Monday, May 13, 2024

Using ABM to simulate Covid-19 vaccine uptake

In past blog posts we have discussed how one can use social media to study vaccine discussions and even tried to build a very simple disease model where vaccination rates were a factor in the spread of an outbreak. However, when it comes to vaccinations, especially that of Covid-19 vaccine there has been intense discussions in the physical (e.g., family), hybrid (e.g., work, school) and cyber (e.g., social media) spaces we inhabit. 

One thing that is unclear is how do these discussions in these various hybrid spaces impact our decision to get vaccinated or not? To this end, in a new paper published in the International Journal of Geographical Information Science with Fuzhen Yin, Li Yin and myself, entitled “How information propagation in hybrid spaces affects decision-making: using ABM to simulate Covid-19 vaccine uptake” we explore this. 

More specially we explore how through opinion dynamics modeling, how agents can chose to vaccinate or not and how much emphasis they place on physical, relational and cyber spaces Using Chautauqua County in New York State as a case study our model results captures the temporal dynamics of vaccination progress with small errors but we also find that different age groups demonstrate various preferences for different spaces to receive vaccine related information. 

If this sounds of interest, below you can read the abstract of the paper, see a flow chart of the model logic and some of the results. While at the bottom of the post you can find the full reference and link to the paper. Furthermore, Fuzhen has also provided a detailed Overview, Design Concepts and Details Protocol (ODD) document along with the source code and data needed to run the model at CoMSES Net 

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 (i.e., 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. 

Keywords: Agent-based modeling, hybrid space, opinion dynamics, Covid-19, vaccination. 

Flowchart of the modeling process. 

Comparing predicted and observed vaccination rates of all populations by giving physical, relational, cyber spaces different weights. Mean absolute error (MAE) and root mean square error (RMSE) are reported to evaluate the quality of predictions.

Comparing predicted and observed vaccination rates among different age groups by using the weight combination 3 (physical), 1 (relational), 1 (cyber) for hybrid spaces. 

Comparing predicted and observed vaccination rates by varying weights of hybrid spaces for different age groups.

Spatial distribution of Covid-19 vaccines. (a)-(d) Point density of vaccination allocation at different time steps. (e) Predicted vaccination rates at census block group level.

Full Referece:
Yin, F., Crooks, A.T. and 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, (pdf)

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