A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology

Picault, Sébastien; Huang, Yili; Sicard, Vianney; Beaudeau, François; Ezanno, Pauline

doi:10.1007/978-3-319-59930-4_17

Cited by 9 publications

(5 citation statements)

References 19 publications

(23 reference statements)

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“…1. Un cadre générique de simulation en épidémiologie (EMuLSion) a été développé (Picault et al, 2017). Les processus d'infection et de cycle de vie des animaux sont représentés sous forme de « machines à états » qui permettent de décrire des systèmes séquentiels dont l'évolution est plus complexe que de simples compteurs ou registres.…”

Section: ❚ ❚ De Nombreux Domaines Et Types De Processus éCologiques Représentésunclassified

Agroécologie : des recherches pour la transition des filières et des territoires

Caquet¹,

Gascuel²,

Tixier‐Boichard³

2020

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Cet ouvrage présente le fruit de cette réflexion collective. L'objectif est de partager et de mettre en débat ces travaux, en interne et avec nos partenaires de la recherche, du monde agricole et de la société.La création d'INRAE, fruit de la fusion de l'Inra et d'Irstea, l'élargissement des compétences, la mise en place de nouveaux métaprogrammes interdisciplinaires, de projets de territoires d'innovation vont contribuer à amplifier les recherches pour l'agroécologie, à déplacer les fronts de connaissances nécessaires, à mettre la connaissance et la coconstruction au coeur des évolutions des filières et des territoires avec l'ensemble des acteurs concernés.

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Section: ❚ ❚ De Nombreux Domaines Et Types De Processus éCologiques Représentésunclassified

Agroécologie : des recherches pour la transition des filières et des territoires

Caquet¹,

Gascuel²,

Tixier‐Boichard³

2020

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“…1. EmuLSion is a generic epidemiology simulation framework (Picault et al, 2017). It uses "state machines" to represent infection processes and animal life cycles and can thus describe sequential systems whose evolution is complex.…”

Section: ❚ Several Domains and Types Of Ecological Processes Representedmentioning

confidence: 99%

Agroecology: research for the transition of agri-food chains and territories

Caquet¹,

Gascuel²,

Tixier‐Boichard³

2020

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“…To better understand the interplay between within-and between-235 herd levels in bovine dairy herds, and identify the contributions of transmission pathways at regional scale, two existing ad hoc models (respectively a within- [29] and a between-herd [30] model) were reimplemented using EMULSION. Assumptions of the within-herd model were simplified, keeping relevant assumptions and removing those less crucial in the perspective of the between-herd dynamics [31]. Then, it was extended to the regional between-herd level, where assumptions regarding airborne 240 transmission were compared.…”

Section: Assumptions 200mentioning

confidence: 99%

EMULSION: transparent and flexible multiscale stochastic models in epidemiology

Picault

Huang

Sicard

et al. 2019

Preprint

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Stochastic mechanistic models are essential to predictive epidemiology, to better explore biological assumptions and anticipate effects of control measures on pathogen spread. Their development is usually long and iterative, involving multi-disciplinary knowledge integration. 25However, knowledge often becomes lost in model code, hindering late changes in assumptions and often making models appearing as black boxes to end-users. We introduce here EMULSION, an artificial intelligence-based software intended to help modellers focus on model design rather than programming.EMULSION defines a domain-specific language to make all components of an epidemiological model (structure, processes, parameters...) explicit as a structured text file. This file is readable by scientists 30 from other fields (epidemiologists, biologists, economists), who can contribute to validate or revise assumptions at any stage of model development. It is then automatically processed by EMULSION generic simulation engine, preventing any discrepancy between model description and implementation.The modelling language and simulation architecture both rely on the combination of advanced artificial intelligence methods (knowledge representation and multi-level agent-based simulation), allowing 35 several modelling paradigms (from compartment-to individual-based models) at several scales (up to metapopulations). The flexibility of EMULSION and its capability to support iterative modelling are illustrated here through examples of progressive complexity, including late revisions of core model assumptions. EMULSION is also currently used to model the spread of several diseases in real pathosystems (zoonoses such as Q fever or the vector-borne Rift Valley fever; or bovine respiratory 40 diseases, with a focus on detection and treatment protocols). EMULSION provides a command-line tool for checking models, producing model diagrams, running simulations, and plotting outputs. Implemented in Python 3, EMULSION runs on Linux, MacOS, and soon Windows. It is released under Apache-2.0 license. A comprehensive documentation with installation instructions, tutorial and examples is available from: https://sourcesup.renater.fr/emulsion-public. 45

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A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology

Cited by 9 publications

References 19 publications

Agroécologie : des recherches pour la transition des filières et des territoires

Agroécologie : des recherches pour la transition des filières et des territoires

Agroecology: research for the transition of agri-food chains and territories

EMULSION: transparent and flexible multiscale stochastic models in epidemiology

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