@incollection{fdi:010073233,
  title = {{I}ndividual-based models for public health},
  author = {{R}oche, {B}enjamin and {D}uboz, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}oday, infectious diseases represent a threatening concern for human health. {U}nderstanding their transmission, and possibly forecasting the dynamics of these pathogens, represents both a scientific and sanitary emergency. {T}o this goal, mathematical modeling has been a widely used tool. {N}evertheless, they have important limitations to explicitly model the mechanisms involved in the infectious processes at the individual level. {T}hanks to the increase of computing capacity, computational models such as individual-based models ({IBM}s) are very relevant for understanding the complexity of mechanisms at the individual level that can be involved in disease outbreaks. {T}heir computational formalism allows a large flexibility, while they rely on the same philosophy than current models in mathematical epidemiology that have proved their relevance. {I}n this chapter, we review the main qualities of {IBM}s, what kind of new knowledge they can bring and they have already produced in epidemiological modeling. {T}hen, we highlight their caveats and what could be developed during the future years to make {IBM}s a more reliable and useful approach.},
  keywords = {{SANTE} {PUBLIQUE} ; {EPIDEMIOLOGIE} ; {AGENT} {PATHOGENE} ; {MODELISATION} ; {MODELE} {MATHEMATIQUE} ; {METHODOLOGIE} ; {LOGICIEL} {D}'{APPLICATION} ; {ANALYSE} {SPATIALE} ; {BIOINFORMATIQUE}},
  booktitle = {{D}isease modelling and public health, part {B}},
  numero = {37},
  pages = {347--365},
  address = {},
  series = {{H}andbook of {S}tatistics},
  year = {2017},
  DOI = {10.1016/bs.host.2017.08.008},
  ISSN = {0169-7161},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073233},
}