scholarly journals Stability analysis for SIS epidemic models with vaccination and constant population size

2004 ◽  
Vol 4 (3) ◽  
pp. 635-642 ◽  
Author(s):  
Jianquan Li ◽  
◽  
Zhien Ma ◽  
Keyword(s):  
Stability Analysis ◽  
Population Size ◽  
Epidemic Models ◽  
Constant Population Size ◽  
Sis Epidemic

scholarly journals Fractional SIS Epidemic Models

2020 ◽  
Vol 4 (3) ◽  
pp. 44
Author(s):  
Caterina Balzotti ◽  
Mirko D’Ovidio ◽  
Paola Loreti
Keyword(s):  
Population Size ◽  
Fractional Order ◽  
Epidemic Model ◽  
Explicit Solution ◽  
Fractional Derivatives ◽  
Epidemic Models ◽  
Limit Case ◽  
Numerical Schemes ◽  
Sis Model ◽  
Sis Epidemic

In this paper, we consider the fractional SIS (susceptible-infectious-susceptible) epidemic model (α-SIS model) in the case of constant population size. We provide a representation of the explicit solution to the fractional model and we illustrate the results by numerical schemes. A comparison with the limit case when the fractional order α converges to 1 (the SIS model) is also given. We analyze the effects of the fractional derivatives by comparing the SIS and the α-SIS models.

scholarly journals Persistence-time estimation for some stochastic SIS epidemic models

2015 ◽  
Vol 20 (9) ◽  
pp. 2933-2947 ◽  
Author(s):  
Francisco de la Hoz ◽  
Anna Doubova ◽  
Fernando Vadillo
Keyword(s):  
Time Estimation ◽  
Epidemic Models ◽  
Persistence Time ◽  
Sis Epidemic

scholarly journals Finite Symmetries in Agent-Based Epidemic Models

2019 ◽  
Vol 24 (2) ◽  
pp. 44 ◽  
Author(s):  
Gilberto M. Nakamura ◽  
Ana Carolina P. Monteiro ◽  
George C. Cardoso ◽  
Alexandre S. Martinez
Keyword(s):  
Population Size ◽  
Transition Matrix ◽  
Large Scale ◽  
Initial Conditions ◽  
Disease Outbreaks ◽  
Epidemic Models ◽  
Small Scale ◽  
Stochastic Effects ◽  
Agent Based ◽  
Computational Performance

Predictive analysis of epidemics often depends on the initial conditions of the outbreak, the structure of the afflicted population, and population size. However, disease outbreaks are subjected to fluctuations that may shape the spreading process. Agent-based epidemic models mitigate the issue by using a transition matrix which replicates stochastic effects observed in real epidemics. They have met considerable numerical success to simulate small scale epidemics. The problem grows exponentially with population size, reducing the usability of agent-based models for large scale epidemics. Here, we present an algorithm that explores permutation symmetries to enhance the computational performance of agent-based epidemic models. Our findings bound the stochastic process to a single eigenvalue sector, scaling down the dimension of the transition matrix to o ( N 2 ) .

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