Mapping and analysis of the distribution of parasitic infections of cats in cities of Kazakhstan

Abstract

Background and Aim. Endoparasitic infections in domestic and stray cats are of veterinary and public health importance due to their potential zoonotic transmission and environmental contamination. In Kazakhstan, systematic spatial data on the distribution of endoparasites in cats remain limited. This study aimed to develop an information database and a GIS-based cartographic model for collecting, analyzing, and spatially visualizing data on endoparasitic infections in cats and to identify areas with
potentially increased infection risk.
Materials and Methods. Data from 1,301 cats from five major cities of Kazakhstan (Almaty, n=282; Astana, n=382; Shymkent, n=389; Uralsk, n=76; and Kostanay, n=192) were collected from veterinary clinics and animal shelters. Fecal samples from 1,301 cats were examined for helminth eggs and coccidian oocysts; 1,256 cats were tested for Giardia spp. coproantigen, and serum samples from 273 cats were tested for Toxoplasma gondii-specific IgG antibodies. The database included biological characteristics, sample types, laboratory results, and geographic coordinates of sampling sites. GISbased spatial visualization was performed using ArcGIS to assess the distribution of Toxocara cati, Giardia spp., Cystoisospora spp., and Cryptosporidium spp. based on coprological examinations, as well as T. gondii seropositivity based on serological testing.
Results. GIS-based visualization demonstrated parasite-specific spatial variation among the studied cities. The distribution patterns differed according to parasite species; for example, higher proportions of Toxocara cati, Cystoisospora spp., and Giardia spp.-positive samples were observed in Almaty, whereas Cryptosporidium spp. showed the highest observed proportion in Uralsk. These descriptive spatial patterns should not be interpreted as evidence of specific climatic or anthropogenic determinants, which were not directly measured in the present study. The developed GIS model enabled visualization of parasite distribution and identification of areas with higher concentrations of positive samples.
Conclusion. The developed information database and GIS-based cartographic model provide useful tools for the systematic collection, spatial analysis, and visualization of data on endoparasitic infections in cats. Their application can support epidemiological surveillance, risk assessment, and the planning of targeted preventive measures in veterinary and public health programs in Kazakhstan.