Edge-based SEIR dynamics with or without infectious force in latent period on random networks

被引:27
|
作者
Wang, Yi [1 ,2 ,3 ]
Cao, Jinde [3 ,4 ]
Alsaedi, Ahmed [5 ]
Ahmad, Bashir [5 ]
机构
[1] China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China
[2] Univ Victoria, Dept Math & Stat, Victoria, BC V8W 3R4, Canada
[3] Southeast Univ, Dept Math, Nanjing 210096, Jiangsu, Peoples R China
[4] King Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
[5] King Abdulaziz Univ, Fac Sci, Dept Math, NAAM Res Grp, Jeddah 21589, Saudi Arabia
基金
中国国家自然科学基金;
关键词
SEIR models; Latent period; Final epidemic size; Random networks; Probability generating function; Stochastic simulations; EPIDEMIC MODEL; GLOBAL STABILITY; SIR DYNAMICS; SIMULATION; GAME;
D O I
10.1016/j.cnsns.2016.09.014
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In nature, most of the diseases have latent periods, and most of the networks look as if they were spun randomly at the first glance. Hence, we consider SEIR dynamics with or without infectious force in latent period on random networks with arbitrary degree distributions. Both of these models are governed by intrinsically three dimensional nonlinear systems of ordinary differential equations, which are the same as classical SEIR models. The basic reproduction numbers and the final size formulae are explicitly derived. Predictions of the models agree well with the large-scale stochastic SEIR simulations on contact networks. In particular, for SEIR model without infectious force in latent period, although the length of latent period has no effect on the basic reproduction number and the final epidemic size, it affects the arrival time of the peak and the peak size; while for SEIR model with infectious force in latent period it also affects the basic reproduction number and the final epidemic size. These accurate model predictions, may provide guidance for the control of network infectious diseases with latent periods. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:35 / 54
页数:20
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