Open AccessPrediction of influenza peaks in Russian cities: Comparing the accuracy of two SEIR models
Author(s) -
Vasiliy N. Leonenko,
Sergey V. Ivanov
Publication year - 2017
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2018009
Subject(s) - saint petersburg , outbreak , ordinary differential equation , statistics , soviet union , econometrics , set (abstract data type) , mathematics , data set , differential equation , geography , computer science , russian federation , virology , mathematical analysis , biology , programming language , regional science , politics , political science , law
This paper is dedicated to the application of two types of SEIR models to the influenza outbreak peak prediction in Russian cities. The first one is a continuous SEIR model described by a system of ordinary differential equations. The second one is a discrete model formulated as a set of difference equations, which was used in the Baroyan-Rvachev modeling framework for the influenza outbreak prediction in the Soviet Union. The outbreak peak day and height predictions were performed by calibrating both models to varied-size samples of long-term data on ARI incidence in Moscow, Saint Petersburg, and Novosibirsk. The accuracy of the modeling predictions on incomplete data was compared with a number of other peak forecasting methods tested on the same dataset. The drawbacks of the described prediction approach and possible ways to overcome them are discussed.