Agricultural landscape and spatial distribution of Toxoplasma gondii in rural environment: an agent-based model

International Journal of Health Geographics

Maud Lélu¹  Emmanuelle Gilot-Fromont⁵  Xiaopeng Zhao³  Brent M McFerrin⁴  Cécile Gotteland² 

[1] Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 S. Second st. Suite 300, Minneapolis, MN 55454, USA;Université de Reims Champagne-Ardenne, Laboratoire de Parasitologie-Mycologie, EA 3800, UFR de Médecine, SFR Cap Santé FED 4231, 51 rue Cognacq-Jay, F-51096 Reims, France;National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN 37996, USA;Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA;Université de Lyon, VetAgro-Sup Campus Vétérinaire, 1 Avenue Bourgelat, F-69280 Marcy l’Etoile, France

关键词: Agent-based model;    Environmental contamination;    Spatial distribution;    Rural landscape;    Toxoplasma gondii;   

Others  :  1135996
DOI  :  10.1186/1476-072X-13-45

 received in 2014-06-16, accepted in 2014-09-25,  发布年份 2014

【 摘 要 】

Background

Predicting the spatial distribution of pathogens with an environmental stage is challenging because of the difficulty to detect them in environmental samples. Among these pathogens, the parasite Toxoplasma gondii is the causative agent of the zoonosis toxoplasmosis, which is responsible for public health issues. Oocysts of T. gondii are excreted by infected cats in the environment, where they may survive and remain infectious for intermediate hosts, specifically rodents, during months to years. The landscape structure that determines the density and distribution of cats may thus impact the spatial distribution of T. gondii. In this study, we investigated the influences of rural settings on the spatial distribution of oocysts in the soil.

Method

We developed a spatially explicit agent based model to study how landscape structures impact on the spatial distribution of T. gondii prevalence in its rodent intermediate host as well as contamination in the environment. The rural landscape was characterized by the location of farm buildings, which provide shelters and resources for the cats. Specifically, we considered two configurations of farm buildings, i.e. inside and outside a village. Simulations of the first setting, with farm buildings inside the village, were validated using data from previous field studies. Then, simulation results of the two settings were compared to investigate the influences of the farm locations.

Results

Model predictions showed a steeper relationship between distance to the nearest farm and infection levels when farm buildings, and thus cats, were concentrated in the same area than when the farms were spread over the area. The relationship between distance to the village center and level of environmental contamination also differed between settings with a potential increased risk for inhabitants when farms are located inside the village. Maps of the risk of soil contaminated with oocysts were also derived from the model.

Conclusion

The agent-based model provides a useful tool to assess the risk of contamination by T. gondii oocysts at a local scale and determine the most at risk areas. Moreover it provides a basis to investigate the spatial dynamics of pathogens with an environmental stage.

【 授权许可】

   
2014 Gotteland et al.; licensee BioMed Central Ltd.

【 图 表 】

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