Models of pathogen propagation in animal population

BIOEPAR develops simulation models that predict the spread of pathogens at different scales (batch of animals, herd, region, production chain), as well as the population dynamics of their vectors if any. These models enable the evaluation of ex-ante control strategies. Some take into account the decision-making process of managers (farmers, groups, public decision-makers).

In particular, we are developing mechanistic, often stochastic, models applied to various animal diseases or vectors, which can be organized as follows.

 * Models at the regional / sector scale

            - between dairy herds: BVD32, FQ30, PTB2,3

            - young cattle movements and BRD

            - between cattle herds (all types): BVD, FCO9

            - between pig herds: salmonella porting17,25

            - multi-host: FCO10, FVR7, PPA

            - other: Vibrio aestuarianus in a spatialized oyster population

            - data visualization: Transmissio

* Herd scale models

            - dairy cattle herd: BVDx, FQ11 to 13, PTB4,6,27 to 29, genetic selection

            - beef cattle herd: BVD14

            - porcine herd : SDRP, salmonella porting26

            - other: pestivirus in a isard population1,23

* Batch scale models

            - calf batch: BRD

            - aquarium : Vibrio aestuarianus in a population of oysters  in an aquarium24

* Intra-host scale models

            - individual immune response to infection with the SDRP virus18

* Decision models

            - individual decision: coupling of epidemiological and economic models, decision to vaccinate

            - group decision: management of the SDRP35

* Vector population dynamics models

            - Mosquitoes5,15,33

            - Tsetse8

            - Ticks19 and transmitted diseases: cattle babesiosis20 and CCHF21,22

 [Disease abbreviations: BRD = bovine respiratory disease, BVD = bovine viral diarrhea, CCHF = Crimean-Congo hemorrhagic fever, FCO = fièvre catarrhale ovine (bluetongue), FQ = Q fever, FVR = Rift Valley fever, PPA = African porcine plague, PTB = paratuberculosis, SDRP = porcine respiratory dysgenic syndrome]

Some models have led to the development of decision-support tools for health managers: MihmesTools16. Some models have been developed by mobilizing the EMULSION software31.


If you are interested in any of these models, please do not hesitate to contact Pauline Ezanno



  1. Beaunée G., Gilot-Fromont E., Garel M., Ezanno P. 2015. Seasonal spread of a Pestivirus in a structured Pyrenean chamois population. Vet Res 46(1):86, doi:10.1186/s13567-015-0218-8
  2. Beaunée G., Vergu E., Ezanno P. 2015. Modelling of paratuberculosis spread between dairy cattle farms at a regional scale. Vet Res 46:111, doi:10.1186/s13567-015-0247-3
  3. Beaunée G., Vergu E., Joly A., Ezanno P. 2017. Controlling bovine paratuberculosis at a regional scale: towards a decision modeling tool. J Theor Biol 435:157-183, doi:10.1016/j.jtbi.2017.09.012
  4. Ben Romdhane R., Beaunée G., Camanes G., Guatteo R., Fourichon C., Ezanno P. 2017. Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach. Vet Res 48:62, doi:10.1186/s13567-017-0468-8
  5. Cailly P., Tran A., Balenghien T., L’Ambert G., Toty C., Ezanno P. 2012. A climate-driven abundance model to assess mosquito control strategies. Ecol Model 227, 7-17, doi:10.1016/j.ecolmodel.2011.10.027
  6. Camanes G., Joly A., Fourichon C., Ben Romdhane R., Ezanno P. 2018. Control measures to avoid increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach. Vet Res 49:60,
  7. Cavalerie L.*, Charron M.V.P.*, Ezanno P.*, Dommergues L., Zumbo B., Cardinale E. 2015. A stochastic model to study Rift Valley Fever persistence with different seasonal patterns of vector abundance: new insights on the endemicity in the tropical island of Mayotte. PLoS ONE 10(7):e0130838, doi:10.1371/journal.pone.0130838
  8. Cecilia H., Arnoux S., Picault S., Dicko A., Seck M.T., Sall B., Bassène M., Vreysen M., Pagabeleguem S., Bancé A., Bouyer J., Ezanno P. 2019. Environmental heterogeneity drives tsetse fly population dynamics and control. bioRxiv,, ver. 3 peer-reviewed and recommended by PCI Ecology (
  9. Charron M., Langlais M., Seegers H., Ezanno P. 2011. Seasonal spread and control of Bluetongue in cattle. J Theor Biol 291, 1-9, doi:10.1016/j.jtbi.2011.08.041
  10. Charron M.V.P., Kluiters G., Langlais M., Seegers H., Baylis M., Ezanno P. 2013. Seasonal and spatial heterogeneities in host and vector abundances impact the spatiotemporal spread of bluetongue. Vet Res 44:44, doi:10.1186/1297-9716-44-44
  11. Courcoul A., Hogerwerf L., Klinkenberg D., Nielen M., Vergu E., Beaudeau F., 2011. Modelling effectiveness of herd level vaccination against Q fever in dairy cattle. Vet. Res., 42(1):68.
  12. Courcoul A., Monod H., Nielen M., Klinkenberg D., Hogerwerf L., Beaudeau F., Vergu E., 2011. Modelling the effect of heterogeneity of shedding on the within herd Coxiella burnetii spread and identification of key parameters by sensitivity analysis. J. Theor. Biol., 284(1):130-141.
  13. Courcoul A., Vergu E., Denis J.-B., Beaudeau F., 2010. Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach. Proceedings of the Royal Society B: Biological Sciences, 277(1695):2857-2865.
  14. Damman A., Viet A-F, Arnoux S., Guerrier-Chatellet M-C, Petit E, Ezanno P. 2015. Modeling the spread of bovine viral diarrhea virus (BVDV) in a beef cattle herd and its impact on herd productivity. Vet Res 46:12, doi:10.1186/s13567-015-0145-8
  15. Ezanno P., Balenghien T., Arnoux S., Cailly P., Aubry-Kientz M., L’Ambert G., Toty C., Tran A. 2015. A generic climate-driven model to predict mosquito population dynamics and the associated risk of mosquito-borne disease transmission. Prev Vet Med 120(1), 39-50, doi:10.1016/j.prevetmed.2014.12.018
  16. Ezanno P., Beaunée G., Picault S., Arnoux S., Sicard V., Beaudeau F., Rault A., Vergu E. 2018. Gestion des maladies endémiques du troupeau aux territoires : contribution de la modélisation épidémiologique pour soutenir la prise de décision (projet MIHMES, 2012-2017). Innovations Agronomiques 68, 53-65.
  17. Ferrer Savall J., Bidot, C., Leblanc-Maridor M., Belloc C., Touzeau S. 2016 Modelling Salmonella transmission among pigs from farm to slaughterhouse: interplay between management variability and epidemiological uncertainty. Internal J Food Microbiol 229:33–43, doi:10.1016/j.ijfoodmicro.2016.03.020
  18. Go N., Bidot C., Belloc C., Touzeau S., 2014. Integrative model of the immune response to a pulmonary macrophage infection: what determines the infection duration? PLoS ONE, 9(9):e107818, doi:10.1371/journal.pone.0107818
  19. Hoch T., Monnet Y., Agoulon A. 2010. Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach. Ecol Model 221:1798-1806.
  20. Hoch T., Goebel J., Agoulon A., Malandrin L. 2012. Modelling bovine babesiosis: A tool to simulate scenarios for pathogen spread and to test control measures for the disease. Prev Vet Med 106:136-142.
  21. Hoch T., Breton E., Josse M., Deniz A., Guven E., Vatansever Z. 2016. Identifying main drivers and testing control strategies for CCHFV spread. Exp Appl Acarol 68(3):347-359.
  22. Hoch T., Breton E., Vatansever Z. 2018. Dynamic Modeling of Crimean Congo Hemorrhagic Fever Virus (CCHFV) Spread to Test Control Strategies. J Med Entomol. 55:1124-1132. DOI: 10.1093/jme/tjy035
  23. Lambert S., Ezanno P., Garel M., Gilot-Fromont E. 2018. Stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management. Sci Rep 8:16846. doi:10.1038/s41598-018-34623-0
  24. Lupo C., Travers M-A., Tourbiez D., Barthélémy C.F., Beaunée G., Ezanno P. 2019. Modeling the transmission of Vibrio aestuarianus in Pacific oysters using experimental infection data. Front Vet Sci 6:142,
  25. Lurette A., Belloc C., Keeling M., 2011. Contact structure and Salmonella control in the network of pig movements in France. Prev. Vet. Med., 102(1):30-40.
  26. Lurette A., Touzeau S., Ezanno P., Hoch T., Seegers H., Fourichon C., Belloc C. 2011. Within-herd biosecurity and Salmonella seroprevalence in slaughter pigs: a simulation study. J Anim Sci 89, 2210-2219, doi:jas.2010-2916v1-20102916
  27. Marcé C., Ezanno P., Seegers H., Pfeiffer D., Fourichon C. 2011. Predicting fadeout versus persistence of paratuberculosis in a dairy cattle herd for management and control purposes: a modelling study. Vet Res 42:36, doi:10.1186/1297-9716-42-36
  28. Marcé C., Ezanno P., Seegers H., Pfeiffer D., Fourichon C. 2011. Within-herd contact structure and transmission of Mycobacterium avium subspecies paratuberculosis in a persistently infected dairy cattle herd. Prev Vet Med 100, 116-125, doi:10.1016/j.prevetmed.2011.02.004
  29. More S., Cameron A., Strain S., Cashman B., Ezanno P., Kenny K., Fourichon C., Graham D. 2015. Evaluation of testing strategies to identify infected animals at a single round of testing within dairy herds known to be infected with Mycobacterium avium subsp. paratuberculosis. Dairy Sci 98:5194–5210
  30. Pandit P., Hoch T.*, Ezanno P.*, Beaudeau F., Vergu E. 2016. Q fever spread between dairy cattle herds in an enzootic region: modelling contributions of airborne transmission and trade. Vet Res 47:48, doi:10.1186/s13567-016-0330-4
  31. Picault S., Huang Y.-L., Sicard V., Arnoux S., Beaunée G., Ezanno P. 2019. EMULSION: transparent and flexible multiscale stochastic models in human, animal and plant epidemiology. PLoS Comput Biol 15(9): e1007342,
  32. Qi L., Beaunée G., Arnoux S., Dutta B.L., Joly A., Vergu E., Ezanno P. 2019. Neighbourhood contacts and trade movements drive the regional spread of bovine viral diarrhoea virus (BVDV). Vet Res 50:30,
  33. Tran A., L'Ambert G., Lacour G., Benoît R., Demarchi M., Cros M., Cailly P., Aubry-Kientz M., Balenghien T., Ezanno P. 2013. A rainfall- and temperature-driven abundance model for Aedes albopictus Internal J Envir Res Public Health, 10(5), 1698-719, doi:10.3390/ijerph10051698
  34. Viet A-F., Krebs S., Rat-Aspert O., Jeanpierre L., Belloc C., Ezanno P. 2018. A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. PLoS ONE 13(6): e0197612, doi:10.1371/journal.pone.0197612