Document Type : Original Article


1 MSc Student, Department of Environmental sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

2 Assistant Professor, Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

3 Associate Professor, Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran


Background and aims: Toxoplasmosis, a zoonotic parasitic disease of warm-blooded animals, is notably
influenced by environmental features. Recognizing spatial pattern of Toxoplasma gondii distribution
in environment can provide significant contributions to public health and toxoplasmosis control. This
study was designed to survey the frequency of T. gondii antibody in rural dogs and cats and also
analyze possible relation between environmental factors and spatial distribution of T. gondiiantibody
in Golestan province, using GIS.
Methods: From 2015 to 2016, 106 rural cats and 154 rural dogs were randomly sampled. Serum
samples were tested for presence of T. gondii antibody through modified agglutination test (MAT). The
relation between T. gondii antibody frequency and environmental factors was surveyed in ArcGIS and
Idrisi Selva software with multiple linear regression model.
Results: From sampled rural cats and rural dogs, 85 (80.1%) and 99 (64.2%) were positive for T.
gondii antibody, respectively. The highest frequency was seen in areas with temperate climate, Gorgan
(82.4%) with a humidity of 78%, rainfall of 551 mm and temperature of 12.5°C. The lowest rate was
in Maravetappeh (60.8%) with a humidity of 70%, rainfall of 418 mm and temperature of 15.37°C.
About 53% of the difference in the T. gondii antibody frequency in sampled population was explained
by climatic condition of each region.
Conclusion: The output presented here can facilitate the identification of high risk areas, based on
climate condition, to apply effective planning control measures.


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