American Institute of Mathematical Sciences

Advanced
May  2020, 25(5): 1985-1997. doi: 10.3934/dcdsb.2020012

On the threshold dynamics of the stochastic SIRS epidemic model using adequate stopping times

Adel Settati 1, , Aadil Lahrouz 1, , Mustapha El Jarroudi 1, , Mohamed El Fatini 2,, and  Kai Wang 3,

1. 

Department of Mathematics, Faculty of Sciences and Technics, Abdelmalek Essaâdi University, BP 416, Tangier, Morocco
2. 

Department of Mathematics, Faculty of Sciences, Ibn Tofail University, BP 133 Kénitra, Morocco
3. 

Department of Applied Mathematics, Anhui University of Finance and Economics, Bengbu 233030, China

*Correponding author (melfatini@gmail.com)

Received  April 2019 Revised  July 2019 Published  December 2019

As it is well known, the dynamics of the stochastic SIRS epidemic model with mass action is governed by a threshold $ \mathcal{R_S} $. If $ \mathcal{R_S}<1 $ the disease dies out from the population, while if $ \mathcal{R_S}> 1 $ the disease persists. However, when $ \mathcal{R_S} = 1 $, classical techniques used to study the asymptotic behaviour do not work any more. In this paper, we give answer to this open problem by using a new approach involving some adequate stopping times. Our results show that if $ \mathcal{R_S} = 1 $ then, small noises promote extinction while the large one promote persistence. So, it is exactly the opposite role of the noises in case when $ \mathcal{R_S}\neq 1 $.

Keywords: Stochastic threshold, SIRS epidemic model, Wiener process.
Mathematics Subject Classification: 92B05, 60G51, 60H30, 60G57.
Citation: Adel Settati, Aadil Lahrouz, Mustapha El Jarroudi, Mohamed El Fatini, Kai Wang. On the threshold dynamics of the stochastic SIRS epidemic model using adequate stopping times. Discrete & Continuous Dynamical Systems - B, 2020, 25 (5) : 1985-1997. doi: 10.3934/dcdsb.2020012
References:
[1]

E. Allen, Modeling with Itô Stochastic Differential Equations, Springer, The Netherlands, 2007. Google Scholar

[2]

B. Berrhazi, M. El Fatini, T. Caraballo and R. Pettersson, A stochastic SIRI epidemic model with Lévy noise, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 2415-2431.  doi: 10.3934/dcdsb.2018057.  Google Scholar

[3]

B. Berrhazi, M. El Fatini, A. Laaribi, R. Pettersson and R. Taki, A stochastic SIRS epidemic model incorporating media coverage and driven by Lévy noise, Chaos Solitons Fractals, 105 (2017), 60-68.  doi: 10.1016/j.chaos.2017.10.007.  Google Scholar

[4]

B. Berrhazi, M. El Fatini, A. Lahrouz, A. Settati and R. Taki, A stochastic SIRS epidemic model with a general awareness-induced incidence, Phys. A, 512 (2018), 968-980.  doi: 10.1016/j.physa.2018.08.150.  Google Scholar

[5]

V. Capasso, Mathematical Structures of Epidemic Systems, Lecture Notes in Biomathematics, 97. Springer-Verlag, Berlin, 1993. doi: 10.1007/978-3-540-70514-7.  Google Scholar

[6]

T. Caraballo, M. El Fatini, R. Pettersson and R. Taki, A stochastic SIRI epidemic model with relapse and media coverage, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 3483-3501.  doi: 10.3934/dcdsb.2018250.  Google Scholar

[7]

T. Caraballo and R. Colucci, A comparison between random and stochastic modeling for a SIR model, Commun. Pure Appl. Anal., 16 (2017), 151-162.  doi: 10.3934/cpaa.2017007.  Google Scholar

[8]

C. Castillo-Chavez, Z. L. Feng and W. Z. Huang, On the computation of $\mathcal{R}_0$ and its role on global stability, Mathematical Approaches for Emerging and Reemerging Infectious Diseases: An Introduction (Minneapolis, MN, 1999), IMA Vol. Math. Appl., Springer, New York, 125 (2002), 229-250.   Google Scholar

[9]

O. Diekmann, J. A. P. Heesterbeek and J. A. J. Metz, On the definition and the computation of the basic reproduction ratio $\mathcal{R}_0$ in models for infectious diseases in heterogeneous population, J. Math. Biol., 28 (1990), 365-382.  doi: 10.1007/BF00178324.  Google Scholar

[10]

M. El Fatini, B. Boukanjime, Stochastic analysis of a two delayed epidemic model incorporating Lévy processes with a general non-linear transmission, Stoch. Anal. Appl, (Published online: 26 Oct 2019) https://doi.org/10.1080/07362994.2019.1680295. doi: 10.1080/07362994.2019.1680295.  Google Scholar

[11]

M. El Fatini, A. Laaribi, R. Pettersson and R. Taki, Lévy noise perturbation for an epidemic model with impact of media coverage, Stochastics, 91 (2019), 998-1019.  doi: 10.1080/17442508.2019.1595622.  Google Scholar

[12]

M. El Fatini, A. Lahrouz, R. Pettersson, A. Settati and R. Taki, Stochastic stability and instability of an epidemic model with relapse, Appl. Math. Comput., 316 (2018), 326-341.  doi: 10.1016/j.amc.2017.08.037.  Google Scholar

[13]

A. Gray, D. Greenhalgh, L. Hu, X. Mao and J. Pan, A stochastic differential equation SIS epidemic model, SIAM J. Appl. Math., 71 (2011), 876-902.  doi: 10.1137/10081856X.  Google Scholar

[14]

H. W. Hethcote, Qualitative analyses of communicable disease models, Math. Biosci., 28 (1976), 335-356.  doi: 10.1016/0025-5564(76)90132-2.  Google Scholar

[15]

C. Y. Ji and D. Q. Jiang, Threshold behaviour of a stochastic SIR model, Appl. Math. Model, 38 (2014), 5067-5079.  doi: 10.1016/j.apm.2014.03.037.  Google Scholar

[16]

C. Y. Ji, D. Q. Jiang and N. Z. Shi, Multigroup SIR epidemic model with stochastic perturbation, Physica A, 390 (2011), 1747-1762.   Google Scholar

[17]

P. E. Kloeden and E. Platen, Numerical Solution of Stochastic Differential Equations, Applications of Mathematics (New York), 23. Springer-Verlag, Berlin, 1992. doi: 10.1007/978-3-662-12616-5.  Google Scholar

[18]

A. Lahrouz and L. Omari, Extinction and stationary distribution of a stochastic SIRS epidemic model with non-linear incidence, Statist. Probab. Lett., 83 (2013), 960-968.  doi: 10.1016/j.spl.2012.12.021.  Google Scholar

[19]

A. Lahrouz and A. Settati, Necessary and sufficient condition for extinction and persistence of SIRS system with random perturbation, Appl. Math. Comput., 233 (2014), 10-19.  doi: 10.1016/j.amc.2014.01.158.  Google Scholar

[20]

A. Lahrouz and A. Settati, Asymptotic properties of switching diffusion epidemic model with varying population size, Appl. Math. Comput., 219 (2013), 11134-11148.  doi: 10.1016/j.amc.2013.05.019.  Google Scholar

[21]

Y. G. Lin and D. Q. Jiang, Long-time behavior of a perturbed SIR model by white noise, Discrete Contin. Dyn. Syst. Ser. B, 18 (2013), 1873-1887.  doi: 10.3934/dcdsb.2013.18.1873.  Google Scholar

[22]

Q. Y. Lu, Stability of SIRS system with random perturbations, Physica A, 388 (2009), 3677-3686.  doi: 10.1016/j.physa.2009.05.036.  Google Scholar

[23]

A. Settati, A. Lahrouz, M. El Jarroudi and M. El Jarroudi, Dynamics of hybrid switching diffusions SIRS model, J. Appl. Math. Comput., 52 (2016), 101-123.  doi: 10.1007/s12190-015-0932-4.  Google Scholar

[24]

E. Tornatore, S. M. Buccellato and P. Vetro, Stability of a stochastic SIR system, Physica A, 35 (2005), 4111-4126.   Google Scholar

[25]

P. Van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Mathematical Biosciences, 180 (2002), 29-48.  doi: 10.1016/S0025-5564(02)00108-6.  Google Scholar

[26]

Y. N. Zhao and D. Q. Jiang, The threshold of a stochastic SIS epidemic model with vaccination, Appl. Math. Comput., 243 (2014), 718-727.  doi: 10.1016/j.amc.2014.05.124.  Google Scholar

show all references

References:
[1]

E. Allen, Modeling with Itô Stochastic Differential Equations, Springer, The Netherlands, 2007. Google Scholar

[2]

B. Berrhazi, M. El Fatini, T. Caraballo and R. Pettersson, A stochastic SIRI epidemic model with Lévy noise, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 2415-2431.  doi: 10.3934/dcdsb.2018057.  Google Scholar

[3]

B. Berrhazi, M. El Fatini, A. Laaribi, R. Pettersson and R. Taki, A stochastic SIRS epidemic model incorporating media coverage and driven by Lévy noise, Chaos Solitons Fractals, 105 (2017), 60-68.  doi: 10.1016/j.chaos.2017.10.007.  Google Scholar

[4]

B. Berrhazi, M. El Fatini, A. Lahrouz, A. Settati and R. Taki, A stochastic SIRS epidemic model with a general awareness-induced incidence, Phys. A, 512 (2018), 968-980.  doi: 10.1016/j.physa.2018.08.150.  Google Scholar

[5]

V. Capasso, Mathematical Structures of Epidemic Systems, Lecture Notes in Biomathematics, 97. Springer-Verlag, Berlin, 1993. doi: 10.1007/978-3-540-70514-7.  Google Scholar

[6]

T. Caraballo, M. El Fatini, R. Pettersson and R. Taki, A stochastic SIRI epidemic model with relapse and media coverage, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 3483-3501.  doi: 10.3934/dcdsb.2018250.  Google Scholar

[7]

T. Caraballo and R. Colucci, A comparison between random and stochastic modeling for a SIR model, Commun. Pure Appl. Anal., 16 (2017), 151-162.  doi: 10.3934/cpaa.2017007.  Google Scholar

[8]

C. Castillo-Chavez, Z. L. Feng and W. Z. Huang, On the computation of $\mathcal{R}_0$ and its role on global stability, Mathematical Approaches for Emerging and Reemerging Infectious Diseases: An Introduction (Minneapolis, MN, 1999), IMA Vol. Math. Appl., Springer, New York, 125 (2002), 229-250.   Google Scholar

[9]

O. Diekmann, J. A. P. Heesterbeek and J. A. J. Metz, On the definition and the computation of the basic reproduction ratio $\mathcal{R}_0$ in models for infectious diseases in heterogeneous population, J. Math. Biol., 28 (1990), 365-382.  doi: 10.1007/BF00178324.  Google Scholar

[10]

M. El Fatini, B. Boukanjime, Stochastic analysis of a two delayed epidemic model incorporating Lévy processes with a general non-linear transmission, Stoch. Anal. Appl, (Published online: 26 Oct 2019) https://doi.org/10.1080/07362994.2019.1680295. doi: 10.1080/07362994.2019.1680295.  Google Scholar

[11]

M. El Fatini, A. Laaribi, R. Pettersson and R. Taki, Lévy noise perturbation for an epidemic model with impact of media coverage, Stochastics, 91 (2019), 998-1019.  doi: 10.1080/17442508.2019.1595622.  Google Scholar

[12]

M. El Fatini, A. Lahrouz, R. Pettersson, A. Settati and R. Taki, Stochastic stability and instability of an epidemic model with relapse, Appl. Math. Comput., 316 (2018), 326-341.  doi: 10.1016/j.amc.2017.08.037.  Google Scholar

[13]

A. Gray, D. Greenhalgh, L. Hu, X. Mao and J. Pan, A stochastic differential equation SIS epidemic model, SIAM J. Appl. Math., 71 (2011), 876-902.  doi: 10.1137/10081856X.  Google Scholar

[14]

H. W. Hethcote, Qualitative analyses of communicable disease models, Math. Biosci., 28 (1976), 335-356.  doi: 10.1016/0025-5564(76)90132-2.  Google Scholar

[15]

C. Y. Ji and D. Q. Jiang, Threshold behaviour of a stochastic SIR model, Appl. Math. Model, 38 (2014), 5067-5079.  doi: 10.1016/j.apm.2014.03.037.  Google Scholar

[16]

C. Y. Ji, D. Q. Jiang and N. Z. Shi, Multigroup SIR epidemic model with stochastic perturbation, Physica A, 390 (2011), 1747-1762.   Google Scholar

[17]

P. E. Kloeden and E. Platen, Numerical Solution of Stochastic Differential Equations, Applications of Mathematics (New York), 23. Springer-Verlag, Berlin, 1992. doi: 10.1007/978-3-662-12616-5.  Google Scholar

[18]

A. Lahrouz and L. Omari, Extinction and stationary distribution of a stochastic SIRS epidemic model with non-linear incidence, Statist. Probab. Lett., 83 (2013), 960-968.  doi: 10.1016/j.spl.2012.12.021.  Google Scholar

[19]

A. Lahrouz and A. Settati, Necessary and sufficient condition for extinction and persistence of SIRS system with random perturbation, Appl. Math. Comput., 233 (2014), 10-19.  doi: 10.1016/j.amc.2014.01.158.  Google Scholar

[20]

A. Lahrouz and A. Settati, Asymptotic properties of switching diffusion epidemic model with varying population size, Appl. Math. Comput., 219 (2013), 11134-11148.  doi: 10.1016/j.amc.2013.05.019.  Google Scholar

[21]

Y. G. Lin and D. Q. Jiang, Long-time behavior of a perturbed SIR model by white noise, Discrete Contin. Dyn. Syst. Ser. B, 18 (2013), 1873-1887.  doi: 10.3934/dcdsb.2013.18.1873.  Google Scholar

[22]

Q. Y. Lu, Stability of SIRS system with random perturbations, Physica A, 388 (2009), 3677-3686.  doi: 10.1016/j.physa.2009.05.036.  Google Scholar

[23]

A. Settati, A. Lahrouz, M. El Jarroudi and M. El Jarroudi, Dynamics of hybrid switching diffusions SIRS model, J. Appl. Math. Comput., 52 (2016), 101-123.  doi: 10.1007/s12190-015-0932-4.  Google Scholar

[24]

E. Tornatore, S. M. Buccellato and P. Vetro, Stability of a stochastic SIR system, Physica A, 35 (2005), 4111-4126.   Google Scholar

[25]

P. Van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Mathematical Biosciences, 180 (2002), 29-48.  doi: 10.1016/S0025-5564(02)00108-6.  Google Scholar

[26]

Y. N. Zhao and D. Q. Jiang, The threshold of a stochastic SIS epidemic model with vaccination, Appl. Math. Comput., 243 (2014), 718-727.  doi: 10.1016/j.amc.2014.05.124.  Google Scholar

Figure 1.  simulation results of $ S(t),I(t),R(t) $ respectively for the SDE model (1.1) with different initial conditions $ (S_{0},I_{0},R_{0}) $ and the parameters: $ \mu = 0.1 $, $ \beta = 0.62 $, $ \lambda = 0.5 $, $ \gamma = 0.5 $, $ \sigma = 0.2 $. Here $ \mathcal{R_S} = 1 $ and $ \sigma^{2}<\beta $. For the different values of initial conditions the infection-free equilibrium $ E_0(1,0,0) $ is asymptotically stable in probability
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 2.  simulation results of $ S(t),I(t),R(t) $ respectively for the SDE model (1.1) with different initial conditions $ (S_{0},I_{0},R_{0}) $ and the parameters: $ \mu = 0.1 $, $ \beta = 0.7802 $, $ \lambda = 0.2 $, $ \gamma = 0.2 $, $ \sigma = 0.98 $. Here $ \mathcal{R_S} = 1 $ and $ \beta<\sigma^{2} $. For the different values of initial conditions, respectively, $ S(t) $, $ I(t) $ and $ R(t) $ rises to or above the level $ \xi_s = 0.6247 $, $ \xi_i = 0.2252 $ and $ \xi_r = 0.1501 $ infinitely often with probability one
Figure Options

Download full-size image

Download as PowerPoint slide

[1]

Yanan Zhao, Daqing Jiang, Xuerong Mao, Alison Gray. The threshold of a stochastic SIRS epidemic model in a population with varying size. Discrete & Continuous Dynamical Systems - B, 2015, 20 (4) : 1277-1295. doi: 10.3934/dcdsb.2015.20.1277
[2]

Yanan Zhao, Yuguo Lin, Daqing Jiang, Xuerong Mao, Yong Li. Stationary distribution of stochastic SIRS epidemic model with standard incidence. Discrete & Continuous Dynamical Systems - B, 2016, 21 (7) : 2363-2378. doi: 10.3934/dcdsb.2016051
[3]

Tomás Caraballo, Mohamed El Fatini, Idriss Sekkak, Regragui Taki, Aziz Laaribi. A stochastic threshold for an epidemic model with isolation and a non linear incidence. Communications on Pure & Applied Analysis, 2020, 19 (5) : 2513-2531. doi: 10.3934/cpaa.2020110
[4]

Qingshan Yang, Xuerong Mao. Stochastic dynamics of SIRS epidemic models with random perturbation. Mathematical Biosciences & Engineering, 2014, 11 (4) : 1003-1025. doi: 10.3934/mbe.2014.11.1003
[5]

Yukihiko Nakata, Yoichi Enatsu, Yoshiaki Muroya. On the global stability of an SIRS epidemic model with distributed delays. Conference Publications, 2011, 2011 (Special) : 1119-1128. doi: 10.3934/proc.2011.2011.1119
[6]

Zhixing Hu, Ping Bi, Wanbiao Ma, Shigui Ruan. Bifurcations of an SIRS epidemic model with nonlinear incidence rate. Discrete & Continuous Dynamical Systems - B, 2011, 15 (1) : 93-112. doi: 10.3934/dcdsb.2011.15.93
[7]

Kangbo Bao, Libin Rong, Qimin Zhang. Analysis of a stochastic SIRS model with interval parameters. Discrete & Continuous Dynamical Systems - B, 2019, 24 (9) : 4827-4849. doi: 10.3934/dcdsb.2019033
[8]

Massimiliano Tamborrino. Approximation of the first passage time density of a Wiener process to an exponentially decaying boundary by two-piecewise linear threshold. Application to neuronal spiking activity. Mathematical Biosciences & Engineering, 2016, 13 (3) : 613-629. doi: 10.3934/mbe.2016011
[9]

Geni Gupur, Xue-Zhi Li. Global stability of an age-structured SIRS epidemic model with vaccination. Discrete & Continuous Dynamical Systems - B, 2004, 4 (3) : 643-652. doi: 10.3934/dcdsb.2004.4.643
[10]

Lin Zhao, Zhi-Cheng Wang, Liang Zhang. Threshold dynamics of a time periodic and two–group epidemic model with distributed delay. Mathematical Biosciences & Engineering, 2017, 14 (5&6) : 1535-1563. doi: 10.3934/mbe.2017080
[11]

Toshikazu Kuniya, Yoshiaki Muroya, Yoichi Enatsu. Threshold dynamics of an SIR epidemic model with hybrid of multigroup and patch structures. Mathematical Biosciences & Engineering, 2014, 11 (6) : 1375-1393. doi: 10.3934/mbe.2014.11.1375
[12]

Liang Zhang, Zhi-Cheng Wang. Threshold dynamics of a reaction-diffusion epidemic model with stage structure. Discrete & Continuous Dynamical Systems - B, 2017, 22 (10) : 3797-3820. doi: 10.3934/dcdsb.2017191
[13]

Yijun Lou, Xiao-Qiang Zhao. Threshold dynamics in a time-delayed periodic SIS epidemic model. Discrete & Continuous Dynamical Systems - B, 2009, 12 (1) : 169-186. doi: 10.3934/dcdsb.2009.12.169
[14]

Yoshiaki Muroya, Toshikazu Kuniya, Yoichi Enatsu. Global stability of a delayed multi-group SIRS epidemic model with nonlinear incidence rates and relapse of infection. Discrete & Continuous Dynamical Systems - B, 2015, 20 (9) : 3057-3091. doi: 10.3934/dcdsb.2015.20.3057
[15]

Qun Liu, Daqing Jiang, Tasawar Hayat, Ahmed Alsaedi. Dynamical behavior of a multigroup SIRS epidemic model with standard incidence rates and Markovian switching. Discrete & Continuous Dynamical Systems - A, 2019, 39 (10) : 5683-5706. doi: 10.3934/dcds.2019249
[16]

Qun Liu, Daqing Jiang. Dynamics of a multigroup SIRS epidemic model with random perturbations and varying total population size. Communications on Pure & Applied Analysis, 2020, 19 (2) : 1089-1110. doi: 10.3934/cpaa.2020050
[17]

Min Lu, Chuang Xiang, Jicai Huang. Bogdanov-Takens bifurcation in a SIRS epidemic model with a generalized nonmonotone incidence rate. Discrete & Continuous Dynamical Systems - S, 2018, 0 (0) : 0-0. doi: 10.3934/dcdss.2020115
[18]

Tomás Caraballo, Mohamed El Fatini, Roger Pettersson, Regragui Taki. A stochastic SIRI epidemic model with relapse and media coverage. Discrete & Continuous Dynamical Systems - B, 2018, 23 (8) : 3483-3501. doi: 10.3934/dcdsb.2018250
[19]

Badr-eddine Berrhazi, Mohamed El Fatini, Tomás Caraballo, Roger Pettersson. A stochastic SIRI epidemic model with Lévy noise. Discrete & Continuous Dynamical Systems - B, 2018, 23 (6) : 2415-2431. doi: 10.3934/dcdsb.2018057
[20]

Arnaud Debussche, Sylvain De Moor, Julien Vovelle. Diffusion limit for the radiative transfer equation perturbed by a Wiener process. Kinetic & Related Models, 2015, 8 (3) : 467-492. doi: 10.3934/krm.2015.8.467

2018 Impact Factor: 1.008

Tools

Metrics

  • PDF downloads (141)
  • HTML views (129)
  • Cited by (0)

Other articles
by authors

[Back to Top]

Copyright © 2020 American Institute of Mathematical Sciences