ArticleJournal of medical entomology2021
Exploring the Niche of Rickettsia montanensis (Rickettsiales: Rickettsiaceae) Infection of the American Dog Tick (Acari: Ixodidae), Using Multiple Species Distribution Model Approaches.
Article in Journal of medical entomology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Trends and Opportunities in Tick-Borne Disease Geography.Journal of medical entomology · 2021Pooled it
- Potential risk of heartworm infection in the United States of America and its projected incidence by 2100.Parasites & vectors · 2026Article
- Exploring Metrics of Biological Diversity to Better Predict and Respond to Emerging Diseases.Integrative and comparative biology · 2025Review
- Spatial and temporal analyses of Dermacentor variabilis (Say) (Acari: Ixodidae) in central and eastern Canada.Medical and veterinary entomology · 2025Article
- Current and future ecological niche of Dermacentor similis Lado (Acari: Ixodidae) in western North America.Journal of medical entomology · 2025Article
- Species-specific variation in predicted distribution and habitat suitability of phlebotomine sand flies in Italy under different climate change scenarios.Scientific reports · 2025Article
- Diversity of questing ticks and prevalence of tick-associated pathogens in Khao Kheow-Khao Chomphu Wildlife Sanctuary, Chon Buri, Thailand.Current research in parasitology & vector-borne diseases · 2024Article
- Predicting the distribution of Ixodes ricinus and Dermacentor reticulatus in Europe: a comparison of climate niche modelling approaches.Parasites & vectors · 2023Review
- Newer Surveillance Data Extends our Understanding of the Niche ofVector borne and zoonotic diseases (Larchmont, N.Y.) · 2023Article
- Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases.Tropical medicine and infectious disease · 2023Review
- Estimating the distribution ofEcosphere (Washington, D.C) · 2023Article
- Current and Future Habitat Suitability Models for Four Ticks of Medical Concern in Illinois, USA.Insects · 2023Article
- Newer Surveillance Data Extends our Understanding of the Niche ofbioRxiv : the preprint server for biology · 2023Article
- Predicting Spatial Patterns of Sindbis Virus (SINV) Infection Risk in Finland Using Vector, Host and Environmental Data.International journal of environmental research and public health · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
The American dog tick, Dermacentor variabilis (Say) (Acari: Ixodidae), is a vector for several human disease-causing pathogens such as tularemia, Rocky Mountain spotted fever, and the understudied spotted fever group rickettsiae (SFGR) infection caused by Rickettsia montanensis. It is important for public health planning and intervention to understand the distribution of this tick and pathogen encounter risk. Risk is often described in terms of vector distribution, but greatest risk may be concentrated where more vectors are positive for a given pathogen. When assessing species distributions, the choice of modeling framework and spatial layers used to make predictions are important. We first updated the modeled distribution of D. variabilis and R. montanensis using maximum entropy (MaxEnt), refining bioclimatic data inputs, and including soil variables. We then compared geospatial predictions from five species distribution modeling frameworks. In contrast to previous work, we additionally assessed whether the R. montanensis positive D. variabilis distribution is nested within a larger overall D. variabilis distribution, representing a fitness cost hypothesis. We found that 1) adding soil layers improved the accuracy of the MaxEnt model; 2) the predicted 'infected niche' was smaller than the overall predicted niche across all models; and 3) each model predicted different sizes of suitable niche, at different levels of probability. Importantly, the models were not directly comparable in output style, which could create confusion in interpretation when developing planning tools. The random forest (RF) model had the best measured validity and fit, suggesting it may be most appropriate to these data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.