Multivariate relationships between epidemiologic risk factors and zoonotic infections among military personnel in the country of Georgia: A non-linear canonical correlation analysis

Zoonoses Public Health. 2019 Nov;66(7):835-841. doi: 10.1111/zph.12632. Epub 2019 Jul 23.

Abstract

Zoonotic diseases are endemic in the country of Georgia. Using the non-linear canonical correlation (NCC) method, the aim of this study was to examine the relationship between thirteen epidemiological risk factors and seropositivity to five zoonotic infections (anthrax, Q fever, tularemia, leptospirosis, and Crimean-Congo hemorrhagic fever [CCHF]) among Georgian military recruits during 2014-2016. According to this multivariate statistical technique, which is suitable for the analysis of two or more sets of qualitative variables simultaneously, two canonical variables were identified. These variables accounted for 68% of the variation between the two sets of categorical variables ("risk factors" and "zoonotic infections"). For the first canonical variable, there was a relationship among CCHF (canonical loading, which is interpreted in the same way as the Pearson's correlation coefficient, [cl] = 0.715), tick bites (cl = 0.418) and slaughter of animals (cl = 0.351). As for the second canonical variable, Q fever (cl = -0.604) and leptospirosis (cl = -0.486) were related to rodents inside and outside home (cl = -0.346) and sweeping in or around home (cl = -0.317). The NCC method allows researchers to obtain additional insights into the complex relationship between epidemiological risk factors and multiple zoonotic infections.

Keywords: canonical correlation; epidemiology; military; risk factors; zoonotic.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Animals
  • Bacterial Infections / epidemiology*
  • Georgia (Republic) / epidemiology
  • Hemorrhagic Fever, Crimean / epidemiology*
  • Humans
  • Male
  • Military Personnel*
  • Multivariate Analysis
  • Risk Factors
  • Serologic Tests
  • Zoonoses / epidemiology*