Back to Search Start Over

The role of cell-to-cell transmission in HIV infection: insights from a mathematical modeling approach

Authors :
Sophia Y. Rong
Ting Guo
J. Tyler Smith
Xia Wang
Source :
Mathematical Biosciences and Engineering. 20:12093-12117
Publication Year :
2023
Publisher :
American Institute of Mathematical Sciences (AIMS), 2023.

Abstract

HIV infection remains a serious global public health problem. Although current drug treatment is effective and can reduce plasma viral loads below the level of detection, it cannot eradicate the virus. The reasons for the low virus persistence despite long-term therapy have not been fully elucidated. In addition, multiple HIV infection, i.e., infection of a cell by multiple viruses, is common and can facilitate viral recombination and mutations, evading the immune system and conferring resistance to drug treatment. The mechanisms for multiple HIV infection formation and their respective contributions remain unclear. To answer these questions, we developed a mathematical modeling framework that encompasses cell-free viral infection and cell-to-cell spread. We fit sub-models that only have one transmission route and the full model containing both to the multi-infection data from HIV-infected patients, and show that the multi-infection data can only be reproduced if these two transmission routes are both considered. Computer simulations with the best-fitting parameter values indicate that cell-to-cell spread leads to the majority of multiple infection and also accounts for the majority of overall infection. Sensitivity analysis shows that cell-to-cell spread has reduced susceptibility to treatment and may explain low HIV persistence. Taken together, this work indicates that cell-to-cell spread plays a crucial role in the development of HIV multi-infection and low HIV persistence despite long-term therapy, and therefore has important implications for understanding HIV pathogenesis and developing more effective treatment strategies to control or even eliminate the disease.

Details

ISSN :
15510018
Volume :
20
Database :
OpenAIRE
Journal :
Mathematical Biosciences and Engineering
Accession number :
edsair.doi...........7541b029aa891382b098e74d8acaf045
Full Text :
https://doi.org/10.3934/mbe.2023538