Infodemics: A new challenge for public health

Infodemic Versus Viral Information Spread: Key Differences and Open Challenges

Unlabelled

As we move beyond the COVID-19 pandemic, the risk of future infodemics remains significant, driven by emerging health crises and the increasing influence of artificial intelligence in the information ecosystem. During periods of apparent stability, proactive efforts to advance infodemiology are essential for enhancing preparedness and improving public health outcomes. This requires a thorough examination of the foundations of this evolving discipline, particularly in understanding how to accurately identify an infodemic at the appropriate time and scale, and how to distinguish it from other processes of viral information spread, both within and outside the realm of public health. In this paper, we integrate expertise from data science and public health to examine the key differences between information production during an infodemic and viral information spread. We explore both clear and subtle distinctions, including context and contingency (ie, the association of an infodemic and viral information spread with a health crisis); information dynamics in terms of volume, spread, and predictability; the role of misinformation and information voids; societal impact; and mitigation strategies. By analyzing these differences, we highlight challenges and open questions. These include whether an infodemic is solely associated with pandemics or whether it could arise from other health emergencies; if infodemics are limited to health-related issues or if they could emerge from crises initially unrelated to health (like climate events); and whether infodemics are exclusively global phenomena or if they can occur on national or local scales. Finally, we propose directions for future quantitative research to help the scientific community more robustly differentiate between these phenomena and develop tailored management strategies.

Experiences of Public Health Professionals Regarding Crisis Communication During the COVID-19 Pandemic: Systematic Review of Qualitative Studies

BACKGROUND

The COVID-19 pandemic emerged in the digital age and has been called the first "data-driven pandemic" in human history. The global response demonstrated that many countries had failed to effectively prepare for such an event. Learning through experience in a crisis is one way to improve the crisis management process. As the world has returned to normal after the pandemic, questions about crisis management have been raised in several countries and require careful consideration.

OBJECTIVE

This review aimed to collect and organize public health professionals' experiences in crisis communication to the public during the COVID-19 pandemic.

METHODS

We searched PubMed, MEDLINE, CINAHL, Web of Science, Academic Search Complete, PsycINFO, PsycARTICLES, and Communication Abstracts in February 2024 to locate English-language articles that qualitatively investigated the difficulties and needs experienced by health professionals in their communication activities during the COVID-19 pandemic.

RESULTS

This review included 17 studies. Our analysis identified 7 themes and 20 subthemes. The 7 themes were difficulties in pandemic communication, difficulties caused by the "infodemic," difficulties in partnerships within or outside of public health, difficulties in community engagement, difficulties in effective communication, burnout among communicators, and the need to train communication specialists and establish a permanent organization specializing in communication.

CONCLUSIONS

This review identified the gaps between existing crisis communication guidelines and real-world crisis communication in the digital environment and clarified the difficulties and needs that arose from these gaps. Crisis communication strategies and guidelines should be updated with reference to the themes revealed in this review to effectively respond to subsequent public health crises.

TRIAL REGISTRATION

PROSPERO CRD42024528975; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=528975.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/58040.

COVID-19 vaccines side effects among the general population during the pandemic: a cross-sectional study

Background and aims

The general population have depicted concern about the safety and efficacy of the vaccine and its long-term effects on human health. Pakistan being on the verge of the pandemic is in more demand for vaccination and immunization. Therefore, this study aimed to evaluate the COVID-19 vaccines side effects among the general population.

Methods

A cross-sectional face-to-face study was carried out among individuals who received either the first dosage or both doses of vaccination in twin cities (Islamabad and Rawalpindi) of Pakistan. Data was collected through a self-administered questionnaire. The questionnaire included three sections (socio-demographic, medical history, vaccine, and immunization) with 20 questions. The collected data was analyzed in SPSS (version 25) using descriptive statistics, the chi-square test, and the odd ratio.

Results

A total of 2,618 participants were included and of them, females (55.3%; n = 1,449) were more than males. The majority of the participants reported the use of precautionary medicines including vitamin C (1,319; 50.4%) followed by paracetamol (n = 1,249; 47.7%) and mineral supplements (n = 616; 23.5%) for COVID-19. In this study, 3.8% (n = 99) were unvaccinated and the first and second doses of the vaccine was received by 2,519 and 2,239 of the participants, respectively. Different types of side effects were highlighted in the current study. The most frequently reported side effects after the first dose of COVID-19 were fever (n = 997), pain at the injection site (n = 994), muscle pain (n = 620), and fatigue (n = 482). Additionally, pain at the injection site (n = 852), fever (n = 815), and muscle pain (n = 601) were commonly reported after the 2nd dose of COVID-19. The lowest reported side effects were swollen lymph nodes and anaphylactic shock. In the current study, people who were previously immunized with the flu and pneumonia vaccine had a lower risk of developing side effects (p < 0.05).

Conclusion

This study highlights important information about side effects reported due to the COVID-19 vaccinations. Moreover, the use of precautionary medications was also highlighted. These findings could have a valuable impact on designing future comparative studies and developing policies/guidelines for pandemic preparedness.

Mapping the global election landscape on social media in 2024

In 2024, a significant portion of the global population will participate in elections, creating an opportunity to analyze how information spreads and how users behave on social media. This study examines the media landscape on Facebook by analyzing posts from political parties and major news outlets in Europe, Mexico, and India. By identifying key topics and measuring public engagement, we uncover patterns in political discourse. Using Principal Component Analysis, we explore how these topics are related and distinguish trends in audience interaction. Our findings show how certain topics resonate differently across political groups, providing insights into the relationship between media content, political ideology, and user engagement during elections.

Evaluating the effect of viral posts on social media engagement

As virality has become increasingly central in shaping information sources' strategies, it raises concerns about its consequences for society, particularly when referring to the impact of viral news on the public discourse. Nonetheless, there has been little consideration of whether these viral events genuinely boost the attention received by the source. To address this gap, we analyze content timelines from over 1000 European news outlets from 2018 to 2023 on Facebook and YouTube, employing a Bayesian structural time series model to evaluate the impact of viral posts. Our results show that most viral events do not significantly increase engagement and rarely lead to sustained growth. We identify two primary types of viral effects corresponding to different mechanisms of collective attention response. A 'loaded-type' virality manifests after a sustained growth phase, representing its final burst, followed by a decline in attention. A 'sudden-type' virality, with news emerging unexpectedly, reactivates the collective response process. Moreover, quick viral effects fade faster, while slower processes lead to more persistent growth. These findings highlight the transient nature of viral events and underscore the importance of consistent, steady attention-building strategies to establish a solid connection with the user base rather than relying on sudden visibility spikes.

Epidemiological methods in transition: Minimizing biases in classical and digital approaches

Epidemiology and Public Health have increasingly relied on structured and unstructured data, collected inside and outside of typical health systems, to study, identify, and mitigate diseases at the population level. Focusing on infectious diseases, we review the state of Digital Epidemiology at the beginning of 2020 and how it changed after the COVID-19 pandemic, in both nature and breadth. We argue that Epidemiology's progressive use of data generated outside of clinical and public health systems creates several technical challenges, particularly in carrying specific biases that are almost impossible to correct for a priori. Using a statistical perspective, we discuss how a definition of Digital Epidemiology that emphasizes "data-type" instead of "data-source," may be more operationally useful, by clarifying key methodological differences and gaps. Therefore, we briefly describe some of the possible biases arising from varied collection methods and sources, and offer some recommendations to better explore the potential of Digital Epidemiology, particularly on how to help reduce inequity.

An "opinion reproduction number" for infodemics in a bounded-confidence content-spreading process on networks

We study the spreading dynamics of content on networks. To do this, we use a model in which content spreads through a bounded-confidence mechanism. In a bounded-confidence model (BCM) of opinion dynamics, the agents of a network have continuous-valued opinions, which they adjust when they interact with agents whose opinions are sufficiently close to theirs. Our content-spreading model, which one can also interpret as an independent-cascade model, introduces a twist into BCMs by using bounded confidence for the content spread itself. We define an analog of the basic reproduction number from disease dynamics that we call an opinion reproduction number. A critical value of the opinion reproduction number indicates whether or not there is an "infodemic" (i.e., a large content-spreading cascade) of content that reflects a particular opinion. By determining this critical value, one can determine whether or not an opinion dies off or propagates widely as a cascade in a population of agents. Using configuration-model networks, we quantify the size and shape of content dissemination by calculating a variety of summary statistics, and we illustrate how network structure and spreading-model parameters affect these statistics. We find that content spreads most widely when agents have a large expected mean degree or a large receptiveness to content. When the spreading process slightly exceeds the infodemic threshold, there can be longer dissemination trees than for larger expected mean degrees or receptiveness (which both promote content sharing and hence help push content spread past the infodemic threshold), even though the total number of content shares is smaller.

Emerging global patterns of COVID-19 vaccine information fatigue in 23 countries in 2023

Vaccine information fatigue, exacerbated by the infodemic, misinformation, and cultural influences, hampers public responsiveness to the uptake of vaccines for COVID-19 and other vaccine-preventable diseases. This cross-sectional study of 23,000 respondents surveyed in 23 countries in October 2023 analyzed trust in information sources, perceptions of the pandemic's conclusion, and confidence in one's ability to discern false information from true and the association of these factors with willingness to pay attention to COVID-19 vaccine information, adjusting for sociodemographic characteristics. Results revealed that satisfaction with health authority communication was positively associated with individuals' willingness to pay attention to COVID-19 vaccine information in all 23 countries. Confidence in one's own capacity to distinguish true information from false was associated with willingness in 20 countries. Belief that the pandemic is over was associated with unwillingness to pay attention to COVID-19 vaccine information in 14 countries. These findings underscore the need for tailored communication strategies that build trust in information sources, combat complacency, and enhance discernment skills to address vaccine and pandemic fatigue, aiming to sustain public engagement with vaccine information and, ultimately, support vaccination efforts.

Infodemics and Vaccine Confidence: Protocol for Social Listening and Insight Generation to Inform Action

BACKGROUND

In the fall of 2020, the COVID-19 infodemic began to affect public confidence in and demand for COVID-19 vaccines in the United States. While polls indicated what consumers felt regarding COVID-19 vaccines, they did not provide an understanding of why they felt that way or the social and informational influences that factored into vaccine confidence and uptake. It was essential for us to better understand how information ecosystems were affecting the confidence in and demand for COVID-19 vaccines in the United States.

OBJECTIVE

The US Centers for Disease Control and Prevention (CDC) established an Insights Unit within the COVID-19 Response's Vaccine Task Force in January 2021 to assist the agency in acting more swiftly to address the questions, concerns, perceptions, and misinformation that appeared to be affecting uptake of COVID-19 vaccines. We established a novel methodology to rapidly detect and report on trends in vaccine confidence and demand to guide communication efforts and improve programmatic quality in near real time.

METHODS

We identified and assessed data sources for inclusion through an informal landscape analysis using a snowball method. Selected data sources provided an expansive look at the information ecosystem of the United States regarding COVID-19 vaccines. The CDC's Vaccinate with Confidence framework and the World Health Organization's behavioral and social drivers for vaccine decision-making framework were selected as guiding principles for interpreting generated insights and their impact. We used qualitative thematic analysis methods and a consensus-building approach to identify prevailing and emerging themes, assess their potential threat to vaccine confidence, and propose actions to increase confidence and demand.

RESULTS

As of August 2022, we have produced and distributed 34 reports to >950 recipients within the CDC and externally. State and local health departments, nonprofit organizations, professional associations, and congressional committees have referenced and used the reports for learning about COVID-19 vaccine confidence and demand, developing communication strategies, and demonstrating how the CDC monitored and responded to misinformation. A survey of the reports' end users found that nearly 75% (40/53) of respondents found them "very" or "extremely" relevant and 52% (32/61) used the reports to inform communication strategies. In addition, our methodology underwent continuous process improvement to increase the rigor of the research process, the validity of the findings, and the usability of the reports.

CONCLUSIONS

This methodology can serve as a diagnostic technique for rapidly identifying opportunities for public health interventions and prevention. As the methodology itself is adaptable, it could be leveraged and scaled for use in a variety of public health settings. Furthermore, it could be considered beyond acute public health crises to support adherence to guidance and recommendations and could be considered within routine monitoring and surveillance systems.

Development of AI-generated medical responses using the ChatGPT for cancer patients

BACKGROUND AND OBJECTIVE

To develop a healthcare chatbot service (AI-guided bot) that conducts real-time conversations using large language models to provide accurate health information to patients.

METHODS

To provide accurate and specialized medical responses, we integrated several cancer practice guidelines. The size of the integrated meta-dataset was 1.17 million tokens. The integrated and classified metadata were extracted, transformed into text, segmented to specific character lengths, and vectorized using the embedding model. The AI-guide bot was implemented using Python 3.9. To enhance the scalability and incorporate the integrated dataset, we combined the AI-guide bot with OpenAI and the LangChain framework. To generate user-friendly conversations, a language model was developed based on Chat-Generative Pretrained Transformer (ChatGPT), an interactive conversational chatbot powered by GPT-3.5. The AI-guide bot was implemented using ChatGPT3.5 from Sep. 2023 to Jan. 2024.

RESULTS

The AI-guide bot allowed users to select their desired cancer type and language for conversational interactions. The AI-guided bot was designed to expand its capabilities to encompass multiple major cancer types. The performance of the AI-guide bot responses was 90.98 ± 4.02 (obtained by summing up the Likert scores).

CONCLUSIONS

The AI-guide bot can provide medical information quickly and accurately to patients with cancer who are concerned about their health.

Fighting Fire or Fighting War: Examining the Framing Effects of COVID-19 Metaphors

Metaphorical language describing the COVID-19 pandemic as a war has been pervasive in public discourse (e.g. "the pandemic is a war," "the virus is an enemy," and "the vaccine is a weapon"). This study employs an online survey experiment (N = 551 U.S. adults) to examine the impact of war metaphors compared to non-metaphorical literal frames and fire metaphors (e.g. "the pandemic is a wildfire"). War metaphors exhibited little advantage over literal frames across a variety of desirable outcomes (i.e. the adoption of pro-health behaviors against COVID-19, perceived solidarity and collective responsibility to curb the pandemic, and intentions to discuss and share the health news with others). However, this study revealed some benefits of war metaphors over fire metaphors. Compared with fire metaphors, health news featuring war metaphors increased both positive emotions and perceived threats of COVID-19, which in turn promoted pro-health behaviors against COVID-19 and perceived solidarity to cope with the public health crisis. Moreover, positive emotions in response to war metaphors also indirectly encouraged the retransmission of science-based COVID-19 health news. This study thus showcased the benefits and limitations of war metaphors and revealed the mediating roles of perceived threats and positive emotions in explaining war metaphorical framing effects. Implications of using war and fire metaphors for communicating about public health crises are also discussed.

Ethical Considerations in Infodemic Management: Systematic Scoping Review

BACKGROUND

During health emergencies, effective infodemic management has become a paramount challenge. A new era marked by a rapidly changing information ecosystem, combined with the widespread dissemination of misinformation and disinformation, has magnified the complexity of the issue. For infodemic management measures to be effective, acceptable, and trustworthy, a robust framework of ethical considerations is needed.

OBJECTIVE

This systematic scoping review aims to identify and analyze ethical considerations and procedural principles relevant to infodemic management, ultimately enhancing the effectiveness of these practices and increasing trust in stakeholders performing infodemic management practices with the goal of safeguarding public health.

METHODS

The review involved a comprehensive examination of the literature related to ethical considerations in infodemic management from 2002 to 2022, drawing from publications in PubMed, Scopus, and Web of Science. Policy documents and relevant material were included in the search strategy. Papers were screened against inclusion and exclusion criteria, and core thematic areas were systematically identified and categorized following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We analyzed the literature to identify substantive ethical principles that were crucial for guiding actions in the realms of infodemic management and social listening, as well as related procedural ethical principles. In this review, we consider ethical principles that are extensively deliberated upon in the literature, such as equity, justice, or respect for autonomy. However, we acknowledge the existence and relevance of procedural practices, which we also consider as ethical principles or practices that, when implemented, enhance the efficacy of infodemic management while ensuring the respect of substantive ethical principles.

RESULTS

Drawing from 103 publications, the review yielded several key findings related to ethical principles, approaches, and guidelines for practice in the context of infodemic management. Community engagement, empowerment through education, and inclusivity emerged as procedural principles and practices that enhance the quality and effectiveness of communication and social listening efforts, fostering trust, a key emerging theme and crucial ethical principle. The review also emphasized the significance of transparency, privacy, and cybersecurity in data collection.

CONCLUSIONS

This review underscores the pivotal role of ethics in bolstering the efficacy of infodemic management. From the analyzed body of literature, it becomes evident that ethical considerations serve as essential instruments for cultivating trust and credibility while also facilitating the medium-term and long-term viability of infodemic management approaches.

Followers do not dictate the virality of news outlets on social media

Initially conceived for entertainment, social media platforms have profoundly transformed the dissemination of information and consequently reshaped the dynamics of agenda-setting. In this scenario, understanding the factors that capture audience attention and drive viral content is crucial. Employing Gibrat's Law, which posits that an entity's growth rate is unrelated to its size, we examine the engagement growth dynamics of news outlets on social media. Our analysis includes the Facebook historical data of over a thousand news outlets, encompassing approximately 57 million posts in four European languages from 2008 to the end of 2022. We discover universal growth dynamics according to which news virality is independent of the traditional size of the outlet. Moreover, our analysis reveals a significant long-term impact of news source reliability on engagement growth, with engagement induced by unreliable sources decreasing over time. We conclude the article by presenting a statistical model replicating the observed growth dynamics.

Experiences of Governments and Public Health Agencies Regarding Crisis Communication During the COVID-19 Pandemic in the Digital Age: Protocol for a Systematic Review of Qualitative Studies

BACKGROUND

Governments and public health agencies worldwide experienced difficulties with social media-mediated infodemics on the internet during the COVID-19 pandemic. Existing public health crisis communication strategies need to be updated. However, crisis communication experiences of governments and public health agencies worldwide during the COVID-19 pandemic have not been systematically compiled, necessitating updated crisis communication strategies.

OBJECTIVE

This systematic review aims to collect and organize the crisis communication experiences of senders (ie, governments and public health agencies) during the COVID-19 pandemic. Our focus is on exploring the difficulties that governments and public health agencies experienced, best practices in crisis communication by governments and public health agencies during the COVID-19 pandemic in times of infodemic, and challenges that should be overcome in future public health crises.

METHODS

We plan to begin the literature search on May 1, 2024. We will search PubMed, MEDLINE, CINAHL, PsycINFO, PsycARTICLES, Communication Abstracts, and Web of Science. We will filter our database searches to search from the year 2020 and beyond. We will use a combination of keywords by referring to the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, and Research type) tool to search the abstracts in databases. We intend to include qualitative studies on crisis communication by governments and public health agencies (eg, officials, staff, health professionals, and researchers) to the public. Quantitative data-based studies will be excluded. Only papers written in English will be included. Data on study characteristics, study aim, participant characteristics, methodology, theoretical framework, object of crisis communication, and key results will be extracted. The methodological quality of eligible studies will be assessed using the Joanna Briggs Institute critical appraisal checklist for qualitative research. A total of 2 independent reviewers will share responsibility for screening publications, data extraction, and quality assessment. Disagreement will be resolved through discussion, and the third reviewer will be consulted, if necessary. The findings will be summarized in a table and a conceptual diagram and synthesized in a descriptive and narrative review.

RESULTS

The results will be systematically integrated and presented in a way that corresponds to our research objectives and interests. We expect the results of this review to be submitted for publication by the end of 2024.

CONCLUSIONS

To our knowledge, this will be the first systematic review of the experiences of governments and public health agencies regarding their crisis communication to the public during the COVID-19 pandemic. This review will contribute to the future improvement of the guidelines for crisis communication by governments and public health agencies to the public.

TRIAL REGISTRATION

PROSPERO CRD42024528975; https://tinyurl.com/4fjmd8te.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/58040.

Beyond misinformation: developing a public health prevention framework for managing information ecosystems

The COVID-19 pandemic has highlighted how infodemics (defined as an overabundance of information, including misinformation and disinformation) pose a threat to public health and could hinder individuals from making informed health decisions. Although public health authorities and other stakeholders have implemented measures for managing infodemics, existing frameworks for infodemic management have been primarily focused on responding to acute health emergencies rather than integrated in routine service delivery. We review the evidence and propose a framework for infodemic management that encompasses upstream strategies and provides guidance on identifying different interventions, informed by the four levels of prevention in public health: primary, secondary, tertiary, and primordial prevention. On the basis of a narrative review of 54 documents (peer-reviewed and grey literature published from 1961 to 2023), we present examples of interventions that belong to each level of prevention. Adopting this framework requires proactive prevention and response through managing information ecosystems, beyond reacting to misinformation or disinformation.

Evaluating the influence of a 3-min online video on the community knowledge of stroke in four Arab countries

Introduction

Studies from developed and developing countries showed that the knowledge levels of stroke need improvement. Educational campaigns varied and were of limited influence predominantly because of their short duration and the need for financial support. The study aims to test the impact of a 3-min online video on the knowledge of stroke and factors influencing the knowledge score in four Arab countries.

Methods

A cross-sectional web-based pre-post study was conducted in Egypt, Jordan, Lebanon, and the United Arab Emirates. The data were collected using the snowball technique. Participants were adults aged 18 years and above. The questionnaire sequence was conducting a pretest, followed by the educational video explaining stroke occurrence, types, risks, warning signs, preventive measures, and treatment, and finally, a posttest to evaluate the differences in knowledge from baseline. Statistical analysis included paired t-tests comparing pre-post-education stroke knowledge scores, while repeated measures ANOVA, adjusting for covariates, assessed mean changes.

Results

The total number of participants was 2,721, mainly younger than 55 years. The majority had a university degree and were not healthcare professionals. A significant improvement was noted in the total knowledge score in all countries from a mean average (Mpretest = 21.11; Mposttest = 23.70) with p < 0.001. Identification of the stroke risks (Mpretest = 7.40; Mposttest = 8.75) and warning signs (Mpretest = 4.19; Mposttest = 4.94), understanding the preventive measures (Mpretest = 5.27; Mposttest = 5.39) and the importance of acting fast (Mpretest = 0.82; Mposttest = 0.85) improved from baseline with (p < 0.001) for all score components.

Conclusion

The educational tool successfully enhanced public understanding of stroke risks, the identification of stroke signs, and the critical need for emergency action. The advantages of this video include its short length, free online access, use of evidence-based content in lay language, and reflective images. The ultimate goal remains the long-term improvement of sustainability by mandating full-scale trials.

The Prevalence and Determinants of Hesitancy for Regular COVID-19 Vaccination among Primary Healthcare Patients with Asthma or COPD in Greece: A Cross-Sectional Study

The emergence of novel coronavirus mutations and signs of the waning immunity provided by COVID-19 vaccines underscore the importance of regular vaccination. This study aimed to investigate the prevalence of regular COVID-19 vaccination hesitancy and the factors that influence it among patients with asthma or chronic obstructive pulmonary disease (COPD) who visited primary care centers. The cross-sectional study was conducted in six primary healthcare centers in Crete, Greece (October-December 2023). Participants completed a questionnaire, which included questions about socio-demographic characteristics, health status, previous COVID-19 booster vaccination, attitudes, and beliefs about COVID-19 vaccination. Multivariate logistic regression was used to identify the factors that influenced vaccine hesitancy. Of the 264 participants, 65% exhibited hesitancy towards COVID-19 booster vaccination. Female gender, middle age, lower educational attainment, depression diagnosis, concerns about vaccine side effects, lack of confidence in vaccine efficacy, and reliance on media information were positively associated to vaccine hesitancy. Conversely, those having a cardiovascular disease or type 2 diabetes, those generally adhering to the recommendations of the treating physician, and those having previously received the flu vaccine or more than three COVID-19 vaccine doses were positively associated with regular COVID-19 vaccinations. Consequently, our findings could help develop strategies that could potentially reduce regular vaccination hesitancy among patients with asthma or COPD.

Effect of nutrition-related infodemics and social media on maternal experience: A nationwide survey in a low/middle income country

BACKGROUND

Undernutrition is a crucial cause of morbidity and mortality among children in low- or middle-income countries (LMICs). A better understanding of maternal general healthy nutrition knowledge, as well as misbeliefs, is highly essential, especially in such settings. In the current era of infodemics, it is very strenuous for mothers to select not only the right source for maternal nutrition information but the correct information as well.

AIM

To assess maternal healthy nutritional knowledge and nutrition-related misbeliefs and misinformation in an LMIC, and to determine the sources of such information and their assessment methods.

METHODS

This cross-sectional analytical observational study enrolled 5148 randomly selected Egyptian mothers who had one or more children less than 15 years old. The data were collected through online questionnaire forms: One was for the general nutrition knowledge assessment, and the other was for the nutritional myth score. Sources of information and ways of evaluating internet sources using the Currency, Relevance, Authority, Accuracy, and Purpose test were additionally analyzed.

RESULTS

The mean general nutrition knowledge score was 29 ± 9, with a percent score of 70.8% ± 12.1% (total score: 41). The median myth score was 9 (interquartile range: 6, 12; total score: 18). The primary sources of nutrition knowledge for the enrolled mothers were social media platforms (55%). Half of the mothers managed information for currency and authority, except for considering the author's contact information. More than 60% regularly checked information for accuracy and purpose. The mothers with significant nutrition knowledge checked periodically for the author's contact information (P = 0.012). The nutrition myth score was significantly lower among mothers who periodically checked the evidence of the information (P = 0.016). Mothers dependent on their healthcare providers as the primary source of their general nutritional knowledge were less likely to hold myths by 13% (P = 0.044). However, using social media increased the likelihood of having myths among mothers by approximately 1.2 (P = 0.001).

CONCLUSION

Social media platforms were found to be the primary source of maternal nutrition information in the current era of infodemics. However, healthcare providers were the only source for decreasing the incidence of maternal myths among the surveyed mothers.

Cross-platform social dynamics: an analysis of ChatGPT and COVID-19 vaccine conversations

The role of social media in information dissemination and agenda-setting has significantly expanded in recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to significant events as they unfold. However, online reactions to external developments are influenced by various factors, including the nature of the event and the online environment. This study examines the dynamics of public discourse on digital platforms to shed light on this issue. We analyzed over 12 million posts and news articles related to two significant events: the release of ChatGPT in 2022 and the global discussions about COVID-19 vaccines in 2021. Data was collected from multiple platforms, including Twitter, Facebook, Instagram, Reddit, YouTube, and GDELT. We employed topic modeling techniques to uncover the distinct thematic emphases on each platform, which reflect their specific features and target audiences. Additionally, sentiment analysis revealed various public perceptions regarding the topics studied. Lastly, we compared the evolution of engagement across platforms, unveiling unique patterns for the same topic. Notably, discussions about COVID-19 vaccines spread more rapidly due to the immediacy of the subject, while discussions about ChatGPT, despite its technological importance, propagated more gradually.

Modelling and predicting online vaccination views using bow-tie decomposition

Social media has become increasingly important in shaping public vaccination views, especially since the COVID-19 outbreak. This paper uses bow-tie structure to analyse a temporal dataset of directed online social networks that represent the information exchange among anti-vaccination, pro-vaccination and neutral Facebook pages. Bow-tie structure decomposes a network into seven components, with two components, strongly connected component (SCC) and out-periphery component (OUT), emphasized in this paper: SCC is the largest strongly connected component, acting as an 'information magnifier', and OUT contains all nodes with a directed path from a node in SCC, acting as an 'information creator'. We consistently observe statistically significant bow-tie structures with different dominant components for each vaccination group over time. In particular, the anti-vaccination group has a large OUT, and the pro-vaccination group has a large SCC. We further investigate changes in opinions over time, as measured by fan count variations, using agent-based simulations and machine learning models. Across both methods, accounting for bow-tie decomposition better reflects information flow differences among vaccination groups and improves our opinion dynamics prediction results. The modelling frameworks we consider can be applied to any multi-stance temporal network and could form a basis for exploring opinion dynamics using bow-tie structure in a wide range of applications.

A social media intervention for communicating vaccine safety in low- and middle-income countries: protocol for a pilot study

Vaccine safety is a concern that continues to drive hesitancy and refusal in populations in low-and-middle income countries (LMICs). Communicating about vaccine safety is a strategy that can successfully change personal and community perceptions and behaviors toward vaccination. The COVID-19 infodemic emergency with the rapid rollout of new vaccines and new technology, demonstrated the need for good and effective vaccine safety communication. The Vaccine Safety Net (VSN), a WHO-led global network of websites that provide reliable information on vaccine safety offers the ideal environment for gathering web and social media analytics for measuring impact of vaccine safety messages. Its members work with a wide range of populations, in different geographic locations and at many levels including national, regional, and local. We propose to undertake a pilot study to evaluate the feasibility of implementing COVID-19 vaccine safety communications with VSN members working in LMICs and to assess the impact of communications on public knowledge, attitudes, and perceptions.

Slow data public health

Surveillance and research data, despite their massive production, often fail to inform evidence-based and rigorous data-driven health decision-making. In the age of infodemic, as revealed by the COVID-19 pandemic, providing useful information for decision-making requires more than getting more data. Data of dubious quality and reliability waste resources and create data-genic public health damages. We call therefore for a slow data public health, which means focusing, first, on the identification of specific information needs and, second, on the dissemination of information in a way that informs decision-making, rather than devoting massive resources to data collection and analysis. A slow data public health prioritizes better data, ideally population-based, over more data and aims to be timely rather than deceptively fast. Applied by independent institutions with expertise in epidemiology and surveillance methods, it allows a thoughtful and timely public health response, based on high-quality data fostering trustworthiness.

Infodemic: Challenges and solutions in topic discovery and data process

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) pandemic was a huge shock to society, and the ensuing information problems had a huge impact on society at the same time. The urgent need to understand the Infodemic, i.e., the importance of the spread of false information related to the epidemic, has been highlighted. However, while there is a growing interest in this phenomenon, studies on the topic discovery, data collection, and data preparation phases of the information analysis process have been lacking.

OBJECTIVE

Since the epidemic is unprecedented and has not ended to this day, we aimed to examine the existing Infodemic-related literature from January 2019 to December 2022.

METHODS

We have systematically searched ScienceDirect and IEEE Xplore databases with some search limitations. From the searched literature we selected titles, abstracts and keywords, and limitations sections. We conducted an extensive structured literature search and analysis by filtering the literature and sorting out the available information.

RESULTS

A total of 47 papers ended up meeting the requirements of this review. Researchers in all of these literatures encountered different challenges, most of which were focused on the data collection step, with few challenges encountered in the data preparation phase and almost none in the topic discovery section. The challenges were mainly divided into the points of how to collect data quickly, how to get the required data samples, how to filter the data, what to do if the data set is too small, how to pick the right classifier and how to deal with topic drift and diversity. In addition, researchers have proposed partial solutions to the challenges, and we have also proposed possible solutions.

CONCLUSIONS

This review found that Infodemic is a rapidly growing research area that attracts the interest of researchers from different disciplines. The number of studies in this field has increased significantly in recent years, with researchers from different countries, including the United States, India, and China. Infodemic topic discovery, data collection, and data preparation are not easy, and each step faces different challenges. While there is some research in this emerging field, there are still many challenges that need to be addressed. These findings highlight the need for more articles to address these issues and fill these gaps.

Digital Emergency Management for a Complex One Health Landscape: the Need for Standardization, Integration, and Interoperability

OBJECTIVE

Planning reliable long-term planning actions to handle disruptive events requires a timely development of technological infrastructures, as well as the set-up of focused strategies for emergency management. The paper aims to highlight the needs for standardization, integration, and interoperability between Accident & Emergency Informatics (A&EI) and One Digital Health (ODH), as fields capable of dealing with peculiar dynamics for a technology-boosted management of emergencies under an overarching One Health panorama.

METHODS

An integrative analysis of the literature was conducted to draw attention to specific foci on the correlation between ODH and A&EI, in particular: (i) the management of disruptive events from private smart spaces to diseases spreading, and (ii) the concepts of (health-related) quality of life and well-being.

RESULTS

A digitally-focused management of emergency events that tackles the inextricable interconnectedness between humans, animals, and surrounding environment, demands standardization, integration, and systems interoperability. A consistent and finalized process of adoption and implementation of methods and tools from the International Standard Accident Number (ISAN), via findability, accessibility, interoperability, and reusability (FAIR) data principles, to Medical Informatics and Digital Health Multilingual Ontology (MIMO) - capable of looking at different approaches to encourage the integration between the ODH framework and the A&EI vision, provides a first answer to these needs.

CONCLUSIONS

ODH and A&EI look at different scales but with similar goals for converging health and environmental-related data management standards to enable multi-sources, interdisciplinary, and real-time data integration and interoperability. This allows holistic digital health both in routine and emergency events.

COVID-19 impacts on healthcare access in sub-Saharan Africa: an overview

This overview aimed to describe the situation of healthcare access in sub-Saharan Africa, excluding South Africa, during the COVID-19 pandemic. A PubMed^® search from March 31, 2020, to August 15, 2022, selected 116 articles. Healthcare access and consequences of COVID-19 were assessed based on comparisons with months before its onset or an identical season in previous years. A general reduction of healthcare delivery, associated with the decline of care quality, and closure of many specialty services were reported. The impact was heterogeneous in space and time, with an increase in urban areas at the beginning of the pandemic (March-June 2020). The return to normalcy was gradual from the 3^rd quarter of 2020 until the end of 2021. The impact of COVID-19 on the health system and its use was attributed to (a) conjunctural factors resulting from government actions to mitigate the spread of the epidemic (containment, transportation restrictions, closures of businesses, and places of entertainment or worship); (b) structural factors related to the disruption of public and private facilities and institutions, in particular, the health system; and (c) individual factors linked to the increase in costs, impoverishment of the population, and fear of contamination or stigmatization, which discouraged patients from going to health centers. They have caused considerable socio-economic damage. Several studies emphasized some adaptability of the healthcare offer and resilience of the healthcare system, despite its unpreparedness, which explained a return to normal activities as early as 2022 while the COVID-19 epidemic persisted. There appears to be a strong disproportion between the moderate incidence and severity of COVID-19 in sub-Saharan Africa, and the dramatic impact on healthcare access. Several articles make recommendations for lowering the socioeconomic consequences of future epidemics to ensure better management of health issues.

Characterizing engagement dynamics across topics on Facebook

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting ∼57M posts from ∼2M pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic.

Measuring the burden of infodemics with a research toolkit for connecting information exposure, trust, and health behaviours

BACKGROUND

During a public health emergency, accurate and useful information can be drowned out by questions, concerns, information voids, conflicting information, and misinformation. Very few studies connect information exposure and trust to health behaviours, which limits available evidence to inform when and where to act to mitigate the burden of infodemics, especially in low resource settings. This research describes the features of a toolkit that can support studies linking information exposure to health behaviours at the individual level.

METHODS

To meet the needs of the research community, we determined the functional and non-functional requirements of a research toolkit that can be used in studies measuring topic-specific information exposure and health behaviours. Most data-driven infodemiology research is designed to characterise content rather than measure associations between information exposure and health behaviours. Studies also tend to be limited to specific social media platforms, are unable to capture the breadth of individual information exposure that occur online and offline, and cannot measure differences in trust by information source or content. Studies are also designed very differently, limiting synthesis of results.

RESULTS

We demonstrate a way to address these requirements via a web-based study platform that includes an app that participants use to record topic-specific information exposure, a browser plugin for tracking access to relevant webpages, questionnaires that can be delivered at any time during a study, and app-based incentives for participation such as visual analytics to compare trust levels with other participants. Other features of the platform include the ability to tailor studies to local contexts, ease of use for participants, and frictionless sharing of de-identified data for aggregating individual participant data in international meta-analyses.

CONCLUSIONS

Our proposed solution will be able to capture detailed data about information exposure and health behaviour data, standardise study design while simultaneously supporting localisation, and make it easy to synthesise individual participant data across studies. Future research will need to evaluate the toolkit in realistic scenarios to understand the usability of the toolkit for both participants and investigators.

Establishing Infodemic Management in Germany: A Framework for Social Listening and Integrated Analysis to Report Infodemic Insights at the National Public Health Institute

BACKGROUND

To respond to the need to establish infodemic management functions at the national public health institute in Germany (Robert Koch Institute, RKI), we explored and assessed available data sources, developed a social listening and integrated analysis framework, and defined when infodemic management functions should be activated during emergencies.

OBJECTIVE

We aimed to establish a framework for social listening and integrated analysis for public health in the German context using international examples and technical guidance documents for infodemic management.

METHODS

This study completed the following objectives: identified (potentially) available data sources for social listening and integrated analysis; assessed these data sources for their suitability and usefulness for integrated analysis in addition to an assessment of their risk using the RKI's standardized data protection requirements; developed a framework and workflow to combine social listening and integrated analysis to report back actionable infodemic insights for public health communications by the RKI and stakeholders; and defined criteria for activating integrated analysis structures in the context of a specific health event or health emergency.

RESULTS

We included and classified 38% (16/42) of the identified and assessed data sources for social listening and integrated analysis at the RKI into 3 categories: social media and web-based listening data, RKI-specific data, and infodemic insights. Most data sources can be analyzed weekly to detect current trends and narratives and to inform a timely response by reporting insights that include a risk assessment and scalar judgments of different narratives and themes.

CONCLUSIONS

This study identified, assessed, and prioritized a wide range of data sources for social listening and integrated analysis to report actionable infodemic insights, ensuring a valuable first step in establishing and operationalizing infodemic management at the RKI. This case study also serves as a roadmap for others. Ultimately, once operational, these activities will inform better and targeted public health communication at the RKI and beyond.

Exploring the vaccine conversation on TikTok in Italy: beyond classic vaccine stances

TikTok, a social media platform for creating and sharing short videos, has seen a surge in popularity during the COVID-19 pandemic. To analyse the Italian vaccine conversation on TikTok, we downloaded a sample of videos with a high play count (Top Videos), identified through an unofficial Application Programming Interface (consistent with TikTok's Terms of Service), and collected public videos from vaccine sceptic users through snowball sampling (Vaccine Sceptics' videos). The videos were analysed using qualitative and quantitative methods, in terms of vaccine stance, tone of voice, topic, conformity with TikTok style, and other characteristics. The final datasets consisted of 754 Top Videos (by 510 single users) plus 180 Vaccine Sceptics' videos (by 29 single users), posted between January 2020 and March 2021. In 40.5% of the Top Videos the stance was promotional, 33.9% were indefinite-ironic, 11.3% were neutral, 9.7% were discouraging, and 3.1% were ambiguous (i.e. expressing an ambivalent stance towards vaccines); 43% of promotional videos were from healthcare professionals. More than 95% of the Vaccine Sceptic videos were discouraging. Multiple correspondence analysis showed that, compared to other stances, promotional videos were more frequently created by healthcare professionals and by females, and their most frequent topic was herd immunity. Discouraging videos were associated with a polemical tone of voice and their topics were conspiracy and freedom of choice. Our analysis shows that Italian vaccine-sceptic users on TikTok are limited in number and vocality, and the large proportion of videos with an indefinite-ironic stance might imply that the incidence of affective polarisation could be lower on TikTok, compared to other social media, in the Italian context. Safety is the most frequent concern of users, and we recorded an interesting presence of healthcare professionals among the creators. TikTok should be considered as a medium for vaccine communication and for vaccine promotion campaigns.

Configurational patterns for COVID-19 related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA

Infodemics are intertwined with the COVID-19 pandemic, affecting people's perception and social order. To curb the spread of COVID-19 related false rumors, fuzzy-set qualitative comparative analysis (fsQCA) is used to find configurational pathways to enhance rumor refutation effectiveness. In this paper, a total of 1,903 COVID-19 related false rumor refutation microblogs on Sina Weibo are collected by a web crawler from January 1, 2022 to April 20, 2022, and 10 main conditions affecting rumor refutation effectiveness index (REI) are identified based on "three rules of epidemics". To reduce data redundancy, five ensemble machine learning models are established and tuned, among which Light Gradient Boosting Machine (LGBM) regression model has the best performance. Then five core conditions are extracted by feature importance ranking of LGBM. Based on fsQCA with the five core conditions, REI enhancement can be achieved through three different pathway elements configurations solutions: "Highly influential microblogger * high followers' stickiness microblogger", "high followers' stickiness microblogger * highly active microblogger * concise information description" and "high followers' stickiness microblogger * the sentiment tendency of the topic * concise information description". Finally, decision-making suggestions for false rumor refutation platforms and new ideas for improving false rumor refutation effectiveness are proposed. The innovation of this paper reflects in exploring the REI enhancement strategy from the perspective of configuration for the first time.

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. In this perspective article, we retrace the evolution of LLMs to understand the revolution brought by ChatGPT in the artificial intelligence (AI) field. The opportunities offered by LLMs in supporting scientific research are multiple and various models have already been tested in Natural Language Processing (NLP) tasks in this domain. The impact of ChatGPT has been huge for the general public and the research community, with many authors using the chatbot to write part of their articles and some papers even listing ChatGPT as an author. Alarming ethical and practical challenges emerge from the use of LLMs, particularly in the medical field for the potential impact on public health. Infodemic is a trending topic in public health and the ability of LLMs to rapidly produce vast amounts of text could leverage misinformation spread at an unprecedented scale, this could create an "AI-driven infodemic," a novel public health threat. Policies to contrast this phenomenon need to be rapidly elaborated, the inability to accurately detect artificial-intelligence-produced text is an unresolved issue.

Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference

Background

An infodemic is excess information, including false or misleading information, that spreads in digital and physical environments during a public health emergency. The COVID-19 pandemic has been accompanied by an unprecedented global infodemic that has led to confusion about the benefits of medical and public health interventions, with substantial impact on risk-taking and health-seeking behaviors, eroding trust in health authorities and compromising the effectiveness of public health responses and policies. Standardized measures are needed to quantify the harmful impacts of the infodemic in a systematic and methodologically robust manner, as well as harmonizing highly divergent approaches currently explored for this purpose. This can serve as a foundation for a systematic, evidence-based approach to monitoring, identifying, and mitigating future infodemic harms in emergency preparedness and prevention.

Objective

In this paper, we summarize the Fifth World Health Organization (WHO) Infodemic Management Conference structure, proceedings, outcomes, and proposed actions seeking to identify the interdisciplinary approaches and frameworks needed to enable the measurement of the burden of infodemics.

Methods

An iterative human-centered design (HCD) approach and concept mapping were used to facilitate focused discussions and allow for the generation of actionable outcomes and recommendations. The discussions included 86 participants representing diverse scientific disciplines and health authorities from 28 countries across all WHO regions, along with observers from civil society and global public health-implementing partners. A thematic map capturing the concepts matching the key contributing factors to the public health burden of infodemics was used throughout the conference to frame and contextualize discussions. Five key areas for immediate action were identified.

Results

The 5 key areas for the development of metrics to assess the burden of infodemics and associated interventions included (1) developing standardized definitions and ensuring the adoption thereof; (2) improving the map of concepts influencing the burden of infodemics; (3) conducting a review of evidence, tools, and data sources; (4) setting up a technical working group; and (5) addressing immediate priorities for postpandemic recovery and resilience building. The summary report consolidated group input toward a common vocabulary with standardized terms, concepts, study designs, measures, and tools to estimate the burden of infodemics and the effectiveness of infodemic management interventions.

Conclusions

Standardizing measurement is the basis for documenting the burden of infodemics on health systems and population health during emergencies. Investment is needed into the development of practical, affordable, evidence-based, and systematic methods that are legally and ethically balanced for monitoring infodemics; generating diagnostics, infodemic insights, and recommendations; and developing interventions, action-oriented guidance, policies, support options, mechanisms, and tools for infodemic managers and emergency program managers.

[Impact of COVID-19 on public health in sub-Saharan Africa]

Objective

This work aimed to assess the impact of COVID-19 on healthcare supply in sub-Saharan Africa except South Africa.

Method

A search through PubMed® between April 2020 and August 2022 selected 135 articles. The impact of COVID-19 was assessed on comparisons with the months prior to the onset of COVID-19 or an identical season in previous years.

Results

The decline of health services, associated with a reduction in their quality, and the closure of specialized health units have been reported. Many control programs and public health interventions have been interrupted, with the risk of an increase of the corresponding diseases. Social disorganization has generated mental health issues among the population, including health personnel. The impact was heterogeneous in space and time. The main causes were attributed to containment measures (transport restrictions, trade closures) and the lack of human and material resources. The increase in costs, in addition to the impoverishment of the population, and the fear of being contaminated or stigmatized have discouraged patients from going to health centres. The studies mention the gradual return to normal after the first epidemic wave and the resilience of the healthcare system.

Conclusion

Several articles make recommendations aimed at reducing the impact of future epidemics: support for community workers, training of health workers and reorganization of services to improve the reception and care of patients, technological innovations (use of telephones, drones, etc.) and better information monitoring.

Digital Information Approach through Social Media among Gen Z and Millennials: The Global Scenario during the COVID-19 Pandemic

An infodemic represents a concern for public health, influencing the general population's perceptions of key health issues. Misinformation is rapidly spread by social media, particularly among young generations. We used data from the WHO "Social Media and COVID-19" study, which was conducted in 24 countries worldwide on over 23,000 subjects aged 18-40 years, to explore Generation Z and Millennials' models for health-information-seeking behaviors on social media. We summarized data on the most used sources of information, content of interest, and content sharing, as well as the sentiment toward the infodemic, through descriptive statistics and Chi-square test to verify the differences between groups. Among the survey respondents, 9475 (40.3%) were from high-income countries (HIC), 8000 (34.1%) from upper-middle-income countries (UMIC), and 6007 (25.6%) from lower-middle-income countries (LMIC). Social media were the most used sources of information to retrieve news on COVID-19 disease (about 79% in HIC, 87% in UMIC, and 90% in LIC) and the COVID-19 vaccine (about 78% in HIC and about 88% in UMIC and LIC). More than a half of the young respondents declared that they pay attention to scientific contents (about 51% in HIC, 59% in UMIC, and 55% in LMIC). Finally, most young participants reported feeling overwhelmed by the infodemic. However, this sentiment did not stop them from seeking information about COVID-19. Our findings highlight the importance of shaping public health interventions and campaigns on social media platforms and leveraging scientific contents. Public health authorities should work also on strategies to improve the digital literacy of the population as a driving force to empower them and achieve better health outcomes.

Structural Analysis of the Health Literacy Facet Access to Information on General Health, COVID-19 Infection Prevention, and Early Childhood Allergy Prevention in Pregnant Women and Mothers of Infants

Abstract. The health literacy (HL) facet Access to health information is measured in the European Health Literacy Survey (HLS-EU-Q47) by 12 items. To assess Access, we developed adapted item formulations for COVID-19 infection prevention (COVID-19-IP) and early childhood allergy prevention (ECAP) in addition to the original 12 items on General Health (GH). N = 343 (expectant) mothers of infants answered the items in an online assessment. Confirmatory structural analyses for ordinal data were adopted (WLSMV-algorithm). Women’s item ratings varied significantly across domains (η2 = .017 – .552). Bi-factor models exhibited the best data fit (GH / COVID-19-IP / ECAP: CFI = .964 / .968 / .977; SRMR: .062 / .069 / .035): The general factor Access most strongly determined item information. Additionally, three subfactors contributed significantly (but rather weakly) to the item information in each domain. The overall score Access proved to be internally consistent (McDonald’s ωGH/COVID-19-IP/ECAP = .874 / .883 / .897) and was associated with socioeconomic state (McArthur scale; rGH/COVID-19-IP/ECAP = .218 / .210 / .146). Access correlated not or only weakly with the other HL facets Understand, Appraise, and Apply. The health domains GH, COVID-19-IP, and ECAP moderated both the difficulty and the dimensional structure of the 12 Access items. This suggests that in the HLS-EU Access reflects not only the search competence but also the availability of health information.

The Preventive Health Professions in Italy: The Efficient Use of Resources, Skills and Best Practice during the Pandemic

Health visitors (HVs) and environmental health officers (EHOs) are the healthcare workers (HCWs) who, in the Italian National Health Service, mainly operate in the prevention departments of local health authorities, guaranteeing the territorial activities specifically declared with the respective professional profiles. During the SARS-CoV-2 pandemic, it was necessary to reallocate all HCWs supporting Hygiene and Public Health Services involved on the front lines of the emergency, in order to perform preventive activities and to take immediate action to fight the spread of the virus. By means of an IT survey consisting of three sections, this study investigated how 960 HVs and EHOs dealt with this reallocation, with the shifting in service assignment, and with the perceived level of fatigue and pressure, through the application of skills acquired from university training. The synergy among the preventive health professions, the ability to work in a multi-professional team, and the complementary training of HCWs represent the main strengths for overcoming future public health challenges, aimed at protecting human health.

Acceptance of COVID-19 Vaccine Booster Doses Using the Health Belief Model: A Cross-Sectional Study in Low-Middle- and High-Income Countries of the East Mediterranean Region

Coronavirus disease (COVID-19) booster doses decrease infection transmission and disease severity. This study aimed to assess the acceptance of COVID-19 vaccine booster doses in low, middle, and high-income countries of the East Mediterranean Region (EMR) and its determinants using the health belief model (HBM). In addition, we aimed to identify the causes of booster dose rejection and the main source of information about vaccination. Using the snowball and convince sampling technique, a bilingual, self-administered, anonymous questionnaire was used to collect the data from 14 EMR countries through different social media platforms. Logistic regression analysis was used to estimate the key determinants that predict vaccination acceptance among respondents. Overall, 2327 participants responded to the questionnaire. In total, 1468 received compulsory doses of vaccination. Of them, 739 (50.3%) received booster doses and 387 (26.4%) were willing to get the COVID-19 vaccine booster doses. Vaccine booster dose acceptance rates in low, middle, and high-income countries were 73.4%, 67.9%, and 83.0%, respectively (p < 0.001). Participants who reported reliance on information about the COVID-19 vaccination from the Ministry of Health websites were more willing to accept booster doses (79.3% vs. 66.6%, p < 0.001). The leading causes behind booster dose rejection were the beliefs that booster doses have no benefit (48.35%) and have severe side effects (25.6%). Determinants of booster dose acceptance were age (odds ratio (OR) = 1.02, 95% confidence interval (CI): 1.01-1.03, p = 0.002), information provided by the Ministry of Health (OR = 3.40, 95% CI: 1.79-6.49, p = 0.015), perceived susceptibility to COVID-19 infection (OR = 1.88, 95% CI: 1.21-2.93, p = 0.005), perceived severity of COVID-19 (OR = 2.08, 95% CI: 137-3.16, p = 0.001), and perceived risk of side effects (OR = 0.25, 95% CI: 0.19-0.34, p < 0.001). Booster dose acceptance in EMR is relatively high. Interventions based on HBM may provide useful directions for policymakers to enhance the population's acceptance of booster vaccination.

Emotional profiling and cognitive networks unravel how mainstream and alternative press framed AstraZeneca, Pfizer and COVID-19 vaccination campaigns

COVID-19 vaccines have been largely debated by the press. To understand how mainstream and alternative media debated vaccines, we introduce a paradigm reconstructing time-evolving narrative frames via cognitive networks and natural language processing. We study Italian news articles massively re-shared on Facebook/Twitter (up to 5 million times), covering 5745 vaccine-related news from 17 news outlets over 8 months. We find consistently high trust/anticipation and low disgust in the way mainstream sources framed "vaccine/vaccino". These emotions were crucially missing in alternative outlets. News titles from alternative sources framed "AstraZeneca" with sadness, absent in mainstream titles. Initially, mainstream news linked mostly "Pfizer" with side effects (e.g. "allergy", "reaction", "fever"). With the temporary suspension of "AstraZeneca", negative associations shifted: Mainstream titles prominently linked "AstraZeneca" with side effects, while "Pfizer" underwent a positive valence shift, linked to its higher efficacy. Simultaneously, thrombosis and fearful conceptual associations entered the frame of vaccines, while death changed context, i.e. rather than hopefully preventing deaths, vaccines could be reported as potential causes of death, increasing fear. Our findings expose crucial aspects of the emotional narratives around COVID-19 vaccines adopted by the press, highlighting the need to understand how alternative and mainstream media report vaccination news.

Therapeutic strategies to address monkeypox

Introduction

Monkeypox is a viral zoonosis, with symptoms similar to those seen in smallpox patients, although the clinical presentation may be less severe. Until recently, human monkeypox infection was rare, and primarily occurred in Central and West Africa.

Areas covered

An international outbreak began in May 2022, and monkeypox has now been detected on every continent except Antarctica. The first recognized case from the current outbreak was confirmed in the United Kingdom on 6 May 2022, in an adult with travel links to Nigeria, but it has been suggested that cases had been spreading in Europe for months. On 23 July 2022 the Director-General of the World Health Organization declared the monkeypox outbreak a public health emergency of international concern.

Expert opinion

There are no treatments specifically for monkeypox virus infections. However, monkeypox and smallpox viruses are genetically similar, and therapeutics developed to combat smallpox may be used to treat monkeypox. This manuscripts reviews what is known about these potential treatments, including tecovirimat and brincidofovir, based on a literature search of PubMed through 9 August 2022, and explores how these therapeutics may be used in the future to address the expanding monkeypox pandemic.

Conspiracy theories and social media platforms

Conspiracy theories proliferate online. We provide an overview of information consumption patterns related to conspiracy content on four mainstream social media platforms (Facebook, Twitter, YouTube, and Reddit), with a focus on niche ones. Opinion polarisation and echo chambers appear as pivotal elements of communication around conspiracy theories. A relevant role may also be played by the content moderation policies enforced by each social media platform. Banning contents or users from a social media could lead to a level of user segregation that goes beyond echo chambers and reaches the entire social media space, up to the formation of 'echo platforms'. The insurgence of echo platforms is a new online phenomenon that needs to be investigated as it could foster many dangerous phenomena that we observe online, including the spreading of conspiracy theories.

Dynamical intervention planning against COVID-19-like epidemics

COVID-19 has got us to face a new situation where, for the lack of ready-to-use vaccines, it is necessary to support vaccination with complex non-pharmaceutical strategies. In this paper, we provide a novel Mixed Integer Nonlinear Programming formulation for fine-grained optimal intervention planning (i.e., at the level of the single day) against newborn epidemics like COVID-19, where a modified SIR model accounting for heterogeneous population classes, social distancing and several types of vaccines (each with its efficacy and delayed effects), allows us to plan an optimal mixed strategy (both pharmaceutical and non-pharmaceutical) that takes into account both the vaccine availability in limited batches at selected time instants and the need for second doses while keeping hospitalizations and intensive care occupancy below a threshold and requiring that new infections die out at the end of the planning horizon. In order to show the effectiveness of the proposed formulation, we analyze a case study for Italy with realistic parameters.

COVID-19 infodemic on Facebook and containment measures in Italy, United Kingdom and New Zealand

The COVID-19 pandemic has been characterized by a social media “infodemic”: an overabundance of information whose authenticity may not always be guaranteed. With the potential to lead individuals to harmful decisions for the society, this infodemic represents a severe threat to information security, public health and democracy. In this paper, we assess the interplay between the infodemic and specific aspects of the pandemic, such as the number of cases, the strictness of containment measures, and the news media coverage. We perform a comparative study on three countries that employed different managements of the COVID-19 pandemic in 2020—namely Italy, the United Kingdom, and New Zealand. We first analyze the three countries from an epidemiological perspective to characterize the impact of the pandemic and the strictness of the restrictions adopted. Then, we collect a total of 6 million posts from Facebook to describe user news consumption behaviors with respect to the reliability of such posts. Finally, we quantify the relationship between the number of posts published in each of the three countries and the number of confirmed cases, the strictness of the restrictions adopted, and the online news media coverage about the pandemic. Our results show that posts referring to reliable sources are consistently predominant in the news circulation, and that users engage more with reliable posts rather than with posts referring to questionable sources. Furthermore, our modelling results suggest that factors related to the epidemiological and informational ecosystems can serve as proxies to assess the evolution of the infodemic.

Digital Strategy and Social Media for Infectious Diseases

This supplement demonstrates the profound reach of social media across several domains: improved clinical care and advocacy, data analysis, broad reach to diverse patient populations, educational access, best practices in medical education, peer review, digital strategy for individuals and institutions, and combating misinformation.

The impact of COVID-19 on routine vaccinations in Taiwan and an unexpected surge of pneumococcal vaccination

The coronavirus disease 2019 (COVID-19) pandemic has had substantial impacts, including disruptions in routine vaccinations. In Taiwan, COVID-19 was relatively controllable, and the reduction in routine vaccinations was not profound. The impact of the pandemic on vaccination remained unclear. We collected vaccination uptake data at our hospital and analyzed the weekly trends of different vaccines. We calculated the monthly number of vaccinations and compared consumption before and during the COVID-19 pandemic (year 2019 vs years 2020 and 2021). Except for self-paid pneumococcal conjugate vaccines (PCV13), a mild (14.6%, p < .001) monthly decrease in government-funded routine vaccination and a moderate (28.2%, p = .018) monthly decrease in self-paid vaccination were observed during the COVID-19 pandemic. Interestingly, an unexpected surge of PCV13 vaccination occurred with a 355.8% increase. The shortage of COVID-19 vaccines and the potential benefits of PCV13 against COVID-19 may have contributed to this surge. In conclusion, our study found an obvious disruption of vaccination rates in Taiwan during the COVID-19 epidemic. However, an increase in PCV13 vaccination was also observed, and the important role of the infodemic was emphasized.

Cognitive Networks Extract Insights on COVID-19 Vaccines from English and Italian Popular Tweets: Anticipation, Logistics, Conspiracy and Loss of Trust

Monitoring social discourse about COVID-19 vaccines is key to understanding how large populations perceive vaccination campaigns. This work reconstructs how popular and trending posts framed semantically and emotionally COVID-19 vaccines on Twitter. We achieve this by merging natural language processing, cognitive network science and AI-based image analysis. We focus on 4765 unique popular tweets in English or Italian about COVID-19 vaccines between December 2020 and March 2021. One popular English tweet contained in our data set was liked around 495,000 times, highlighting how popular tweets could cognitively affect large parts of the population. We investigate both text and multimedia content in tweets and build a cognitive network of syntactic/semantic associations in messages, including emotional cues and pictures. This network representation indicates how online users linked ideas in social discourse and framed vaccines along specific semantic/emotional content. The English semantic frame of “vaccine” was highly polarised between trust/anticipation (towards the vaccine as a scientific asset saving lives) and anger/sadness (mentioning critical issues with dose administering). Semantic associations with “vaccine,” “hoax” and conspiratorial jargon indicated the persistence of conspiracy theories and vaccines in extremely popular English posts. Interestingly, these were absent in Italian messages. Popular tweets with images of people wearing face masks used language that lacked the trust and joy found in tweets showing people with no masks. This difference indicates a negative effect attributed to face-covering in social discourse. Behavioural analysis revealed a tendency for users to share content eliciting joy, sadness and disgust and to like sad messages less. Both patterns indicate an interplay between emotions and content diffusion beyond sentiment. After its suspension in mid-March 2021, “AstraZeneca” was associated with trustful language driven by experts. After the deaths of a small number of vaccinated people in mid-March, popular Italian tweets framed “vaccine” by crucially replacing earlier levels of trust with deep sadness. Our results stress how cognitive networks and innovative multimedia processing open new ways for reconstructing online perceptions about vaccines and trust.

Exploring the Association between Misinformation Endorsement, Opinions on the Government Response, Risk Perception, and COVID-19 Vaccine Hesitancy in the US, Canada, and Italy

The COVID-19 pandemic has highlighted the adverse consequences created by an infodemic, specifically bringing attention to compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between the perceived risk of COVID-19, level of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2697 respondents from the US, Canada, and Italy using a mobile platform between 21–28 May 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement were associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response and higher misinformation endorsement were associated with higher hesitancy.