Evidence map›Paper›PMID 32834649›Full record

ArticleChaos, solitons, and fractals2020

An SEIARD epidemic model for COVID-19 in Mexico: Mathematical analysis and state-level forecast.

Ugo Avila-Ponce de León, Ángel G C Pérez, Eric Avila-Vales

Abstract read
In one paragraph

Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
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  3. Article
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  6. Machine Learning and COVID-19: Lessons from SARS-CoV-2.Advances in experimental medicine and biology · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Non-Markovian SIR epidemic spreading model of COVID-19.Chaos, solitons, and fractals · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Dynamical Analysis of COVID-19 Model Incorporating Environmental Factors.Iranian journal of science and technology. Transaction A, Science · 2022
    Article
  20. 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.

Ugo Avila-Ponce de LeónPrograma de Doctorado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Ángel G C PérezFacultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Catastral 13615, Mérida, C.P. 97119, Yucatán, Mexico.
Eric Avila-ValesFacultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Catastral 13615, Mérida, C.P. 97119, Yucatán, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose an SEIARD mathematical model to investigate the current outbreak of coronavirus disease (COVID-19) in Mexico. Our model incorporates the asymptomatic infected individuals, who represent the majority of the infected population (with symptoms or not) and could play an important role in spreading the virus without any knowledge. We calculate the basic reproduction number (

Indexed as

COVID-19Disease dynamicsEffective daily reproduction ratioMexicoSensitivity analysis

Identifiers

PMID32834649
PMCPMC7434626

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.