infoXpand: Modeling Network: infoXpand - Information, Opinions, Mobility, Behavior, and Bayesian Inference in Infectious Disease Modeling - Subproject C

The COVID-19 pandemic has been accompanied by an "infodemic," i.e., an excess of information about the virus, protective measures, and government interventions. In particular, misinformation and conspiracy theories spread online have been blamed for increasing opinion polarization, radicalization, and declining trust in institutions. It has been warned that this has fueled the pandemic and made it even more difficult to manage. However, models of disease spread used to predict pandemic dynamics ignore the complex interaction between information and the pandemic. While these models consider that, for example, low vaccination rates increase the number of hospitalizations, they fail to consider that knowledge of the increasing number of hospitalizations motivates people to get vaccinated. The main goal of infoXpand is to understand this feedback loop between the pandemic and information dissemination and to derive suggestions for future decision-makers.
To this end, we have established an interdisciplinary consortium with unique expertise in pandemic modeling, opinion dynamics, mobility, and human behavior. We closely develop and analyze agent-based and compartment models that capture both classical disease dynamics and opinion dynamics. We calibrate critical model assumptions with data from social science survey studies and behavioral experiments, as well as with extensive mobility data.