AI Insight
A short-term field survey conducted across 171 sites in central Hokkaido, Japan in spring 2024 collected 9,908 ticks and screened them for five endemic tick-borne pathogens, including tick-borne encephalitis virus, Yezo virus, Beiji nairovirus, and two groups of borreliae. Ixodes persulcatus and Ixodes ovatus were identified as the principal vector species driving pathogen distribution patterns, and ecological niche models with acceptable predictive performance (median AUC = 0.83) revealed that suitable habitats differ across tick and pathogen species. Snow depth emerged as a particularly important environmental variable explaining distributional differences among ticks and their associated pathogens.
Why it matters
These findings provide high-resolution spatial risk maps for tick-borne diseases in a region where such data were limited, which can directly inform public health surveillance, veterinary risk assessment, and targeted prevention strategies in Hokkaido and potentially similar temperate environments.
by Mebuki Ito, Yuma Ohari, Mai Kishimoto, Keita Matsuno
Tick-borne pathogens are transmitted by tick bites to cause infectious diseases in humans and domestic animals. To anticipate tick-borne disease occurrence, a high resolution understanding of infection risk distribution and its ecological drivers is needed. We aimed to map the spatial distribution of ticks and pathogen-infected ticks in central Hokkaido, Japan. Adult and nymphal ticks were collected with constant effort at 171 sites from 13 May to 26 June 2024, followed by screening tick-borne pathogens and ecological niche modeling. A total of 9,908 ticks were collected and the endemic tick-borne pathogens (i.e., tick-borne encephalitis virus, Yezo virus, Beiji nairovirus, Lyme disease group borreliae, and relapsing fever group borreliae) were primarily detected in Ixodes spp. ticks. Potential suitable habitats of the ticks and pathogens were predicted using the presence/absence data based on tick collection and pathogen detection. The models achieved acceptable predictive performance (median AUC = 0.83 and median TSS = 0.59 in leave-one-out cross‑validation). Ixodes persulcatus and Ixodes ovatus were identified as the primary ticks for determining the distributions of all the pathogens. Besides, the predicted suitable habitats differed among pathogen and tick species. Among the environmental variables considered for modeling, snow depth appeared to significantly contribute to the distribution differences between ticks and pathogens. The findings of this study expand our understanding of the spatial risk distribution of tick-borne pathogen infections and its ecological context.