Modelling the spread of livestock disease on a national scale: The case for a hybrid approach

Proceedings - 20th International Congress on Modelling and Simulation, MODSIM 2013

Volumn , Issue , 2013, Pages 345-351

  Bradhurst, R A ^a   Roche, S E ^b   Garner, M G ^b   Sajeev, A S M ^a   Kwan, P ^a  

^a UNIVERSITY OF NEW ENGLAND   (Australia)

^b Department of Agriculture   (Australia)

Author keywords

AADIS; Epidemiological model; Hybrid model; Livestock disease spread; Spatiotemporal model

Indexed keywords

AGRICULTURE; ANIMALS; AUTONOMOUS AGENTS; CLUSTER COMPUTING; COMPUTATIONAL METHODS; LOSSES; OPEN SOURCE SOFTWARE; OPERATIONS RESEARCH; ORDINARY DIFFERENTIAL EQUATIONS; SIMULATION PLATFORM; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TOPOLOGY; VETERINARY MEDICINE;

AADIS; EPIDEMIOLOGICAL MODELING; HYBRID MODEL; LIVESTOCK DISEASE; SPATIO-TEMPORAL MODELS;

DISEASE CONTROL;

EID: 84989214652     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. Balcan D., Colizza V., Goncalves B., Hu J., Ramasco J.J. and Vespignani A. (2009). Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences of the USA, 106(51), 21484-21489.
2. Bobashev G.V., Goedecke D.M., Yu F. and Epstein J.M. (2007). A hybrid epidemic model: Combining the advantages of agent-based and equation-based approaches. Proceedings of the 2007 Winter Simulation Conference, pp. 1532-1537.
3. Boman M. and Holm E. (2004). System Approaches and Their Application. Springer, Netherlands (2004), 95-118.
4. Carley K.M., Fridsma D.B., Casman E., Yahja A., Altman N., Chen L., Kaminsky B. and Nave D. (2006). BioWar: Scalable agent-based model of bioattacks. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 36(2), 252-265.
5. Cash J.R. and Karp A.R. (1990). A variable order Runge-Kutta method for initial value problems with rapidly varying right-hand sides. ACM Transactions on Mathematical Software, 16(3), 201-222.
6. Colizza V. and Vespgnani A. (2010). The Flu Fighters. Physics World, 23(2), 26-30.
7. Dietz K. and Heesterbeek J.A.P. (2002). Daniel Bernoulli's epidemiological model revisited. Mathematical Biosciences, 180(2002), 1-21.
8. Doran R.J. and Laffan S.W. (2005). 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. Preventative Veterinary Medicine, 70(1-2), 133-152.
9. D'Souza R.M., Marino S. and Kirschner D. (2009). Data-Parallel Algorithms for Agent-Based Model Simulation of Tuberculosis On Graphics Processing Units. Proceedings of the 2009 Agent-Directed Simulation Symposium, The Society for Modeling and Simulation International, March 2009.
10. Dube C., Ribble C., Kelton D. and McNab B. (2011). Introduction to network analysis and its implications for animal disease modelling. Review Scientific et Technique, 30(2), 425-436.
11. Earn D.J.D. (2008). A light introduction to modelling recurrent epidemics. Mathematical Epidemiology, eds F. Brauer, P. Van den Driessche and J. Wu., Springer-Verlag Berlin, pp. 3-17.
12. Feder T. (2007). Statistical physics is for the birds. Physics Today, 60(10), 28-30.
13. Fine P.E.M. (1977). A commentary on the mechanical analogue to the Reed-Frost epidemic model. American Journal of Epidemiology, 106(2), 87-100.
14. Garner M.G. and Beckett S.D. (2005). Modelling the spread of foot-and-mouth disease in Australia. Australian Veterinary Journal, 83(12), 758-766.
15. Garner M.G. and Hamilton S.A. (2011). Principles of Epidemiological Modelling. Review Scientific et Technique, 30(2), 407-416.
16. Heppenstall A.J., Evans A.J. and Birkin M.H. (2005). A hybrid multi-agent/spatial interaction model system for petrol price setting. Transactions in GIS, 9(1), 35-51.
17. Macal C.M. and North M.J. (2010). Tutorial on agent-based modeling and simulation. Journal of Simulation, 4(3), 151-162.
18. Matthews K. (2011). A review of Australia's preparedness for the threat of foot-and-mouth disease'. Australian Government Department of Agriculture, Fisheries and Forestry, Canberra.
19. Miller W.M. (1976). A state-transition model of epidemic foot-and-mouth disease. New Techniques in Veterinary Epidemiology and Economics, 1976, 56-72.
20. Morris R.S., Sanson R.L., Stern M.W., Stevenson M. and Wilesmith J.W. (2002). Decision-support tools for foot and mouth disease control. Review Scientific et Technique, 21(3), 557-567.
21. Parker J. and Epstein J.M. (2011). A distributed platform for global-scale agent-based models of disease transmission. ACM Transactions on Modeling and Computer Simulation (TOMACS), 22(1).
22. Parunak H.V.D., Savit R. and Riolo R.L. (1998). Agent-based modeling vs. equation-based modeling: a case study and users' guide. Proceedings of Multi-agent systems and Agent-based Simulation (MABS'98), 10-25.
23. Taylor N. (2003). Review of the use of models in informing disease control policy development and adjustment. School of Agriculture, Policy and Development, The University of Reading.
24. Vincenot C.E. and Moriya K. (2011). Impact of the topology of metapopulations on the resurgence of epidemics rendered by a new multiscale hybrid modeling approach. Ecological Informatics, 6, 177-186.
25. Ward M.P., Laffan S.W. & Highfield L.D. (2011). Disease spread models in wild and feral animal populations: application of artificial life models, Review Scientific et Technique, 30(2), 437-446.