Modelling long-term human immunodeficiency virus dynamic models with application to acquired immune deficiency syndrome clinical study
AbstractMathematical modelling of human immunodeficiency virus (HIV) dynamics has played an important role in acquired immune deficiency syndrome research. Deterministic dynamic models have been developed to study the viral dynamic process for understanding the pathogenesis of HIV type 1 infection and antiviral treatment strategies. We propose a new multistage estimation procedure which uses data, HIV viral load and CD4+ T-cell counts, from an acquired immune deficiency syndrome clinical study, to estimate the parameters in a long-term HIV dynamic model containing both constant and time varying parameters. Simulation studies and a real data application show that the methods proposed are efficient and appropriate to estimate both constant and time varying parameters in long-term HIV dynamic models. Copyright (c) 2010 Royal Statistical Society.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).
Volume (Year): 59 (2010)
Issue (Month): 5 ()
Contact details of provider:
Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom
Web page: http://wileyonlinelibrary.com/journal/rssc
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.