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Pandemics, in addition to affecting the health of populations, can have hugeimpacts on their social and economic behavior. These factors, on the otherhand, have the potential to feed back to and influence the disease spreading.It is important to systematically study these interrelations, to determinewhich ones have significant effects, and whether the effects are adverse orbeneficial. Our recently developed epidemic model with agent-based andgeographical elements is used in this study for such a purpose. We perform anextensive parameter space exploration of the socio-economic part of the model,including factors like the attitudes (called values) of the agents towards thedisease spreading, health, economic situation, and regulations by governmentagents. We search for prominent patterns from the resulting simulated datausing basic classification tools, namely self-organizing maps and principalcomponent analysis. We seek to isolate the most important value parameters ofthe population and government agents influencing the disease spreading speedand patterns, and monitor different quantities of the model output, such asinfection rates, the propagation speed of the epidemic, economic activity,government regulations, and the compliance of population. Out of these, theones describing the epidemic spreading were resulting in the most distinctiveclustering of the data, and they were selected as the basis of the remaininganalysis. We relate the found clusters to three distinct types of diseasespreading: wave-like, chaotic, and transitional spreading patterns. The mostimportant value parameter contributing to phase changes between these phaseswas found to be the compliance of the population agents towards the governmentregulations.

Exploration of the effects of epidemics on the regional socio-economics: a modelling approach