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A SIR epidemic model structured by immunological variables

  • Oscar Angulo
    ,
  • Fabio Milner(corresponding author)
    ,
  • Laurentiu Sega
*Corresponding author for this work
  • University of Valladolid
    ,
  • Arizona State University
    ,
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

Standard mathematical models for analyzing the spread of a disease are usually either epidemiological or immunological. The former are mostly ordinary differential equation (ODE)-based models that use classes like susceptibles, recovered, infectives, latently infected, and others to describe the evolution of an epidemic in a population. Some of them also use structure variables, such as size or age. The latter describe the evolution of the immune system/pathogen in the infected host - evolution that usually results in death, recovery or chronic infection. There is valuable insight to be gained from combining these two types of models, as that may lead to a better understanding of the severity of an epidemic. In this article, we propose a new type of model that combines the two by using variables of immunological nature as structure variables for epidemiological models. We prove the well-posedness of the proposed model under some restrictions and conclude with a look at a practical application of the model.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Article number

1340013

Journal (Volume, Issue Number)

Journal of Biological Systems (Volume 21, Issue 4)

Publication milestones

  • Published - 12/2013

Publication status

Published - 12/2013

ISSN

0218-3390

Publication IDs

  • Scopus: 84893392366

Publication metrics

Metrics

Scopus
citations
SciVal
FWCI
0.40
SciVal
Author count
3
SciVal
citations
6
SciVal
Paper percentile
57
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
1

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Captures
9
Citation count
11

Funding Details

Óscar Angulo was supported in part by Ministerio de Ciencia e Innovación (Spain), Project MTM2011-25238.
FunderFunding number
MICINN
MTM2011-25238