Evidence map›Paper›PMID 35336719›Full record

ArticleBiology2022

Modeling Vaccine Efficacy for COVID-19 Outbreak in New York City.

Jacques Demongeot, Quentin Griette, Pierre Magal, Glenn Webb

Abstract read
In one paragraph

Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Jacques DemongeotUniversité Grenoble Alpes, AGEIS EA7407, F-38700 La Tronche, France.ORCID 0000-0002-8335-9240
Quentin GrietteUniversité Bordeaux, IMB, UMR 5251, F-33400 Talence, France.ORCID 0000-0001-5978-9358
Pierre MagalUniversité Bordeaux, IMB, UMR 5251, F-33400 Talence, France.ORCID 0000-0002-4776-0061
Glenn WebbMathematics Department, Vanderbilt University, Nashville, TN 37212, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this article we study the efficacy of vaccination in epidemiological reconstructions of COVID-19 epidemics from reported cases data. Given an epidemiological model, we developed in previous studies a method that allowed the computation of an instantaneous transmission rate that produced an exact fit of reported cases data of the COVID-19 outbreak. In this article, we improve the method by incorporating vaccination data. More precisely, we develop a model in which vaccination is variable in its effectiveness. We develop a new technique to compute the transmission rate in this model, which produces an exact fit to reported cases data, while quantifying the efficacy of the vaccine and the daily number of vaccinated. We apply our method to the reported cases data and vaccination data of New York City.

Indexed as

coronavirusepidemic modelparameters identificationreported and unreported casesvaccine efficacy

Identifiers

PMID35336719
PMCPMC8945193

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.