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      Time series analysis performed on nephropathia epidemica in humans of northern Sweden in relation to bank vole population dynamic and the NAO index.

      Zoonoses and Public Health
      Animals, Arvicolinae, virology, Climate, Disease Reservoirs, veterinary, Hemorrhagic Fever with Renal Syndrome, epidemiology, transmission, Humans, Multivariate Analysis, Population Density, Population Dynamics, Population Growth, Prevalence, Sweden, Time Factors, Zoonoses

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          Abstract

          Time series analysis was performed on two data series of human nephropathia epidemica (NE) infections in northern Sweden between the years 1959-1975 and 1985-2006. The analysis confirms that the bank vole (Myodes glareolus), the main reservoir species, shows regular peaks in population density approximately every fourth year. The periodicity in NE cases of the more recent time period (1985-2006) is 2.8-3.3 years and the older period shows a periodicity ranging 3.4-4.2 years, but this is not significantly different from that expected by vole dynamics. A comparison of North Atlantic Oscillation (NAO) index between the two periods reveals higher mean winter NAO index in the period 1985-2006 than in 1959-1975. No difference was found in frequency of the NAO index between the older period (2.8-3.4 years) compared with the recent period (2.4-2.8 years). Cross-correlation revealed a delayed effect by NAO index on vole abundance but a multivariate model showed that NAO index did not explain the variation in NE cases. Vole index was the only factor that contributed significantly to the variation in numbers of NE cases and that no climate effect could be detected. The climate signal from NAO index does not appear to significantly affect the human NE cases and this suggests that the transmission of disease to man is not particularly sensitive to variations in weather factors. The results favour the hypothesis that higher NAO index will not increase the likelihood of virus transmission from voles to man in northern Sweden under present climatic conditions.

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