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

Abstract

BackgroundPredicting 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.MethodWe 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.ResultsModel 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.ConclusionThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-072X-13-45) contains supplementary material, which is available to authorized users.

A multi-event capture-recapture analysis of Toxoplasma gondii seroconversion dynamics in farm cats

“…The average annual seroconversion rates estimated on the five studied farms (0.42 for the farms B and T, 0.88 for the farm C and 0.96 for the farms A and F) are high compared to those previously reported in an urban population of stray cats (0.17 seroconversions/year) [ 35 ] and in three rural populations of owned domestic cats (0.26, 0.36 and 0.39 seroconversions/year) [ 36 ]. These results support previous findings showing that livestock farms are hotspots of T. gondii infection in rural areas [ 29 , 31 , 59 – 61 ]. However, the seroconversion rates, as well as the estimated seroprevalences were highly variable between farms (from 15.38 to 73.08% or from 29.63 to 73.08% depending on the selected cut-off value) and the range of seroprevalences we obtained corresponds to the range of seroprevalences in farm cats previously reported in the literature: 33.3% in Spain [ 62 ]; 41.9% [ 63 ]; 68% [ 64 ] and 53.19% [ 65 ] in the USA; 62% in the UK [ 66 ]; and 75% in Poland [ 67 ].…”

Impact of environmental factors on the emergence, transmission and distribution of Toxoplasma gondii

“…Gotteland et al . developed an Agent Based Model (ABM) taking spatial distribution of landscape structures (farm buildings) into account [ 70 , 71 ]. They found that spatial distribution of farm buildings in rural environments is associated with the infection of humans and animals: humans and animals in the villages where the farms are located might be at a higher risk of exposure to T. gondii oocyst due to the high density of cats [ 70 , 71 ].…”

Evolution of research in health geographics through the International Journal of Health Geographics (2002–2015)

“…In Agricultural landscape and spatial distribution of Toxoplasma gondii in rural environment: an agent-based model [ 23 ], the authors consider space essentially as a medium of interactions aiming, via multi-agent model, to predict the spatial distribution of a pathogenic factor (difficult to assess in real life), via a number of variables that seem to influence its distribution. Here the parasite is Toxoplasma gondii , which is responsible for toxoplasmosis and is excreted in the environment by infected cats (the definitive host) and rodents (intermediate host).…”