Individual decision making can drive epidemics: a fuzzy cognitive map study

Existing studies on the propagation of infectious diseases have not sufficiently considered the uncertainties related to individual behavior and its influence on individual decision making to prevent infections, even though it is well known that changes in behavior can lead to variations in the macro dynamics of infectious diseases spreading. These influencing factors can be categorized into emotion-related and cognition-related components.We present an FCM (Fuzzy Cognitive Map) denotative model to describe how the factors of individual emotions and cognition influence each other.We adjust the weight matrix of causal relationships between these factors by using a socalled nonlinear Hebbian learning method. Based on this FCM model, we can implement individual decision rules against possible infections for disease propagation studies. We take the simulation of influenza A [H1N1] spreading on a campus as an example. We find that individual decisionmaking against infections (frequent washes, respirator usages and crowd contact avoidances) can significantly decrease the at-peak number of infected patients, even when common policies such as isolation and vaccination etc., are not deployed.