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A multi-agent simulation to assess the risk of malaria re-emergence in southern France

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  • Linard, Catherine
  • Ponçon, Nicolas
  • Fontenille, Didier
  • Lambin, Eric F.

Abstract

A multi-agent simulation (MAS) was developed to assess the risk of malaria re-emergence in the Camargue in southern France, a non-endemic area where mosquitoes of the genus Anopheles (Culicidae) live. The 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. Our model (called MALCAM) represents the different agents that could influence malaria transmission in the Camargue – people, mosquitoes, animal hosts and the landscape – in a spatially explicit environment. The model simulates spatial and temporal variations in human biting rate at the landscape scale. These 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. The model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. The 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. It allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. This application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.

Suggested Citation

  • Linard, Catherine & Ponçon, Nicolas & Fontenille, Didier & Lambin, Eric F., 2009. "A multi-agent simulation to assess the risk of malaria re-emergence in southern France," Ecological Modelling, Elsevier, vol. 220(2), pages 160-174.
    • Handle: RePEc:eee:ecomod:v:220:y:2009:i:2:p:160-174
    DOI: 10.1016/j.ecolmodel.2008.09.001
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    References listed on IDEAS

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    Cited by:

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    2. Annelise Tran & Grégory L'Ambert & Guillaume Lacour & Romain Benoît & Marie Demarchi & Myriam Cros & Priscilla Cailly & Mélaine Aubry-Kientz & Thomas Balenghien & Pauline Ezanno, 2013. "A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations," IJERPH, MDPI, vol. 10(5), pages 1-22, April.
    3. Jian, Yun & Silvestri, Sonia & Belluco, Enrica & Saltarin, Andrea & Chillemi, Giovanni & Marani, Marco, 2014. "Environmental forcing and density-dependent controls of Culex pipiens abundance in a temperate climate (Northeastern Italy)," Ecological Modelling, Elsevier, vol. 272(C), pages 301-310.
    4. Khelifa, Amira & El Saadi, Nadjia, 2024. "The impact of aquatic habitats on the malaria parasite transmission: A view from an agent-based model," Ecological Modelling, Elsevier, vol. 487(C).
    5. Bonnell, Tyler R. & Sengupta, Raja R. & Chapman, Colin A. & Goldberg, Tony L., 2010. "An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission," Ecological Modelling, Elsevier, vol. 221(20), pages 2491-2500.
    6. Degenne, P. & Lo Seen, D. & Parigot, D. & Forax, R. & Tran, A. & Ait Lahcen, A. & Curé, O. & Jeansoulin, R., 2009. "Design of a Domain Specific Language for modelling processes in landscapes," Ecological Modelling, Elsevier, vol. 220(24), pages 3527-3535.
    7. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    8. Dion, Elise & VanSchalkwyk, Louis & Lambin, Eric F., 2011. "The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation," Ecological Modelling, Elsevier, vol. 222(13), pages 2059-2072.

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