Evidence map›Paper›PMID 33288314›Full record

ArticleMedical hypotheses2021

COVID-19: Does the infectious inoculum dose-response relationship contribute to understanding heterogeneity in disease severity and transmission dynamics?

Wim Van Damme, Ritwik Dahake, Remco van de Pas, Guido Vanham, Yibeltal Assefa

Abstract read
In one paragraph

Article in Medical hypotheses, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
–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

48 citing papers in PubMed.

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  10. A simplicial epidemic model for COVID-19 spread analysis.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  16. Measured Air Flow Leakage in Facemask Usage.International journal of environmental research and public health · 2023
    Article
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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

5 authors.

Wim Van DammeInstitute of Tropical Medicine, Antwerp, Belgium. Electronic address: wvdamme@itg.be.
Ritwik DahakeIndependent Researcher, Bengaluru, India.
Remco van de PasInstitute of Tropical Medicine, Antwerp, Belgium.
Guido VanhamInstitute of Tropical Medicine, Antwerp, Belgium.
Yibeltal AssefaThe University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The variation in the speed and intensity of SARS-CoV-2 transmission and severity of the resulting COVID-19 disease are still imperfectly understood. We postulate a dose-response relationship in COVID-19, and that "the dose of virus in the initial inoculum" is an important missing link in understanding several incompletely explained observations in COVID-19 as a factor in transmission dynamics and severity of disease. We hypothesize that: (1) Viral dose in inoculum is related to severity of disease, (2) Severity of disease is related to transmission potential, and (3) In certain contexts, chains of severe cases can build up to severe local outbreaks, and large-scale intensive epidemics. Considerable evidence from other infectious diseases substantiates this hypothesis and recent evidence from COVID-19 points in the same direction. We suggest research avenues to validate the hypothesis. If proven, our hypothesis could strengthen the scientific basis for deciding priority containment measures in various contexts in particular the importance of avoiding super-spreading events and the benefits of mass masking.

Indexed as

Models, BiologicalAdaptive ImmunityCOVID-19Host Microbial InteractionsHumansImmunity, InnatePandemicsSARS-CoV-2Severity of Illness IndexViral LoadCOVID-19Initial infectious inoculumPublic healthSARS-CoV-2Viral dose

Identifiers

PMID33288314
PMCPMC7686757

What OpenQuestion holds

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Registered trials

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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.