Agrarian Bulletin of the Urals

The journal has been published since 2000

ISSN 1997 - 4868 (Print); ISSN 2307-0005 (Online)

 

Modern methods of spatial data analysis in the practice of epizootological research

Authors:

P. E. GORBENKO, postgraduate student,

O. G. PETROVA, doctor of veterinary sciences, professor,

Ural State Agrarian University (42 K. Liebknechta str., 620075, Ekaterinburg).

Abstract. In veterinary epidemiology, the advantage of comparing farm locations and other sites with animals is obvious. In an outbreak, this could facilitate the management of the situation and could also serve as a tool for assessing various strategies to prevent the spread of infectious diseases. This article is intended to provide an overview of the possibilities and potential use of Geographic information system (GIS) in the field of animal disease surveillance and monitoring. The following areas where GIS and special GIS functions can be included are presented: recording and reporting information, epidemic situation, cluster analysis, disease modelling and planning management strategies. Spatial analysis is a product of computational operations on GEODATA in order to extract additional information from them. Spatial analysis is typically performed in GIS applications. GIS applications have specialized spatial analysis tools for feature statistics. Epizootic or other necessary information in GIS may contain information about the spatiotemporal position of the sources of infection (recorded outbreaks), the location of their clusters on the territory, the General direction in the spread of the infection. Currently developed methods of collecting and analyzing cartographic information about the epizootic situation on especially dangerous diseases of animals with the use of GPS-navigators, which are integrated with the selected geographic information system ArcGIS and space navigation and topographic system Google Earth (Planet Earth). The tools used depend on the application. The main purpose of the software is to provide the user with a natural path through empirical analysis of spatial data, from simple mapping and geovisualization, transition to research, spatial autocorrelation analysis and ending with spatial regression.

Keywords: geographic information systems, GIS, spatial data analysis, epizootology, animal infectious diseases, monitoring, veterinary epidemiology, spatial regression.

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