2407.20711
Information index augmented eRG to model vaccination behaviour: A case study of COVID-19 in the US
Bruno Buonomo, Alessandra D’Alise, Rossella Della Marca, Francesco Sannino
incompletehigh confidence
- Category
- Not specified
- Journal tier
- Specialist/Solid
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The paper introduces BeRG and fits it to US data but provides no formal comparison theorem versus the baseline eRG with constant c0. The candidate solution gives a rigorous single-region comparison proof under the paper’s equations: with c(M) ≥ c0, it shows γB ≤ γ0, AB ≤ A0, αB' ≤ α0' on the pre-peak set, and hence IB(t) ≤ I0(t), with strictness whenever c(M) > c0 on sets of positive measure. These steps are consistent with the model equations given in the paper, but the paper itself does not supply such a proof.
Referee report (LaTeX)
\textbf{Recommendation:} major revisions
\textbf{Journal Tier:} specialist/solid
\textbf{Justification:}
The manuscript clearly formulates BeRG and demonstrates improved fits in appropriate US divisions. However, it lacks a rigorous analysis of qualitative properties suggested in the text (e.g., why behavioural vaccination should reduce incidence pre-peak). Providing even a concise mathematical comparison (as in the model solution herein) would significantly strengthen the work. Clarifications about parameter regimes ensuring positivity of γ and a short discussion of the single-region vs multi-region implications would also be valuable.