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We examined how age and exposure to different types of COVID-19 (mis)information affect misinformation beliefs, perceived credibility of the message and intention-to-share it on WhatsApp. Through two mixed-design online experiments in the UK and Brazil (total N = 1454) we first randomly exposed adult WhatsApp users to full misinformation, partial misinformation, or full truth about the therapeutic powers of garlic to cure COVID-19. We then exposed all participants to corrective information from the World Health Organisation debunking this claim. We found stronger misinformation beliefs among younger adults (18–54) in both the UK and Brazil and possible backfire effects of corrective information among older adults (55+) in the UK. Corrective information from the WHO was effective in enhancing perceived credibility and intention-to-share of accurate information across all groups in both countries. Our findings call for evidence-based infodemic interventions by health agencies, with greater engagement of younger adults in pandemic misinformation management efforts.

Social media analytics enable public health institutions to quickly learn what information is being disseminated, and by whom, regarding infectious diseases. Such information can help public health institutions identify and engage with news media and other active information providers. It also provides insights into media and public concerns, accuracy of information on Twitter, and information gaps. The study identifies implications for pandemic preparedness and response in the digital era and presents the agenda for future research and practice.

Social media have transformed traditional configurations of how risk signals related to an infectious disease outbreak (IDO) are transmitted from public health authorities to the general public. However, our understanding of how social media might influence risk perceptions during these situations, and the influence of such processes on ensuing societal responses remains limited. This paper draws on key ideas from the Social Amplification of Risk Framework (SARF), Socially Mediated Crisis Communication (SMCC) model and a case study of the US Centers for Disease Control and Prevention’s (CDC) social media management of the 2009 H1N1 pandemic to propose a new conceptual model. The Risk Amplification through Media Spread (RAMS) model brings clarity to the new complexities in media management of IDOs by delineating the processes of message diffusion and risk amplification through communication channels that are often highly integrated due to social media. The model offers recommendations for communication priorities during different stages of an IDO. The paper concludes with a discussion of the RAMS model from theoretical and applied perspectives, and sets the direction for future conceptual refinement and empirical testing.

The public health communication challenges that arise in times of infectious disease threats (IDTs) were examined using the Risk Amplification through Media Spread (RAMS) Framework and in-depth phone interviews with 40 national, state, and local public health information officers (PIOs). Interviewees shared their experiences and insights related to how IDTs are communicated to the public, including the different types of traditional and social media used, how they develop and assess IDT messages, and their perceptions regarding the IDT risk amplification process. Theoretical and practical implications for health public relations and public health communication are discussed.