The Future of Infodemic Surveillance as Public Health Surveillance

#SharingHEOR: Developing Modern Media for Communication and Dissemination of Health Economics and Outcomes Research

Questions regarding the effectiveness and safety of health interventions and allocation of health care resources are frequently discussed in mainstream and social media. Additionally, government and foundation funders are increasingly mandating that results be disseminated to the lay public and patients may benefit from being able to digest scientific research regarding their health conditions. Therefore, it is important to widely disseminate and clearly communication health economics and outcomes research (HEOR) findings to a range of interested parties. Digital media features such as graphical or visual abstracts, infographics and videos are informative and add value to research articles by improving reader engagement with articles, potentially increasing their impact, and allowing results to be more widely disseminated. However, use of novel digital media for research dissemination has been relatively limited to date. In this article, we discuss the rationale for developing novel media to communicate and disseminate research findings and offer practical advice for doing so. We conclude by outlining a future agenda for research regarding HEOR communication and dissemination.

The role of the (in)accessibility of social media data for infodemic management: a public health perspective on the situation in the European Union in March 2024

Public health institutions rely on the access to social media data to better understand the dynamics and impact of infodemics - an overabundance of information during a disease outbreak, potentially including mis-and disinformation. The scope of the COVID-19 infodemic has led to growing concern in the public health community. The spread of harmful information or information voids may negatively impact public health. In this context, social media are of particular relevance as an integral part of our society, where much information is consumed. In this perspective paper, we discuss the current state of (in)accessibility of social media data of the main platforms in the European Union. The European Union's relatively new Digital Services Act introduces the obligation for platforms to provide data access to a wide range of researchers, likely including researchers at public health institutions without formal academic affiliation. We examined eight platforms (Facebook, Instagram, LinkedIn, Pinterest, Snapchat, TikTok, X, YouTube) affected by the new legislation in regard to data accessibility. We found that all platforms apart from TikTok offer data access through the Digital Services Act. Potentially, this presents a fundamentally new situation for research, as before the Digital Services Act, few platforms granted data access or only to very selective groups of researchers. The access regime under the Digital Services Act is, however, still evolving. Specifics such as the application procedure for researcher access are still being worked out and results can be expected in spring 2024. The impact of the Digital Services Act on research will therefore only become fully apparent in the future.

Strengthening COVID-19 vaccine confidence & demand during the US COVID-19 emergency response

In October 2020, the CDC's Vaccinate with Confidence strategy specific to COVID-19 vaccines rollout was published. Adapted from an existing vaccine confidence framework for childhood immunization, the Vaccinate with Confidence strategy for COVID-19 aimed to improve vaccine confidence, demand, and uptake of COVID-19 vaccines in the US. The objectives for COVID-19 were to 1. build trust, 2. empower healthcare personnel, and 3. engage communities and individuals. This strategy was implemented through a dedicated unit, the Vaccine Confidence and Demand (VCD) team, which collected behavioral insights; developed and disseminated toolkits and best practices in collaboration with partners; and collaborated with health departments and community-based organizations to engage communities and individuals in behavioral interventions to strengthen vaccine demand and increase COVID-19 vaccine uptake. The VCD team collected and used social and behavioral data through establishing the Insights Unit, implementing rapid community assessments, and conducting national surveys. To strengthen capacity at state and local levels, the VCD utilized "Bootcamps," a rapid training of trainers on vaccine confidence and demand, "Confidence Consults", where local leaders could request tailored advice to address local vaccine confidence challenges from subject matter experts, and utilized surge staffing to embed "Vaccine Demand Strategists" in state and local public health agencies. In addition, collaborations with Prevention Research Centers, the Institute of Museum and Library Services, and the American Psychological Association furthered work in behavioral science, community engagement, and health equity. The VCD team operationalized CDC's COVID-19 Vaccine with Confidence strategy through behavioral insights, capacity building opportunities, and collaborations to improve COVID-19 vaccine confidence, demand, and uptake in the US. The inclusion of applied behavioral science approaches were a critical component of the COVID-19 vaccination program and provides lessons learned for how behavioral science can be integrated in future emergency responses.

Ivermectin prescription fill rates among U.S. Military members during the coronavirus disease 2019 (COVID-19) pandemic

This report describes ivermectin prescription fill rates among U.S. active component service members (ACSM) over time during the early phases of the COVID-19 pandemic. Information about the unsubstantiated benefits of ivermectin for coronavirus 2019 (COVID-19) prevention and treatment was widely available online early in the COVID-19 pandemic. Ivermectin prescription fill rates increased among ACSM during periods of Alpha and Delta coronavirus variant predominance, but not during the predominance of the Omicron variant. At the peak of the fill rate curve, in August 2021, rates were higher among men compared to women, older compared to younger age groups, senior officers compared to junior officers, senior enlisted compared to junior enlisted service members, and those with a bachelor's or advanced degree compared to those without a bachelor's degree. Ivermectin prescriptions were more likely to have been filled at a retail pharmacy than at a military hospital or clinic. During the COVID-19 pandemic fill rates for ivermectin prescriptions among ACSM increased, including those without a qualifying diagnosis. Rates peaked in August 2021 but subsequently declined. The decrease in ivermectin fill rates was coincident with vigorous efforts to correct previous misinformation and implement pre-authorization requirements for prescriptions. Research on the impact of unproven online claims about clinical and public health interventions has potential to curtail future unnecessary and potentially harmful treatments.

Informing social media analysis for public health: a cross-sectional survey of professionals

BACKGROUND

During the COVID-19 pandemic, the field of infodemic management has grown in response to urgent global need. Social listening is the first step in managing the infodemic, and many organizations and health systems have implemented processes. Social media analysis tools have traditionally been developed for commercial purposes, rather than public health, and little is known of the experiences and needs of those professionals using them for infodemic management.

METHODS

We developed a cross sectional survey and distributed through global infodemic management networks between December 2022 and February 2023. Questions were structured over four sections related to work-practice and user needs and did not collect any personal details from participants. Descriptive analysis was conducted on the study results. Qualitative analysis was used to categorise and understand answers to open-text questions.

RESULTS

There were 417 participants, 162/417 who completed all survey questions, and 255/417 who completed some, all responses are included in analysis. Respondents came from all global regions and a variety of workplaces. Participants had an average of 4.4 years' experience in the analysis of social media for public health. COVID-19 was the most common health issue people had conducted social media analysis for. Results reveal a range of training, technical capacity, and support needs.

CONCLUSIONS

This paper is the first we are aware of to seek and describe the needs of those using social media analysis platforms for public health purposes since the start of the COVID-19 pandemic. There are key areas for future work and research, including addressing the training, capacity building and leadership needs of those working in this space, and the need to facilitate easier access to better platforms for performing social media analysis.

Detecting nuance in conspiracy discourse: Advancing methods in infodemiology and communication science with machine learning and qualitative content coding

The spread of misinformation and conspiracies has been an ongoing issue since the early stages of the internet era, resulting in the emergence of the field of infodemiology (i.e., information epidemiology), which investigates the transmission of health-related information. Due to the high volume of online misinformation in recent years, there is a need to continue advancing methodologies in order to effectively identify narratives and themes. While machine learning models can be used to detect misinformation and conspiracies, these models are limited in their generalizability to other datasets and misinformation phenomenon, and are often unable to detect implicit meanings in text that require contextual knowledge. To rapidly detect evolving conspiracist narratives within high volume online discourse while identifying nuanced themes requiring the comprehension of subtext, this study describes a hybrid methodology that combines natural language processing (i.e., topic modeling and sentiment analysis) with qualitative content coding approaches to characterize conspiracy discourse related to 5G wireless technology and COVID-19 on Twitter (currently known as 'X'). Discourse that focused on correcting 5G conspiracies was also analyzed for comparison. Sentiment analysis shows that conspiracy-related discourse was more likely to use language that was analytic, combative, past-oriented, referenced social status, and expressed negative emotions. Corrections discourse was more likely to use words reflecting cognitive processes, prosocial relations, health-related consequences, and future-oriented language. Inductive coding characterized conspiracist narratives related to global elites, anti-vax sentiment, medical authorities, religious figures, and false correlations between technology advancements and disease outbreaks. Further, the corrections discourse did not address many of the narratives prevalent in conspiracy conversations. This paper aims to further bridge the gap between computational and qualitative methodologies by demonstrating how both approaches can be used in tandem to emphasize the positive aspects of each methodology while minimizing their respective drawbacks.

Lessons learnt from the COVID-19 pandemic in selected countries to inform strengthening of public health systems: a qualitative study

INTRODUCTION

The COVID-19 pandemic has prompted governments internationally to consider strengthening their public health systems. To support the work of Ireland's Public Health Reform Expert Advisory Group, the Health Information and Quality Authority, an independent governmental agency, was asked to describe the lessons learnt regarding the public health response to COVID-19 internationally and the applicability of this response for future pandemic preparedness.

METHODS

Semi-structured interviews with key public health representatives from nine countries were conducted. Interviews were conducted in March and April 2022 remotely via Zoom and were recorded. Notes were taken by two researchers, and a thematic analysis undertaken.

RESULTS

Lessons learnt from the COVID-19 pandemic related to three main themes: 1) setting policy; 2) delivering public health interventions; and 3) providing effective communication. Real-time surveillance, evidence synthesis, and cross-sectoral collaboration were reported as essential for policy setting; it was noted that having these functions established prior to the pandemic would lead to a more efficient implementation in a health emergency. Delivering public health interventions such as testing, contact tracing, and vaccination were key to limiting and or mitigating the spread of the SARS-CoV-2 virus. However, a number of challenges were highlighted such as staff capacity and burnout, delays in vaccination procurement, and reduced delivery of regular healthcare services. Clear, consistent, and regular communication of the scientific evidence was key to engaging citizens with mitigation strategies. However, these communication strategies had to compete with an infodemic of information being circulated, particularly through social media.

CONCLUSIONS

Overall, functions relating to policy setting, public health interventions, and communication are key to pandemic response. Ideally, these should be established in the preparedness phase so that they can be rapidly scaled-up during a pandemic.

Addressing Antivaccine Sentiment on Public Social Media Forums Through Web-Based Conversations Based on Motivational Interviewing Techniques: Observational Study

BACKGROUND

Health misinformation shared on social media can have negative health consequences; yet, there is a dearth of field research testing interventions to address health misinformation in real time, digitally, and in situ on social media.

OBJECTIVE

We describe a field study of a pilot program of "infodemiologists" trained with evidence-informed intervention techniques heavily influenced by principles of motivational interviewing. Here we provide a detailed description of the nature of infodemiologists' interventions on posts sharing misinformation about COVID-19 vaccines, present an initial evaluation framework for such field research, and use available engagement metrics to quantify the impact of these in-group messengers on the web-based threads on which they are intervening.

METHODS

We monitored Facebook (Meta Platforms, Inc) profiles of news organizations marketing to 3 geographic regions (Newark, New Jersey; Chicago, Illinois; and central Texas). Between December 2020 and April 2021, infodemiologists intervened in 145 Facebook news posts that generated comments containing either false or misleading information about vaccines or overt antivaccine sentiment. Engagement (emojis plus replies) data were collected on Facebook news posts, the initial comment containing misinformation (level 1 comment), and the infodemiologist's reply (level 2 reply comment). A comparison-group evaluation design was used, with numbers of replies, emoji reactions, and engagements for level 1 comments compared with the median metrics of matched comments using the Wilcoxon signed rank test. Level 2 reply comments (intervention) were also benchmarked against the corresponding metric of matched reply comments (control) using the Wilcoxon signed rank test (paired at the level 1 comment level). Infodemiologists' level 2 reply comments (intervention) and matched reply comments (control) were further compared using 3 Poisson regression models.

RESULTS

In total, 145 interventions were conducted on 132 Facebook news posts. The level 1 comments received a median of 3 replies, 3 reactions, and 7 engagements. The matched comments received a median of 1.5 (median of IQRs 3.75) engagements. Infodemiologists made 322 level 2 reply comments, precipitating 189 emoji reactions and a median of 0.5 (median of IQRs IQR 0) engagements. The matched reply comments received a median of 1 (median of IQRs 2.5) engagement. Compared to matched comments, level 1 comments received more replies, emoji reactions, and engagements. Compared to matched reply comments, level 2 reply comments received fewer and narrower ranges of replies, reactions, and engagements, except for the median comparison for replies.

CONCLUSIONS

Overall, empathy-first communication strategies based on motivational interviewing garnered less engagement relative to matched controls. One possible explanation is that our interventions quieted contentious, misinformation-laden threads about vaccines on social media. This work reinforces research on accuracy nudges and cyberbullying interventions that also reduce engagement. More research leveraging field studies of real-time interventions is needed, yet data transparency by technology platforms will be essential to facilitate such experiments.

Detection of Vaccine Adverse Events Before Package Insert Revisions Using a Japanese Spontaneous Reporting System

The usefulness of disproportionality analysis for the pharmacovigilance of vaccines in the Japanese Adverse Drug Event Report (JADER) database is yet to be proven. This study aimed to verify whether significant disproportionality could be detected before adding new vaccine adverse event information to package inserts. Information on package insert revisions related to vaccine adverse drug events from January 2013 to March 2023 was extracted from the Pharmaceuticals and Medical Devices Agency website. This period was set as the maximum period for which early disproportionalities could be detected by the latest JADER database (April 2004 to December 2022). From JADER data, 15 revision histories (10 types of vaccines) of package inserts were identified, and 823,662 cases were obtained. Of the 15, 12 (80%) adverse events were identified as significant disproportionalities before package insert revisions were made. Nine of the 15 (60%) events were identified as significant disproportionalities earlier than at least 12 months. These findings suggest that the JADER database may detect vaccine adverse events earlier than package insert revisions, indicating its usefulness for the safety surveillance of vaccines.

Addressing Viral Medical Rumors and False or Misleading Information

The rapid spread of medical rumors and false or misleading information on social media during times of uncertainty is a vexing challenge that threatens public health. Understanding the information ecosystem, social media networks, and the scope of incentives that drive users and social media platforms can provide critical insights for strong coordination between stakeholders and funders to address this challenge. The COVID-19 pandemic created an opportunity to demonstrate the role of media monitoring and counter-messaging efforts in responding to dangerous medical rumors, misinformation, and disinformation. It also highlighted the challenges. The efforts of ThisIsOurShot and VacunateYa to spread accurate health information about COVID-19 and COVID-19 vaccines are described and lessons learned are discussed. These lessons include the need for substantial financial investments at the local and national levels to sustain and scale these types of programs. Examples in other fields that offer a path forward include Information Sharing and Analysis Centers and Public Health Emergency Operations Centers. Understanding the scale and scope of what it takes to address viral medical rumors, misinformation, and disinformation in a networked information environment should inspire elected leaders to consider policy and regulatory reforms. Our transformed information ecosystem requires new public health infrastructure to address information that threatens personal safety and population health.

Investigating the aftermath of the Türkiye 2023 earthquake: exploring post-disaster uncertainty among Syrian migrants using social network analysis with public health approach

Objectives

On February 6th, 2023, a doublet earthquake struck Türkiye, impacting more than 15 million people including migrants, and resulting in over 50,000 deaths. The Syrian migrants experience multiple uncertainties in their daily lives which are further compounded by multifaceted challenges of the post-disaster environment. Social media was used intensively and with impunity in this environment and thereby provides a window into the explicit and implicit dynamics of daily life after a disaster. We aimed to explore how a post-disaster environment potentially generates new uncertainties or exacerbating pre-existing ones for migrants through social media analysis with an indirect perspective, in the context of 2023-Earthquake in Türkiye and Syrian migrants.

Methods

Social network analysis was used to analyze Twitter-data with the hashtags 'Syrian' and 'earthquake' during a 10-day period beginning on March 22nd, 2023. We calculated network metrics, including degree-values and betweenness-centrality and clustered the network to understand groups. We analyzed a combination of 27 tweets with summative content analysis using a text analysis tool, to identify the most frequently used words. We identified the main points of each tweet and assessed these as possible contributors to post-disaster uncertainty among migrants by using inductive reasoning.

Results

There were 1918 Twitter users, 274 tweets, 124 replies and 1726 mentions. Discussions about Syrian migrants and earthquakes were established across various groups (ngroups(edges > 15) = 16). Certain users had a greater influence on the overall network. The nine most frequently used words were included under uncertainty-related category (nmost_frequently_used_words = 20); 'aid, vote, house, citizen, Afghan, illegal, children, border, and leave'. Nine main points were identified as possible post-disaster uncertainties among migrants.

Conclusion

The post-disaster environment has the potential to exacerbate existing uncertainties, such as being an undocumented migrant, concerns about deportation and housing, being or having a child, inequality of rights between being a citizen and non-citizen, being in minority within minority, political climate of the host nation and access to education or to generate new ones such equitable distribution of aid, which can lead to poor health outcomes. Recognizing the possible post-disaster uncertainties among migrants and addressing probable underlying factors might help to build more resilient and healthy communities.