Evidence map›Paper›PMID 37155606›Full record

ReviewPloS one2023

Candidate historical events for the emergence of Human Coronavirus OC43: A critical reassessment of the molecular evidence.

Brandon Shaw, Derek Gatherer

Open access · goldAbstract readReview
In one paragraph

Review in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Human coronaviruses: activation and antagonism of innate immune responses.Microbiology and molecular biology reviews : MMBR · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Brandon ShawDivision of Biomedical & Life Sciences, Faculty of Health & Medicine, Lancaster University, Lancaster, United Kingdom.ORCID 0000-0002-5061-3994
Derek GathererDivision of Biomedical & Life Sciences, Faculty of Health & Medicine, Lancaster University, Lancaster, United Kingdom.ORCID 0000-0002-7385-5734
Lancaster University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The "Russian Influenza"-coronavirus theory (RICT) proposes that the pandemic of 1889-1892, conventionally regarded as an influenza pandemic, was caused by the emergence of human coronavirus OC43 (HCoV-OC43) as a zoonosis of bovine coronavirus (BCoV). RICT is based on a Bayesian phylogenetic calculation of the date of the most recent common ancestor (MRCA) of HCoV-OC43 and BCoV. The theory also draws on comparison of both symptoms and some epidemiological parameters of the best studied coronavirus pandemic, i.e. COVID-19, with those reported in 1889-1892. The case is completed with circumstantial evidence involving a panzoonotic among cattle in the decade prior to the "Russian Influenza", with characteristics suggesting it may have been caused by BCoV. In this paper, we review the Bayesian phylogenetic evidence for RICT, replicating previous studies and adding our own, in each case critically reviewing the suitability of the datasets used and the parameters applied. We conclude that the most probable date for the MRCA of HCoV-OC43 and BCoV is 1898-1902. This is a decade too late for compatibility with RICT but happens to coincide with another serious outbreak of respiratory illness, reported in both the USA and the UK, in the winter of 1899-1900.

Indexed as

Coronavirus OC43, HumanCOVID-19Influenza, HumanAnimalsBayes TheoremCattleHumansPhylogeny

Identifiers

PMID37155606
PMCPMC10166493
OpenAlexW4375955995

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.