{"references": ["E. Amouroux, S. Desvaux, A. Drogoul, \"Towards virtual epidemiology: an agent-based approach to the modeling of H5N1 propagation and persistence in North-Vietnam\", journal of Intelligent Agents and Multi-Agent Systems, Springer, p.26-33, (2008).", "E. Amouroux, P. Taillandier, A. Drogoul, & Nord, I. R. D. F, \u00ab Complex environment representation in epidemiology ABM: application on H5N1 propagation \u00bb, 1\u201312, (2010).", "H. Andersson and T. Britton, \"Stochastic Epidemic Models and their Statistical Analysis\". Lecture Notes in Statistics, Springer Verlag, (2000).", "M. Artzrouni, et J.P. Gouteux, \"Population dynamics of sleeping sickness : A micro simulation\", Simulation & Gaming, Vol. 32, No. 2, 215-227 (2001)", "S. Benkirane, J. Hillston, C. McCaig, R. Norman and C. Shankland, \"Improved Continuous Approximation of PEPA Models through Epidemiological Examples\", ENTCS 229 (1), pp. 59\u201374, (2009).", "G. A. Bocharov, A. A. Romanyukha, \"Mathematical model of antiviral immune response III. Influenza A virus infection\", J. Theor. Biol. 167 (4), 323\u2013360, (1994).", "J. Bouyer, S. Cordier, P. Levallois, \u00ab \u00c9pid\u00e9miologie \u00bb, In: Environnement et sant\u00e9 publique - Fondements et pratiques, pp.89\u2013118. (2003).", "S. M. Blower, J. L. Gerberding, \"Understanding, predicting and controlling the emergence of drug-resistant tuberculosis: a theoretical framework\", J. Mol. Med. 76 624, (1998).", "S. M. Blower and al, \"The intrinsic transmission dynamics of tuberculosis epidemics\", Nat. Med. 8 815, (1995).\n[10]\tS. M. Blower, T. C. Porco, T. M. Lietman, \"Tuberculosis: the evolution of antibiotic resistance and the design of epidemic control strategies\", Mathematical Models in Medical and Health Sciences, (1998)\n[11]\tF. Brauer, \"Compartmental Models in Epidemiology\", Mathematical epidemiology, p19-79, springer, (2008).\n[12]\tL. Brouwers, \"MicroPox: a Large-scale and Spatially Explicit Microsimulation Model for Smallpox Transmission\", Proc. of the Intl. Conf. of Health Sciences Simulation, (2005).\n[13]\tF. Ciocchetta, J. Hillston, \"Bio-PEPA for epidemiological models\", 1\u201320. Electronic Notes in Theoretical Computer Science, Volume 261, 22 February 2010, Pages 43-69, (2009).\n[14]\tF. Ciocchetta, J. Hillston, \"Bio-PEPA: a Framework for the Modelling and Analysis of Biochemical Networks\", Theoretical Computer Science 410, pp. 45\u201368, (2009). \n[15]\tM. Costa, \u00ab Mod\u00e9lisation stochastique d'une \u00e9pid\u00e9mie SIR Un bref historique \u00bb, 1\u201311, (2011).\n[16]\tA. L. De Esp\u00edndola, C. T. Bauch, B. C. Troca Cabella & A. S. Martinez, \"An agent-based computational model of the spread of tuberculosis\". Journal of Statistical Mechanics: Theory and Experiment, P05003. doi:10.1088/1742-5468/2011/05/P05003, (2011).\n[17]\tS. C. Fu, \"Modelling epidemic spread using cellular automata\", Master's Thesis The University of Western Australia, Department of Computer Science and Software Engineering, (2002). \n[18]\tL. Hartwell, J. Hopfield, S. Leibler, A. Murray, \"From molecular to modular cell biology\". Nature 402:C47\u2013C52, (1999).\n[19]\t J. Hillston, \"Tuning Systems: From Composition to Performance\", BCS Roger Needham Award Lecture, The Royal Society, London, (2004).\n[20]\tW. O. Kermack, A. G. McKendrick, \"A contribution to the mathematical theory of epidemics\". Proc. R. Soc. Of London Series A 115 (772), pp. 700\u2014721, (1927).\n[21]\tE. L. Landguth,\" A Cellular Automata SIR Model for Landscape Epidemiology\", 1\u201310, (2007).\n[22]\tM. Y. Li, \"Mathematical Epidemiology: Models and Analysis\", University of Alberta Lecture Notes, (2010).\n[23]\tG. Macdonald, \"The epidemiology and control of malaria London\", Oxford University Press, (1957).\n[24]\tD. Machado, R. S. Costa, M. Rocha, E. C. Ferreira, B. Tidor & I. Rocha, \"Modeling formalisms in Systems Biology\". AMB Express, 1(1), 45. doi:10.1186/2191-0855-1-45, (2011).\n[25]\tS. Mandal, R. R. Sarkar & S. Sinha, \"Mathematical models of malaria\", a review. Malaria journal, 10(1), 202. doi:10.1186/1475-2875-10-202, (2011).\n[26]\tC. McCaig, R. Norman and C. Shankland, \"Process Algebra Models of Population Dynamics\", in: Proc. of Algebraic Biology, 3rd International Conference, AB 2008, LNCS 5147, pp. 139\u2013155, (2008).\n[27]\tM. E. J Newman, \"Spread of epidemic disease on networks\". Physical Review E66, (2002).\n[28]\tA. S. Perelson, \"Modelling viral and immune system dynamics\". Nat. Rev. Immunol. 2 (1), 28\u201336, (2002). \n[29]\tE. Ravasz, A. Somera, D. Mongru, Z. Oltvai, A. Barab\u00e1si, \"Hierarchical organization of modularity in metabolic networks\". Science 297(5586):1551\u20131555, (2002).\n[30]\tT. Sellke, \"On the Asymptotic Distribution of the Size of a Stochastic Epidemic\", Journal of Applied Probability, Vol. 20, No. 2, pp. 390-394,(1983).\n[31]\tH. Situngkir, \"Epidemiology through cellular automata: case of study avian influenza in Indonesia\", Bandung Fe Institute, (2004). \n[32]\tD. L. Smith, L. A. Waller, C. A. Russell, J. E. Childs, L. A. Real, \"Assessing the role of long-distance translocation and spatial heterogeneity in the raccoon rabies epidemic in Connecticut\", Prev. Vet. Med., 71, 3-4, 225-240, (2005).\n[33]\tJ. Turner, M. Begon, R. Bowers, \"Modelling pathogen transmission: the interrelationship between local and global approaches\". Proc Biol Sci.,270(1510): 105\u2013112, (2003).\n[34]\tA. J. Valleron, \u00ab L'\u00e9pid\u00e9miologie humaine: Conditions de son d\u00e9veloppement en France, et r\u00f4le des math\u00e9matiques \u00bb, Volume 23 de Rapport sur la science et la technologie : RST / Acad\u00e9mie des sciences , EDP Sciences, 2868837964, 9782868837967, 424 pages, (2006).\n[35]\tC. T. Webb, C.P. Brooks, K.L. Gage, and M. F. Antolin. \"Classic flea-borne transmissoin does not drive plague epizootics in prairie dogs\". PNAS, 103(16):6236\u20136241, (2006).\n[36]\thttp://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology."]}

Modelling is a widely used tool to facilitate the evaluation of disease management. The interest of epidemiological models lies in their ability to explore hypothetical scenarios and provide decision makers with evidence to anticipate the consequences of disease incursion and impact of intervention strategies. All models are, by nature, simplification of more complex systems. Models that involve diseases can be classified into different categories depending on how they treat the variability, time, space, and structure of the population. Approaches may be different from simple deterministic mathematical models, to complex stochastic simulations spatially explicit. Thus, epidemiological modelling is now a necessity for epidemiological investigations, surveillance, testing hypotheses and generating follow-up activities necessary to perform complete and appropriate analysis. The state of the art presented in the following, allows us to position itself to the most appropriate approaches in the epidemiological study.