evidence to support the contention that there are key differences between salient topics discussed across the four countries on the Reddit platform. Further, our approach indicates that Reddit data have the potential to provide insights not readily apparent in survey-based approaches.

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

Social Media News Use and COVID-19 Misinformation Engagement: Survey Study

BACKGROUND

Social media is widely used as a source of news and information regarding COVID-19. However, the abundance of misinformation on social media platforms has raised concerns regarding the spreading infodemic. Accordingly, many have questioned the utility and impact of social media news use on users' engagement with (mis)information.

OBJECTIVE

This study offers a conceptual framework for how social media news use influences COVID-19 misinformation engagement. More specifically, we examined how news consumption on social media leads to COVID-19 misinformation sharing by inducing belief in such misinformation. We further explored if the effects of social media news use on COVID-19 misinformation engagement depend on individual differences in cognition and personality traits.

METHODS

We used data from an online survey panel administered by a survey agency (Qualtrics) in Singapore. The survey was conducted in March 2022, and 500 respondents answered the survey. All participants were older than 21 years and provided consent before taking part in the study. We used linear regression, mediation, and moderated mediation analyses to explore the proposed relationships between social media news use, cognitive ability, personality traits, and COVID-19 misinformation belief and sharing intentions.

RESULTS

The results suggested that those who frequently used social media for news consumption were more likely to believe COVID-19 misinformation and share it on social media. Further probing the mechanism suggested that social media news use translated into sharing intent via the perceived accuracy of misinformation. Simply put, social media news users shared COVID-19 misinformation because they believed it to be accurate. We also found that those with high levels of extraversion than those with low levels were more likely to perceive the misinformation to be accurate and share it. Those with high levels of neuroticism and openness than those with low levels were also likely to perceive the misinformation to be accurate. Finally, it was observed that personality traits did not significantly influence misinformation sharing at higher levels of cognitive ability, but low cognitive users largely drove misinformation sharing across personality traits.

CONCLUSIONS

The reliance on social media platforms for news consumption during the COVID-19 pandemic has amplified, with dire consequences for misinformation sharing. This study shows that increased social media news consumption is associated with believing and sharing COVID-19 misinformation, with low cognitive users being the most vulnerable. We offer recommendations to newsmakers, social media moderators, and policymakers toward efforts in limiting COVID-19 misinformation propagation and safeguarding citizens.

Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?

Background

Crowdsourcing is a low-cost, adaptable, and innovative method to collect ideas from numerous contributors with diverse backgrounds. Crowdsourcing from social media like Twitter can be used for generating ideas in a noticeably brief time based on contributions from globally distributed users. The world has been challenged by the COVID-19 pandemic in the last several years. Measures to combat the pandemic continue to evolve worldwide, and ideas and opinions on optimal counteraction strategies are of high interest.

Objective

This study aimed to validate the use of Twitter as a crowdsourcing platform in order to gain an understanding of public opinion on what measures can help to end the COVID-19 pandemic faster.

Methods

This cross-sectional study was conducted during the period from December 22, 2021, to February 4, 2022. Tweets were posted by accounts operated by the authors, asking “How to faster end the COVID-19 pandemic?” and encouraging the viewers to comment on measures that they perceive would be effective to achieve this goal. The ideas from the users' comments were collected and categorized into two major themes – personal and institutional measures. In the final stage of the campaign, a Twitter poll was conducted to get additional comments and to estimate which of the two groups of measures were perceived to be important amongst Twitter users.

Results

The crowdsourcing campaign generated seventeen suggested measures categorized into two major themes (personal and institutional) that received a total of 1,727 endorsements (supporting comments, retweets, and likes). The poll received a total of 325 votes with 58% of votes underscoring the importance of both personal and institutional measures, 20% favoring personal measures, 11% favoring institutional measures, and 11% of the votes given just out of curiosity to see the vote results.

Conclusions

Twitter was utilized successfully for crowdsourcing ideas on strategies how to end the COVID-19 pandemic faster. The results indicate that the Twitter community highly values the significance of both personal responsibility and institutional measures to counteract the pandemic. This study validates the use of Twitter as a primary tool that could be used for crowdsourcing ideas with healthcare significance.

Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis

The impact of the COVID-19 pandemic on public mental health has become increasingly prominent. Therefore, it is of great value to study the spatial-temporal characteristics of public sentiment responses to COVID-19 exposure to improve urban anti-pandemic decision-making and public health resilience. However, the majority of recent studies have focused on the macro scale or large cities, and there is a relative lack of adequate research on the small-city scale in China. To address this lack of research, we conducted a case study of Shaoxing city, proposed a spatial-based pandemic-cognition-sentiment (PCS) conceptual model, and collected microblog check-in data and information on the spatial-temporal trajectory of cases before and after a wave of the COVID-19 pandemic. The natural language algorithm of dictionary-based sentiment analysis (DSA) was used to calculate public sentiment strength. Additionally, local Moran's I, kernel-density analysis, Getis-Ord Gi* and standard deviation ellipse methods were applied to analyze the nonlinear evolution and clustering characteristics of public sentiment spatial-temporal patterns at the small-city scale concerning the pandemic. The results reveal that (1) the characteristics of pandemic spread show contagion diffusion at the micro level and hierarchical diffusion at the macro level, (2) the pandemic has a depressive effect on public sentiment in the center of the outbreak, and (3) the pandemic has a nonlinear gradient negative impact on mood in the surrounding areas. These findings could help propose targeted pandemic prevention policies applying spatial intervention to improve residents' mental health resilience in response to future pandemics.

Impact of social media on public fear, adoption of precautionary behaviors, and compliance with health regulations during COVID-19 pandemic

Social media has become an essential source of information during the coronavirus disease 2019 (COVID-19) pandemic. This study aims to understand social media's effect on the general public's fear, degree of adopting precautionary behaviors, and compliance with health authorities' regulations during the pandemic. A cross-sectional online survey was conducted in Jordan during the early period of COVID-19 pandemic. 827 individuals completed the questionnaire. Factors that had a significant association with increased fear included female gender (OR 2.6, 95% CI: 1.8-3.7), married status (OR 1.9, 95% CI: 1.2-3.4), following medical pages on social media (OR 1.6, 95% CI: 1.04, 2.42), and sharing of COVID-19 information on social media (OR 3.6, 95% CI: 1.8-7.1). The variables that were significantly associated with higher levels of precautionary behaviors were knowledge score (OR 1.2, 95% CI: 1.07-1.3), feeling of fear (OR 2.6, 95% CI: 1.71-3.), and following medical pages on social media (OR 2.8, 95% CI: 1.8-4.24). Regarding compliance with health officials' regulations, social media as a source of information and sharing information were significantly associated with lower odds of compliance with the Ministry of Health's regulations (OR 0.27, 95% CI: 0.13-0.5 and OR 0.46, 95% CI: 0.25-0.8, respectively). Social media is an essential platform for risk communication during pandemics. It plays a positive role in spreading knowledge and promotes certain preventive behaviors among the public. However, it may spread fear and encourage disruptive behaviors, which might be propagated by sharing the pandemic's news.

Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.

Network social capital and health information acquisition

OBJECTIVE

This study examines the associations of network social capital with obtaining health information from health care professionals, the media, and laypeople. We also investigate whether and how the relationship between social capital and health information acquisition differs by personal health literacy. We used a position generator to measure network social capital.

METHODS

We conducted a survey with a nationally representative sample (N = 626) in the United States in April 2014.

RESULTS

Network social capital was positively associated with obtaining health information from health professionals, the media, and laypeople. Also, the associations of social capital with health information acquisition from health professionals were enhanced among those with adequate personal health literacy. However, health literacy did not moderate the relationship between social capital and health information acquisition from the media and laypeople.

CONCLUSION

Social capital may encourage individuals to utilize health information sources. Also, health literacy might reinforce the linkage between social capital and acquiring health information from health professionals.

PRACTICE IMPLICATIONS

Social capital interventions may promote health information acquisition. Also, health professionals should communicate with patients in a patient-centered way so that low-literate individuals easily understand health information. Moreover, a universal precaution approach should be employed.