IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0070578.html
   My bibliography  Save this article

A Stochastic Multi-Scale Model of HIV-1 Transmission for Decision-Making: Application to a MSM Population

Author

Listed:
  • Lilit Yeghiazarian
  • William G Cumberland
  • Otto O Yang

Abstract

Background: In the absence of an effective vaccine against HIV-1, the scientific community is presented with the challenge of developing alternative methods to curb its spread. Due to the complexity of the disease, however, our ability to predict the impact of various prevention and treatment strategies is limited. While ART has been widely accepted as the gold standard of modern care, its timing is debated. Objectives: To evaluate the impact of medical interventions at the level of individuals on the spread of infection across the whole population. Specifically, we investigate the impact of ART initiation timing on HIV-1 spread in an MSM (Men who have Sex with Men) population. Design and Methods: A stochastic multi-scale model of HIV-1 transmission that integrates within a single framework the in-host cellular dynamics and their outcomes, patient health states, and sexual contact networks. The model captures disease state and progression within individuals, and allows for simulation of therapeutic strategies. Results: Early ART initiation may substantially affect disease spread through a population. Conclusions: Our model provides a multi-scale, systems-based approach to evaluate the broader implications of therapeutic strategies.

Suggested Citation

  • Lilit Yeghiazarian & William G Cumberland & Otto O Yang, 2013. "A Stochastic Multi-Scale Model of HIV-1 Transmission for Decision-Making: Application to a MSM Population," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
  • Handle: RePEc:plo:pone00:0070578
    DOI: 10.1371/journal.pone.0070578
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0070578
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0070578&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0070578?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. Catharina P. B. Van der Ploeg & Carina Van Vliet & Sake J. De Vlas & Jeckoniah O. Ndinya-Achola & Lieve Fransen & Gerrit J. Van Oortmarssen & J. Dik F. Habbema, 1998. "STDSIM: A Microsimulation Model for Decision Support in STD Control," Interfaces, INFORMS, vol. 28(3), pages 84-100, June.
    2. David D. Ho & Avidan U. Neumann & Alan S. Perelson & Wen Chen & John M. Leonard & Martin Markowitz, 1995. "Rapid Turnover of Plasma Virions and CD4 Lymphocytes in HIV-1 Infection," Working Papers 95-01-002, Santa Fe Institute.
    3. Andrew C Ahn & Muneesh Tewari & Chi-Sang Poon & Russell S Phillips, 2006. "The Clinical Applications of a Systems Approach," PLOS Medicine, Public Library of Science, vol. 3(7), pages 1-1, May.
    4. Ronald L. Iman & Jon C. Helton, 1988. "An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models," Risk Analysis, John Wiley & Sons, vol. 8(1), pages 71-90, March.
    5. Eric S. Rosenberg & Marcus Altfeld & Samuel H. Poon & Mary N. Phillips & Barbara M. Wilkes & Robert L. Eldridge & Gregory K. Robbins & Richard T. D'Aquila & Philip J. R. Goulder & Bruce D. Walker, 2000. "Immune control of HIV-1 after early treatment of acute infection," Nature, Nature, vol. 407(6803), pages 523-526, September.
    6. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
    Full references (including those not matched with items on IDEAS)

    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. Floriana Gargiulo & Sônia Ternes & Sylvie Huet & Guillaume Deffuant, 2010. "An Iterative Approach for Generating Statistically Realistic Populations of Households," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-9, January.
    2. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    3. Saturnino Luz & Masood Masoodian, 2022. "Exploring Environmental and Geographical Factors Influencing the Spread of Infectious Diseases with Interactive Maps," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    4. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    5. Pablo D. Fajgelbaum & Amit Khandelwal & Wookun Kim & Cristiano Mantovani & Edouard Schaal, 2021. "Optimal Lockdown in a Commuting Network," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 503-522, December.
    6. 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).
    7. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    8. Iraj Hosseini & Feilim Mac Gabhann, 2012. "Multi-Scale Modeling of HIV Infection in vitro and APOBEC3G-Based Anti-Retroviral Therapy," PLOS Computational Biology, Public Library of Science, vol. 8(2), pages 1-17, February.
    9. Wiriya Mahikul & Somkid Kripattanapong & Piya Hanvoravongchai & Aronrag Meeyai & Sopon Iamsirithaworn & Prasert Auewarakul & Wirichada Pan-ngum, 2020. "Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand," IJERPH, MDPI, vol. 17(7), pages 1-11, March.
    10. Robert S. Bernstein & David C. Sokal & Steven T. Seitz & Bertran Auvert & John Stover & Warren Naamara, 1998. "Simulating the Control of a Heterosexual HIV Epidemic in a Severely Affected East African City," Interfaces, INFORMS, vol. 28(3), pages 101-126, June.
    11. Hillmann, Andreas & Crane, Martin & Ruskin, Heather J., 2017. "HIV models for treatment interruption: Adaptation and comparison," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 44-56.
    12. Stefano Guarino & Enrico Mastrostefano & Massimo Bernaschi & Alessandro Celestini & Marco Cianfriglia & Davide Torre & Lena Rebecca Zastrow, 2021. "Inferring Urban Social Networks from Publicly Available Data," Future Internet, MDPI, vol. 13(5), pages 1-45, April.
    13. Xiaoyan Mu & Anthony Gar-On Yeh & Xiaohu Zhang, 2021. "The interplay of spatial spread of COVID-19 and human mobility in the urban system of China during the Chinese New Year," Environment and Planning B, , vol. 48(7), pages 1955-1971, September.
    14. Alberto Bisin & Andrea Moro, 2020. "Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses," NBER Working Papers 27590, National Bureau of Economic Research, Inc.
    15. Richard C. Larson, 2007. "Simple Models of Influenza Progression Within a Heterogeneous Population," Operations Research, INFORMS, vol. 55(3), pages 399-412, June.
    16. Askitas, Nikos & Tatsiramos, Konstantinos & Verheyden, Bertrand, 2020. "Lockdown Strategies, Mobility Patterns and COVID-19," IZA Discussion Papers 13293, Institute of Labor Economics (IZA).
    17. Sun, Hongquan & Li, Jin, 2020. "A numerical method for a diffusive virus model with general incidence function, cell-to-cell transmission and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    18. Jürgen Hackl & Thibaut Dubernet, 2019. "Epidemic Spreading in Urban Areas Using Agent-Based Transportation Models," Future Internet, MDPI, vol. 11(4), pages 1-14, April.
    19. Gumel, A.B. & Twizell, E.H. & Yu, P., 2000. "Numerical and bifurcation analyses for a population model of HIV chemotherapy," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(1), pages 169-181.
    20. Lee, Sang-Hee & Park, Cheol-Min, 2022. "The effect of hunter-wild boar interactions and landscape heterogeneity on wild boar population size: A simulation study," Ecological Modelling, Elsevier, vol. 464(C).

    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:pone00:0070578. 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.