Validation of a Multi-Strain HIV Within-Host Model with AIDS Clinical Studies

Necibe Tuncer (), Kia Ghods, Vivek Sreejithkumar, Adin Garbowit, Mark Zagha and Maia Martcheva
Additional contact information
Necibe Tuncer: Department of Mathematics and Statistics, Florida Atlantic University, Boca Raton, FL 33431, USA
Kia Ghods: Department of Mathematics, Princeton University, Princeton, NJ 08544, USA
Vivek Sreejithkumar: Department of Mathematics and Statistics, Florida Atlantic University, Boca Raton, FL 33431, USA
Adin Garbowit: Department of Mathematics and Statistics, Florida Atlantic University, Boca Raton, FL 33431, USA
Mark Zagha: Department of Mathematics and Statistics, Florida Atlantic University, Boca Raton, FL 33431, USA
Maia Martcheva: Department of Mathematics, University of Florida, P.O. Box 118105, Gainesville, FL 32611, USA

Mathematics, 2024, vol. 12, issue 16, 1-20

Abstract: We used a previously introduced HIV within-host model with sensitive and resistant strains and validated it with two data sets. The first data set is from a clinical study that investigated multi-drug treatments and measured the total CD4 + cell count and viral load. All nine patients in this data set experienced virologic failure. The second data set includes a unique patient who was treated with a unique drug and for whom both the sensitive and resistant strains were measured as well as the CD4 + cells. We studied the structural identifiability of the model with respect to each data set. With respect to the first data set, the model was structurally identifiable when the viral production rate of the sensitive strain was fixed and distinct from the viral production rate of the resistant strain. With respect to the second data set, the model was always structurally identifiable. We fit the model to the first data set using nonlinear mixed effect modeling in Monolix and estimated the population-level parameters. We inferred that the average time to emergence of a resistant strain is 844 days after treatment starts. We fit the model to the second data set and found out that the all the parameters except the mutation rate were practically identifiable.

Keywords: HIV within-host model; two-strain model; identifiability analysis; drug resistance (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/16/2583/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/16/2583/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:16:p:2583-:d:1460972

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().