Ecology and Evolution (Nov 2024)

Integrating Systematic Surveys With Historical Data to Model the Distribution of Ornithodoros turicata americanus, a Vector of Epidemiological Concern in North America

  • Sebastian Botero‐Cañola,
  • Carson Torhorst,
  • Nicholas Canino,
  • Lorenza Beati,
  • Kathleen C. O'Hara,
  • Angela M. James,
  • Samantha M. Wisely

DOI
https://doi.org/10.1002/ece3.70547
Journal volume & issue
Vol. 14, no. 11
pp. n/a – n/a

Abstract

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ABSTRACT Globally, vector‐borne diseases are increasing in distribution and frequency, affecting humans, domestic animals, and wildlife. Science‐based management and prevention of these diseases requires a sound understanding of the distribution and environmental requirements of the vectors and hosts involved in disease transmission. Integrated Species Distribution Models (ISDM) account for diverse data types through hierarchical modeling and represent a significant advancement in species distribution modeling. We assessed the distribution of the soft tick subspecies Ornithodoros turicata americanus. This tick species is a potential vector of African swine fever virus (ASFV), a pathogen responsible for an ongoing global epizootic that threatens agroindustry worldwide. Given the novelty of this method, we compared the results to a conventional Maxent SDM and validated the results through data partitioning. Our input for the model consisted of systematically collected detection data from 591 sampled field sites and 12 historical species records, as well as four variables describing climatic and soil characteristics. We found that a combination of climatic variables describing seasonality and temperature extremes, along with the amount of sand in the soil, determined the predicted intensity of occurrence of this tick species. When projected in geographic space, this distribution model predicted 62% of Florida as suitable habitat for this tick species. The ISDM presented a higher TSS and AUC than the Maxent conventional model, while sensitivity was similar between both models. Our case example shows the utility of ISDMs in disease ecology studies and highlights the broad range of geographic suitability for this important disease vector. These results provide important foundational information to inform future risk assessment work for tick‐borne relapsing fever surveillance and potential ASF introduction and maintenance in the United States.

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