1. Information

1.1. Contributors and contact

https://img.shields.io/twitter/follow/bioepar_dynamo?label=DYNAMO%20research%20group&style=plastic&logo=twitter

Oniris, INRAE, BIOEPAR, 44300 Nantes, France

1.2. How to cite

If you are using EMULSION in your work, please acknowledge it when publishing, with a reference to the following article:

Main reference

S. Picault, Y.-L. Huang, V. Sicard, S. Arnoux, G. Beaunée, P. Ezanno (2019). “EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology”, PLoS Computational Biology 15(9): e1007342.

 DOI: 10.1371/journal.pcbi.1007342

@Article{EMULSION-ploscb2019,
  author =	 {Picault, Sébastien and Huang, Yu-Lin and Sicard,
                  Vianney and Arnoux, Sandie and Beaunée, Gaël and
                  Ezanno, Pauline},
  title =	 {{EMULSION}: Transparent and flexible multiscale
                  stochastic models in human, animal and plant
                  epidemiology},
  journal =	 {{PLoS} {C}omputational {B}iology},
  year =	 {2019},
  volume =	 {15},
  number =	 {9},
  pages =	 {e1007342},
  DOI =		 {10.1371/journal.pcbi.1007342},
  url =		 {https://doi.org/10.1371/journal.pcbi.1007342}
}

1.3. Educational Resources

1.4. Selected publications

  • On bovine respiratory disease (BRD) in fattening farms:

    • S. Picault, P. Ezanno, K. Smith, D. Amrine, B. White, S. Assié (2022). “Modelling the effects of antimicrobial metaphylaxis and pen size on bovine respiratory disease in high and low risk fattening cattle”, Veterinary Research 53:77,

      DOI: 10.1186/s13567-022-01094-1

    • S. Picault, P. Ezanno, S. Assié (2019). “Combining early hyperthermia detection with metaphylaxis for reducing antibiotics usage in newly received beef bulls at fattening operations: a simulation-based approach”, Proceedings of the Conference of the Society for Veterinary Epidemiology and Preventive Medicine (SVEPM), p. 148-159

      author version on HAL

  • On Swine influenza virus in batch-rearing pig farms:

    • V. Sicard, M. Andraud, S. Picault (2022). “Coupling spatial and temporal structure in batch rearing modeling for understanding the spread of the swine influenza A virus”, Proceedings of the Conference of the Society for Veterinary Epidemiology and Preventive Medicine (SVEPM)

      author version on HAL

  • On the generation of synthetic epidemiological data for the first modelling challenge in animal health (ASF Challenge):

    • S. Picault, T. Vergne, M. Mancini, S. Bareille, P. Ezanno (2022). “The African swine fever modelling challenge: Objectives, model description and synthetic data generation”, Epidemics 40

      DOI: 10.1016/j.epidem.2022.100616

  • On Q fever (Coxiellosis) in dairy herds:

    • S. Picault, Y.-L. Huang, V. Sicard, F. Beaudeau, P. Ezanno (2017). “A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology”, in: Demazeau et al. (eds.), 15th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), Lecture Notes in Computer Science 10349, p. 209-221, Springer.

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

  • On Artificial Intelligence research involved in EMULSION:

    • V. Sicard, M. Andraud, S. Picault (2022). “A declarative modelling language for the design of complex structured agent-based epidemiological models”, Proceedings of the 20th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), Springer.

      DOI: 10.1007/978-3-031-18192-4_31

    • V. Sicard, M. Andraud, S. Picault (2021). “Organization as a multi-level design pattern for agent-based simulation of complex systems”, Proceedings of the 13th International Conference on Agents and Artificial Intelligence (ICAART’2021), p. 232-241, SCITEPRESS

      DOI: 10.5220/0010223202320241

    • P. Mathieu, G. Morvan, S. Picault (2018). “Multi-level agent-based simulations: Four design patterns”, Simulation Modelling Practice and Theory 83, p. 51-64, Agent-Based Modelling and Simulation special issue Elsevier.

      DOI: 10.1016/j.simpat.2017.12.015

    • S. Picault, Y.-L. Huang, V. Sicard, P. Ezanno (2017). “Enhancing Sustainability of Complex Epidemiological Models through a Generic Multilevel Agent-based Approach” in: C. Sierra (ed.), 26th International Joint Conference on Artificial Intelligence (IJCAI), AAAI, p. 374-380.

      DOI: 10.24963/ijcai.2017/53

    • S. Picault, P. Mathieu (2011). “An Interaction-Oriented Model for Multi-Scale Simulation”, in: T. Walsh (ed.), 22nd International Joint Conference on Artificial Intelligence (IJCAI), AAAI, p. 332-337.

      DOI: 10.5591/978-1-57735-516-8/IJCAI11-065

1.5. Funding

This work was carried out with the financial support of:

  • INRAE, the French National Research Institute for Agriculture, Food and Environment:

    • Animal Health Division

    • Partnerships and Innovation Transfer Division (“DPTI”)

  • the European Union:

    • the European fund for the regional development (FEDER) of Pays de la Loire

    • project H2020 DECIDE (101000494)

  • the French Research Agency (ANR):

    • Program Investments for the Future, project ANR-10-BINF-0007 (MIHMES)

    • project ANR-16-CE32-0007-01 (CADENCE)

  • the French Région Pays de la Loire:

    • PULSAR grant

    • CAENOME Ph.D. grant

  • the Carnot Institute “France Futur Élevage” (SEPTIME project)

  • the For and On Regional Development (PSDR) French research programme, funded by INRAE and the French regions of Bretagne, Pays de la Loire, Normandie and Nouvelle Aquitaine (SANT’Innov)