Survey on the Role of Environmental Factors in the Spatial Distribution of the Toxoplasma gondii Antibody in Hosts (Rural Dogs and Cats) Using GIS Software: A Case Study in Golestan Province

Document Type: Original Article

Authors

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

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

Abstract

 
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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