Baumann Hendrik, Sandmann Werner
Department of Applied Stochastics and Operations Research, Clausthal University of Technology, Clausthal-Zellerfeld, Germany.
Department of Computer Science, Saarland University, Saarbrücken, Germany.
PLoS One. 2016 Mar 24;11(3):e0152144. doi: 10.1371/journal.pone.0152144. eCollection 2016.
Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity.
考虑具有可变人口规模的开放人群中的随机流行病,由于移民和人口统计学效应,流行病最终不会永远消失。潜在的随机过程是遍历多维连续时间马尔可夫链,具有独特的平衡概率分布。将这些流行病建模为水平相关的准生灭过程,能够通过矩阵分析方法有效地计算平衡分布。提供了特定参数集的数值示例,这表明该方法特别适合研究移民、出生、死亡、感染、感染恢复和免疫力丧失等不同速率的影响。