Quantifying Fine-scale Vegetation Associated with Ixodes scapularis Density to Inform Public Health Programming, Western Massachusetts
- 1University of Massachusetts, Amherst
Abstract
Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m{superscript 2}/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.
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BibTeX
@misc{tsalah2026quantifying,
title = {{Quantifying Fine-scale Vegetation Associated with Ixodes scapularis Density to Inform Public Health Programming, Western Massachusetts}},
author = {J. M. Tsalah and V. Bobskill and J. Ravenhurst and K. Ross and A. Gardner and W. Landesman and A. A. Lover},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.14.26363243},
url = {https://www.medrxiv.org/content/10.64898/2026.10.14.26363243v1},
note = {CC BY-ND},
}
RIS
TY - UNPB
TI - Quantifying Fine-scale Vegetation Associated with Ixodes scapularis Density to Inform Public Health Programming, Western Massachusetts
AU - J. M. Tsalah
AU - V. Bobskill
AU - J. Ravenhurst
AU - K. Ross
AU - A. Gardner
AU - W. Landesman
AU - A. A. Lover
PY - 2026
DA - 2026/10/14
PB - medRxiv
DO - 10.64898/2026.10.14.26363243
UR - https://www.medrxiv.org/content/10.64898/2026.10.14.26363243v1
AB - Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m{superscript 2}/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.
ER -