Mathematical formulation and validation of the Be-FAST model for Classical Swine Fever Virus spread between and within farms

Benjamin Ivorra, Beatriz Martinez Lopez, José M. Sánchez-Vizcaíno, Ángel M. Ramos

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Classical Swine Fever is a viral disease of pigs that causes severe restrictions on the movement of pigs and pig products in the affected areas. The knowledge of its spread patterns and risk factors would help to implement specific measures for controlling future outbreaks. In this article, we describe in detail a spatial hybrid model, called Be-FAST, based on the combination of a stochastic Individual-Based model (modeling the interactions between the farms, considered as individuals) for between-farm spread with a Susceptible-Infected model for within-farm spread, to simulate the spread of this disease and identify risk zones in a given region. First, we focus on the mathematical formulation of each component of the model. Then, in order to validate Be-FAST, we perform various numerical experiments considering the Spanish province of Segovia. Obtained results are compared with the ones given by two other Individual-Based models and real outbreaks data from Segovia and The Netherlands.

Original languageEnglish (US)
Pages (from-to)25-47
Number of pages23
JournalAnnals of Operations Research
Volume219
Issue number1
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

Fever
Virus
Swine
Farm
Pig
Modeling
Numerical experiment
Hybrid model
Risk factors
Interaction
The Netherlands

Keywords

  • Classical Swine Fever
  • Epidemiological modeling
  • Individual-Based model
  • Model validation
  • Susceptible-Infected model

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Decision Sciences(all)

Cite this

Mathematical formulation and validation of the Be-FAST model for Classical Swine Fever Virus spread between and within farms. / Ivorra, Benjamin; Martinez Lopez, Beatriz; Sánchez-Vizcaíno, José M.; Ramos, Ángel M.

In: Annals of Operations Research, Vol. 219, No. 1, 2014, p. 25-47.

Research output: Contribution to journalArticle

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