Models, prediction, and estimation of outbreaks of infectious disease

Conventional SEIR (susceptible-exposed-infectious-recovered) models have been utilized by numerous researchers to study and predict disease outbreak. By combining the predictive nature of such mathematical models along with the measured occurrences of disease, a more robust estimate of disease progression can be made. The Kalman filter is the method designed to incorporate model prediction and measurement correction. Consequently, we produce an SEIR model which governs the short term behaviour of an epidemic outbreak. The mathematical structure for an associated Kalman filter is developed and estimates of a simulated outbreak are provided.