@article{fdi:010048293,
  title = {{A} multi-agent simulation to assess the risk of malaria re-emergence in southern {F}rance},
  author = {{L}inard, {C}. and {P}on{\c{c}}on, {N}icolas and {F}ontenille, {D}idier and {L}ambin, {E}. {F}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A} multi-agent simulation ({MAS}) was developed to assess the risk of malaria re-emergence in the {C}amargue in southern {F}rance, a non-endemic area where mosquitoes of the genus {A}nopheles ({C}ulicidae) live. {T}he contact rate between people and potential malaria vectors, or the human biting rate, is one of the key factor to predict the risk of re-emergence of malaria, would the parasite be introduced in the region. {O}ur model (called {MALCAM}) represents the different agents that could influence malaria transmission in the {C}amargue people, mosquitoes, animal hosts and the landscape - in a spatially explicit environment. {T}he model simulates spatial and temporal variations in human biting rate at the landscape scale. {T}hese variations depend on the distribution of people and potential vectors, their behaviour and their interactions. {A} land use/cover map was used as a cellular-spatial support for the movements of and interactions between mobile agents. {T}he model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. {T}he {MALCAM} model provides a tool to better understand the interactions between the multiple agents of the disease transmission system, and the land use and land cover factors that control the spatial heterogeneity in these interactions. {I}t allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. {T}his application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.},
  keywords = {{M}ulti-agent simulation ; {H}uman biting rate ; {M}alaria ; {C}amargue ; {A}nopheles hyrcanus ; {L}and use},
  booktitle = {},
  journal = {{E}cological {M}odelling},
  volume = {220},
  numero = {2},
  pages = {160--174},
  ISSN = {0304-3800},
  year = {2009},
  DOI = {10.1016/j.ecolmodel.2008.09.001},
  URL = {https://www.documentation.ird.fr/hor/fdi:010048293},
}