Canadian COVID-19 Crisis Communication on Twitter: Mixed Methods Research Examining Tweets from Government, Politicians, and Public Health for Crisis Communication Guiding Principles and Tweet Engagement

Persuasive Effects of Crisis Communication during Public Health Emergency Outbreaks in China

Major global public health emergencies face unprecedented challenges, such as an infodemic and scientific disputes, and governments especially need to implement fast and effective crisis communication. Firstly, this paper takes the Elaboration Likelihood Model as a framework and constructs a crisis communication persuasion effect evaluation method with emotion analysis. Secondly, this paper takes the crisis communication at the beginning of the COVID-19 outbreak in China as an example and examines the persuasive effects of the peripheral route, represented by medical experts, and the central route, represented by mainstream media. This study finds that the peripheral route of persuasive communication can quickly establish communication trust and quickly change the public's peripheral attitude, but the persuasive effect is unstable. The central route of persuasive communication demonstrates a significantly positive, stable, and anti-interference persuasive effect. Dual-subject persuasion is an important strategy for controlling an outbreak by rapidly establishing communication trust, combating an infodemic, boosting public confidence, and popularizing medical knowledge. This study evaluates the persuasive effects of crisis communication in the early stages of the COVID-19 outbreak in China, hoping to provide valuable practical references for crisis communication during the outbreak in future global public health emergencies.

Evaluating Multi-Jurisdictional Enteric Illness Outbreak Messaging in Canada: A Content Analysis of Public Health Notices

Effective risk communication during enteric illness outbreaks requires the provision of clear and consistent information to diverse audiences to reduce risk of exposure, inform behavior changes, and prevent illness. Most enteric illnesses are caused by pathogens transmitted through consumption of contaminated food or water, contact with animals, or person-to-person contact. When multi-jurisdictional outbreaks occur, the Public Health Agency of Canada posts web-based Public Health Notices (PHNs) to inform Canadians. This study evaluated the comprehensibility of PHNs to optimize federal risk communication approaches. Publicly available web-based PHNs (n = 42) from 2014-2022 were obtained. A codebook was developed using the Centers for Disease Control and Prevention's (CDC) Clear Communication Index (CCI) and Health Belief Model (HBM) and systematically applied. A SMOG readability calculator was used to determine reading grade level. Descriptive statistics were calculated to summarize coded data. The average reading grade level was above Grade 12 (13.9 ± 1.1). PHNs communicated the nature of the risk (100%) and behavioral recommendations (96.5%) clearly. An active voice was sometimes used (61.9%), but numerical information was less commonly presented using best practices (38.1%). The HBM was fully incorporated in seven PHNs, with most PHNs using five of six constructs (66.7%). PHNs shared similar information in a consistent order (75.0%). Aligning PHNs to best practices in risk communication is recommended, including writing content at a reading grade level that supports comprehension by diverse audiences, following the CCI to increase clarity, including all HBM constructs to promote behavior change, and maintaining message consistency.

Public health agencies' use of social media for communication during pandemics: a scoping review of the literature

Public health agencies (PHAs) have increasingly incorporated social media into their communication mix during successive pandemics in the 21st century. However, the quality, timing, and accuracy of their health messages have varied significantly, resulting in mixed outcomes for communication, audience engagement, and pandemic management. This study aimed to identify factors influencing the effectiveness of pandemic-related health messages shared by PHAs on social media and to report their impact on public engagement as documented in the literature. A scoping literature review was conducted following a predefined protocol. An electronic search of 7 relevant databases and 5 grey literature repositories yielded 9,714 papers published between January 2003 and November 2022. Seventy-three papers were deemed eligible and selected for review. The results underscored the insufficiency of social media guidance policies for PHAs. Six themes were identified: message source, message topic, message style, message timing, content credibility and reliability, and message recipient profile. These themes encompassed 20 variables that could inform PHAs' social media public health communication during pandemics. Additionally, the findings revealed potential interconnectedness among the variables, and this study concluded by proposing a conceptual model that expands upon existing theoretical foundations for developing and evaluating pandemic-related health messaging.

Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models

The present research deals with sentiment analysis performed with Microsoft Azure Machine Learning Studio to classify Facebook posts on the Greek National Public Health Organization (EODY) from November 2021 to January 2022 during the pandemic. Positive, negative and neutral sentiments were included after processing 300 reviews. This approach involved analyzing the words appearing in the comments and exploring the sentiments related to daily surveillance reports of COVID-19 published on the EODY Facebook page. Moreover, machine learning algorithms were implemented to predict the classification of sentiments. This research assesses the efficiency of a few popular machine learning models, which is one of the initial efforts in Greece in this domain. People have negative sentiments toward COVID surveillance reports. Words with the highest frequency of occurrence include government, vaccinated people, unvaccinated, telephone communication, health measures, virus, COVID-19 rapid/molecular tests, and of course, COVID-19. The experimental results disclose additionally that two classifiers, namely two class Neural Network and two class Bayes Point Machine, achieved high sentiment analysis accuracy and F1 score, particularly 87% and over 35%. A significant limitation of this study may be the need for more comparison with other research attempts that identified the sentiments of the EODY surveillance reports of COVID in Greece. Machine learning models can provide critical information combating public health hazards and enrich communication strategies and proactive actions in public health issues and opinion management during the COVID-19 pandemic.

COVID-19 and Masking Disparities: Qualitative Analysis of Trust on the CDC's Facebook Page

This exploratory paper examines individual levels of risk assessment as impacting institutional trust in the CDC while also contributing to disparities in expressed willingness to mask early in the COVID-19 pandemic. Using both content and thematic analysis of the CDC's Facebook (FB) page from April 2020 and Gidden's modern risk society theory, I consider how social media (SM) users retrospectively perceived a dramatic change in public health (PH) advisory-from the CDC advising against masking in February 2020 (Time 1) to advising the use of "do-it-yourself" (DIY) cloth masking in April 2020 (Time 2)-through a lens of prior, self-guided research. Expressed "knowledge" of masking as preventative (or not) yielded unwavering and sometimes increasing distrust in the CDC based on user perception of the "correct" advisory, regardless of the CDC's position at Time 1 or Time 2. Simultaneously, disparities in masking behaviors appeared to be driven not by CDC guidance but by this same self-guided research. I show this via three themes: (1) claims of ineffectiveness for DIY masking (do not trust CDC now-no masking from the start); (2) conflict between the first and second CDC advisories on masking (do not trust CDC-either already masking anyway or will now); (3) disappointed in the CDC for length of time taken to make a DIY mask recommendation (do not trust CDC-either already masking anyway or will mask now). I discuss the imperative nature of two-way engagement with SM users by PH rather than using SM as a one-way mode of advisory dissemination. This and other recommendations may decrease disparities in preventative behaviors based on individual-level risk assessment as well as increase institutional trust and transparency.

COVID-19 messages targeting young people on social media: content analysis of Australian health authority posts

Health authorities utilized social media during the COVID-19 pandemic to disseminate critical and timely health messages, specifically targeting priority groups such as young people. To understand how social media was used for this purpose, we investigated the content of COVID-19-related social media posts targeting young people (16-29 years old) shared by Australian health departments. Posts targeting young people with COVID-19 information were extracted from all eight Australian State and Territory health department Facebook, Instagram and TikTok accounts over 1 month of the Delta outbreak (September 2021) and analysed thematically. In total, 238 posts targeting young people were identified from 1059 COVID-19 posts extracted. All eight health departments used Facebook, five used Instagram and only one used TikTok. The majority of posts implicitly targeted young people; only 14.7% explicitly mentioned age or 'young people'. All posts included accompanying visuals; 77% were still images like photos or illustrations whilst 23% were moving images like videos and GIFs. Communication techniques included calls to action (63% of posts), responsive communication (32% of posts) and positive emotional appeal (31% of posts). Social marketing techniques catering to young people were used to varying extents despite receiving higher levels of engagement; 45% featured emojis whilst only 16% used humour, 14% featured celebrities and 6% were memes. Priority groups like ethnic/cultural groups and chronic health/disability communities were rarely targeted in this communication. The findings indicate a lack of health communication on social media directed towards young people, highlighting an opportunity for increased use of platforms like TikTok and trends popular with young people online.

Social Media Engagement in Two Governmental Schemes during the COVID-19 Pandemic in Macao

Social media engagement is a vehicle for effective communication and engagement between governments and individuals, especially in crises such as the COVID-19 pandemic. Additionally, it can be used to communicate resilience measures and receive feedback. This research aims to investigate public social media engagement with resilience measures related to COVID-19 in Macao. We examined 1107 posts and 791 comments about the government’s face mask supply and consumption voucher schemes on Facebook. Using the Crisis Lifecycle model, we partitioned the data and analyzed the content and engagement of related posts, as well as the word semantics in user comments. Our findings show that social media engagement in these resilience measures is high and positive in the early stages of the pandemic, suggesting social media’s potential in mobilizing society, preserving social resilience, and serving as a two-way communication tool in public health emergencies.