The impact of wildlife and environmental factors on hantavirus infection in the host and its translation into human risk

Abstract

Identifying factors that drive infection dynamics in reservoir host populations is essential in understanding human risk from wildlife-originated zoonoses. We studied zoonotic Puumala orthohantavirus (PUUV) in the host, the bank vole (Myodes glareolus), populations in relation to the host population, rodent and predator community and environment-related factors and whether these processes are translated into human infection incidence. We used 5-year rodent trapping and bank vole PUUV serology data collected from 30 sites located in 24 municipalities in Finland. We found that PUUV seroprevalence in the host was negatively associated with the abundance of red foxes, but this process did not translate into human disease incidence, which showed no association with PUUV seroprevalence. The abundance of weasels, the proportion of juvenile bank voles in the host populations and rodent species diversity were negatively associated with the abundance index of PUUV positive bank voles, which, in turn, showed a positive association with human disease incidence. Our results suggest certain predators, a high proportion of young bank vole individuals, and a diverse rodent community, may reduce PUUV risk for humans through their negative impacts on the abundance of infected bank voles.

Keywords: dilution effect; juvenile dilution effect; top–down trophic interactions; zoonotic Puumala orthohantavirus.

Figure 1.

Rodent trapping sites (red dots) in Finland. Municipalities (black boundaries) for the human NE incidence data overlapped the rodent trapping sites.

Figure 2.

Path diagram of piecewise SEMs showing direct and indirect effects of predictors on human NE incidence through (a) PUUV seroprevalence in bank voles (SEM1) and (b) the abundance index of seropositive bank voles (SEM2). Variables with green backgrounds were the response variable of each component model in SEMs. Solid red arrows represent positive effects (p < 0.05), solid blue arrows represent negative effects (p < 0.05) and dotted grey arrows represent non-significant effects (p > 0.05). We report the path coefficients as standardized effect sizes next to arrows.