School of Mathematics and Physics, The University of Queensland, Qld 4072, Australia.
Math Biosci Eng. 2024 Mar 14;21(4):5446-5455. doi: 10.3934/mbe.2024240.
We study an extension of the stochastic SIS (Susceptible-Infectious-Susceptible) model in continuous time that accounts for variation amongst individuals. By examining its limiting behaviour as the population size grows we are able to exhibit conditions for the infection to become endemic.
我们研究了连续时间随机 SIS(易感-感染-易感)模型的扩展,该模型考虑了个体之间的变异。通过研究其在种群规模增长时的极限行为,我们能够展示感染成为地方病的条件。