Evidence map›Paper›PMID 35141702›Full record

ArticleEpidemiologia (Basel, Switzerland)2021

Analysis of Key Factors of a SARS-CoV-2 Vaccination Program: A Mathematical Modeling Approach.

David Martínez-Rodríguez, Gilberto Gonzalez-Parra, Rafael-J Villanueva

Open access · goldAbstract read
In one paragraph

Article in Epidemiologia (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Impact of Infective Immigrants on COVID-19 Dynamics.Mathematical & computational applications · 2022
    Article
  11. Effectiveness of COVID-19 vaccines and their challenges (Review).Experimental and therapeutic medicine · 2021
    Review
  12. Deep-Data-Driven Neural Networks for COVID-19 Vaccine Efficacy.Epidemiologia (Basel, Switzerland) · 2021
    Article
  13. Article
  14. Article
  15. Article
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 at 2 institutions in 2 countries.

David Martínez-RodríguezInsituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, 46022 Valencia, Spain.ORCID 0000-0002-2093-7840
Gilberto Gonzalez-ParraDepartment of Mathematics, New Mexico Tech, Socorro, NM 87801, USA.ORCID 0000-0001-5847-678X
Rafael-J VillanuevaInsituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, 46022 Valencia, Spain.ORCID 0000-0002-0131-0532
Universitat Politècnica de València · ESNew Mexico Institute of Mining and Technology · US

Funding

NM-INBRE Sequencing and Bioinformatics CoreP20GM103451 · NIGMS · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI Charlotte C. Gard · 2012 to 2026
$61.2M
NIGMS NIH HHS P20 GM103451
6 · The paper itself

Abstract

The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination programs in different regions may vary due to differences in implementation, for instance, simply the availability of the vaccine. In this article, we study the impact of the pace of vaccination and the intrinsic efficacy of the vaccine on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. Then we study different potential scenarios regarding the burden of the COVID-19 pandemic in the near future. We construct a compartmental mathematical model and use computational methodologies to study these different scenarios. Thus, we are able to identify some key factors to reach the aims of the vaccination programs. We use some metrics related to the outcomes of the COVID-19 pandemic in order to assess the impact of the efficacy of the vaccine and the pace of the vaccine inoculation. We found that both factors have a high impact on the outcomes. However, the rate of vaccine administration has a higher impact in reducing the burden of the COVID-19 pandemic. This result shows that health institutions need to focus on increasing the vaccine inoculation pace and create awareness in the population about the importance of COVID-19 vaccines.

Indexed as

mathematical modelingSARS-CoV-2 virussimulationvaccination

Identifiers

PMID35141702
PMCPMC8824484
OpenAlexW3144500220

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.