2012.15585
Dynamical Characterization of Antiviral Effects in COVID-19
Pablo Abuin, Alejandro Anderson, Antonio Ferramosca, Esteban A. Hernandez-Vargas, Alejandro H. Gonzalez
incompletemedium confidence
- Category
- math.DS
- Journal tier
- Specialist/Solid
- Processed
- Sep 28, 2025, 12:55 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The paper’s Theorem 4.1 correctly identifies the threshold R(t_tr) = 1 for efficacy and the qualitative behaviors (items ii–iv), but its item (i) asserts that the viral maximum occurs at t_tr for both p- and β-inhibition; this is only guaranteed for sufficiently strong p-inhibition because V̇ depends on p but not directly on β. The sketch proof relies on the approximation V̇ ≈ (R−1)δV and ignores the α(t) correction, which conflates sign changes at t_tr in the β-only case. The model’s solution improves the analysis with an exact second-derivative identity at stationary points, but it repeats the over-strong claim that the peak is at t_tr for β-inhibition and implicitly infers V̇(t_tr^+) < 0 from R(t_tr) < 1 without justification. Overall, both are close on the main qualitative picture but each misses crucial conditions at the intervention boundary.
Referee report (LaTeX)
\textbf{Recommendation:} major revisions
\textbf{Journal Tier:} specialist/solid
\textbf{Justification:}
The paper develops a clear threshold-based framework for antiviral timing in a standard within-host model and backs it with simulations, but it overstates item (i) of Theorem 4.1 by treating p- and β-inhibitions symmetrically at the treatment boundary. This stems from using an approximation for the sign of V̇ at a discontinuity, which is not valid for β-only inhibition. Correcting item (i), clarifying boundary behavior, and incorporating exact stationary-point arguments would rectify the issue without undermining the main qualitative insights.