Stochastic Epidemics in Growing Populations

被引:5
作者
Britton, Tom [1 ]
Trapman, Pieter [1 ]
机构
[1] Stockholm Univ, Dept Math, S-10691 Stockholm, Sweden
关键词
S(E)IR epidemic; Dynamic population;
D O I
10.1007/s11538-014-9942-x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Consider a uniformly mixing population which grows as a super-critical linear birth and death process. At some time an infectious disease (of SIR or SEIR type) is introduced by one individual being infected from outside. It is shown that three different scenarios may occur: (i) an epidemic never takes off, (ii) an epidemic gets going and grows but at a slower rate than the community thus still being negligible in terms of population fractions, or (iii) an epidemic takes off and grows quicker than the community eventually leading to an endemic equilibrium. Depending on the parameter values, either scenario (i) is the only possibility, both scenarios (i) and (ii) are possible, or scenarios (i) and (iii) are possible.
引用
收藏
页码:985 / 996
页数:12
相关论文
共 11 条
[1]  
Andersson H., 2000, Stochastic epidemic models and their statistical analysis, V4
[2]   STRONG APPROXIMATIONS FOR EPIDEMIC MODELS [J].
BALL, F ;
DONNELLY, P .
STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 1995, 55 (01) :1-21
[3]   Linking population-level models with growing networks: A class of epidemic models [J].
Breban, R ;
Vardavas, R ;
Blower, S .
PHYSICAL REVIEW E, 2005, 72 (04)
[4]  
Diekmann O., 2012, Mathematical tools for understanding infectious disease dynamics
[5]  
Durrett R., 2007, RANDOM GRAPH DYNAMIC, V20
[6]  
Ethier S. N., 2005, MARKOV PROCESSES CHA, V282
[7]  
Haccou Patsy, 2005, Branching processes: variation, growth, and extinction of populations
[8]  
Jagers P., 1975, BRANCHING PROCESSES
[9]   Global dynamics of a SEIR model with varying total population size [J].
Li, MY ;
Graef, JR ;
Wang, LC ;
Karsai, J .
MATHEMATICAL BIOSCIENCES, 1999, 160 (02) :191-213
[10]   EPIDEMIC AND DEMOGRAPHIC INTERACTION IN THE SPREAD OF POTENTIALLY FATAL DISEASES IN GROWING POPULATIONS [J].
THIEME, HR .
MATHEMATICAL BIOSCIENCES, 1992, 111 (01) :99-103