2208.07543
On parameter identifiability in network-based epidemic models
István Z. Kiss, Péter L. Simon
correctmedium confidence
- Category
- Not specified
- Journal tier
- Strong Field
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The paper and the model reach the same conclusions: (i) in the well-mixed SIR ODE only β=τn is identifiable (strong unidentifiability), (ii) in the pairwise SIR with κ=(n−1)/n one reduces the inference to a single scalar equation in n where the function f(n) is nearly constant, yielding weak unidentifiability, and (iii) in the EBCM on Poisson(n), eliminating τ gives λ+γ=γq (n−1)/(n−q) with q=ln(s∞)/(s∞−1)>1, and f(n) decreases to 1, again implying weak unidentifiability. The model reproduces the paper’s reductions and asymptotics, and (for EBCM) correctly proves monotonicity on (2,∞) under q<2. Minor differences are present in exposition and in how “infinite measure” is justified (line vs. band), but the mathematical content agrees.
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} strong field \textbf{Justification:} The paper offers a clear, analytically grounded exploration of parameter unidentifiability across several mean-field network epidemic models. The reductions, limits, and conclusions are correct and well motivated. With small clarifications on measure-theoretic wording (infinite measure) and on how global definitions translate into model-specific error tolerances, the work would be even clearer and more rigorous.