Models, prediction, and estimation of outbreaks of infectious disease

被引:7
作者
Costa, PJ
Dunyak, JP
Mohtashemi, M
机构
来源
PROCEEDINGS OF THE IEEE SOUTHEASTCON 2004: EXCELLENCE IN ENGINEERING, SCIENCE, AND TECHNOLOGY | 2005年
关键词
D O I
10.1109/SECON.2005.1423240
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:174 / 178
页数:5
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