文档介绍：Models, Prediction, and Estimation of Outbreaks of Infectious Disease
Peter J. Costa, James P. Dunyak, Mojdeh Mohtashemi
The MITRE Corporation
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Abstract Notation
Conventional SEIR (Susceptible–Exposed–Infectious– S = S(t) = number of people in the population susceptible to
Recovered) models have been utilized by numerous the disease at time t
researchers to study and predict disease outbreak. By E = E(t) = number of people in the population exposed/
combining the predictive nature of such mathematical infected by the disease at time t
models along with the measured occurrences of disease, a I = I(t) = number of people in the population who are
more robust estimate of disease progression can be made. infectious at time t
The Kalman filter is the method designed to incorporate R = R(t) = number of people in the population who have
model prediction and measurement correction. recovered from the disease at time t
Consequently, we produce an SEIR model which governs There are a number of parameters which will need to be
the short term behaviour of an epidemic outbreak. The either modeled or estimated from the data. It is assumed
mathematical structure for