Mapping the distribution of Amblyomma americanum in Georgia, USA

Stephanie Bellman, Ellie Fausett, Leah Aeschleman, Audrey Long, Isabella Roeske, Josie Pilchik, Anne Piantadosi,Gonzalo Vazquez-Prokopec

Parasites & Vectors(2024)

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摘要
Background Amblyomma americanum , the lone star tick, is an aggressive questing species that harbors several pathogens dangerous to humans in the United States. The Southeast in particular has large numbers of this tick due to the combined suitable climate and habitats throughout the region. No studies have estimated the underlying distribution of the lone star tick across the state of Georgia, a state where it is the dominant species encountered. Methods Ticks were collected by flagging 198 transects of 750 m 2 at 43 state parks and wildlife management areas across the state from March to July of 2022. A suite of climate, landscape, and wildlife variables were assembled, and a logistic regression model was used to assess the association between these environmental factors and the presence of lone star ticks and to predict the distribution of these ticks across the state. Results A total of 59/198 (30%) transects sampled contained adult or nymph A. americanum , with the majority of transects containing these ticks (54/59, 91.5%) in forested habitats. The presence of A. americanum was associated with elevation, normalized difference vegetation index (NDVI) on January 1, isothermality, temperature seasonality, and precipitation in the wettest quarter. Vast regions of central, eastern, and southern coastal Georgia (57% of the state) were categorized as suitable habitat for the lone star tick. Conclusions This study describes the distribution of the lone star tick across the state of Georgia at a finer scale than the current county-level information available. It identifies specific variables associated with tick presence and provides a map that can be used to target areas for tick prevention messaging and awareness. Graphical Abstract
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关键词
Amblyomma americanum,Georgia USA,Tick,Species distribution,Predictive vector map
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