COVID-19: Fear, quackery, false representations and the law.

Fear, anxiety and even paranoia can proliferate during a pandemic. Such conditions, even when subclinical, tend to be a product of personal and predispositional factors, as well as shared cultural influences, including religious, literary, film, and gaming, all of which can lead to emotional and less than rational responses. They can render people vulnerable to engage in implausible conspiracy theories about the causes of illness and governmental responses to it. They can also lead people to give credence to simplistic and unscientific misrepresentations about medications and devices which are claimed to prevent, treat or cure disease. In turn such vulnerability creates predatory opportunities for the unscrupulous. This article notes the eruption of quackery during the 1889-1892 Russian Flu and the 1918-1920 Spanish Flu and the emergence during 2020 of spurious claims during the COVID-19 pandemic. It identifies consumer protection strategies and interventions formulated during the 2020 pandemic. Using examples from the United States, Japan, Australia and the United Kingdom, it argues that during a pandemic there is a need for three responses by government to the risks posed by conspiracy theories and false representations: calm, scientifically-based messaging from public health authorities; cease and desist warnings directed toward those making extravagant or inappropriate claims; and the taking of assertive and well publicised legal action against individuals and entities that make false representations in order to protect consumers rendered vulnerable by their emotional responses to the phenomenology of the pandemic.

The Nature and Extent of Online Marketing by Big Food and Big Alcohol During the COVID-19 Pandemic in Australia: Content Analysis Study.

BACKGROUND: Emerging evidence demonstrates that obesity is associated with a higher risk of COVID-19 morbidity and mortality. Excessive alcohol consumption and "comfort eating" as coping mechanisms during times of high stress have been shown to further exacerbate mental and physical ill-health. Global examples suggest that unhealthy food and alcohol brands and companies are using the COVID-19 pandemic to further market their products. However, there has been no systematic, in-depth analysis of how "Big Food" and "Big Alcohol" are capitalizing on the COVID-19 pandemic to market their products and brands. OBJECTIVE: We aimed to quantify the extent and nature of online marketing by alcohol and unhealthy food and beverage companies during the COVID-19 pandemic in Australia. METHODS: We conducted a content analysis of all COVID-19-related social media posts made by leading alcohol and unhealthy food and beverage brands (n=42) and their parent companies (n=12) over a 4-month period (February to May 2020) during the COVID-19 pandemic in Australia. RESULTS: Nearly 80% of included brands and all parent companies posted content related to COVID-19 during the 4-month period. Quick service restaurants (QSRs), food and alcohol delivery companies, alcohol brands, and bottle shops were the most active in posting COVID-19-related content. The most common themes for COVID-19-related marketing were isolation activities and community support. Promotion of hygiene and home delivery was also common, particularly for QSRs and alcohol and food delivery companies. Parent companies were more likely to post about corporate social responsibility (CSR) initiatives, such as donations of money and products, and to offer health advice. CONCLUSIONS: This is the first study to show that Big Food and Big Alcohol are incessantly marketing their products and brands on social media platforms using themes related to COVID-19, such as isolation activities and community support. Parent companies are frequently posting about CSR initiatives, such as donations of money and products, thereby creating a fertile environment to loosen current regulation or resist further industry regulation. "COVID-washing" by large alcohol brands, food and beverage brands, and their parent companies is both common and concerning. The need for comprehensive regulations to restrict unhealthy food and alcohol marketing, as recommended by the World Health Organization, is particularly acute in the COVID-19 context and is urgently required to "build back better" in a post-COVID-19 world.

Social Media Use, Unhealthy Lifestyles, and the Risk of Miscarriage Among Pregnant Women During the COVID-19 Pandemic: Prospective Observational Study.

BACKGROUND: The COVID-19 pandemic has resulted in changes to normal life and disrupted social and economic function worldwide. However, little is known about the impact of social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women during the COVID-19 pandemic. OBJECTIVE: This study aims to assess the association between social media use, unhealthy lifestyles, and the risk of miscarriage among pregnant women in the early stage of the COVID-19 pandemic in China. METHODS: In this prospective cohort study, 456 singleton pregnant women in mainland China were recruited during January and February 2020. Sociodemographic characteristics, history of previous health, social media use, and current lifestyles were collected at baseline, and we followed up about the occurrence of miscarriage. Log-binomial regression models were used to estimate the risk ratios (RRs) of miscarriage for women with different exposures to COVID-19-specific information. RESULTS: Among all the 456 pregnant women, there were 82 (18.0%) who did no physical activities, 82 (18.0%) with inadequate dietary diversity, 174 (38.2%) with poor sleep quality, and 54 (11.8%) spending >3 hours on reading COVID-19 news per day. Women with excessive media use (>3 hours) were more likely to be previously pregnant (P=.03), have no physical activity (P=.003), have inadequate dietary diversity (P=.03), and have poor sleep quality (P<.001). The prevalence of miscarriage was 16.0% (n=73; 95% CI 12.6%-19.4%). Compared with women who spent 0.5-2 hours (25/247, 10.1%) on reading COVID-19 news per day, miscarriage prevalence in women who spent <0.5 hours (5/23, 21.7%), 2-3 hours (26/132, 19.7%), and >3 hours (17/54, 31.5%) was higher (P<.001). Miscarriage prevalence was also higher in pregnant women with poor sleep quality (39/174, 22.4% vs 34/282, 12.1%; P=.003) and a high education level (66/368, 17.9% vs 7/88, 8.0%; P=.02). In the multivariable model, poor sleep quality (adjusted RR 2.06, 95% CI 1.24-3.44; P=.006), 2-3 hours of media use daily (adjusted RR 1.74, 95% CI 1.02-2.97; P=.04), and >3 hours of media use daily (adjusted RR 2.56, 95% CI 1.43-4.59; P=.002) were associated with miscarriage. In the sensitivity analysis, results were still stable. CONCLUSIONS: Pregnant women with excessive media use were more likely to have no physical activity, inadequate dietary diversity, and poor sleep quality. Excessive media use and poor sleep quality were associated with a higher risk of miscarriage. Our findings highlight the importance of healthy lifestyles during the COVID-19 pandemic.

Knowledge About COVID-19 in Brazil: Cross-Sectional Web-Based Study.

BACKGROUND: COVID-19 is a highly transmissible illness caused by SARS-CoV-2. The disease has affected more than 200 countries, and the measures that have been implemented to combat its spread, as there is still no vaccine or definitive medication, have been based on supportive interventions and drug repositioning. Brazil, the largest country in South America, has had more than 140,000 recorded deaths and is one of the most affected countries. Despite the extensive quantity of scientifically recognized information, there are still conflicting discussions on how best to face the disease and the virus, especially with regard to social distancing, preventive methods, and the use of medications. OBJECTIVE: The main purpose of this study is to evaluate the Brazilian population's basic knowledge about COVID-19 to demonstrate how Brazilians are managing to identify scientifically proven information. METHODS: A cross-sectional study design was used. An original online questionnaire survey was administered from June 16 to August 21, 2020, across all five different geopolitical regions of the country (ie, the North, Northeast, Center-West, Southeast, and South). The questionnaire was comprised of questions about basic aspects of COVID-19, such as the related symptoms, conduct that should be followed when suspected of infection, risk groups, prevention, transmission, and social distancing. The wrong questionnaire response alternatives were taken from the fake news combat website of the Brazilian Ministry of Health. Participants (aged ≥18 years) were recruited through social networking platforms, including Facebook, WhatsApp, and Twitter. The mean distributions, frequencies, and similarities or dissimilarities between the responses for the different variables of the study were evaluated. The significance level for all statistical tests was less than .05. RESULTS: A total of 4180 valid responses representative of all the states and regions of Brazil were recorded. Most respondents had good knowledge about COVID-19, getting an average of 86.59% of the total score with regard to the basic aspects of the disease. The region, education level, age, sex, and social condition had a significant association (P<.001) with knowledge about the disease, which meant that women, the young, those with higher education levels, nonrecipients of social assistance, and more economically and socially developed regions had more correct answers. CONCLUSIONS: Overall, Brazilians with social media access have a good level of basic knowledge about COVID-19 but with differences depending on the analyzed subgroup. Due to the limitation of the platform used in carrying out the study, care should be taken when generalizing the study findings to populations with less education or who are not used to accessing social networking platforms.

Associations Between the Perceived Severity of the COVID-19 Pandemic, Cyberchondria, Depression, Anxiety, Stress, and Lockdown Experience: Cross-sectional Survey Study.

BACKGROUND: The outbreak of the COVID-19 pandemic has caused great panic among the public, with many people suffering from adverse stress reactions. To control the spread of the pandemic, governments in many countries have imposed lockdown policies. In this unique pandemic context, people can obtain information about pandemic dynamics on the internet. However, searching for health-related information on the internet frequently increases the possibility of individuals being troubled by the information that they find, and consequently, experiencing symptoms of cyberchondria. OBJECTIVE: We aimed to examine the relationships between people's perceived severity of the COVID-19 pandemic and their depression, anxiety, and stress to explore the role of cyberchondria, which, in these relationship mechanisms, is closely related to using the internet. In addition, we also examined the moderating role of lockdown experiences. METHODS: In February 2020, a total of 486 participants were recruited through a web-based platform from areas in China with a large number of infections. We used questionnaires to measure participants' perceived severity of the COVID-19 pandemic, to measure the severity of their cyberchondria, depression, anxiety, and stress symptoms, and to assess their lockdown experiences. Confirmatory factor analysis, exploratory factor analysis, common method bias, descriptive statistical analysis, and correlation analysis were performed, and moderated mediation models were examined. RESULTS: There was a positive association between perceived severity of the COVID-19 pandemic and depression (ß=0.36, t=8.51, P<.001), anxiety (ß=0.41, t=9.84, P<.001), and stress (ß=0.46, t=11.45, P<.001), which were mediated by cyberchondria (ß=0.36, t=8.59, P<.001). The direct effects of perceived severity of the COVID-19 pandemic on anxiety (ß=0.07, t=2.01, P=.045) and stress (ß=0.09, t=2.75, P=.006) and the indirect effects of cyberchondria on depression (ß=0.10, t=2.59, P=.009) and anxiety (ß=0.10, t=2.50, P=.01) were moderated by lockdown experience. CONCLUSIONS: The higher the perceived severity of the COVID-19 pandemic, the more serious individuals' symptoms of depression, anxiety, and stress. In addition, the associations were partially mediated by cyberchondria. Individuals with higher perceived severity of the COVID-19 pandemic were more likely to develop cyberchondria, which aggravated individuals' depression, anxiety, and stress symptoms. Negative lockdown experiences exacerbated the COVID-19 pandemic's impact on mental health.

Natural Language Processing Insight into LGBTQ+ Youth Mental Health During the COVID-19 Pandemic: Longitudinal Content Analysis of Anxiety-Provoking Topics and Trends in Emotion in LGBTeens Microcommunity Subreddit.

BACKGROUND: Widespread fear surrounding COVID-19, coupled with physical and social distancing orders, has caused severe adverse mental health outcomes. Little is known, however, about how the COVID-19 crisis has impacted LGBTQ+ youth, who disproportionately experienced a high rate of adverse mental health outcomes before the COVID-19 pandemic. OBJECTIVE: We aimed to address this knowledge gap by harnessing natural language processing methodologies to investigate the evolution of conversation topics in the most popular subreddit for LGBTQ+ youth. METHODS: We generated a data set of all r/LGBTeens subreddit posts (n=39,389) between January 1, 2020 and February 1, 2021 and analyzed meaningful trends in anxiety, anger, and sadness in the posts. Because the distribution of anxiety before widespread social distancing orders was meaningfully different from the distribution after (P<.001), we employed latent Dirichlet allocation to examine topics that provoked this shift in anxiety. RESULTS: We did not find any differences in LGBTQ+ youth anger and sadness before and after government-mandated social distancing; however, anxiety increased significantly (P<.001). Further analysis revealed a list of 10 anxiety-provoking topics discussed during the pandemic: attraction to a friend, coming out, coming out to family, discrimination, education, exploring sexuality, gender pronouns, love and relationship advice, starting a new relationship, and struggling with mental health. CONCLUSIONS: During the COVID-19 pandemic, LGBTQ+ teens increased their reliance on anonymous discussion forums when discussing anxiety-provoking topics. LGBTQ+ teens likely perceived anonymous forums as safe spaces for discussing lifestyle stressors during COVID-19 disruptions (eg, school closures). The list of prevalent anxiety-provoking topics in LGBTQ+ teens' anonymous discussions can inform future mental health interventions in LGBTQ+ youth.

Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data.

BACKGROUND: Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. OBJECTIVE: This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases. METHODS: We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series. RESULTS: The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days. CONCLUSIONS: These findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics.

Texas Public Agencies' Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach.

BACKGROUND: The ongoing COVID-19 pandemic is characterized by different morbidity and mortality rates across different states, cities, rural areas, and diverse neighborhoods. The absence of a national strategy for battling the pandemic also leaves state and local governments responsible for creating their own response strategies and policies. OBJECTIVE: This study examines the content of COVID-19-related tweets posted by public health agencies in Texas and how content characteristics can predict the level of public engagement. METHODS: All COVID-19-related tweets (N=7269) posted by Texas public agencies during the first 6 months of 2020 were classified in terms of each tweet's functions (whether the tweet provides information, promotes action, or builds community), the preventative measures mentioned, and the health beliefs discussed, by using natural language processing. Hierarchical linear regressions were conducted to explore how tweet content predicted public engagement. RESULTS: The information function was the most prominent function, followed by the action or community functions. Beliefs regarding susceptibility, severity, and benefits were the most frequently covered health beliefs. Tweets that served the information or action functions were more likely to be retweeted, while tweets that served the action and community functions were more likely to be liked. Tweets that provided susceptibility information resulted in the most public engagement in terms of the number of retweets and likes. CONCLUSIONS: Public health agencies should continue to use Twitter to disseminate information, promote action, and build communities. They need to improve their strategies for designing social media messages about the benefits of disease prevention behaviors and audiences' self-efficacy.

"Thought I'd Share First" and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study.

BACKGROUND: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. OBJECTIVE: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. METHODS: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. RESULTS: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to nonmisinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. CONCLUSIONS: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will need to target evolving conspiracy theories and the new facets of each as they become incorporated.

Using Social Media to Predict Food Deserts in the United States: Infodemiology Study of Tweets.

BACKGROUND: The issue of food insecurity is becoming increasingly important to public health practitioners because of the adverse health outcomes and underlying racial disparities associated with insufficient access to healthy foods. Prior research has used data sources such as surveys, geographic information systems, and food store assessments to identify regions classified as food deserts but perhaps the individuals in these regions unknowingly provide their own accounts of food consumption and food insecurity through social media. Social media data have proved useful in answering questions related to public health; therefore, these data are a rich source for identifying food deserts in the United States. OBJECTIVE: The aim of this study was to develop, from geotagged Twitter data, a predictive model for the identification of food deserts in the United States using the linguistic constructs found in food-related tweets. METHODS: Twitter's streaming application programming interface was used to collect a random 1% sample of public geolocated tweets across 25 major cities from March 2020 to December 2020. A total of 60,174 geolocated food-related tweets were collected across the 25 cities. Each geolocated tweet was mapped to its respective census tract using point-to-polygon mapping, which allowed us to develop census tract-level features derived from the linguistic constructs found in food-related tweets, such as tweet sentiment and average nutritional value of foods mentioned in the tweets. These features were then used to examine the associations between food desert status and the food ingestion language and sentiment of tweets in a census tract and to determine whether food-related tweets can be used to infer census tract-level food desert status. RESULTS: We found associations between a census tract being classified as a food desert and an increase in the number of tweets in a census tract that mentioned unhealthy foods (P=.03), including foods high in cholesterol (P=.02) or low in key nutrients such as potassium (P=.01). We also found an association between a census tract being classified as a food desert and an increase in the proportion of tweets that mentioned healthy foods (P=.03) and fast-food restaurants (P=.01) with positive sentiment. In addition, we found that including food ingestion language derived from tweets in classification models that predict food desert status improves model performance compared with baseline models that only include socioeconomic characteristics. CONCLUSIONS: Social media data have been increasingly used to answer questions related to health and well-being. Using Twitter data, we found that food-related tweets can be used to develop models for predicting census tract food desert status with high accuracy and improve over baseline models. Food ingestion language found in tweets, such as census tract-level measures of food sentiment and healthiness, are associated with census tract-level food desert status.

Violence against girls during COVID-19 pandemic and associated factors in Gondar city, North West Ethiopia.

In Ethiopia, the magnitude of violence against girls during COVID-19 in the study area is not known. Therefore, this study aimed to assess the violence and associated factors during COVID-19 pandemic among Gondar city secondary school girls in North West Ethiopia. An institution-based cross-sectional study was conducted from January to February 2021. Data were collected from four public and two private Gondar city secondary schools. Investigators used stratified simple random sampling to select participants and the investigators used roster of the students at selected schools. Investigators collected the data using self-reported history of experiencing violence (victimisation). Investigators analysed data using descriptive statistics and multivariable logistic regression. Investigators invited a total of 371 sampled female students to complete self-administered questionnaires. The proportion of girls who experienced violence was 42.05% and psychological violence was the highest form of violence. Having a father who attended informal education (AOR = 1.95, 95% CI 1.08-3.51), ever use of social media 1.65 (AOR = 1.65, 95% CI 1.02-2.69), ever watching sexually explicit material (AOR = 2.04, 95% CI 1.24-3.36) and use of a substance (AOR = 1.92, 95% CI 1.17-3.15) were significantly associated variables with violence. Almost for every five girls, more than two of them experienced violence during the COVID-19 lockdown. The prevalence of violence might be under reported due to desirability bias. Therefore, it is better to create awareness towards violence among substance users, fathers with informal education and social media including user females.

The intensive use of the internet by children and adolescents in the context of COVID-19 and the risks for self-inflicted violence. / O uso intensivo da internet por crianças e adolescentes no contexto da COVID-19 e os riscos para violências autoinflingidas.

This essay aimed to discuss the implications of social isolation due to the COVID-19 pandemic for the intensive use of the internet among children and adolescents and its possible consequences for the practice of self-inflicted violence. We briefly discussed the anxiogenic potential and the reproduction of a "global fear" that are consolidated with the massive and unmediated exposure of the content consumed, which can increase the vulnerabilities to stress and suicidal ideas. We centered our debate on "recreational" practices, called "challenges" with self-harm power, carried out by teenagers on the YouTube website. This practice has been shown to increase with the social isolation measures. Our reflection on these risks builds on the theoretical perspective of digital sociability, and its implications for the internet-mediated interactions of adolescents.

O presente ensaio busca discutir as implicações do isolamento social devido à pandemia do COVID-19 para o uso intensivo da internet entre crianças e adolescentes e suas possíveis consequências para a prática de violências autoinflingidas. Discutimos brevemente o potencial ansiogênico e a reprodução de um "medo global" que se consolidam com a exposição maciça e sem mediação dos conteúdos consumidos, que podem aumentar as vulnerabilidades para estresse e ideações suicidas. Centramos nosso debate sobre práticas "recreativas", denominadas de "desafios" com poder autolesivo, realizados por adolescentes no site Youtube. Essa prática revelou-se crescente a partir das medidas de isolamento social. Nossa reflexão sobre esses riscos é feita a partir da perspectiva teórica da sociabilidade digital, e suas implicações nas interações de adolescentes mediadas pela internet.

Nurses' use of social media during the COVID-19 pandemic-A scoping review.

BACKGROUND: During the COVID-19 pandemic, nurses stand in an unknown situation while facing continuous news feeds. Social media is a ubiquitous tool to gain and share reliable knowledge and experiences regarding COVID-19. The article aims to explore how nurses use social media in relation to the COVID-19 pandemic. METHOD: A scoping review inspired by Arksey and O'Mally was conducted by searches in Medline, CINAHL, Academic Search Complete and Web of Sciences. Empirical research studies investigating nurses' use of social media in relation to COVID-19 were included. Exclusion criteria were: Literature reviews, articles in languages other than English, articles about E-health, and articles investigating healthcare professionals without specification of nurses included. Articles, published in January-November 2020, were included and analysed through a thematic analysis. The PRISMA-ScR checklist was used. RESULTS: Most of the eleven included studies were cross-sectional surveys, conducted in developing countries, and had neither social media nor nurses as their main focus of interest. Three themes were identified: 'Social media as a knowledge node', 'Social media functioned as profession-promoting channels' and 'Social media as a disciplinary tool'. Nurses used social media as channels to gain and share information about COVID-19, and to support each other by highlighting the need for training and changes in delivery of care and redeployment. Further, social media functioned as profession-promoting channels partly sharing heroic self-representations and acknowledgment of frontline persons in the pandemic, partly by displaying critical working conditions. Finally, nurses used social media to educate people to perform the 'right 'COVID-19' behaviours in society. CONCLUSION: This review provided snapshots of nurses' uses of social media from various regions in the world, but revealed a need for studies from further countries and continents. The study calls for further multi-methodological and in depth qualitative research, including theoretically framed studies, with a specific focus on the uses of social media among nurses during the pandemic.

Topical analysis of migration coverage during lockdown in India by mainstream print media.

Implementing countrywide lockdown measures in India, from March 2020 to May 2020 was a major step to deal with the COVID -19 pandemic crisis. The decision of country lockdown adversely affected the urban migrant population, and a large section of them was compelled to move out of the urban areas to their native places. The reverse migration garnered widespread media attention and coverage in electronic as well as print media. The present study focuses on the coverage of the issue by print media using descriptive natural language text mining. The study uses topic modelling, clustering, and sentiment analysis to examine the articles on migration issues during the lockdown period published in two leading English newspapers in India- The Times of India and The Hindu. The sentiment analysis results indicate that the majority of articles have neutral sentiment while very few articles show high negative or positive polarity. Descriptive topic modelling results show that transport, food security, special services, and employment with migration and migrants are the majorly covered topics after employing Bag of Words and TF-IDF models. Clustering is performed to group the article titles based on similar traits using agglomerative hierarchical clustering.

The impact of risk perceptions and belief in conspiracy theories on COVID-19 pandemic-related behaviours.

Throughout the COVID-19 pandemic, conspiracy theories about the virus spread rapidly, and whilst governments across the globe put in place different restrictions and guidelines to contain the pandemic, these were not universally adhered to. This research examined the association between pandemic related risk perceptions, belief in conspiracy theories, and compliance with COVID-19 public guidelines amongst a UK sample (n = 368). Participants rated their level of concern for a series of potential risks during the pandemic (to the economy, personal health, freedom, media integrity and health risk to others). Participants also rated their level of belief in different conspiracy theories and self-reported their behaviour during the first UK lockdown. Mediational analyses showed that stronger belief in conspiracy theories was associated with perceptions of lower risk to health and higher risk to the economy and freedom, which in turn were associated with lower compliance with COVID-19 related governmental guidelines. Perception of information transparency risks did not mediate the association between belief in conspiracy theories and compliant behaviours. These results highlight the key role that risk perception may play in translating belief in conspiracy theories into low compliance with governmental COVID-19 related guidelines. Our findings suggest new patterns with respect to the relationship between conspiracy theory adherence and salience of different risk perceptions amidst the pandemic, which could have implications for the development of public health messaging and communication interventions.

COVID-19 increased censorship circumvention and access to sensitive topics in China.

Crisis motivates people to track news closely, and this increased engagement can expose individuals to politically sensitive information unrelated to the initial crisis. We use the case of the COVID-19 outbreak in China to examine how crisis affects information seeking in countries that normally exert significant control over access to media. The crisis spurred censorship circumvention and access to international news and political content on websites blocked in China. Once individuals circumvented censorship, they not only received more information about the crisis itself but also accessed unrelated information that the regime has long censored. Using comparisons to democratic and other authoritarian countries also affected by early outbreaks, the findings suggest that people blocked from accessing information most of the time might disproportionately and collectively access that long-hidden information during a crisis. Evaluations resulting from this access, negative or positive for a government, might draw on both current events and censored history.

Quantifying the Influence of Delay in Opinion Transmission of COVID-19 Information Propagation: Modeling Study.

BACKGROUND: In a fast-evolving public health crisis such as the COVID-19 pandemic, multiple pieces of relevant information can be posted sequentially on a social media platform. The interval between subsequent posting times may have a different impact on the transmission and cross-propagation of the old and new information that results in a different peak value and a final size of forwarding users of the new information, depending on the content correlation and whether the new information is posted during the outbreak or quasi-steady-state phase of the old information. OBJECTIVE: This study aims to help in designing effective communication strategies to ensure information is delivered to the maximal number of users. METHODS: We developed and analyzed two classes of susceptible-forwarding-immune information propagation models with delay in transmission to describe the cross-propagation process of relevant information. A total of 28,661 retweets of typical information were posted frequently by each opinion leader related to COVID-19 with high influence (data acquisition up to February 19, 2020). The information was processed into discrete points with a frequency of 10 minutes, and the real data were fitted by the model numerical simulation. Furthermore, the influence of parameters on information dissemination and the design of a publishing strategy were analyzed. RESULTS: The current epidemic outbreak situation, epidemic prevention, and other related authoritative information cannot be timely and effectively browsed by the public. The ingenious use of information release intervals can effectively enhance the interaction between information and realize the effective diffusion of information. We parameterized our models using real data from Sina Microblog and used the parameterized models to define and evaluate mutual attractiveness indexes, and we used these indexes and parameter sensitivity analyses to inform optimal strategies for new information to be effectively propagated in the microblog. The results of the parameter analysis showed that using different attractiveness indexes as the key parameters can control the information transmission with different release intervals, so it is considered as a key link in the design of an information communication strategy. At the same time, the dynamic process of information was analyzed through index evaluation. CONCLUSIONS: Our model can carry out an accurate numerical simulation of information at different release intervals and achieve a dynamic evaluation of information transmission by constructing an indicator system so as to provide theoretical support and strategic suggestions for government decision making. This study optimizes information posting strategies to maximize communication efforts for delivering key public health messages to the public for better outcomes of public health emergency management.

Using Tweets to Understand How COVID-19-Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study.

BACKGROUND: The emergence of SARS-CoV-2 (ie, COVID-19) has given rise to a global pandemic affecting 215 countries and over 40 million people as of October 2020. Meanwhile, we are also experiencing an infodemic induced by the overabundance of information, some accurate and some inaccurate, spreading rapidly across social media platforms. Social media has arguably shifted the information acquisition and dissemination of a considerably large population of internet users toward higher interactivities. OBJECTIVE: This study aimed to investigate COVID-19-related health beliefs on one of the mainstream social media platforms, Twitter, as well as potential impacting factors associated with fluctuations in health beliefs on social media. METHODS: We used COVID-19-related posts from the mainstream social media platform Twitter to monitor health beliefs. A total of 92,687,660 tweets corresponding to 8,967,986 unique users from January 6 to June 21, 2020, were retrieved. To quantify health beliefs, we employed the health belief model (HBM) with four core constructs: perceived susceptibility, perceived severity, perceived benefits, and perceived barriers. We utilized natural language processing and machine learning techniques to automate the process of judging the conformity of each tweet with each of the four HBM constructs. A total of 5000 tweets were manually annotated for training the machine learning architectures. RESULTS: The machine learning classifiers yielded areas under the receiver operating characteristic curves over 0.86 for the classification of all four HBM constructs. Our analyses revealed a basic reproduction number R0 of 7.62 for trends in the number of Twitter users posting health belief-related content over the study period. The fluctuations in the number of health belief-related tweets could reflect dynamics in case and death statistics, systematic interventions, and public events. Specifically, we observed that scientific events, such as scientific publications, and nonscientific events, such as politicians' speeches, were comparable in their ability to influence health belief trends on social media through a Kruskal-Wallis test (P=.78 and P=.92 for perceived benefits and perceived barriers, respectively). CONCLUSIONS: As an analogy of the classic epidemiology model where an infection is considered to be spreading in a population with an R0 greater than 1, we found that the number of users tweeting about COVID-19 health beliefs was amplifying in an epidemic manner and could partially intensify the infodemic. It is "unhealthy" that both scientific and nonscientific events constitute no disparity in impacting the health belief trends on Twitter, since nonscientific events, such as politicians' speeches, might not be endorsed by substantial evidence and could sometimes be misleading.

Loss of childcare and classroom teaching during the Covid-19-related lockdown in spring 2020: A longitudinal study on consequences on leisure behavior and schoolwork at home.

AIM: In spring 2020, the first Covid-19-related lockdown included the closing of kindergartens and schools. Home schooling, the lack of social contacts with peers and the care of the children at home posed an enormous challenge for many families. METHODS: The present study investigated the leisure behavior of 285 one- to 10-year-old German children at two time points (t1 and t2) during the Covid-19-related lockdown in spring 2020. In the subsample of primary school children (n = 102), we also explored children's attitudes towards schoolwork at home. Analyses focused on the change of behavior from t1 to t2, on differences in these changes depending on socio-economic status (SES), and on associations of behavior with SES, the number of children at home, and the frequency of receiving learning materials from school. RESULTS: While the frequency of playing outside increased significantly from t1 to t2, the frequency of handicrafts, playing board games, indoor sports, and motivation to do schoolwork decreased. The observed changes between t1 and t2 did not differ depending on SES. However, a lower SES was associated with higher media use, less outdoor activity, and (though only marginally significant) a reduced time doing schoolwork and a reduced ability to concentrate on schoolwork at t1. In households with more children, children played outside more often, but were read to less frequently and (though only marginally significant) watched movies and series less frequently. Children receiving learning materials from school on a regular basis spent significantly more time doing schoolwork at home than children receiving materials only irregularly. CONCLUSIONS: A continuing loss of childcare in day-care facilities and schools entails the danger of declining education in the form of (inter)active indoor activities and schoolwork.