Int J Health Geogr - Agricultural landscape and spatial distribution of Toxoplasma gondii in rural environment: an agent-based model.

Tópicos

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Resumo

CKGROUND: 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.

Resumo Limpo

ckground predict spatial distribut pathogen environment stage challeng difficulti detect environment sampl among pathogen parasit toxoplasma gondii causat agent zoonosi toxoplasmosi respons public health issu oocyst t gondii excret infect cat environ may surviv remain infecti intermedi host specif rodent month year landscap structur determin densiti distribut cat may thus impact spatial distribut t gondii studi investig influenc rural set spatial distribut oocyst soilmethod develop spatial explicit agent base model studi landscap structur impact spatial distribut t gondii preval rodent intermedi host well contamin environ rural landscap character locat farm build provid shelter resourc cat specif consid two configur farm build ie insid outsid villag simul first set farm build insid villag valid use data previous field studi simul result two set compar investig influenc farm locationsresult model predict show steeper relationship distanc nearest farm infect level farm build thus cat concentr area farm spread area relationship distanc villag center level environment contamin also differ set potenti increas risk inhabit farm locat insid villag map risk soil contamin oocyst also deriv modelconclus agentbas model provid use tool assess risk contamin t gondii oocyst local scale determin risk area moreov provid basi investig spatial dynam pathogen environment stage

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