DYNAMO: Modelling in population dynamics and animal epidemiology

DYNAMO: Modelling in population dynamics and animal epidemiology

Understanding, anticipating and controlling the spread of animal diseases through mechanistic modelling: from intra-host mechanisms to epidemic dynamics at large scale, including decision and economic processes

DYNAMO aims to better understand and predict the spread and persistence of pathogens in animal populations, and to identify efficient and targeted control strategies. Such complex biological systems are studied at the within-host, between-host, and metapopulation scales, also using in the latter case trade network data and graph theory. We mainly focus on infectious diseases of cattle and swine, on arbovirus diseases, and on vector population dynamics.



Expertise & skills

  • Predictive modelling approaches combining mechanistic models and data-driven simulations
  • Model reproducibility, robustness, and clarity: a generic multiscale simulation framework to ease knowledge and data integration, and to capitalise developed models
  • Development of innovative inference methods to promote realistic models and quantify uncertain processes at different scales
  • Decision support tools for health advisers to guide on-farm management of livestock infectious risks and associated public health issues

On-going projects

  • WiLiMan-ID: Ecology of wildlife, livestock, human and infectious diseases in changing environments (2023-2028; funding: Horizon Europe)
  • DECIDE: Data-driven control and prioritisation of non-EU-regulated contagious animal diseases (especially respiratory and digestive diseases of young animals) (2021-2026; funding: H2020)
  • MIDIIVEC : Modelling and inference of intra-vector infection dynamics from experimental data (2022–2024; funding: INRAE MP Digit-BIO)
  • SEPTIME: Sensor-Enhanced Projection Tool Informed by an Epidemiological Model: a decision-support system based on the coupling between real-time sensor data and a mechanistic epidemiological model of bovine respiratory diseases (2022-2024; funding: Carnot Institute F2E)

Key past projects

  • RobustInfer: Combine & estimate: towards a reduction in data complexity to better calibrate large-scale dynamic epidemiological models (2021-2023; funding: région Pays-de-la-Loire)
  • ATOM: Automatisation of the software process from epidemiological models to decision support tools (2020-2021; funding: INRAE DPTI)
  • ASF Challenge: An interntaional modelling challenge to better predict the spread of african swine fever (ASF) at the wildlife / pig herd interface (2019-2021; funding: INRAE Animal Health Division)
  • FORESEE: Virus-host-environment interplay and drivers behind pathogen emergence, spread and persistence: Rift Valley fever (RVF) as a case study (2018-2021; funding: INRAE MP GISA)
  • CADENCE: Spread of epidemic processes on dynamical networks of animal movements with application to cattle in France (2017-2021; funding: ANR)
  • MIHMES: Multiscale modelling of infection dynamics, from intra-host to metapopulation scale, to evaluate control strategies (2012-2017; funding: PIA & FEDER Pays-de-la-Loire)

Membres de l'équipe

Researchers :

Technical and scientific support :

PhD & post-doc


Examples of recent past research topics of master interships, PhDs, and post-docs

M1 & M2 internships, vet theses

  • Brendan Borne: Improve farm geolocalisation to predict pathogen spread among French cattle herds (M1 MODE, 2022)
  • Grégoire Azé: Modelling arbovirus infection dynamics in mosquito cells (West-Nil virus and Usutu virus) in a context of primo- and co-infection (collaboration with UMR VIRO; M1 MODE, 2022)
  • Servane Bareille: First modelling challenge in animal health: African swine fever at the interface between wildlife and livestock (collaboration with UMR IHAP; M2 MODE & vet thesis, 2021): Ezanno et al. 2022, Picault et al. 2022
  • Juliette Hervio: Surveillance and monitoring of bovine viral diarrhea virus spread among cattle herd (vet thesis, 2021)


  • Hélène Cecilia: Modelling Rift Valley fever virus transmission dynamics: insights from micro- and macro-scale studies (collaboration Cirad; 2018-2021): Bron et al. 2021, Cecilia et al. 2020, 2022a, 2022b
  • Lina Cristancho-Fajardo: Modelling and optimising decision-making for the control of infectious diseases spreading on animal metapopulation networks (collaboration UR MaIAGE; 2019-2022): Cristancho-Fajardo et al. 2021, 2022a, 2022b
  • Abdel Osseni : Preventive management and consequences of health risks on animal productions: application tp bovine tuberculosis in France (collaboration UMR SMART LERECO; 2018-2021): Osseni et al. 2019, 2022


  • Floor Biemans: Modelling the spread of bovine paratuberculosis within and between cattle herds in Ireland (collaboration UCD, Dublin; 2019-2022): Biemans et al. 2021, 2022a, 2022b
  • Thibaut Morel-Journel: Reorganising cattle trade network between farms to limit infection risks (collaboration Terrena; 2018-2021): Morel-Journel et al. 2021a, 2021b


The team is also on Twitter (@bioepar_dynamo) !


Pauline Ezanno

Modification date : 07 February 2024 | Publication date : 10 November 2023 | Redactor : ML