A conceptual scheme of a predictive-analytical model for describing incidence of west nile fever based on weather and climate estimation (exemplified by the Volgograd region)

Abstract

The present study focuses on weather and climatic factors influencing the incidence of West Nile fever (WNF) in the Vol-gograd region. We aimed to describe a relationship between these factors and the WNF incidence and to create a conceptual scheme of a predictive-analytical model for making forecasts how an epidemiological situation would develop in future. According to this aim, we selected an approach that involved identifying a statistical correlation between the analyzed factors and the WNF incidence in the Volgograd region and estimating the power of this correlation. The study primarily relied on using correlation analysis that was followed by assessing authenticity of the study results. The obtained data made it possible to establish that air temperature was a leading potentiating factor in the Volgograd region. It produced certain effects that varied in their intensity on a whole set of abiotic and biotic factors (water level and temperature, numbers and activity of carriers, how fast the virus amplifies in carriers, etc.). The study established that use of comprehensive statistical data (average monthly indicators) allowed more precise esti-mation of correlations. We also considered and confirmed a hypothesis about a delayed effect produced by air temperature on population incidence and numbers of West Nile virus carriers in the Volgograd region; it was the most apparent in years with the maximum numbers of infected people (1999, 2010, and 2012). We revealed a statistical correlation between air temperature and average annual water level and the WNF incidence among population and the number of West Nile virus carriers. There was a strong correlation between the number of carriers and the WNF incidence. A conceptual scheme of a predictive model for determining rate of the WHF incidence in Volgograd region was created based on the statistical analysis results.