Evidence map›Paper›PMID 38175864›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2024

Estimates of early outbreak-specific SARS-CoV-2 epidemiological parameters from genomic data.

Timothy G Vaughan, Jérémie Scire, Sarah A Nadeau, Tanja Stadler

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  6. Estimating epidemic dynamics with genomic and time series data.Journal of the Royal Society, Interface · 2025
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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

4 authors.

Timothy G VaughanDepartment of Biosystems Science and Engineering, Eidgenössiche Technische Hochschule Zurich, Basel 4058, Switzerland.ORCID 0000-0001-6220-2239
Jérémie ScireDepartment of Biosystems Science and Engineering, Eidgenössiche Technische Hochschule Zurich, Basel 4058, Switzerland.
Sarah A NadeauDepartment of Biosystems Science and Engineering, Eidgenössiche Technische Hochschule Zurich, Basel 4058, Switzerland.ORCID 0000-0003-1008-8918
Tanja StadlerDepartment of Biosystems Science and Engineering, Eidgenössiche Technische Hochschule Zurich, Basel 4058, Switzerland.ORCID 0000-0001-6431-535X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We estimate the basic reproductive number and case counts for 15 distinct Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks, distributed across 11 populations (10 countries and one cruise ship), based solely on phylodynamic analyses of genomic data. Our results indicate that, prior to significant public health interventions, the reproductive numbers for 10 (out of 15) of these outbreaks are similar, with median posterior estimates ranging between 1.4 and 2.8. These estimates provide a view which is complementary to that provided by those based on traditional line listing data. The genomic-based view is arguably less susceptible to biases resulting from differences in testing protocols, testing intensity, and import of cases into the community of interest. In the analyses reported here, the genomic data primarily provide information regarding which samples belong to a particular outbreak. We observe that once these outbreaks are identified, the sampling dates carry the majority of the information regarding the reproductive number. Finally, we provide genome-based estimates of the cumulative number of infections for each outbreak. For 7 out of 11 of the populations studied, the number of confirmed cases is much bigger than the cumulative number of infections estimated from the sequence data, a possible explanation being the presence of unsequenced outbreaks in these populations.

Indexed as

COVID-19SARS-CoV-2Disease OutbreaksGenomicsHumansShipsbirth–deathepidemiologyphylodynamics

Identifiers

PMID38175864
PMCPMC10786264

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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.