Misinformation about science in the public sphere

Perceived experts are prevalent and influential within an antivaccine community on Twitter

Perceived experts (i.e. medical professionals and biomedical scientists) are trusted sources of medical information who are especially effective at encouraging vaccine uptake. The role of perceived experts acting as potential antivaccine influencers has not been characterized systematically. We describe the prevalence and importance of antivaccine perceived experts by constructing a coengagement network of 7,720 accounts based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the antivaccine community. Perceived experts had a sizable presence across the coengagement network, including within the antivaccine community where they were 9.8% of individual, English-language users. Perceived experts within the antivaccine community shared low-quality (misinformation) sources at similar rates and academic sources at higher rates compared to perceived nonexperts in that community. Perceived experts occupied important network positions as central antivaccine users and bridges between the antivaccine and provaccine communities. Using propensity score matching, we found that perceived expertise brought an influence boost, as perceived experts were significantly more likely to receive likes and retweets in both the antivaccine and provaccine communities. There was no significant difference in the magnitude of the influence boost for perceived experts between the two communities. Social media platforms, scientific communications, and biomedical organizations may focus on more systemic interventions to reduce the impact of perceived experts in spreading antivaccine misinformation.

Naïve information aggregation in human social learning

To glean accurate information from social networks, people should distinguish evidence from hearsay. For example, when testimony depends on others' beliefs as much as on first-hand information, there is a danger of evidence becoming inflated or ignored as it passes from person to person. We compare human inferences with an idealized rational account that anticipates and adjusts for these dependencies by evaluating peers' communications with respect to the underlying communication pathways. We report on three multi-player experiments examining the dynamics of both mixed human-artificial and all-human social networks. Our analyses suggest that most human inferences are best described by a naïve learning account that is insensitive to known or inferred dependencies between network peers. Consequently, we find that simulated social learners that assume their peers behave rationally make systematic judgment errors when reasoning on the basis of actual human communications. We suggest human groups learn collectively through naïve signaling and aggregation that is computationally efficient and surprisingly robust. Overall, our results challenge the idea that everyday social inference is well captured by idealized rational accounts and provide insight into the conditions under which collective wisdom can emerge from social interactions.

Demography as a Field: Where We Came From and Where We Are Headed

This essay provides a series of reflections on the current state of demography as seen by four early-career researchers who are actively engaged in aspects of the discipline as varied as research, teaching, mentorship, data collection efforts, policy making, and policy advising. Despite some claims that the discipline is weakening, we showcase the great potential of the field and outline promising pathways and novel directions for the future. In so doing, we critically assess recent innovations in data quality and availability, stressing the need to "revolutionize" the way that demographic methods are taught by adopting a viewpoint that more closely reflects the rapidly changing, or "fast," nature of global social phenomena such as conflict-related displacements, environmental disasters, migration streams, pandemics, and evolving population policies. We conclude by discussing the relevance of careful demographic analyses for policy making, stressing three main points: (i) the need to make demography more visible and understandable to the public eye; (ii) the importance of engaging and co-creating with local communities to "break" the academic bubble; and (iii) the urge to counteract the spread of misinformation-a phenomenon that has become even more visible in the aftermath of the COVID-19 outbreak.

Dynamics and characteristics of misinformation related to earthquake predictions on Twitter

The spread of misinformation on social media can lead to inappropriate behaviors that can make disasters worse. In our study, we focused on tweets containing misinformation about earthquake predictions and analyzed their dynamics. To this end, we retrieved 82,129 tweets over a period of 2 years (March 2020-March 2022) and hand-labeled 4157 tweets. We used RoBERTa to classify the complete dataset and analyzed the results. We found that (1) there are significantly more not-misinformation than misinformation tweets; (2) earthquake predictions are continuously present on Twitter with peaks after felt events; and (3) prediction misinformation tweets sometimes link or tag official earthquake notifications from credible sources. These insights indicate that official institutions present on social media should continuously address misinformation (even in quiet times when no event occurred), check that their institution is not tagged/linked in misinformation tweets, and provide authoritative sources that can be used to support their arguments against unfounded earthquake predictions.

Science Communication Training Imparts Confidence and Influences Public Engagement Activity

The impacts of science are felt across all socio-ecological levels, ranging from the individual to societal. In order to adapt or respond to scientific discoveries, novel technologies, or biomedical or environmental challenges, a fundamental understanding of science is necessary. However, antiscientific rhetoric, mistrust in science, and the dissemination of misinformation hinder the promotion of science as a necessary and beneficial component of our world. Scientists can promote scientific literacy by establishing dialogues with nonexperts, but they may find a lack of formal training as a barrier to public engagement. To address this, the American Society for Biochemistry and Molecular Biology (ASBMB) launched the Art of Science Communication course in 2015 in order to provide scientists at all career stages with introductory science communication training. In 2020, we conducted a retrospective survey of former participants to evaluate how the course had impacted participants' science communication behaviors and their confidence engaging with nonexperts, as well as other benefits to their professional development. We found that scientists were significantly more likely to communicate with nonexpert audiences following the course compared to before (77% versus 51%; P < 0.0001). In addition, quantitative and qualitative data suggested that scientists were more confident in their ability to communicate science after completing the course (median of 8, standard deviation [SD] of 0.98 versus median of 5, SD of 1.57; P < 0.0001). Qualitative responses from participants supported quantitative findings. This suggested that the Art of Science Communication course is highly effective at improving the confidence of scientists to engage with the public and other nonexpert audiences regardless of career status. These data-driven perspectives provide a rationale for the implementation of broadly accessible science communication training programs that promote public engagement with science.

Is the COVID-19 bad news game good news? Testing whether creating and disseminating fake news about vaccines in a computer game reduces people's belief in anti-vaccine arguments

Improving vaccination eagerness is crucial, especially during the ongoing COVID-19 pandemic and establishing new procedures to achieve that goal is highly important. Previous research (Roozenbeek & van der Linden, 2019a, 2019b) has indicated that playing the "Bad News" game, in which a player spreads fake news to gain followers, reduces people's belief in fake news. The goal of the present paper was to test an analogous new game called "COVID-19 Bad News (CBN)" to improve one's eagerness to vaccinate against coronavirus. CBN was constructed to examine whether creating and disseminating fake news focused on vaccinations and the COVID-19 pandemic has a similar effect and improves people's attitudes toward vaccination. Two experiments were conducted where participants played CBN or Tetris and afterwards evaluated the credibility of statements about vaccines against COVID-19 and finally filled out a questionnaire concerning their attitudes toward vaccination. The results show that playing CBN does not reduce evaluations of the credibility of all statements that are unfavorable to vaccines (false as well as true). Additionally, it does not enhance readiness to vaccinate. Future research and limitations are discussed.

The Need for Systems Approaches for Precision Communications in Public Health

A major challenge in communicating health-related information is the involvement of multiple complex systems from the creation of the information to the sources and channels of dispersion to the information users themselves. To date, public health communications approaches have often not adequately accounted for the complexities of these systems to the degree necessary to have maximum impact. The virality of COVID-19 misinformation and disinformation has brought to light the need to consider these system complexities more extensively. Unaided, it is difficult for humans to see and fully understand complex systems. Luckily, there are a range of systems approaches and methods, such as systems mapping and systems modeling, that can help better elucidate complex systems. Using these methods to better characterize the various systems involved in communicating public health-related information can lead to the development of more tailored, precise, and proactive communications. Proceeding in an iterative manner to help design, implement, and adjust such communications strategies can increase impact and leave less opportunity for misinformation and disinformation to spread.

Partisan polarization, historical heritage, and public health: Exploring COVID-19 outcomes

When the COVID-19 virus first arrived in the United States in early 2020, many epidemiologists and public health officers counseled for shutdowns and advised policymakers to prepare for a major pandemic. In 2020, though, US society was rife with major political and cultural divides. Some elected leaders promoted policies at odds with the experts, and many people refused to heed the public health-based communications about the coming pandemic. Additionally, the capacity to respond to a pandemic was distributed in the country in a highly unequal fashion. This paper analyzes the noteworthy geopolitical patterns of COVID-19 illnesses, subsequent demands on hospitals, and resulting deaths. This description is based on a snapshot of archival data gathered in the midst of the pandemic during late January and early February of 2021. Demographic data, indicators of political party support, indicators of citizen attitudes, and public health compliance behaviors are combined in a multivariate analysis to explain COVID-19 outcomes at the local government (county) level. The analysis suggests strongly that regional political culture and local demographics played a substantial role in determining the severity of the public health impact of the COVID-19 pandemic.

We Need to Do Better: Five Notable Failings in Science Communication

Despite significant growth in interest and investment in science communication, the field has demonstrated some high-profile failures in recent years—exemplified by anti-vaccine and anti-climate change beliefs—supported by interest groups that are often highly effective at promoting anti-science messages. This paper looks at five key areas where science communication research and practice need to do better, and offers some solutions, in order to achieve the impact that science communicators strive for.

Multiplicity and dynamics of social representations of the COVID-19 pandemic on Chinese social media from 2019 to 2020

Documenting the emergent social representations of COVID-19 in public communication is necessary for critically reflecting on pandemic responses and providing guidance for global pandemic recovery policies and practices. This study documents the dynamics of changing social representations of the COVID-19 pandemic on one of the largest Chinese social media, Weibo, from December 2019 to April 2020. We draw on the social representation theory (SRT) and conceptualize topics and topic networks as a form of social representation. We analyzed a dataset of 40 million COVID-19 related posts from 9.7 million users (including the general public, opinion leaders, and organizations) using machine learning methods. We identified 12 topics and found an expansion in social representations of COVID-19 from a clinical and epidemiological perspective to a broader perspective that integrated personal illness experiences with economic and sociopolitical discourses. Discussions about COVID-19 science did not take a prominent position in the representations, suggesting a lack of effective science and risk communication. Further, we found the strongest association of social representations existed between the public and opinion leaders and the organizations’ representations did not align much with the other two groups, suggesting a lack of organizations’ influence in public representations of COVID-19 on social media in China.

Mis-Dis Information in COVID-19 Health Crisis: A Narrative Review

Background: In this narrative review, we address the COVID-19 pandemic mis–dis information crisis in which healthcare systems have been pushed to their limits, with collapses occurring worldwide. The context of uncertainty has resulted in skepticism, confusion, and general malaise among the population. Informing the public has been one of the major challenges during this pandemic. Misinformation is defined as false information shared by people who have no intention of misleading others. Disinformation is defined as false information deliberately created and disseminated with malicious intentions. Objective: To reach a consensus and critical review about mis–dis information in COVID-19 crisis. Methods: A database search was conducted in PsychINFO, MedLine (Pubmed), Cochrane (Wiley), Embase and CinAhl. Databases used the MeSH-compliant keywords of COVID-19, 2019-nCoV, Coronavirus 2019, SARS-CoV-2, misinformation, disinformation, information, vaccines, vaccination, origin, target, spread, communication. Results: Both misinformation and disinformation can affect the population’s confidence in vaccines (development, safety, and efficacy of vaccines, as well as denial of the severity of SARS-CoV infection). Institutions should take into account that a great part of the success of the intervention to combat a pandemic has a relationship with the power to stop the misinformation and disinformation processes. The response should be well-structured and addressed from different key points: central level and community level, with official and centralized communication channels. The approach should be multifactorial and enhanced by the collaboration of social media companies to stop misleading information, and trustworthy people both working or not working in the health care systems to boost the power of the message. Conclusions: The response should be well-structured and addressed from different key points: central level and community level, with official and clearly centralized communication channels. The approach should be multifactorial and enhanced from the collaboration of social media companies to stop misleading information, and trustworthy people both working and not working in the health care systems to boost the power of a message based on scientific evidence.

Ivermectin for the Treatment of Coronavirus Disease 2019: A Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

We systematically assessed benefits and harms of the use of ivermectin (IVM) in patients with coronavirus disease 2019 (COVID-19).

METHODS

Published and preprint randomized controlled trials (RCTs) assessing the effects of IVM on adult patients with COVID-19 were searched until 22 March 2021 in 5 engines. Primary outcomes were all-cause mortality rate, length of hospital stay (LOS), and adverse events (AEs). Secondary outcomes included viral clearance and severe AEs (SAEs). The risk of bias (RoB) was evaluated using the Cochrane Risk of Bias 2.0 tool. Inverse variance random effect meta-analyses were performed, with quality of evidence (QoE) evaluated using GRADE methods.

RESULTS

Ten RCTs (n = 1173) were included. The controls were the standard of care in 5 RCTs and placebo in 5. COVID-19 disease severity was mild in 8 RCTs, moderate in 1, and mild and moderate in 1. IVM did not reduce all-cause mortality rates compared with controls (relative risk [RR], 0.37 [95% confidence interval, .12-1.13]; very low QoE) or LOS compared with controls (mean difference, 0.72 days [95% confidence interval, -.86 to 2.29 days]; very low QoE). AEs, SAEs, and viral clearance were similar between IVM and control groups (low QoE for all outcomes). Subgroups by severity of COVID-19 or RoB were mostly consistent with main analyses; all-cause mortality rates in 3 RCTs at high RoB were reduced with IVM.

CONCLUSIONS

Compared with the standard of care or placebo, IVM did not reduce all-cause mortality, LOS, or viral clearance in RCTs in patients with mostly mild COVID-19. IVM did not have an effect on AEs or SAEs and is not a viable option to treat patients with COVID-19.