Public perception of the appropriateness of COVID-19 management strategies and level of disturbances in daily activities: A focus on educational level.

BACKGROUND: This study investigated the association between public perception of the appropriateness of management strategies implemented during the COVID-19 pandemic and the level of disturbances in daily activities reported by the general population. METHODS: This cross-sectional study used Korea Community Health Survey conducted from August to November 2020. Public perception of COVID-19 management strategies included those implemented by the government (central, city or provincial, and administrative districts), the mass media, regional medical institutions, and neighbors. The subjective level of disturbances in daily activities was measured using a 0-100 numeric rating scale developed by Korea Disease Control and Prevention Agency. Multivariable linear regression analysis was used. A subgroup analysis was conducted based on education level. RESULTS: The present study analyzed 211,353 participants. Compared to individuals who perceived that the management strategies implemented during the pandemic was 'highly appropriate,' those who reported 'mediocre appropriateness' (ß: -1.96, p-value: <0.001) or 'low appropriateness' (ß: -3.60, p-value: 0.010) reported higher levels of subjective disturbances. The appropriateness of measures implemented by the mass media was associated with levels of subjective disturbances felt by individuals of lower education with statistical significance, whereas that applied by the mass media and the government were important in those with higher education. CONCLUSIONS: The findings suggest the importance of public perception of management strategies when implementing containment policies and minimizing its disturbances on daily lives is essential.

Understanding public perceptions in social media responses to posts about acute severe hepatitis of unknown etiology in Indonesia: a qualitative study.

BACKGROUND: Acute Severe Hepatitis of Unknown Etiology (ASHUE) emerged as a new global outbreak in Indonesia early May 2022, coinciding with the COVID-19 pandemic. This study aimed to understand public reactions and responses to the emergence of ASHUE Indonesia and to Government-led disease prevention responses. Understanding how the public perceived government-led preventive messaging about the hepatitis outbreak is crucial to controlling viral spread - particularly given the rapid and unforeseen emergence of ASHUE coincided with COVID-19 and public trust in the Indonesian Government to manage health outbreaks was already tenuous. METHODS: Social media users' responses to information disseminated via Facebook, YouTube, and Twitter were analyzed to understand public perceptions about ASHUE outbreak and their attitudes toward Government-led prevention measures. Data were extracted on a daily basis from 1st May 2022 to 30th May 2022 and analyzed manually. We inductively generated the codes, from which we formed a construct and then grouped to identify themes. RESULTS: A total of 137 response comments collected from 3 social medial platforms were analyzed. Of these, 64 were from Facebook, 57 were from YouTube, and 16 were from Twitter. We identified 5 main themes, including (1) disbelief in the existence of the infection; (2) suspicion about a potential new business after COVID-19; (3) suspicion that COVID-19 vaccine(s) are the cause; (4) religion-related fatalism and (5) trust in government measures. CONCLUSIONS: The findings advance knowledge about public perceptions, reactions and attitudes towards the emergence of ASHUE and the efficacy of disease countermeasures. The knowledge from this study will provide an understanding of why disease prevention measures might not be followed. It can be used to develop public awareness programs in Indonesia about both the ASHUE and its possible consequences and the available healthcare support.

Understanding and managing pandemic-related panic buying.

Pandemics are associated with panic buying (PB) of groceries and other supplies. During the COVID-19 pandemic, community leaders expressed frustration and bewilderment about PB. Psychological explanatory concepts, including those from social learning theory and the concept of the behavioral immune system, along with recent research, suggests the following account of pandemic-related PB. PB arises when people are told to go into self-isolation as part of pandemic containment interventions. Empirically, episodes of PB typically last 7-10 days and are likely initiated by highly fearful people. PB by an anxious minority of shoppers leads to fear contagion among other shoppers, amplified by widespread dissemination, via social media, of images and videos of PB and empty shelves in stores. Thus, a snow-balling effect arises where fear of scarcity creates real but short-term scarcity. People who are highly frightened of infection tend to have heightened disgust proneness. Toilet paper is a means of escaping disgust stimuli, and for this and other reasons, toilet paper became a target of PB for people frightened of contracting COVID-19. Exploitative or selfish over-purchasing also occurred, motivated by "dark" (e.g., psychopathic) personality traits. "Don't panic!" messages from community leaders were ineffective or counter-productive. Alternative forms of messaging are discussed.

Understanding COVID-19 vaccine hesitancy in Malaysia: Public perception, knowledge, and acceptance.

BACKGROUND: Vaccine hesitancy has been around since the introduction of smallpox vaccine. Vaccine hesitancy has become more intense due to the rise of vaccine information in social media and mass adult vaccination during COVID-19 pandemic. This study investigated knowledge, perception, and reasons for rejection of the COVID-19 vaccine among Malaysian adults who refused to get free COVID-19 vaccination. METHODS: An online cross-sectional survey using an embedded mixed-method study [QUAN(quali)] was conducted among Malaysian adults. The quantitative section consisted of a 49-item questionnaire, whereas the qualitative sections consisted of two open-ended questions (1) "Please state your reason why you have not registered or have no intention to register at all for COVID-19 vaccines?" and (2) "Please tell us if you have any suggestions for improvement about COVID-19 vaccine delivery". Data from respondents who were not willing to get vaccination were extracted from the overall data and further analyzed in this paper. RESULT: Sixty-one adults completed the online open-ended survey with a mean age of 34.28 years (SD = 10.30). Among factors that influenced them to get vaccinated was information on vaccine effectiveness (39.3%), death due to COVID-19 (37.7%), and recommendations from the Ministry of Health (36.1%). Most of the respondents (77.0%) were knowledgeable about vaccines, with half having high-perceived risks (52.5%) to COVID-19. While 55.7% and 52.5% had, high perceived barriers and benefits to COVID-19 vaccines respectively. The reasons for vaccine rejections included vaccine safety, indecisiveness, underlying medical conditions, herd immunity, non-transparent data, and use of traditional or complementary medicine. CONCLUSION: The study explored the multitude factors that drive perception, acceptance, and rejection. The qualitative approach with a small sample size provided more data point for interpretations and allowed participants to express themselves. This is important to develop strategies to create public awareness on vaccines not just for COVID-19 but any infectious diseases that can be curbed through vaccination.

Public Perception Before and After COVID-19 Vaccine Pass for the Unvaccinated to Eat Alone: Social Media Data Analytics.

This study was conducted to compare the trends of public perception in South Korea about the vaccine pass requiring the unvaccinated to eat alone during the COVID-19 crisis. Data were collected via Text mining; frequency, association, and sentiment analysis using the social big data analysis service, (known as "Some-Trend"), 2 months before and after December 16, 2021, when the vaccine pass was announced. The total number of search results was 4899 occurrences of the keywords using "eating alone" and "Hon-bab" (Korean abbreviation for eating alone). During the week of December 16, the frequency was the highest (770 occurrences). Compared to the weeks before the announcement sentiment analysis shows that words including "Reject," "Discrimination," and "Uncomfortable," among others, either newly appeared or increased in frequency. And also, the percentage of positive words decreased from 54.5% to 34% and that of negative words increased from 30.2% to 43.3%. The introduction of the vaccine pass has raised negative public interest, particularly regarding the policy of unvaccinated people forcefully restricted to eat alone. Accordingly, this study showed that the vaccine policy had not gain positive perception of the public.

Canadian public perceptions and experiences with information during the COVID-19 pandemic: strategies to optimize future risk communications.

BACKGROUND: The COVID-19 pandemic accelerated the spread of misinformation worldwide. The purpose of this study was to explore perceptions of misinformation and preferred sources of obtaining COVID-19 information from those living in Canada. In particular, we sought to explore the perceptions of East Asian individuals in Canada, who experienced stigma related to COVID-19 messaging. METHODS: We conducted a qualitative thematic analysis study. Interviews were offered in English, Mandarin and Cantonese. Interviewers probed for domains related to knowledge about COVID-19, preferred sources of information, perceived barriers and facilitators of misinformation, and preferences for communication during a health emergency. Interviews were recorded, translated, transcribed verbatim and analyzed using a framework approach. Transcripts were independently double-coded until > 60% agreement was reached. This study received research ethics approval. RESULTS: Fifty-five interviews were conducted. The majority of participants were women (67%); median age was 52 years. 55% of participants were of East-Asian descent. Participants obtained information about COVID-19 from diverse English and non-English sources including news media, government agencies or representatives, social media, and personal networks. Challenges to seeking and understanding information included: encountering misinformation, making sense of evolving or conflicting public health guidance, and limited information on topics of interest. 65% of participants reported encountering COVID-19  misinformation. East Asian participants called on government officials to champion messaging to reduce stigmatizing and racist rhetoric and highlighted the importance of having accessible, non-English language information sources. Participants provided recommendations for future public health communications guidance during health emergencies, including preferences for message content, information messengers, dissemination platforms and format of messages. Almost all participants preferred receiving information from the Canadian government and found it helpful to utilize various mediums and platforms such as social media and news media for future risk communication, urging for consistency across all platforms. CONCLUSIONS: We provide insights on Canadian experiences navigating COVID-19 information, where more than half perceived encountering misinformation on platforms when seeking COVID-19 information . We provide recommendations to inform public health communications during future health emergencies.

Priming COVID-19's consequences can increase support for investments in public health.

Can messaging that emphasizes the costs of COVID-19 increase popular support for more proactive public health policies? People who experience disasters often become more supportive of policies to address their underlying causes, and the pandemic may have similar spillover effects for public opinion. To test this idea, the study implements a survey experiment in Italy, Germany, and the United States in which half of the respondents were randomly assigned to a prime about the impact of the pandemic prior to answering questions about their support for public health policies. The results show that respondents who received the prime became more favorable toward increased government spending on domestic and foreign public health programs alike. These treatment effects were consistent across countries, across two different surveys in the United States conducted at different points in time, and across partisan subgroups. However, the treatment did not consistently increase support for more active and intrusive government policies to address specific public health challenges like smoking or HIV/AIDS. The results suggest that public health advocates may benefit from messaging that connects COVID-19 to the need for public health funding beyond the context of the pandemic.

On order and disorder during the COVID-19 pandemic.

In this paper, we analyse the conditions under which the COVID-19 pandemic will lead either to social order (adherence to measures put in place by authorities to control the pandemic) or to social disorder (resistance to such measures and the emergence of open conflict). Using examples from different countries (principally the United Kingdom, the United States, and France), we first isolate three factors which determine whether people accept or reject control measures. These are the historical context of state-public relations, the nature of leadership during the pandemic and procedural justice in the development and operation of these measures. Second, we analyse the way the crisis is policed and how forms of policing determine whether dissent will escalate into open conflict. We conclude by considering the prospects for order/disorder as the pandemic unfolds.

Evolution of Public Attitudes and Opinions Regarding COVID-19 Vaccination During the Vaccine Campaign in China: Year-Long Infodemiology Study of Weibo Posts.

BACKGROUND: Monitoring people's perspectives on the COVID-19 vaccine is crucial for understanding public vaccination hesitancy and developing effective, targeted vaccine promotion strategies. Although this is widely recognized, studies on the evolution of public opinion over the course of an actual vaccination campaign are rare. OBJECTIVE: We aimed to track the evolution of public opinion and sentiment toward COVID-19 vaccines in online discussions over an entire vaccination campaign. Moreover, we aimed to reveal the pattern of gender differences in attitudes and perceptions toward vaccination. METHODS: We collected COVID-19 vaccine-related posts by the general public that appeared on Sina Weibo from January 1, 2021, to December 31, 2021; this period covered the entire vaccination process in China. We identified popular discussion topics using latent Dirichlet allocation. We further examined changes in public sentiment and topics during the 3 stages of the vaccination timeline. Gender differences in perceptions toward vaccination were also investigated. RESULTS: Of 495,229 crawled posts, 96,145 original posts from individual accounts were included. Most posts presented positive sentiments (positive: 65,981/96,145, 68.63%; negative: 23,184/96,145, 24.11%; neutral: 6980/96,145, 7.26%). The average sentiment scores were 0.75 (SD 0.35) for men and 0.67 (SD 0.37) for women. The overall trends in sentiment scores showed a mixed response to the number of new cases and significant events related to vaccine development and important holidays. The sentiment scores showed a weak correlation with new case numbers (R=0.296; P=.03). Significant sentiment score differences were observed between men and women (P<.001). Common and distinguishing characteristics were found among frequently discussed topics during the different stages, with significant differences in topic distribution between men and women (January 1, 2021, to March 31, 2021: χ23=3030.9; April 1, 2021, to September 30, 2021: χ24=8893.8; October 1, 2021, to December 31, 2021: χ25=3019.5; P<.001). Women were more concerned with side effects and vaccine effectiveness. In contrast, men reported broader concerns around the global pandemic, the progress of vaccine development, and economics affected by the pandemic. CONCLUSIONS: Understanding public concerns regarding vaccination is essential for reaching vaccine-induced herd immunity. This study tracked the year-long evolution of attitudes and opinions on COVID-19 vaccines according to the different stages of vaccination in China. These findings provide timely information that will enable the government to understand the reasons for low vaccine uptake and promote COVID-19 vaccination nationwide.

A Study of Public Attitudes toward Shanghai's Image under the Influence of COVID-19: Evidence from Comments on Sina Weibo.

With the advent of the Internet era, Chinese users tend to choose to express their opinions on social media platforms represented by Sina Weibo. The changes in people's emotions toward cities from the microblogging texts can reflect the image of cities presented on mainstream social media, and thus target a good image of cities. In this paper, we collected microblog data containing "Shanghai" from 1 January 2019 to 1 September 2022 by Python technology, and we used three methods: Term Frequency-Inverse Document Frequency keyword statistics, Latent Dirichlet Allocation theme model construction, and sentiment analysis by Zhiwang Sentiment Dictionary. We also explore the impact of the COVID-19 epidemic on Shanghai's urban image in the context of the "Shanghai Territorial Static Management", an important public opinion topic during the COVID-19 epidemic. The results of the study show that the "Shanghai-wide static management" of COVID-19 epidemic has significantly reduced the public's perception of Shanghai and negatively affected the city's image. By analyzing the data results, we summarize the basic characteristics of Shanghai's city image and provide strategies for communicating Shanghai's city image in the post-epidemic era.

Who does COVID-19 hurt most? Perceptions of unequal impact and political implications.

While the overall impact of the COVID-19 pandemic on U.S. population health has been devastating, it has not affected everyone equally. The risks of hospitalization and death from the disease are relatively low for the population as a whole, but much higher for specific subpopulations defined by age, health status, and race or ethnicity. The extent to which Americans perceive these disparities is an open question, with potentially important political implications. Recognition of unequal impacts may prime concerns about justice and fairness, making Americans more concerned and willing to support government intervention. On the other hand, belief that the pandemic primarily threatens "other people" or out-groups may reduce, rather than increase, a person's concern. Partisanship and media consumption habits are also likely to play a role in these perceptions, as they do in most issues related to COVID-19. In this paper, we use original survey data from the Cooperative Election Study (N = 1000) to explore Americans' perceptions of which groups are most harmed by the pandemic, the demographic and political determinants of these perceptions, and the relationship of these perceptions with their opinions about COVID-related mitigation policy. We find that, on average, people perceived accurately that certain groups (e.g., Black Americans, older people) were more affected, but these group perceptions varied by demographic and political characteristics of respondents. We find, in contrast with recent experimental evidence, that the perception that populations of color were harmed was associated with more support for pandemic mitigation strategies. More research should investigate the relationships among pandemic politics and the racial dynamics of the target populations most affected.

Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter.

BACKGROUND: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. OBJECTIVE: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. METHODS: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. RESULTS: There were fewer neutral mask-related tweets in 2020 (ß=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (ß=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (ß=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (ß=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (ß=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (ß=-.001, 95% CI -.002 to 0; P=.008). CONCLUSIONS: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.

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

Background: Public sentiments arising from public opinion communication pose a serious psychological risk to public and interfere the communication of nonpharmacological intervention information during the COVID-19 pandemic. Problems caused by public sentiments need to be timely addressed and resolved to support public opinion management. Objective: This study aims to investigate the quantified multidimensional public sentiments characteristics for helping solve the public sentiments issues and strengthen public opinion management. Methods: This study collected the user interaction data from the Weibo platform, including 73,604 Weibo posts and 1,811,703 Weibo comments. Deep learning based on pretraining model, topics clustering and correlation analysis were used to conduct quantitative analysis on time series characteristics, content-based characteristics and audience response characteristics of public sentiments in public opinion during the pandemic. Results: The research findings were as follows: first, public sentiments erupted after priming, and the time series of public sentiments had window periods. Second, public sentiments were related to public discussion topics. The more negative the audience sentiments were, the more deeply the public participated in public discussions. Third, audience sentiments were independent of Weibo posts and user attributes, the steering role of opinion leaders was invalid in changing audience sentiments. Discussion: Since the COVID-19 pandemic, there has been an increasing demand for public opinion management on social media. Our study on the quantified multidimensional public sentiments characteristics is one of the methodological contributions to reinforce public opinion management from a practical perspective.

Applying Blockchain Technology in Network Public Opinion Risk Management System in Big Data Environment.

Network public opinion represents public social opinion to a certain extent and has an important impact on formulating national policies and judgment. Therefore, China and other countries attach great importance to the study of online public opinion. However, the current researches lack the combination of theory and practical cases and lack the intersection of social and natural sciences. This work aims to overcome the technical defects of traditional management systems, break through the difficulties and pain points of existing network public opinion risk management, and improve the efficiency of network public opinion risk management. Firstly, a network public opinion isolation strategy based on the infectious disease propagation model is proposed, and the optimal control theory is used to realize a functional control model to maximize social utility. Secondly, blockchain technology is used to build a network public opinion risk management system. The system is used to conduct a detailed study on identifying and perceiving online public opinion risk. Finally, a Chinese word segmentation scheme based on Long Short-Term Memory (LSTM) network model and a text emotion recognition scheme based on a convolutional neural network are proposed. Both schemes are validated on a typical corpus. The results show that when the system has a control strategy, the number of susceptible drops significantly. Two days after the public opinion is generated, the number of susceptible people decreased from 1,000 to 250; 3 days after the public opinion is generated, the number of susceptible people stabilized. 2 days after the public opinion is generated, the number of lurkers increased from 100 to 620; 3 days after the public opinion is generated, the number of lurkers stabilized. The data demonstrate that the designed isolation control strategy is effective. Changes in public opinion among infected people show that quarantine control strategies played a significant role in the early days of Corona Virus Disease 2019. The rate of change in the number of infections is more affected when quarantine controls are increased, especially in the days leading up to the outbreak. When the system adopts the optimal control strategy, the influence scope of public opinion becomes smaller, and the control becomes easier. When the dimension of the word vector of emergent events is 200, its accuracy may be higher. This method provides certain ideas for blockchain and deep learning technology in network public opinion control.

Public Perceptions and Attitudes on the Image of Nursing in the Wake of COVID-19.

BACKGROUND: The COVID-19 pandemic in recent years has given nursing teams a unique place in this war, and an opportunity to change public opinion. The perceptions have the power to affect the users of health services, the nurses' performance, health policy, and even the choice to become a nurse. AIM: To examine the relationship between the public's perceptions and attitudes to the nursing profession compared with other healthcare professions, and to examine the relationship with the image of nursing in the wake of the COVID-19 pandemic. DESIGN AND METHODS: This study is a cross-sectional study, with a descriptive correlational design. Specifically, 80 respondents, men and women aged 18-75, joined a survey consisting of an anonymous questionnaire. RESULTS: A positive relationship was found between the public's perceptions and attitudes to nursing compared with other professions and the image of nursing in the wake of COVID-19, so the more positive public opinion was, the more positive the image of nursing would be. CONCLUSION: In the wake of COVID-19, the public's opinion and perception of the nursing profession compared to other professions and their attitudes to nurses are more positive. It is important to continue to explore which factors most affected and changed the image of nursing during the pandemic, and to design strategies to preserve the improved image of nursing among the public on an ongoing basis.

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.

Canadians' opinions towards COVID-19 data-sharing: a national cross-sectional survey.

OBJECTIVES: COVID-19 research has significantly contributed to pandemic response and the enhancement of public health capacity. COVID-19 data collected by provincial/territorial health authorities in Canada are valuable for research advancement yet not readily available to the public, including researchers. To inform developments in public health data-sharing in Canada, we explored Canadians' opinions of public health authorities sharing deidentified individual-level COVID-19 data publicly. DESIGN/SETTING/INTERVENTIONS/OUTCOMES: A national cross-sectional survey was administered in Canada in March 2022, assessing Canadians' opinions on publicly sharing COVID-19 datatypes. Market research firm Léger was employed for recruitment and data collection. PARTICIPANTS: Anyone greater than or equal to 18 years and currently living in Canada. RESULTS: 4981 participants completed the survey with a 92.3% response rate. 79.7% were supportive of provincial/territorial authorities publicly sharing deidentified COVID-19 data, while 20.3% were hesitant/averse/unsure. Datatypes most supported for being shared publicly were symptoms (83.0% in support), geographical region (82.6%) and COVID-19 vaccination status (81.7%). Datatypes with the most aversion were employment sector (27.4% averse), postal area (26.7%) and international travel history (19.7%). Generally supportive Canadians were characterised as being ≥50 years, with higher education, and being vaccinated against COVID-19 at least once. Vaccination status was the most influential predictor of data-sharing opinion, with respondents who were ever vaccinated being 4.20 times more likely (95% CI 3.21 to 5.48, p=0.000) to be generally supportive of data-sharing than those unvaccinated. CONCLUSIONS: These findings suggest that the Canadian public is generally favourable to deidentified data-sharing. Identifying factors that are likely to improve attitudes towards data-sharing are useful to stakeholders involved in data-sharing initiatives, such as public health agencies, in informing the development of public health communication and data-sharing policies. As Canada progresses through the COVID-19 pandemic, and with limited testing and reporting of COVID-19 data, it is essential to improve deidentified data-sharing given the public's general support for these efforts.

Public conformism with health regulation is crumbling as COVID-19 becomes a chronic threat: Repeated Cross-sectional Studies.

BACKGROUND: The purpose of this study is to analyze the long terms trends in public attitudes toward the COVID-19 pandemic and compliance with self-quarantine regulations. METHODS: Repeated cross-sectional studies looking into data collected from nationally representative samples (N = 2568) of the adult population in Israel at five points in time representing the five morbidity waves of the COVID-19 pandemic. This study examined public trust in Israeli health regulations, levels of public panic, feelings of personal worry, and compliance with health regulations, specifically self-quarantine. RESULTS: Public trust in health regulations in January 2022 is at an all-time low (25%) compared to the maximum value of nearly 75% measured in March 2020. While reported worry is steadily reducing, the perception of public panic is increasing. In earlier rounds, public compliance with self-quarantine was reported close to 100%; however, it has dropped to 38% by January 2022 when compensation is not assumed. Regression analysis suggests that trust is a major predictor of compliance with health regulations. CONCLUSIONS: The "fifth wave" of the COVID-19 pandemic brought about an all-time low in public trust in health regulations. The Israeli public, normally a highly compliant one, is showing signs of crumbling conformity.

Analysis of network public opinion on COVID-19 epidemic based on the WSR theory.

Objective: To obtain the influencing factors of public opinion reactions and to construct a basic framework of the factors causing the occurrence of online public opinion in the epidemic area. Methods: The hot news comments on microblogs during the epidemic in Shanghai were collected and analyzed with qualitative analysis, grounded theory, and the "Wuli-Shili-Renli" (WSR) methodology as an auxiliary method. Results: (1) Three core categories of the Wuli system, the Shili system, and the Renli system, 15 main categories, and 86 categories that influence the development of network public opinion are obtained. (2) WSR Elements Framework Of Network Public Opinion (WSR-EFONPO) is established. (3) The WSR-EFONPO is explained. Conclusion: The framework of factors for the occurrence of network public opinion is proposed, and the development process of network public opinion under COVID-19 is sorted out, which is of great theoretical value in guiding the public in the epidemic area to form reasonable behavior.