A hierarchical mixed-effects model is proposed to account for both individual- and population-level variability in human immunodeficiency virus (HIV) dynamics. This model is implemented by formulating the crucial parameters as random variables in an in-host HIV model. Model reduction is used to guide the choice for a minimal set of parameters, whose distributions are estimated by the global two-stage method. We analyze the system of ordinary differential equations with random coefficients and provide numerical simulations illustrating its asymptotic behaviors.
Bibliographical noteFunding Information:
\ast Received by the editors February 20, 2019; accepted for publication (in revised form) March 26, 2020; published electronically May 20, 2020. https://doi.org/10.1137/19M1246031 Funding: The work of the third author was supported by the NRF through grant 2016R1D1A1B04931897 and by the National Research Council of Science \& Technology (NST) grant by the Korea government (MSIP) through award CRC-16-01-KRICT. The work of the fifth author was supported by the NRF through grant 2015R1A5A1009350 and NRF-2016R1A2B4014178. \dagger Department of Computational Science and Engineering, Yonsei University, Korea (yunjung0104@ gmail.com, email@example.com). \ddagger Department of Mathematics, Inha University, Korea (firstname.lastname@example.org). \S Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Korea (email@example.com). \P Department of Mathematics \& Department of CSE, Yonsei University, Korea (ezhyun@yonsei. ac.kr).
© 2020 Society for Industrial and Applied Mathematics.
All Science Journal Classification (ASJC) codes
- Applied Mathematics