Agent-based perspectives on epidemiological models: analysis of interviews with upper high-school students

Abstract

In disease spread modeling, a prevalent approach employs differential equations to depict the dynamics of susceptible, infectious, and recovered populations over time. Nonetheless, alternative avenues exist through agent-based epidemiological models, drawing inspiration from interaction models from the physics of complex systems. This study delves into the formulation of such models by upper high-school students who attended a teaching-learning module on computational simulations. The paper focuses on their development of agent-based virus spread models, exploring their ability to forge analogies with previously encountered models of complex systems - namely, predator-prey, opinion dynamics, and cooperative behaviour models. Through the qualitative analysis of individual interviews, our findings reveal that effective strategies of analogy’s construction embed a comprehensive exploration of the underlying interaction mechanisms governing the evolution of the system under study. Conversely, in instances where the mechanistic dimension remains unexplored or vague, the depth and quality of the model elaborated is lower and the potential of comparing models to construct a more robust analogy remains unexploited.