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7 - Models for Understanding Disease Dynamics

Published online by Cambridge University Press:  03 July 2017

Andrew P. Robinson
Affiliation:
University of Melbourne
Terry Walshe
Affiliation:
Australian Institute of Marine Science
Mark A. Burgman
Affiliation:
Imperial College London
Mike Nunn
Affiliation:
Australian Centre for International Agricultural Research
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Type
Chapter
Information
Invasive Species
Risk Assessment and Management
, pp. 152 - 180
Publisher: Cambridge University Press
Print publication year: 2017

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References

Abdalla, A., Beare, S., Cao, L., Garner, G. & Heaney, A. (2005). Foot and mouth disease: evaluating alternatives for controlling a possible outbreak in Australia, ABARE eReport 05.6. Canberra: Australian Bureau of Agricultural and Resource Economics.Google Scholar
Alam, K. & Rolfe, J. (2006). Economics of plant disease outbreaks. Agenda, 13(2), 133146.Google Scholar
Animal Health Australia. (2014). Disease strategy: foot-and-mouth disease (version 3.4), Australian Veterinary Emergency Plan (AUSVETPLAN), edition 3. Canberra: Primary Industries Ministerial Council.Google Scholar
Bansal, S., Grenfell, B. T. & Meyers, L. A. (2007). When individual behaviour matters: Homogeneous and network models in epidemiology. Journal of the Royal Society Interface, 4(6), 879891.Google Scholar
Bates, T. W., Thurmond, M. C. & Carpenter, T. E. (2003). Results of epidemic simulation modeling to evaluate strategies to control an outbreak of foot-and-mouth disease. American Journal of Veterinary Research, 64(2), 205210.CrossRefGoogle ScholarPubMed
Baylis, M., Mellor, P. S., Wittmann, E. J. & Rogers, D. J. (2001). Prediction of areas around the Mediterranean at risk of bluetongue by modelling the distribution of its vector by satellite imaging. Veterinary Record, 149(21), 639643.Google Scholar
Beckett, S. & Garner, M. G. (2007). Simulating disease spread within a geographic information system environment. Veterinaria Italiana, 43(3), 595604.Google ScholarPubMed
Boklund, A., Toft, N., Alban, L. & Uttenthal, A. (2009). Comparing the epidemiological and economic effects of control strategies against classical swine fever in Denmark. Preventive Veterinary Medicine, 90(3–4), 180193.Google Scholar
Buetre, B., Wicks, S., Kruger, H., et al. (2013). Potential socioeconomic impacts of an outbreak of foot-and-mouth disease in Australia. ABARES Research Report, Canberra, September. CC BY 3.0. Research report 13.11.Google Scholar
Cacho, O. J. & Hester, S. M. (2011). Deriving efficient frontiers for effort allocation in the management of invasive species. Australian Journal of Agricultural and Resource Economics, 55(1), 7289.CrossRefGoogle Scholar
Cacho, O. J., Spring, D., Hester, S. & Mac Nally, R. (2010). Allocating surveillance effort in the management of invasive species: A spatially-explicit model. Environmental Modelling & Software, 25(4), 444454.CrossRefGoogle Scholar
Cacho, O. J., Spring, D., Pheloung, P. & Hester, S. (2006). Evaluating the feasibility of eradicating an invasion. Biological Invasions, 8(4), 903917.Google Scholar
Caley, P. (1997). Movements, activity patterns and habitat use of feral pigs (Sus scrofa) in a tropical habitat. Wildlife Research, 24(1), 7787.CrossRefGoogle Scholar
Carpenter, T. E., O’Brien, J. M., Hagerman, A. D. & McCarl, B. A. (2011). Epidemic and economic impacts of delayed detection of foot-and-mouth disease: A case study of a simulated outbreak in California. Journal of Veterinary Diagnostic Investigation, 23(1), 2633.CrossRefGoogle ScholarPubMed
Chadès, I., Martin, T. G., Nicol, S., et al. (2011). General rules for managing and surveying networks of pests, diseases and endangered species. Proceedings of the National Academy of Sciences of the USA, 108(20), 83238328.Google Scholar
Chapagain, P. P., Van Kessel, J. S., Karns, J. S., et al. (2008). A mathematical model of the dynamics of Salmonella cerro infection in a US dairy herd. Epidemiology and Infection, 136(2), 236272.CrossRefGoogle Scholar
Choquenot, D., McIlroy, J. & Korn, T. (1996). Managing vertebrate pests: Feral pigs. Canberra: Bureau of Resource Sciences, Australian Government Publishing Service.Google Scholar
Choquenot, D. & Ruscoe, W. A. (2003). Landscape complementation and food limitation of large herbivores: Habitat-related constraints on the foraging efficiency of wild pigs. Journal of Animal Ecology, 72(1), 1426.CrossRefGoogle Scholar
Cowled, B. & Garner, G. (2008). A review of geospatial and ecological factors affecting disease spread in wild pigs: Considerations for models of foot-and-mouth disease spread. Preventive Veterinary Medicine, 87(3–4), 197212.Google Scholar
Cowled, B. D., Garner, M. G., Negus, K. & Ward, M. P. (2012a). Controlling disease outbreaks in wildlife using limited culling: Modelling classical swine fever incursions in wild pigs in Australia. Veterinary Research, 43(1), 3.Google Scholar
Cowled, B. D., Giannini, F., Beckett, S. D., et al. (2009). Feral pigs: Predicting future distributions. Wildlife Research, 36(3), 242251.Google Scholar
Cowled, B. D., Lapidge, S. J., Hampton, J. O. & Spence, P. B. S. (2006). Measuring the demographic and genetic effects of pest control in a highly persecuted feral pig population. Journal of Wildlife Management, 70(6), 16901697.Google Scholar
Cowled, B. D., Ward, M. P., Laffan, S. W., et al. (2012b). Integrating survey and molecular approaches to better understand wildlife disease ecology. PLoS ONE, 7(10), e46310.CrossRefGoogle ScholarPubMed
Dalla Pria, M., Christiano, R. C. S., Furtado, E. L., Amorim, L. & Bergamin Filho, A. (2006). Effect of temperature and leaf wetness duration on infection of sweet oranges by Asiatic citrus canker. Plant Pathology, 55(5), 657663.Google Scholar
Dempsey, S., Evans, G. & Szandala, E. (2002). A target list of high risk pathogens of citrus. Canberra: Department of Agriculture, Fisheries and Forestry.Google Scholar
Dubé, C., Garner, G., Stevenson, M., et al. (2007a). The use of epidemiological models for the management of animal diseases. Paper presented to 75th General Session of the International Committee of the World Organization for Animal Health (OIE), Paris, 20−25 May 2007.Google Scholar
Dubé, C., Ribble, C., Kelton, D. & McNab, B. (2009). Comparing network analysis measures to determine potential epidemic size of highly contagious exotic diseases in fragmented monthly networks of dairy cattle movements in Ontario, Canada. Transboundary and Emerging Diseases, 55(9–10), 382392.CrossRefGoogle Scholar
Dubé, C., Stevenson, M. A., Garner, M. G., et al. (2007b). A comparison of predictions made by three simulation models of foot-and-mouth disease. New Zealand Veterinary Journal, 55(6), 280288.CrossRefGoogle ScholarPubMed
Dürr, S., zu Dohna, H., Di Labio, E., Carpenter, T. E. & Doherr, M. G. (2013). Evaluation of control and surveillance strategies for classical swine fever using a simulation model. Preventive Veterinary Medicine, 108(1), 7384.CrossRefGoogle ScholarPubMed
East, I. J., Martin, P. A. J., Langstaff, I., et al. (2016). Assessing the delay to detection and the size of the outbreak at the time of detection of incursions of foot and mouth disease in Australia. Preventive Veterinary Medicine, 123, 111.CrossRefGoogle ScholarPubMed
East, I. J., Roche, S. E., Wicks, R. M., de Witte, K. & Garner, M. G. (2014). Options for managing animal welfare on intensive pig farms confined by movement restrictions during an outbreak of foot and mouth disease. Preventive Veterinary Medicine, 117(3–4), 533541.Google Scholar
Fox, J. C., Buckley, Y. M., Panetta, F. D., Bourgoin, J. & Pullar, D. (2009). Surveillance protocols for management of invasive plants: Modelling Chilean needle grass (Nassella neesiana) in Australia. Diversity and Distributions, 15(4), 577589.Google Scholar
Gambley, C. F., Miles, A. K., Ramsden, M., et al. (2009). The distribution and spread of citrus canker in Emerald, Australia. Australasian Plant Pathology, 38(6), 547557.CrossRefGoogle Scholar
Garner, M. G. & Beckett, S. D. (2005). Modelling the spread of foot-and-mouth disease in Australia. Australian Veterinary Journal, 83(12), 3038.Google Scholar
Garner, M. G., Bombarderi, N., Cozens, M., et al. (2014). Estimating resource requirements to staff a response to a medium to large outbreak of foot and mouth disease in Australia. Transboundary and Emerging Diseases. doi: 10.1111/tbed.12239Google Scholar
Garner, M. G., Cowled, B., East, I. J., Moloney, B. J. & Yung, N. Y. (2011). Evaluating the effectiveness of early vaccination in the control and eradication of equine influenza – A modelling approach. Preventive Veterinary Medicine, 99(1), 1527.Google Scholar
Garner, M. G., Dubé, C., Stevenson, M. A., et al. (2007). Evaluating alternative approaches to managing animal disease outbreaks – the role of modelling in policy formulation. Veterinaria Italiana, 43(2), 285298.Google Scholar
Garner, M. G., East, I. J., Kompas, T., et al. (2016). Comparison of alternatives to passive surveillance to detect foot and mouth disease incursions in Victoria, Australia. Preventive Veterinary Medicine, 128, 7886.Google Scholar
Garner, M. G. & Hamilton, S. A. (2011). Principles of epidemiological modelling. OIE Scientific and Technical Review, 30(2), 407416.Google Scholar
Garner, M. G. & Lack, M. B. (1995). An evaluation of alternate control strategies for foot-and mouth disease in Australia: A regional approach. Preventive Veterinary Medicine, 23(1–2), 932.CrossRefGoogle Scholar
Gertzen, E. L., Leung, B. & Yan, D. (2011). Propagule pressure, Allee effects and the probability of establishment of an invasive species (Bythotrephes longimanus). Ecosphere, 2(3), art30.CrossRefGoogle Scholar
Gibbens, J. C., Wilesmith, J. W., Sharpe, C. E., et al. (2001). Descriptive epidemiology of the 2001 foot-and-mouth disease epidemic in Great Britain: The first four months. Veterinary Record, 149(24), 729743.CrossRefGoogle Scholar
Goto, M. (1992). Citrus canker. In Kumar, J., Chaube, H. S., Singh, U. S. & Mukhopadhyay (eds.), A. N. Plant diseases of international importance (pp. 250269). Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Gottwald, T. R. & Graham, J. H. (1992). A device for precise and nondisruptive stomatal inoculation of leaf tissue with bacterial pathogens. Phytopathology, 82(9), 930935.Google Scholar
Gottwald, T. R., Graham, J. H. & Schubert, T. S. (2002). Citrus canker: The pathogen and its impact. Plant Health Progress. doi:10.1094/PHP-2002-0812-01-RVGoogle Scholar
Gottwald, T. R., Sun, X., Riley, T. D., et al. (2001). Geo-referenced, spatiotemporal analysis of the urban citrus canker epidemic in Florida. Phytopathology, 92(4), 361377.CrossRefGoogle Scholar
Gottwald, T. R., Timmer, L. W. & McGuire, R. G. (1989). Analysis of disease progress of citrus canker in nurseries in Argentina. Phytopathology, 79(11), 12761283.CrossRefGoogle Scholar
Graham, J. H., Gottwald, T. R., Cubero, J. & Achor, D. (2004). Xanthomonas axonopodus pv. citri: Factors affecting successful eradication of citrus canker. Molecular Plant Pathology, 5(1), 115.CrossRefGoogle ScholarPubMed
Green, L. E. & Medley, G. F. (2002). Mathematical modelling of the foot and mouth disease epidemic of 2001: Strengths and weaknesses. Research in Veterinary Science, 73(3), 201205.CrossRefGoogle ScholarPubMed
Groenendaal, H., Nielen, M. & Hesselink, J. W. (2003). Development of the Dutch Johne’s disease control program supported by a simulation model. Preventive Veterinary Medicine, 60(1), 6990.Google Scholar
Hagerman, A. D., McCarl, B. A., Carpenter, T. E., Ward, M. P. & O’Brien, J. (2012). Emergency vaccination to control foot-and-foot disease: Consequences of its inclusion as a US policy option. Applied Economic Perspectives and Policy, 34(1), 119146.Google Scholar
Hamede, R., Bashford, J., Jones, M. & McCallum, H. (2012). Simulating devil facial tumour disease outbreaks across empirically derived contact networks. Journal of Applied Ecology, 49, 447456.CrossRefGoogle Scholar
Harvey, N., Reeves, A. P., Schoenbaum, M. A., et al. (2007). The North American Animal Disease Spread Model: A simulation model to assist decision making in evaluating animal disease incursions. Preventive Veterinary Medicine, 82(3–4), 176197.Google Scholar
Hester, S. & Garner, M. G. (2012). Post-border surveillance techniques: Review, synthesis and deployment. Final Report: ACERA Project No. 1004. Available from www.acera.unimelb.edu.au/materials/core.htmlGoogle Scholar
Hone, J. (1990). How many feral pigs in Australia. Australian Wildlife Research, 17(6), 571572.Google Scholar
Hopp, P., Webb, C. R. & Jarp, J. (2003). Monte Carlo simulation of surveillance strategies for scrapie in Norwegian sheep. Preventive Veterinary Medicine, 61(2), 103125.CrossRefGoogle ScholarPubMed
Hurd, H. S. & Kaneene, J. B. (1993). The application of simulation models and systems analysis in epidemiology: A review. Preventive Veterinary Medicine, 15(2–3), 8199.CrossRefGoogle Scholar
Jalvingh, A. W., Nielen, M., Maurice, H., et al. (1999). Spatial and stochastic simulation to evaluate the impact of events and control measures on the 1997–1998 classical swine fever epidemic in the Netherlands. I. Description of simulation model. Preventive Veterinary Medicine, 42(3–4), 271295.Google Scholar
Jeger, M. J., Pautasso, M., Holdenrieder, O. & Shaw, M.W. (2007). Modelling disease spread and control in networks: Implications for plant sciences. New Phytologist, 174(2), 279297.CrossRefGoogle ScholarPubMed
Jones, K. E., Patel, N. G., Levy, M. A., et al. (2008). Global trends in emerging infectious diseases. Nature, 451, 990993.Google Scholar
Keeling, M. J. (2005). Models of foot-and mouth disease. Proceedings of the Royal Society B: Biological Sciences, 272(1569), 11951202.CrossRefGoogle ScholarPubMed
Kitching, R. P., Thrusfield, M. V. & Taylor, N. M. (2006). Use and abuse of mathematical models: An illustration from the 2001 foot and mouth disease epidemic in the United Kingdom. OIE Scientific and Technical Review, 25(1), 293311.Google Scholar
Laddomada, A. (2000). Incidence and control of CSF in wild boar in Europe. Veterinary Microbiology, 73(2–3), 121130.CrossRefGoogle ScholarPubMed
Le Menach, A., Legrand, J., Grais, R. F., et al. (2005). Modeling spatial and temporal transmission of foot-and-mouth disease in France: Identification of high risk areas. Veterinary Research, 36(5–6), 699712.CrossRefGoogle ScholarPubMed
Leslie, E., Cowled, B., Garner, M. G. & Ward, M. P. (2012). Effective surveillance strategies following a potential classical swine fever incursion in a remote feral pig population in north-western Australia. Transboundary and Emerging Diseases, 61(5), 432442.CrossRefGoogle Scholar
Li, W., Shi, Z., Yu, M., et al. (2005). Bats are natural reservoirs of SARS-like coronaviruses. Science, 310(5748), 676679.Google Scholar
Macal, C. M. & North, M. J. (2007). Agent-based modeling and simulation: Desktop ABMS. In Henderson, S. G., Biller, B., Hsieh, M.-H., Shortle, J., Tew, J. D. & Barton (eds., R.), Proceedings of the 2007 Winter Simulation Conference, Washington, DC (pp. 95106).Google Scholar
Mangano, P., Hardie, D., Speijers, J., et al. (2011). The capacity of groups within the community to carry out plant pest surveillance detection. The Open Entomology Journal, 5, 1523.Google Scholar
Mangen, M. J., Jalvingh, A. W., Nielen, M., et al. (2001). Spatial and stochastic simulation to compare two emergency-vaccination strategies with a marker vaccine in the 1997/1998 Dutch classical swine fever epidemic. Preventive Veterinary Medicine, 48(3), 177200.Google Scholar
Mansley, L. M., Donaldson, A. I., Thrusfield, M. V. & Honhold, N. (2011). Destructive tension: Mathematics versus experience – the progress and control of the 2001 foot-and-mouth disease epidemic in Great Britain. OIE Scientific and Technical Review, 30(2), 483498.Google Scholar
Martin, P. A. J., Langstaff, I., Iglesias, R. M., et al. (2015). Assessing the efficacy of general surveillance for detection of incursions of livestock diseases in Australia. Preventive Veterinary Medicine, 121, 215230.CrossRefGoogle ScholarPubMed
Matthews, K. (2011). A review of Australia’s preparedness for the threat of foot-and-mouth disease. Canberra: Australian Government Department of Agriculture, Fisheries and Forestry.Google Scholar
McCallum, H., Jones, M., Hawkins, C., et al. (2009). Transmission dynamics of Tasmanian devil facial tumor disease may lead to disease-induced extinction. Ecology, 90(12), 33793392.Google Scholar
Meuwissen, M. P., Horst, S. H., Huirne, R. B. & Dijkhuizen, A. A. (1999). A model to estimate the financial consequences of classical swine fever outbreaks: Principles and outcomes. Preventive Veterinary Medicine, 42(3–4), 249270.Google Scholar
Morris, R. S., Wilesmith, J. W., Stern, M. W., Sanson, R. L. & Stevenson, M. A. (2001). Predictive spatial modelling of alternative control strategies for the foot-and-mouth disease epidemic in Great Britain, 2001. Veterinary Record, 149(5), 137144.Google Scholar
Nerlich, B. (2007). Media, metaphors and modelling: how the UK newspapers reported the epidemiological modelling controversy during the 2001 foot and mouth outbreak. Science, Technology and Human Values, 32(4), 432457.Google Scholar
Normile, D. (2008). Driven to extinction. Science, 319(5870), 16061609.Google Scholar
OIE. (2011). Classical swine fever, general disease information sheets. Paris: World Organisation for Animal Health.Google Scholar
OIE. (2012). Foot and mouth disease. In Terrestrial animal health code, Vol. 2. Available from www.oie.int/en/international-standard-setting/terrestrial-codeGoogle Scholar
Oliver, W. & Leus, K. (2008). Sus scrofa. In IUCN Red List of Threatened Species, version 2010.4. Available from www.iucnredlist.org/details/41775/0Google Scholar
Owen, K., Stevenson, M. A. & Sanson, R. L. (2011). A sensitivity analysis of the New Zealand standard model of foot and mouth disease. OIE Scientific and Technical Review, 30(2), 513526.Google Scholar
Parnell, S., Gottwald, T. R., Gilligan, C. A., Cunniffe, N. J. & van den Bosch, F. (2010). The effect of landscape pattern on the optimal eradication zone of an invading epidemic. Phytopathology, 100(7), 638644.CrossRefGoogle ScholarPubMed
Pasman, E. J., Dijkhuizen, A. A. & Wentink, G. H. (1994). A state-transition model to simulate the economics of bovine virus diarrhoea control. Preventive Veterinary Medicine, 20, 269277.Google Scholar
Pech, R. P., McIlroy, J. C. & Clough, M. F. (1995). Models for predicting the dynamics and control of contact-spread diseases in feral pigs (Sus scrofa) in Australia. Ibex: Journal of Mountain Ecology, 3, 9597.Google Scholar
Pech, R. P., McIlroy, J. C., Clough, M. F. & Green, D. G. (1992). A microcomputer model for predicting the spread and control of foot and mouth disease in feral pigs. In Boorrecco, J. E. & Marsh, R. E. (eds.), Proceedings of the 15th Vertebrate Pest Conference, University of California, Davis (pp. 360364).Google Scholar
Perez, A. M., Ward, M. P., Charmandarian, A. & Ritacco, V (2002). Simulation model of within-herd transmission of bovine tuberculosis in Argentine dairy herds. Preventive Veterinary Medicine, 54(4), 361372.Google Scholar
Perez, L. & Dragicevic, S. (2009). An agent-based approach for modeling dynamics of contagious disease spread. International Journal of Health Geographics, 8, 5067.Google Scholar
Perry, B., McDermott, J. & Randolph, T. (2001). Can epidemiology and economics make a meaningful contribution to national animal-disease control? Preventive Veterinary Medicine, 48(4), 231260.Google Scholar
Pineda-Krch, M., O’Brien, J. M., Thunes, C. & Carpenter, T. E. (2010). Potential impact of introduction of foot-and-mouth disease from wild pigs into commercial livestock premises in California. American Journal of Veterinary Research, 71(1), 8288.Google Scholar
Potts, J. M., Cox, M. J., Barkley, P., et al. (2013). Model-based search strategies for plant diseases: A case-study using citrus canker (Xanthomonas citri). Diversity and Distributions, 19(5–6), 590602.Google Scholar
Potts, J. M., Cox, M. J. & Burgman, M. A. (2012). Model-based search strategies for plant diseases: A case-study using citrus canker (Xanthomonas citri). The University of Melbourne submitted to the Department of Agriculture, Fisheries and Forestry.Google Scholar
Reeves, A., Salman, M. D. & Hill, A. E. (2011). Approaches for evaluating veterinary epidemiological models: Verification, validation and limitations. OIE Scientific and Technical Review, 30(2), 499512.Google Scholar
Roche, S. E., Garner, M. G., Sanson, R. L., et al. (2014a). Evaluating vaccination strategies to control foot-and-mouth disease: A model comparison study. Epidemiology and Infection, 143(6), 12561275.Google Scholar
Roche, S. E., Garner, M. G., Wicks, R. M., et al. (2014b). How do resources influence control measures during a simulated outbreak of foot and mouth disease in Australia? Preventive Veterinary Medicine, 113, 436446.Google Scholar
Rovira, A., Reicks, D. & Muñoz-Zanzi, C. (2007). Evaluation of surveillance protocols for detecting porcine reproductive and respiratory syndrome virus infection in boar studs by simulation modeling. Journal of Veterinary Diagnosis Investigation, 19(5), 492501.CrossRefGoogle ScholarPubMed
Sanson, R. L., Harvey, N., Garner, M. G., et al. (2011). Foot and mouth disease model verification and ‘relative validation’ through a formal model comparison. OIE Scientific and Technical Review, 30(2), 527540.Google Scholar
Schoenbaum, M. A. & Disney, T. W. (2003). Modeling alternative mitigation strategies for a hypothetical outbreak of foot-and-mouth disease in the United States. Preventive Veterinary Medicine, 58(1–2), 2552.Google Scholar
Senate Rural and Regional Affairs and Transport Legislation Committee. (2006). The Administration by the Department of Agriculture, Fisheries and Forestry of the Citrus Canker Outbreak, June 2006. Canberra: Senate Rural and Regional Affairs and Transport Legislation Committee.Google Scholar
Slovic, P. (1999). Trust, emotion, sex, politics, and science: surveying the risk-assessment battlefield. Risk Analysis, 19(4), 689701.Google Scholar
Smith, D. L., Battle, K. E., Hay, S. I., et al. (2012). Ross, Macdonald, and a theory for the dynamics and control of mosquito-transmitted pathogens. PLoS Pathogens, 8(4), e1002588.Google Scholar
Smith, G. & Grenfell, B. T. (1990). Population biology of pseudorabies in swine. American Journal of Veterinary Research, 51(1), 148155.Google ScholarPubMed
Spencer, P. B. S. & Hampton, J. O. (2005). Illegal translocation and genetic structure of feral pigs in Western Australia. Journal of Wildlife Management, 69(1), 377384.Google Scholar
Taylor, N. (2003). Review of the use of models in informing disease control policy development and adjustment, A report for DEFRA. Reading, UK: Veterinary Epidemiology and Economics Research Unit (VEERU).Google Scholar
Thrusfield, M. (2007). Veterinary epidemiology, 3rd ed. Oxford: Blackwell Science.Google Scholar
Travis, J. M. J., Harris, C. M., Park, K. J. & Bullock, J. M. (2011). Improving prediction and management of range expansions by combining analytical and individual-based modelling approaches. Methods in Ecology and Evolution, 2(5), 477488.CrossRefGoogle Scholar
Twigg, L. E., Lowe, T., Martin, G. & Everett, M. (2005). Feral pigs in north-western Australia: Basic biology, bait consumption, and the efficacy of 1080 baits. Wildlife Research, 32(4), 281296.Google Scholar
van Asseldonk, M. A. P. M., van Roermund, H. J. W., Fischer, E. A. J., de Jong, M. C. M. & Huirne, R. M. B. (2005). Stochastic efficiency analysis of bovine tuberculosis-surveillance programs in the Netherlands. Preventive Veterinary Medicine, 69(1–2), 3952.Google Scholar
Ward, M. P., Laffan, S. W. & Highfield, L. D. (2009). Modelling spread of foot-and-mouth disease in wild white-tailed deer and feral pig populations using a geographic-automata model and animal distributions. Preventive Veterinary Medicine, 91(1), 5563.Google Scholar
Wilkinson, K., Grant, W. P., Green, L. E., et al. (2011). Infectious diseases of animals and plants: An interdisciplinary approach. Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1573), 19331942.CrossRefGoogle ScholarPubMed
Yoon, H., Wee, S.-H., Stevenson, M. A., et al. (2006). Simulation analyses to evaluate alternative control strategies for the 2002 foot-and-mouth disease outbreak in the Republic of Korea. Preventive Veterinary Medicine, 74(2–3), 212225.Google Scholar

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