Multilayer Network Models Integrating Social, Biological, and Digital Transmission for Pandemic Preparedness

While Hotton et al. (2025) and Stella (2021) highlight the importance of social determinants and cognitive networks in disease modeling, most epidemic models treat social or digital networks as exogenous or static. This research proposes the development of truly multilayer network models where nodes participate in biological contagion (e.g., SARS-CoV-2), social contagion (e.g., adherence to health behaviors), and digital contagion (e.g., spread of health misinformation) simultaneously. Inter-layer feedbacks—such as misinformation leading to reduced vaccine uptake, or social reinforcement amplifying both risk and protection—would be explicitly modeled. This approach offers a more realistic simulation of pandemics in the age of social media, and could identify leverage points for coordinated interventions across physical and virtual domains. Its novelty lies in the integrated treatment of different contagion processes, which is rarely attempted despite clear evidence of their intertwined effects.

References:

1. Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions. Anna Hotton, Pedro Nascimento de Lima, A. Fadikar, Nicholson T. Collier, Aditya S. Khanna, D. Motley, E. Tatara, Sara Rimer, Ellen Almirol, Harold A. Pollack, John A Schneider, R. Lempert, J. Ozik (2025). Frontiers in Epidemiology.
2. Cognitive network science for understanding online social cognitions: A brief review. Massimo Stella (2021). Topics in Cognitive Science.