What peer‑reviewed replications or rebuttals exist that test Fenton and Neil’s principal statistical claims?

1. What Fenton and Neil have published and where it sits in the evidence ecosystem

Fenton and Neil’s work on COVID‑19 — including papers alleging systematic miscategorisation of vaccine status and uncertainty in vaccine effectiveness — is represented in the supplied material as a mix of preprints (medRxiv), research‑gate entries and conference outputs rather than a trail of standalone, peer‑reviewed journal articles that would be the usual target for formal replication or rebuttal ^[1]. Their team also authored a Significance piece and other commentary that have fed public debate; these contributions have visibility but do not by themselves constitute independent, peer‑reviewed replication studies ^[1].

2. Where peer review and replication tend to show up in the research lifecycle

Meta‑research and replication projects make clear that replication is expensive and selective, and that faster, lower‑cost signals (prediction markets, expert elicitation) are sometimes used to triage which claims should be replicated ^[3]. The supplied sources also point to longstanding worries about the reliability of published research — the Ioannidis thesis that “most published research findings are false” remains a foundational critique of relying on single studies without replication ^{[4] [5]}. That context explains why a controversial statistical claim like Fenton and Neil’s ideally requires formal reanalysis by independent teams and eventual journal‑based replication to be decisive ^{[3] [4]}.

3. What the supplied reporting shows about direct rebuttals or replications

Within the provided sources there is no documented example of a peer‑reviewed paper that directly replicates or rebuts the principal statistical claims made by Fenton and Neil about COVID‑19 mortality or vaccine‑status miscoding; the visible follow‑ups are primarily commentary (e.g., Daily Sceptic’s review of their book) and internal team preprints and conference material that extend their own analyses rather than independent confirmations or refutations ^{[2] [1]}. Because the material includes medRxiv preprints and institutional pages rather than downstream journal articles, it is not possible from these sources to point to an orthodox, peer‑reviewed counterstudy that tests their central assertions ^[1].

4. How to interpret the absence of peer‑reviewed replications in these sources

The absence of documented peer‑reviewed replications or rebuttals in the supplied reporting does not prove Fenton and Neil’s claims true or false; it simply reflects a gap in the specific corpus of articles made available here and a broader reality that contested statistical claims often languish untested while the policy and public debate moves on ^{[3] [4]}. The supplied meta‑science literature suggests that resolving such disputes would normally require independent access to the same datasets, preregistered reanalysis plans, and journal peer review — none of which the provided snippets confirm has yet occurred ^{[3] [1]}.

5. Where independent testing should come from next

Given the contested nature of the claims and the primacy of replication in settling statistical disputes, the logical next steps are formal reanalyses published in peer‑reviewed journals, coordinated replication efforts prioritised by prediction or elicitation techniques, or data releases that enable independent verification; the existing preprints and commentaries provide hypotheses but not the final scientific adjudication that peer‑reviewed replication would provide ^{[1] [3] [4]}. Readers should therefore treat the claims as unresolved in the peer‑reviewed record reflected by the supplied sources.