IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v45y2004i1p3-23.html
   My bibliography  Save this article

Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction

Author

Listed:
  • Wierman, John C.
  • Marchette, David J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Wierman, John C. & Marchette, David J., 2004. "Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction," Computational Statistics & Data Analysis, Elsevier, vol. 45(1), pages 3-23, February.
  • Handle: RePEc:eee:csdana:v:45:y:2004:i:1:p:3-23
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(03)00113-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ball, Frank & Donnelly, Peter, 1995. "Strong approximations for epidemic models," Stochastic Processes and their Applications, Elsevier, vol. 55(1), pages 1-21, January.
    2. Oppenheim, Irwin & Shuler, Kurt E. & Weiss, George H., 1977. "Stochastic theory of nonlinear rate processes with multiple stationary states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 88(2), pages 191-214.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yonghong Xu & Jianguo Ren, 2016. "Propagation Effect of a Virus Outbreak on a Network with Limited Anti-Virus Ability," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-15, October.
    2. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    3. Abdel-Gawad, Hamdy I. & Baleanu, Dumitru & Abdel-Gawad, Ahmed H., 2021. "Unification of the different fractional time derivatives: An application to the epidemic-antivirus dynamical system in computer networks," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Hohle, Michael & Feldmann, Ulrike, 2007. "RLadyBug--An R package for stochastic epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 680-686, October.
    5. McKinley, Trevelyan J. & Ross, Joshua V. & Deardon, Rob & Cook, Alex R., 2014. "Simulation-based Bayesian inference for epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 434-447.
    6. Zhang, Chunming & Huang, Haitao, 2016. "Optimal control strategy for a novel computer virus propagation model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 251-265.
    7. Singh, Jagdev & Kumar, Devendra & Hammouch, Zakia & Atangana, Abdon, 2018. "A fractional epidemiological model for computer viruses pertaining to a new fractional derivative," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 504-515.
    8. A.H. Nzokem, 2021. "SIS Epidemic Model Birth-and-Death Markov Chain Approach," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 1-10, July.
    9. Amador, Julia, 2014. "The stochastic SIRA model for computer viruses," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 1112-1124.
    10. Ren, Jianguo & Yang, Xiaofan & Yang, Lu-Xing & Xu, Yonghong & Yang, Fanzhou, 2012. "A delayed computer virus propagation model and its dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 45(1), pages 74-79.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Simon, Matthieu, 2020. "SIR epidemics with stochastic infectious periods," Stochastic Processes and their Applications, Elsevier, vol. 130(7), pages 4252-4274.
    2. Barbour, A. D. & Utev, Sergey, 2004. "Approximating the Reed-Frost epidemic process," Stochastic Processes and their Applications, Elsevier, vol. 113(2), pages 173-197, October.
    3. Terrazas-Santamaria Diana & Mendoza-Palacios Saul & Berasaluce-Iza Julen, 2023. "An Alternative Approach to Frequency of Patent Technology Codes: The Case of Renewable Energy Generation," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 17(1), pages 1-14, January.
    4. Ball, Frank & Neal, Peter, 2003. "The great circle epidemic model," Stochastic Processes and their Applications, Elsevier, vol. 107(2), pages 233-268, October.
    5. Ross, J.V. & Pollett, P.K., 2010. "Simple rules for ranking and optimally managing metapopulations," Ecological Modelling, Elsevier, vol. 221(21), pages 2515-2520.
    6. Claude Lefe`vre & Sergey Utev, 1999. "Branching Approximation for the Collective Epidemic Model," Methodology and Computing in Applied Probability, Springer, vol. 1(2), pages 211-228, September.
    7. van Doorn, Erik A. & Pollett, Philip K., 2013. "Quasi-stationary distributions for discrete-state models," European Journal of Operational Research, Elsevier, vol. 230(1), pages 1-14.
    8. Villela, Daniel A.M., 2016. "Analysis of the vectorial capacity of vector-borne diseases using moment-generating functions," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 1-8.
    9. Johannes Müler & Volker Hösel, 2007. "Estimating the Tracing Probability from Contact History at the Onset of an Epidemic," Mathematical Population Studies, Taylor & Francis Journals, vol. 14(4), pages 211-236, November.
    10. Demiris, Nikolaos & Kypraios, Theodore & Smith, L. Vanessa, 2012. "On the epidemic of financial crises," MPRA Paper 46693, University Library of Munich, Germany.
    11. Chen, Zezhun & Dassios, Angelos & Kuan, Valerie & Lim, Jia Wei & Qu, Yan & Surya, Budhi & Zhao, Hongbiao, 2021. "A two-phase dynamic contagion model for COVID-19," LSE Research Online Documents on Economics 105064, London School of Economics and Political Science, LSE Library.
    12. Clancy, Damian & O'Neill, Philip, 1998. "Approximation of epidemics by inhomogeneous birth-and-death processes," Stochastic Processes and their Applications, Elsevier, vol. 73(2), pages 233-245, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:45:y:2004:i:1:p:3-23. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.