Abstract
Stochastic models have an important role in modeling and analyzing epidemic diseases for small size population. In this article, we study the generation of stochastic models for epidemic disease susceptible-infective-susceptible model. Here, we use the separation variable method to solve partial differential equation and the new developed modified probability generating function (PGF) of a random process to include a random catastrophe to solve the ordinary differential equations generated from partial differential equation. The results show that the probability function is too sensitive to μ, β and γ parameters.
| Original language | English |
|---|---|
| Article number | 7 |
| Journal | Advances in Difference Equations |
| Volume | 2013 |
| DOIs | |
| Publication status | Published - 2013 |
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Keywords
- deterministic model
- epidemic diseases
- probability function
- stochastic model
- susceptible-infective-susceptible
ASJC Scopus subject areas
- Applied Mathematics
- Algebra and Number Theory
- Analysis
Cite this
The use of generation stochastic models to study an epidemic disease. / Seddighi Chaharborj, S.; Fudziah, I.; Abu Bakar, Mr; Seddighi Chaharborj, R.; Majid, Z. A.; Ahmad, Abd. Ghafur.
In: Advances in Difference Equations, Vol. 2013, 7, 2013.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The use of generation stochastic models to study an epidemic disease
AU - Seddighi Chaharborj, S.
AU - Fudziah, I.
AU - Abu Bakar, Mr
AU - Seddighi Chaharborj, R.
AU - Majid, Z. A.
AU - Ahmad, Abd. Ghafur
PY - 2013
Y1 - 2013
N2 - Stochastic models have an important role in modeling and analyzing epidemic diseases for small size population. In this article, we study the generation of stochastic models for epidemic disease susceptible-infective-susceptible model. Here, we use the separation variable method to solve partial differential equation and the new developed modified probability generating function (PGF) of a random process to include a random catastrophe to solve the ordinary differential equations generated from partial differential equation. The results show that the probability function is too sensitive to μ, β and γ parameters.
AB - Stochastic models have an important role in modeling and analyzing epidemic diseases for small size population. In this article, we study the generation of stochastic models for epidemic disease susceptible-infective-susceptible model. Here, we use the separation variable method to solve partial differential equation and the new developed modified probability generating function (PGF) of a random process to include a random catastrophe to solve the ordinary differential equations generated from partial differential equation. The results show that the probability function is too sensitive to μ, β and γ parameters.
KW - deterministic model
KW - epidemic diseases
KW - probability function
KW - stochastic model
KW - susceptible-infective-susceptible
UR - http://www.scopus.com/inward/record.url?scp=84874026558&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874026558&partnerID=8YFLogxK
U2 - 10.1186/1687-1847-2013-7
DO - 10.1186/1687-1847-2013-7
M3 - Article
AN - SCOPUS:84874026558
VL - 2013
JO - Advances in Difference Equations
JF - Advances in Difference Equations
SN - 1687-1839
M1 - 7
ER -