Effect of individual protective behaviors on influenza transmission: an agent-based model

It is well established in the epidemiological literature that individual behaviors have a significant effect on the spread of infectious diseases. Agent-based models are increasingly being recognized as the next generation of epidemiological models. In this research, we use the ability of agent-based models to incorporate behavior into simulations by examining the relative importance of vaccination and social distancing, two common measures for controlling the spread of infectious diseases, with respect to seasonal influenza. We modeled health behaviour using the result of a Health Belief Model study focused on influenza. We considered a control and a treatment group to explore the effect of education on people's health-related behaviors patterns. The control group reflects the behavioral patterns of students based on their general knowledge of influenza and its interventions while the treatment group illustrates the level of behavioral changes after individuals have been educated by a health care expert. The results of this study indicate that self-initiated behaviors are successful in controlling an outbreak in a high contact rate location such as a university. Self-initiated behaviors resulted in a population attack rate decrease of 17% and a 25% reduction in the peak number of cases. The simulation also provides significant evidence for the effect of an HBM theory-based educational program to increase the rate of applying the target interventions (vaccination by 22% percent and social distancing by 41%) and consequently to control the outbreak.