Evidence map›Paper›PMID 35125676›Full record

ArticleChaos, solitons, and fractals2022

Sensitivity theorems of a model of multiple imperfect vaccines for COVID-19.

Fernando Javier Aguilar-Canto, Ugo Avila-Ponce de León, Eric Avila-Vales

Open access · greenAbstract read
In one paragraph

Article in Chaos, solitons, and fractals, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
2.5field-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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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 1 institution in 1 country.

Fernando Javier Aguilar-CantoFacultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Catastral 13615, Merida, C.P. 97119, Yucatan, Mexico.
Ugo Avila-Ponce de LeónPrograma de Doctorado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Eric Avila-ValesFacultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Catastral 13615, Merida, C.P. 97119, Yucatan, Mexico.
Universidad Nacional Autónoma de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In response to the ongoing pandemic of COVID-19, several companies across the world have proposed a wide variety of vaccines of different mechanisms of action. As a consequence, a new scenario of multiple imperfect vaccines against the SARS-CoV-2 arose. Mathematical modeling needs to consider this complex situation with different vaccines, some of them with two required doses. Using compartmental models we can simplify, simulate and most importantly, answer questions related to the development of the outbreak and the vaccination campaign. We present a model that addresses the current situation of COVID-19 and vaccination. Two important questions were considered in this paper: are more vaccines useful to reduce the spread of the coronavirus? How can we know if the vaccination campaign is sufficient? Two sensitivity criteria are helpful to answer these questions. The first criterion is the Multiple Vaccination Theorem, which indicates whether a vaccine is giving a positive or negative impact on the reproduction number. The second result (Insufficiency Theorem) provides a condition to answer the second question. Finally, we fitted the parameters with data and discussed the empirical results of six countries: Israel, Germany, the Czech Republic, Portugal, Italy, and Lithuania.

Indexed as

92B0599-00,COVID-19ElasticityImperfect vaccinesSARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2SEIARD, Susceptible-Exposed-Infectious-Asymptomatic-Recovered-DeadSensitivity analysisSIR-Based modelsSIR, Susceptible-Infectious-RecoveredSVEIHQRD, Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Quarantined-Recovered-DeadSVIR, Susceptible-Vaccinated-Infectious-Recovered

Identifiers

PMID35125676
PMCPMC8801312
OpenAlexW4210752082

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.