RAMS model

Earlier this year in May 2023, I had an opportunity to speak Dr. Santosh Vijayakumar, who is a health and risk communication scientist, and currently an associate professor in the department of Psychology at Nortumbria University, Newcastle (UK). A series of exchanges led me to discover one of his works where he and his colleagues explored the role of social media in shaping public risk perceptions during infectious disease outbreaks. Drawing from previous frameworks and using the 2009 H1N1 pandemic as a case study, they introduce the Risk Amplification through Media Spread (RAMS) model [1]. This model highlights the interconnected nature of social media in amplifying risk perceptions and offers communication strategies for outbreak scenarios. The study underscores the importance of further research on the RAMS model, which also piqued my interest.

To put it simply, the Risk Amplification through Media Spread (RAMS) model is a framework that explains how risk perceptions related to events, like infectious disease outbreaks, are shared and affected through communication channels, mainly social media. The Risk Amplification through Media Spread (RAMS) model offers a deep dive into the dynamics of risk communication. At its foundation, the model identifies primary information sources, mainly stemming from the public health community and the general public. Notably, during significant events like the COVID-19 outbreak, organizations such as the WHO and CDC emerge as primary informants. The model also highlights 'amplification stations'—the boosters of risk information. This category encompasses individuals sharing insights on social media, influencers offering their takes, and traditional news outlets broadcasting updates. Furthermore, in present times, the model underscores the rapid spread of risk messages, where a single tweet or article can swiftly reach vast audiences, amplifying the perceived risk. The RAMS model culminates in its focus on outcomes, which are the tangible and intangible effects of risk communication. These outcomes can manifest as changes in individual and community behaviors, shifts in emotions like heightened fear, and even policy alterations at institutional levels.

Studying the RAMS model empirically helps us see how it works in practice. At the same time, using math helps us understand the model's details better. By using both these methods together, RAMS model could be developed further. In simple terms, empirical data could give us the big picture, and math could fill in the details.

1. Vijaykumar, Santosh, Jin, Yan and Nowak, Glen. "Social Media and the Virality of Risk: The Risk Amplification through Media Spread (RAMS) Model" Journal of Homeland Security and Emergency Management, vol. 12, no. 3, 2015, pp. 653-677. https://doi.org/10.1515/jhsem-2014-0072