Current and future applications of species distribution and ecological niche modelling for the study of ticks and tick-borne pathogens.

Ecological niche models (ENMs) and species distribution models (SDMs) are essential tools for investigating the ecological requirements and geographic distributions of species at multiple spatial and temporal scales. While these modelling techniques have been employed across various taxonomic groups to explore ecology, evolution and biogeography, their application to ticks and tick-borne pathogens (TBPs) has yielded valuable-though not yet conclusive-perspectives for understanding epidemiology and pathogen transmission risk. Advances in research on these topics necessitate a review to determine whether there is consistency in the conceptual and methodological implementation of these approaches, as well as to identify needs for improvement and adaptation to more informative alternatives. Here, we aim to review the state of the art in the use of these concepts and tools in the study of tick species and TBPs worldwide to provide a clear understanding of their theoretical and methodological foundations, study topics, involved species, variables, geographic resolutions, applications of model outputs and thematic evolution. We conducted a formal literature review of 158 publications in the period from 1997 to May 2024, along with bibliometric and scientometric analyses. Results indicate that the main topic of study resides in the prediction of current and future potential geographic distribution, and most of the work has been carried out only for nine genera of ticks, with major focus on species belonging to the family Ixodidae and those affecting human health. Borrelia burgdorferi Johnson et al. (Spirochaetales: Borreliaceae) is the most explored pathogen. Studies have mostly used bioclimatic variables, but some studies also incorporate topographic variables from local to global scales, with resolutions ranging from 30 m to 80 km. Although ENM and SDM in ticks and TBPs have been routinely used, very few have been validated in the field, and their projections are not used in epidemiological monitoring. Over 60% of the studies do not report sufficient methodological information for replication. We also detected imprecise usage of the terms ENM and SDM, which are often used interchangeably. This lack of conceptual clarity impedes the adequate treatment of both ecological niches and geographic distributions, hindering advancement in this research field worldwide. We recommend including species of the family Argasidae in future studies to analyse their ecological requirements and potential distributions. These species have been poorly studied despite being vectors of pathogens causing diseases with medical and veterinary importance (e.g., relapsing fever and spirochetosis). Lastly, we identify key areas for improvement-from biogeographical knowledge gaps to the use of modern sampling methods, algorithms and hypotheses-that would enhance the application of these concepts and modelling techniques.