ReviewBiologicals : journal of the International Association of Biological Standardization2021
Animal experiments show impact of vaccination on reduction of SARS-CoV-2 virus circulation: A model for vaccine development?
Review in Biologicals : journal of the International Association of Biological Standardization, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Ferritin Complex Vaccine against Influenza A Using Screened Immunogenic Sequences from Fv-Antibody Library.ACS pharmacology & translational science · 2026Article
- CoviWall, a whole-virion-inactivated B.1.617.2 vaccine candidate, induces potent humoral and Th1 cell response in mice and protects against B.1.617.2 strain challenge in Syrian hamsters.Frontiers in immunology · 2024Article
- Emergence of SARS-CoV-2 Omicron (B.1.1.529) variant, salient features, high global health concerns and strategies to counter it amid ongoing COVID-19 pandemic.Environmental research · 2022Review
- Article
- Animal models for SARS-CoV-2 and SARS-CoV-1 pathogenesis, transmission and therapeutic evaluation.World journal of virology · 2022Review
- Consecutive Hits of COVID-19 in India: The Mystery of Plummeting Cases and Current Scenario.Archives of Razi Institute · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the pre-clinical phase, SARS-CoV-2 vaccines were tested in animal models, including exposure trials, to investigate protection against SARS-CoV-2. These studies paved the way for clinical development. The objective of our review was to provide an overview of published animal exposure results, focussing on the capacity of vaccines to reduce/prevent viral shedding.
methodUsing Medline, we retrieved eighteen papers on eight different vaccine platforms in four animal models. Data were extracted on presence/absence of viral RNA in nose, throat, or lungs, and neutralizing antibody levels in the blood.
resultsAll vaccines showed a tendency of reduced viral load after exposure. Particularly nasal swab results are likely to give an indication about the impact on virus excretion in the environment. Similarly, the reduction or prevention of viral replication in the bronchoalveolar environment might be related with disease prevention, explaining the high efficacy in clinical trials. DISCUSSION: Although it remains difficult to compare the results directly, the potential for a strong reduction of transmission was shown, indicating that the animal models predicted what is observed in the field after large scale human vaccination. This merits further attention for standardization of exposure experiments, with the intention to speed up future vaccine development.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.