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2025 ; 23
(1
): 321
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Enhancing viral dynamics modeling: reliable initial estimation and validity
conditions for quasi-steady state approximation (QSSA)
#MMPMID41131548
Byun JH
; Jung IH
; Iwami S
; Jeong YD
; Kim KS
BMC Biol
2025[Oct]; 23
(1
): 321
PMID41131548
show ga
BACKGROUND: Mathematical models are essential for understanding viral dynamics,
with the basic viral model widely used to describe infection kinetics.
Quasi-steady-state approximation (QSSA) is often applied to improve computational
efficiency and simplify the system. However, the existing viral QSSA model
incorrectly assumes that infected cells evolve on the same fast timescale as the
virus, leading to biologically invalid simplifications. RESULTS: In this study,
we resolved this issue by developing a revised QSSA viral model that correctly
accounts for timescale separation and prevents the erroneous loss of infected
cell initial values during model reduction. We introduce a mathematical method to
estimate the initial condition of infected cells and define a validity condition
( Cv = ?/c ), under which QSSA is accurate only when Cv ? 1 , ensuring proper
timescale separation. Comparative analysis shows that the revised QSSA model
retains biological fidelity while improving predictive accuracy and computational
efficiency. Sensitivity analysis confirmed that it preserves key dynamic
responses to parameter changes, further validating its robustness. Parameter
estimation demonstrated that the revised QSSA model more accurately recovers true
parameter values under strong timescale separation. CONCLUSIONS: This work
resolves a key flaw in existing QSSA models, enabling more accurate and
consistent modeling of viral dynamics. By correcting the infected cell loss
issue, our findings provide a robust framework for virological applications,
particularly useful when experimental data are limited.