Modeling individual fear factor with optimal control in a disease-dynamic system

This paper proposes a new, information-transmission-based behavior-switch that applies the individual fear factor (IFF) to describe how information regarding current disease epidemics can cause human behavior change in a disease-dynamic system. This research is a first attempt to mathematically model how an individual's emotions influence behavior. The approach can be used to study the relationship of information dissemination (e.g., broadcasting, public health education, news media, etc.) and human behaviors during disease outbreaks. The expression of IFF and a mathematical IFF model that combines human behaviors with a classic SIR model is presented, and an optimal strategy that reduces the number of infected individuals and financial loss due to switch behaviors is proposed. In particular, model stability is analyzed and corresponding necessary conditions are determined. This novel modeling approach shows that information transmission influence individual fear, resulting in a variety of human behaviors and leading to numerous disease consequences.