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. 2025 May;72(3):313-323.
doi: 10.1111/zph.13208. Epub 2025 Jan 16.

There Goes the Neighbourhood-A Multi-City Study Reveals Ticks and Tick-Borne Pathogens Commonly Occupy Urban Green Spaces

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There Goes the Neighbourhood-A Multi-City Study Reveals Ticks and Tick-Borne Pathogens Commonly Occupy Urban Green Spaces

Jani J Sormunen et al. Zoonoses Public Health. 2025 May.

Abstract

Introduction: Humans acquire tick-borne pathogens (TBPs) from infected ticks contacted during outdoor activities. Outdoor activity is at its highest in urban green spaces, where the presence of tick populations has increasingly been observed. Consequently, more insight into factors influencing the presence of ticks therein is needed. Here, we assess the occurrence of ticks and several TBPs in urban green spaces in Finland, estimate related human hazard and assess how landscape features influence tick and TBP occurrence therein.

Methods: Ticks collected from five cities during 2019-2020 were utilised. Borrelia, Rickettsia, Neoehrlichia mikurensis, Anaplasma phagocytophilum , Babesia and TBEV were screened from ticks using qPCR. Various landscape features were calculated and utilised in generalised linear mixed models to assess their contribution towards tick and TBP occurrence in green spaces. Finally, human population density proximate to each study site was calculated and used to create population-weighted risk indices.

Results: Borrelia were the most common pathogens detected, with 22% of nymphs and 43% of adults infected. Increasing forest cover had a positive effect on the densities of nymphs and adults, whereas forest size had a negative effect. Middling percentages of artificial surfaces predicted higher nymph densities than low or high values. Human population-weighted risk estimates were highly varied, even within cities. A positive correlation was observed between total city population and risk indices.

Conclusions: Ticks and TBPs are commonplace in urban green spaces in Finland. Enzootic cycles for Borrelia and Rickettsia appear to be well maintained within cities, leading to widespread risk of infection therein. Our results suggest that nymph densities are highest in urban forests of medium size, whereas small or large forests show reduced densities. Green spaces of roughly similar risk can be found in cities of different sizes, emphasising that the identification of areas of particularly high hazard is important for effective mitigation actions.

Keywords: landscape features; public health; risk index; ticks; tick‐borne pathogens; urban green spaces.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Locations of study sites within Turku (a), Jyväskylä (b), Oulu (c), Tampere (d) and Helsinki (e), and locations of the cities in Finland (f). Maps (a)–(e) are Corine Land Cover maps (CLC2018, 20 m resolution; Finnish Environment Institute), visualised according to the first level CLC2018, with the exception of urban green space (Level 3, Classes 141 and 142). Note that one study site can be represented by more than one circle, as described in Section 2. Location names are listed in Table S1.
FIGURE 2
FIGURE 2
Densities of Ixodes ricinus and Ixodes persulcatus in different study cities in Finland, with 95% confidence limits. No differences between cities were observed for adult densities, whereas for nymphs and larvae, differences between cities with different letters are statistically significant in pairwise comparisons (p < 0.05).
FIGURE 3
FIGURE 3
Seasonal activity patterns of Ixodes ricinus (A) and Ixodes persulcatus (B), and density of infected nymphs or adults (C), with 95% confidence limits. In I. ricinus cities, risk index is calculated as the density of nymphs infected with Borrelia spp. (DIN), whereas in I. persulcatus cities, the density of infected adults (DIA) is used.
FIGURE 4
FIGURE 4
Observed nymph densities (dots) and predictions from the statistical models (lines with 95% confidence limits), presented for: percentage of forest cover (A), size of forest area (B) and percentage of artificial surface (C). Estimates were obtained from the GLMM models encompassing all I. ricinus cities. Only predictions from statistically significant models (p < 0.05) are presented.
FIGURE 5
FIGURE 5
Population density–weighted infection risk estimates calculated within: (A) 500 m and (B) 1000 m of study sites in urban green spaces. City names and populations are given on the x‐axes. Please note the logarithmic scale for the y‐axes.

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