Abstract
Most previous models for epidemic spreading are based on an assumption that all individual characteristics in a population are identical and stochastically distributed. However, in the real world, individuals have different behavioral characteristics for resisting infections, one of which is self-protective behavior. In this study, we suggest an equation describing self-protective behavior and use the equation in an agent-based model to simulate epidemic spreading in a population. The self-protective behavior was simply defined as the behavioral rule that when a susceptible individual meets an infective individual, the susceptible tends to move in the opposite direction of the infective individual. The degree of the tendency was quantified as a value of [Formula: see text] ranging from 0.0 to 1.0, with a higher [Formula: see text] representing a stronger tendency. The simulation results showed that when the recovery and infection probability are balanced to some extent, the [Formula: see text] effect clearly appeared. The [Formula: see text] effect led to a reduction in the number of infective individuals in a stable state. In addition, the effect decreased with an increase in population size. We briefly discuss how the results can be applied in real life situations.
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