Evidence map›Paper›PMID 33132005›Full record

ReviewTrends in immunology2020

Mechanisms of SARS-CoV-2 Transmission and Pathogenesis.

Andrew G Harrison, Tao Lin, Penghua Wang

Abstract readReview
In one paragraph

Review in Trends in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 635 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
635citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

635 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Seawater nasal wash to reduce symptom duration and viral load in COVID-19 and upper respiratory tract infections: a randomized controlled multicenter trial.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
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575 more citing papers are in PubMed but not listed here.

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

3 authors.

Andrew G HarrisonDepartment of Immunology, School of Medicine, University of Connecticut Health Center, Farmington, CT 06030, USA.
Tao LinDepartment of Immunology, School of Medicine, University of Connecticut Health Center, Farmington, CT 06030, USA.
Penghua WangDepartment of Immunology, School of Medicine, University of Connecticut Health Center, Farmington, CT 06030, USA. Electronic address: pewang@uchc.edu.

Funding

The role of UBXNs in antiviral immunityR01AI132526 · NIAID · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI WANG, PENGHUA · 2018 to 2022
$2.1M
NIAID NIH HHS R01 AI132526
6 · The paper itself

Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) marks the third highly pathogenic coronavirus to spill over into the human population. SARS-CoV-2 is highly transmissible with a broad tissue tropism that is likely perpetuating the pandemic. However, important questions remain regarding its transmissibility and pathogenesis. In this review, we summarize current SARS-CoV-2 research, with an emphasis on transmission, tissue tropism, viral pathogenesis, and immune antagonism. We further present advances in animal models that are important for understanding the pathogenesis of SARS-CoV-2, vaccine development, and therapeutic testing. When necessary, comparisons are made from studies with SARS to provide further perspectives on coronavirus infectious disease 2019 (COVID-19), as well as draw inferences for future investigations.

Indexed as

AnimalsCOVID-19HumansSARS-CoV-2coronavirusCOVID-19SARS, SARS-CoV-2severe acute respiratory syndrome

Identifiers

PMID33132005
PMCPMC7556779

What OpenQuestion holds

Textmetadata
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.