IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1001058.html
   My bibliography  Save this article

Stochastic Theory of Early Viral Infection: Continuous versus Burst Production of Virions

Author

Listed:
  • John E Pearson
  • Paul Krapivsky
  • Alan S Perelson

Abstract

Viral production from infected cells can occur continuously or in a burst that generally kills the cell. For HIV infection, both modes of production have been suggested. Standard viral dynamic models formulated as sets of ordinary differential equations can not distinguish between these two modes of viral production, as the predicted dynamics is identical as long as infected cells produce the same total number of virions over their lifespan. Here we show that in stochastic models of viral infection the two modes of viral production yield different early term dynamics. Further, we analytically determine the probability that infections initiated with any number of virions and infected cells reach extinction, the state when both the population of virions and infected cells vanish, and show this too has different solutions for continuous and burst production. We also compute the distributions of times to establish infection as well as the distribution of times to extinction starting from both a single virion as well as from a single infected cell for both modes of virion production.Author Summary: The dynamics of HIV infection and treatment has been extensively studied using ordinary differential equation models. Recent work on HIV transmission has suggested that most sexually transmitted infections are started by a single virus or infected cell. This observation coupled with the fact that successful HIV transmission only occurs in 1 per 100 to 1 per 1000 coital acts suggests that early events in infection are stochastic. Here we develop a stochastic model of HIV infection and use it to characterize the dynamics of early infection when virus is released from cells either continuously or in a burst. We show that these mechanisms of viral production produce different early dynamics, with different probabilities of extinction and different distributions of time to establish infection. In deterministic models, these modes of viral production are indistinguishable.

Suggested Citation

  • John E Pearson & Paul Krapivsky & Alan S Perelson, 2011. "Stochastic Theory of Early Viral Infection: Continuous versus Burst Production of Virions," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-17, February.
  • Handle: RePEc:plo:pcbi00:1001058
    DOI: 10.1371/journal.pcbi.1001058
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1001058
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1001058&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1001058?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. Alan S. Perelson & Paulina Essunger & Yunzhen Cao & Mika Vesanen & Arlene Hurley & Kalle Saksela & Martin Markowitz & David D. Ho, 1997. "Decay characteristics of HIV-1-infected compartments during combination therapy," Nature, Nature, vol. 387(6629), pages 188-191, May.
    2. J. O. Lloyd-Smith & S. J. Schreiber & P. E. Kopp & W. M. Getz, 2005. "Superspreading and the effect of individual variation on disease emergence," Nature, Nature, vol. 438(7066), pages 355-359, November.
    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. Jonathan Carruthers & Grant Lythe & Martín López-García & Joseph Gillard & Thomas R Laws & Roman Lukaszewski & Carmen Molina-París, 2020. "Stochastic dynamics of Francisella tularensis infection and replication," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-26, June.

    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. Tardy, Olivia & Lenglos, Christophe & Lai, Sandra & Berteaux, Dominique & Leighton, Patrick A., 2023. "Rabies transmission in the Arctic: An agent-based model reveals the effects of broad-scale movement strategies on contact risk between Arctic foxes," Ecological Modelling, Elsevier, vol. 476(C).
    2. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    3. Moshe B Hoshen & Anthony H Burton & Themis J V Bowcock, 2007. "Simulating disease transmission dynamics at a multi-scale level," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 26-34.
    4. Lazebnik, Teddy & Spiegel, Orr, 2025. "Individual variation affects outbreak magnitude and predictability in multi-pathogen model of pigeons visiting dairy farms," Ecological Modelling, Elsevier, vol. 499(C).
    5. Luc E. Coffeng & Sake J. de Vlas, 2022. "Predicting epidemics and the impact of interventions in heterogeneous settings: Standard SEIR models are too pessimistic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S1), pages 28-35, November.
    6. Joseph B. Bak-Coleman & Ian Kennedy & Morgan Wack & Andrew Beers & Joseph S. Schafer & Emma S. Spiro & Kate Starbird & Jevin D. West, 2022. "Combining interventions to reduce the spread of viral misinformation," Nature Human Behaviour, Nature, vol. 6(10), pages 1372-1380, October.
    7. Qi, Kai & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed, 2021. "Virus dynamic behavior of a stochastic HIV/AIDS infection model including two kinds of target cell infections and CTL immune responses," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 548-570.
    8. Kris V. Parag & Robin N. Thompson & Christl A. Donnelly, 2022. "Are epidemic growth rates more informative than reproduction numbers?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S1), pages 5-15, November.
    9. Thomas Ash & Antonio M. Bento & Daniel Kaffine & Akhil Rao & Ana I. Bento, 2022. "Disease-economy trade-offs under alternative epidemic control strategies," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    10. Maarten Jan Wensink & Linda Juel Ahrenfeldt & Sören Möller, 2020. "Variability Matters," IJERPH, MDPI, vol. 18(1), pages 1-8, December.
    11. Lingcai Kong & Jinfeng Wang & Weiguo Han & Zhidong Cao, 2016. "Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model," IJERPH, MDPI, vol. 13(3), pages 1-13, February.
    12. Carolyn Ingram & Vicky Downey & Mark Roe & Yanbing Chen & Mary Archibald & Kadri-Ann Kallas & Jaspal Kumar & Peter Naughton & Cyril Onwuelazu Uteh & Alejandro Rojas-Chaves & Shibu Shrestha & Shiraz Sy, 2021. "COVID-19 Prevention and Control Measures in Workplace Settings: A Rapid Review and Meta-Analysis," IJERPH, MDPI, vol. 18(15), pages 1-26, July.
    13. A. M. Elaiw & E. Kh. Elnahary, 2019. "Analysis of General Humoral Immunity HIV Dynamics Model with HAART and Distributed Delays," Mathematics, MDPI, vol. 7(2), pages 1-35, February.
    14. Brendan D Cowled & Michael P Ward & Shawn W Laffan & Francesca Galea & M Graeme Garner & Anna J MacDonald & Ian Marsh & Petra Muellner & Katherine Negus & Sumaiya Quasim & Andrew P Woolnough & Stephen, 2012. "Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-8, October.
    15. Lu, Xiaosun & Huang, Yangxin & Zhu, Yiliang, 2016. "Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 119-130.
    16. Wayne M. Getz & Jean-Paul Gonzalez & Richard Salter & James Bangura & Colin Carlson & Moinya Coomber & Eric Dougherty & David Kargbo & Nathan D. Wolfe & Nadia Wauquier, 2015. "Tactics and Strategies for Managing Ebola Outbreaks and the Salience of Immunization," Post-Print hal-01214432, HAL.
    17. Robin N Thompson & Christopher A Gilligan & Nik J Cunniffe, 2016. "Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-18, April.
    18. Glenn Ellison, 2024. "Implications of heterogeneous SIR models for analyses of COVID-19," Review of Economic Design, Springer;Society for Economic Design, vol. 28(4), pages 651-687, December.
    19. Kathrin Büttner & Joachim Krieter & Arne Traulsen & Imke Traulsen, 2013. "Efficient Interruption of Infection Chains by Targeted Removal of Central Holdings in an Animal Trade Network," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-12, September.
    20. Ahmed M. Elaiw & Taofeek O. Alade & Saud M. Alsulami, 2018. "Global Stability of Within-Host Virus Dynamics Models with Multitarget Cells," Mathematics, MDPI, vol. 6(7), pages 1-19, July.

    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:pcbi00:1001058. 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: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    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.