Monitoring and prediction of an epidemic outbreak using syndromic observations

► A novel method for syndromic surveillance of an emerging epidemic is presented. ► The framework of stochastic nonlinear filtering (Kalman particle filter) is used. ► An epidemic is modeled with the generalised SIR model with demographic noise. ► The observations in behavioural changes are used for prediction of the epidemic. ► The method is validated by an agent-based simulation.