IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0138765.html
   My bibliography  Save this article

Modeling and Analyzing the Transmission Dynamics of HBV Epidemic in Xinjiang, China

Author

Listed:
  • Tailei Zhang
  • Kai Wang
  • Xueliang Zhang

Abstract

Hepatitis B is an infectious disease caused by the hepatitis B virus (HBV) which affects livers. In this paper, we formulate a hepatitis B model to study the transmission dynamics of hepatitis B in Xinjiang, China. The epidemic model involves an exponential birth rate and vertical transmission. For a better understanding of HBV transmission dynamics, we analyze the dynamic behavior of the model. The modified reproductive number σ is obtained. When σ 1, the disease-free equilibrium is unstable and the disease is uniformly persistent. In the simulation, parameters are chosen to fit public data in Xinjiang. The simulation indicates that the cumulated HBV infection number in Xinjiang will attain about 600,000 cases unless there are stronger or more effective control measures by the end of 2017. Sensitive analysis results show that enhancing the vaccination rate for newborns in Xinjiang is very effective to stop the transmission of HBV. Hence, we recommend that all infants in Xinjiang receive the hepatitis B vaccine as soon as possible after birth.

Suggested Citation

  • Tailei Zhang & Kai Wang & Xueliang Zhang, 2015. "Modeling and Analyzing the Transmission Dynamics of HBV Epidemic in Xinjiang, China," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-14, September.
    • Handle: RePEc:plo:pone00:0138765
    DOI: 10.1371/journal.pone.0138765
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138765
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0138765&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0138765?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hongyu Miao & Carrie Dykes & Lisa M. Demeter & Hulin Wu, 2009. "Differential Equation Modeling of HIV Viral Fitness Experiments: Model Identification, Model Selection, and Multimodel Inference," Biometrics, The International Biometric Society, vol. 65(1), pages 292-300, March.
    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. Huo, Hai-Feng & Jing, Shuang-Lin & Wang, Xun-Yang & Xiang, Hong, 2020. "Modeling and analysis of a H1N1 model with relapse and effect of Twitter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Hussain, Ghulam & Khan, Amir & Zahri, Mostafa & Zaman, Gul, 2022. "Ergodic stationary distribution of stochastic epidemic model for HBV with double saturated incidence rates and vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    3. Khan, Tahir & Khan, Amir & Zaman, Gul, 2018. "The extinction and persistence of the stochastic hepatitis B epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 123-128.
    4. Liping Zhang & Li Wang & Yanling Zheng & Kai Wang & Xueliang Zhang & Yujian Zheng, 2017. "Time Prediction Models for Echinococcosis Based on Gray System Theory and Epidemic Dynamics," IJERPH, MDPI, vol. 14(3), pages 1-14, March.
    5. Shah, Syed Azhar Ali & Khan, Muhammad Altaf & Farooq, Muhammad & Ullah, Saif & Alzahrani, Ebraheem O., 2020. "A fractional order model for Hepatitis B virus with treatment via Atangana–Baleanu derivative," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).

    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. Xinyu Zhang & Jiguo Cao & Raymond J. Carroll, 2015. "On the selection of ordinary differential equation models with application to predator-prey dynamical models," Biometrics, The International Biometric Society, vol. 71(1), pages 131-138, March.
    2. Commenges, D. & Jolly, D. & Drylewicz, J. & Putter, H. & Thiébaut, R., 2011. "Inference in HIV dynamics models via hierarchical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 446-456, January.
    3. Afnizanfaizal Abdullah & Safaai Deris & Mohd Saberi Mohamad & Sohail Anwar, 2013. "An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    4. Afnizanfaizal Abdullah & Safaai Deris & Sohail Anwar & Satya N V Arjunan, 2013. "An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-16, March.
    5. Wang, Lianwen & Liu, Zhijun & Guo, Caihong & Li, Yong & Zhang, Xinan, 2021. "New global dynamical results and application of several SVEIS epidemic models with temporary immunity," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    6. Xuming Tong & Jinghang Chen & Hongyu Miao & Tingting Li & Le Zhang, 2015. "Development of an Agent-Based Model (ABM) to Simulate the Immune System and Integration of a Regression Method to Estimate the Key ABM Parameters by Fitting the Experimental Data," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    7. Hanwen Huang, 2022. "Bayesian multi‐level mixed‐effects model for influenza dynamics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1978-1995, November.
    8. Hong, Zhaoping & Lian, Heng, 2012. "Time-varying coefficient estimation in differential equation models with noisy time-varying covariates," Journal of Multivariate Analysis, Elsevier, vol. 103(1), pages 58-67, January.

    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:plo:pone00:0138765. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.