Principles of mathematical modeling of infectious diseases in the zone of interaction of wildlife and livestock
https://doi.org/10.52419/issn2782-6252.2025.3.42
Abstract
Modeling of infectious diseases at the intersection of industrial or farm animal husbandry and wildlife is a rare type of mathematical modeling due to the many problems that arise. This review article focuses on the characteristics of mathematical models in various combinations of "pathogen of an infectious disease nosological unit (a disease with a unique combination of characteristics) type of farm animal type of wild animal factors and vectors of pathogen transmission." The most common combinations of animal species were cattle, badgers, brush-tailed opossums (for tuberculosis in cattle), domestic pigs, and wild boars (for African swine fever, classical swine fever, foot-and-mouth disease, and other contagious diseases). The primary goal of most studies in this review was to analyze strategies for controlling infectious animal diseases, including zoonoses, with a focus on interventions targeting wild hosts and their impact on domesticated livestock. Some strategies for combating infectious diseases in animals include: preventing contact between domestic livestock, poultry, and feed and wild animals; eliminating carriers of pathogens; and providing preventive immunization for all domestic animals, including dogs and cats; oral immunization of wild carnivorous animals with control over their numbers; monitoring the health status of livestock and animal movements; and the procedure for determining the zoosanitary status of industrial farms (compartmentalization) to determine the level of protection of farms from the entry of dangerous pathogens.
About the Authors
V. A. KuzminRussian Federation
Vladimir A. Kuzmin - Dr. of Veterinary Science, Professor
D. A. Orekhov
Russian Federation
Dmitry An. Orekhov - Candidate of Veterinary Science, Associate Professor
A. B. Aidiev
Russian Federation
Akhmed B. Aidiev - Candidate of Veterinary Science, Associate Professor
A. V. Tsyganov
Russian Federation
Andrey V. Tsyganov - Candidate of Pedagogical Science, Associate Professor
References
1. Korennoy, F.I. Mathematical and cartographic modeling of the spread of particularly dangerous diseases in farm animals: diss. Cand. Geogr. Sci. (2019): 154 p. (in Russ)
2. Shabeykin, A.A., Belimenko, V.V., Patrikeev, V.V., Gulyukin, E.A., Kuzmin, V.A. Spatiotemporal patterns of development of the ASF epizootic process in the wild boar population. Veterinary Science. 2023; 11: 33-39. (in Russ) DOI: 10.30896/0042-4846.2023.26.11.33-38
3. Buhnerkempe M.G., Roberts M.G., Dobson A.P., Heesterbeek H., Hudson P.J., Lloyd-Smith J.O. Eight challenges in modelling disease ecology in multi-host, multi-agent systems. Epidem Chall Model Infect Dis Dyn. 2015;10:26–30.
4. Roberts M., Dobson A., Restif O., Wells K. Challenges in modelling the dynamics of infectious diseases at the wildlife– human interface. Epidemics. 2021;37:100523. doi: 10.1016/j.epidem.2021.100523
5. Huyvaert K.P., Russell R.E., Patyk K.A., Craft M.E., Cross P.C., Garner M.G. et al. Challenges and opportunities developing mathematical models of shared pathogens of domestic and wild animals. Vet Sci. 2018;5:E92. doi: 10.3390/vetsci5040092
6. Russell R.E., Katz R.A., Richgels K.L.D., Walsh D.P., Grant E.H.C. A framework for Modeling emerging diseases to inform management. Emerg Infect Dis. 2017;23:1–6. doi: 10.3201/eid2301.161452
7. Barron M.C., Tompkins D.M., Ramsey D.S.L., Bosson M.A.J. The role of multiple wildlife hosts in the persistence and spread of bovine tuberculosis in New Zealand. N Z Vet J. 2015;63:68–76. doi: 10.1080/00480169.2014
8. Mateus-Anzola J., Wiratsudakul A., Rico-Chávez O., Ojeda-Flores R. Simulation modeling of influenza transmission through backyard pig trade networks in a wildlife/livestock interface area. Trop Anim Health Prod. 2019;51:2019–24. doi: 10.1007/s11250-019-01892-4
9. Boklund A., Goldbach S.G., Uttenthal A., Alban L. Simulating the spread of classical swine fever virus between a hypothetical wild-boar population and domestic pig herds in Denmark. Prev Vet Med. 2008;85:187–206. doi: 10.1016/j.prevetmed.2008.01
10. Dion E., Van Schalkwyk L., Lambin E.F. The landscape epidemiology of foot-and-mouth disease in South Africa: a spatially explicit multi-agent simulation. Ecol Model. 2011;222:2059–72. doi: 10.1016/j.ecolmodel.2011.03.026
11. Doran R.J., Laffan S.W. Simulating the spatial dynamics of foot and mouth disease outbreaks in feral pigs and livestock in Queensland, Australia, using a susceptible-infected-recovered cellular automata model. Prev Vet Med. 2005;70:133–52. doi: 10.1016/j.prevetmed.2005.03.002
12. Yoo D.S., Kim Y., Lee E.S., Lim J.S., Hong S.K., Lee I.S., et al. Transmission dynamics of African swine fever virus, South Korea, 2019. Emerg Infect Dis. 2021;27:1909–18. doi: 10.3201/eid2707.204230
13. Ramsey D.S.L., O’Brien D.J., Smith R.W., Cosgrove M.K., Schmitt S.M., Rudolph B.A. Management of on-farm risk to livestock from bovine tuberculosis in Michigan, USA, white-tailed deer: predictions from a spatially-explicit stochastic model. Prev Vet Med. 2016;134:26–38. doi: 10.1016/j.prevetmed.2016.09.022
14. Smith G.C., Delahay R.J., McDonald R.A., Budgey R. Model of selective and non-selective Management of Badgers (Meles meles) to control bovine tuberculosis in badgers and cattle. PLoS One. 2016;11:e0167206. doi: 10.1371/journal.pone.0167206
15. Agudelo M.S., Grant W.E., Wang H.-H. Effects of white-tailed deer habitat use preferences on southern cattle fever tick eradication: simulating impact on “pasture vacation” strategies. Parasit Vectors. 2021;14:102. doi: 10.1186/s13071021-04590-z
16. Yang Y., Nishiura H. Assessing the geographic range of classical swine fever vaccinations by spatiotemporal modelling in Japan. Transbound Emerg Dis. 2022;69:1880–9. doi: 10.1111/tbed.14171
17. Birch C.P.D., Goddard A., Tearne O. A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control. BMC Vet Res. 2018;14:273. doi: 10.1186/s12917-018-1595-9
18. Carpenter T.E., Coggins V.L., McCarthy C., O’Brien C.S., O’Brien, J.M., Schommer T.J. A spatial risk assessment of bighorn sheep extirpation by grazing domestic sheep on public lands. Prev Vet Med. 2014;114:3–10. doi: 10.1016/j.prevetmed.2014.01.008
19. Ward M.P., Garner M.G., Cowled B.D. Modelling foot-and-mouth disease transmission in a wild pig-domestic cattle ecosystem. Aust Vet J. 2015;93:4–12. doi: 10.1111/avj.12278
20. Mugabi F., Duffy K.J. Exploring the dynamics of African swine fever transmission cycles at a wildlife-livestock interface. Nonlinear Anal-Real World Appl. 2023;70:103781. doi: 10.1016/j.nonrwa.2022.103781
21. Bouchez-Zacria M., Courcoul A., Durand B. The distribution of bovine tuberculosis in cattle farms is linked to cattle trade and badger-mediated contact networks in South-Western France, 2007-2015. Front Vet Sci. 2018;5:173. doi: 10.3389/fvets.2018.00173
22. Roy S., McElwain T.F., Wan Y. A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa. PLoS Negl Trop Dis. 2011;5:e1259. doi: 10.1371/journal.pntd.0001259
23. Jori F., Etter E. Transmission of foot and mouth disease at the wildlife/livestock interface of the Kruger National Park, South Africa: can the risk be mitigated? Prev Vet Med. 2016;126:19–29. doi: 10.1016/j.prevetmed.2016.01.016
24. Hayama Y., Shimizu Y., Murato Y., Sawai K., Yamamoto T. Estimation of infection risk on pig farms in infected wild boar areas-epidemiological analysis for the reemergence of classical swine fever in Japan in 2018. Prev Vet Med. 2020;175:104873. doi: 10.1016/j.prevetmed.2019.104873
25. Muñoz F., Pleydell D.R.J., Jori F. A combination of probabilistic and mechanistic approaches for predicting the spread of African swine fever on Merry Island. Epidemics. 2022;40:100596. doi: 10.1016/j.epidem.2022.100596
26. Wiethoelter A.K., Beltrán-Alcrudo D., Kock R, Mor S.M. Global trends in infectious diseases at the wildlife-livestock interface. Proc Natl Acad Sci U S A. 2015;112:9662–7. doi: 10.1073/pnas.1422741112
27. Jori F., Hernandez-Jover M., Magouras I., Dürr S., Brookes V.J. Wildlife–livestock interactions in animal production systems: what are the biosecurity and health implications? Anim Front Rev Mag Anim Agric. 2021;11:8–19. doi: 10.1093/af/vfab045
28. Jacquot M., Nomikou K., Palmarini M., Mertens P., Biek R. Bluetongue virus spread in Europe is a consequence of climatic, landscape and vertebrate host factors as revealed by phylogeographic inference. Proc Biol Sci. 2017;284:20170919. doi: 10.1098/rspb.2017.0919
29. Kilpatrick A.M., Gillin C.M., Daszak P. Wildlife-livestock conflict: the risk of pathogen transmission from bison to cattle outside Yellowstone National Park. J Appl Ecol. 2009;46:476–85. doi: 10.1111/j.1365-2664.2008.01602.x
30. Phepa P.B., Chirove F., Govinder K.S. Modelling the role of multi-transmission routes in the epidemiology of bovine tuberculosis in cattle and buffalo populations. Math Biosci. 2016;277:47–58. doi: 10.1016/j.mbs.2016.04.003
Review
For citations:
Kuzmin V.A., Orekhov D.A., Aidiev A.B., Tsyganov A.V. Principles of mathematical modeling of infectious diseases in the zone of interaction of wildlife and livestock. Legal regulation in veterinary medicine. 2025;(3):42-47. (In Russ.) https://doi.org/10.52419/issn2782-6252.2025.3.42