Agent-based Model of Covid-19 Vaccination Uptake in Chautauqua NY

In the previous study on Covid-19 vaccine debates, we have revealed the complex communication patterns in hybrid spaces. A following up question that intrigues us is when people are exposed to such complicated conversational context hybrid spaces, with contradictory opinions, how do they make decisions about Covid-19 vaccine uptake. 

To answer these questions, with Andrew Crooks, and Li Yin, we have published a new article "How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptake" in the International Journal of Geographical Information Science. 

This research is the first one that has combined the Space-place (Splatial) framework with the social influence network theory and applied to them model Covid-19 vaccine uptake at individual level. Our model captures the temporal dynamics of vaccination progress with small errors (MAE = 2.45). Our results suggest that all hybrid spaces are indispensable in vaccination decision-making. However, different demographic groups have different preferences in hybrid spaces to obtain health information.

For interested readers, we have provided a more comprehensive Overview, Design Concepts, and Details Protocol (ODD) along with the source code, data needed to run the model, and simulation output at CoMSES Net. 

Abstract: 

The notion of physical space has long been central in geographical theories. However, the widespread adoption of information and communication technologies (ICTs) has freed human dynamics from purely physical to also relational and cyber spaces. While researchers increasingly recognize such shifts, rarely have studies examined how the information propagates in these hybrid spaces (ie physical, relational, and cyber). By exploring the vaccine opinion dynamics through agent-based modeling, this study is the first that combines all hybrid spaces and explores their distinct impacts on human dynamics from an individual’s perspective. Our model captures the temporal dynamics of vaccination progress with small errors (MAE = 2.45). Our results suggest that all hybrid spaces are indispensable in vaccination decision-making. However, in our model, most of the agents tend to give more emphasis to the information that is spread in the physical instead of other hybrid spaces. Our study not only sheds light on human dynamics research but also offers a new lens to identifying vaccinated individuals which has long been challenging in disease-spread models. Furthermore, our study also provides responses for practitioners to develop vaccination outreach policies and plan for future outbreaks.

Full References:

Yin, F., Crooks, A., & Yin, L. (2024). How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptake. International Journal of Geographical Information Science, 1-27. https://doi.org/10.1080/13658816.2024.2333930