@article{fdi:010044218,
  title = {{M}ulti-agent systems in epidemiology : a first step for computational biology in the study of vector-borne disease transmission},
  author = {{R}oche, {B}enjamin and {G}u{\'e}gan, {J}ean-{F}ran{\c{c}}ois and {B}ousquet, {F}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {C}omputational biology is often associated with genetic or genomic studies only. {H}owever, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. {S}uch modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. {S}o far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with {SIR} models could be seen as an implicit standard in epidemiology. {U}nfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. {F}or instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and {SIR} models might not be the most suitable tool to truly capture the overall disease circulation within that environment. {T}his limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems. {R}esults: {C}omputational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. {I}n this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. {W}e developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment. {C}onclusion: {H}ere we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. {T}o conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.},
  keywords = {},
  booktitle = {},
  journal = {{B}mc {B}ioinformatics},
  volume = {9},
  numero = {},
  pages = {435},
  ISSN = {1471-2105},
  year = {2008},
  DOI = {10.1186/1471-2105-9-435},
  URL = {https://www.documentation.ird.fr/hor/fdi:010044218},
}