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• W2963257046 abstract "Recently, a long-term model of HIV infection dynamics [<span class=xref><a href=#longTerm ref-type=bibr>8</a></span>] was developed to describe the entire time course of the disease. It consists of a large system of ODEs with many parameters, and is expensive to simulate. In the current paper, this model is analyzed by determining all infection-free steady states and studying the local stability properties of the unique biologically-relevant equilibrium. Active subspace methods are then used to perform a global sensitivity analysis and study the dependence of an infected individual's T-cell count on the parameter space. Building on these results, a global-in-time approximation of the T-cell count is created by constructing dynamic active subspaces and reduced order models are generated, thereby allowing for inexpensive computation." @default.
• W2963257046 created "2019-07-30" @default.
• W2963257046 creator A5014034137 @default.
• W2963257046 creator A5036033406 @default.
• W2963257046 date "2017-01-01" @default.
• W2963257046 modified "2023-09-23" @default.
• W2963257046 title "Mathematical analysis and dynamic active subspaces for a long term model of HIV" @default.
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• W2963257046 doi "https://doi.org/10.3934/mbe.2017040" @default.
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