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Separation of concerns in epidemiological modelling

Published: 14 March 2016 Publication History

Abstract

Modeling and simulation have been heavily used in epidemiology, for instance to study the transmission of infectious diseases, their pathogenicity and their propagation. A major hindrance to modeling in epidemiology is the mixing of concerns that ought to be separated. The most obvious one is the computer implementation that should not be mixed with domain aspects. But several domain concerns should also be separated from the core epidemiological ones. These include the distribution of the studied populations into spatial regions, age intervals, sexes, species, viral strains... We propose an approach that relies on a mathematical model of the dynamics of a compartment-based population. The separation of domain concerns is provided by expressing each one as a stochastic automaton and combining them with a tensor sum. A DSL, Kendrick, and a tool, support this approach that has been validated on several case studies.

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  • (2018)Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interfacePeerJ Computer Science10.7717/peerj-cs.1584(e158)Online publication date: 23-Jul-2018
  • (2018)Spatio-temporal modelling of verotoxigenic Escherichia coli O157 in cattle in Sweden: exploring options for controlVeterinary Research10.1186/s13567-018-0574-249:1Online publication date: 2-Aug-2018
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cover image ACM Other conferences
MODULARITY Companion 2016: Companion Proceedings of the 15th International Conference on Modularity
March 2016
217 pages
ISBN:9781450340335
DOI:10.1145/2892664
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 14 March 2016

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Author Tags

  1. Separation of concerns
  2. compartmental models
  3. domain specific languages
  4. epidemiological modeling

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View all
  • (2020)A between-herd data-driven stochastic model to explore the spatio-temporal spread of hepatitis E virus in the French pig production networkPLOS ONE10.1371/journal.pone.023025715:7(e0230257)Online publication date: 13-Jul-2020
  • (2018)Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interfacePeerJ Computer Science10.7717/peerj-cs.1584(e158)Online publication date: 23-Jul-2018
  • (2018)Spatio-temporal modelling of verotoxigenic Escherichia coli O157 in cattle in Sweden: exploring options for controlVeterinary Research10.1186/s13567-018-0574-249:1Online publication date: 2-Aug-2018
  • (2017)Enhancing sustainability of complex epidemiological models through a generic multilevel agent-based approachProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171696(374-380)Online publication date: 19-Aug-2017
  • (2016)Explicit Composition Constructs in DSLsProceedings of the 11th edition of the International Workshop on Smalltalk Technologies10.1145/2991041.2991061(1-11)Online publication date: 23-Aug-2016

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