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<p>Nymphal ticks of <i>Ixodes pacificus</i>, <i>Ixodes scapularis</i>, <i>Ixodes ricinus</i>, and <i>Ixodes persulcatus</i> are primary vectors of Lyme disease, which affects both animal and human health. Understanding their population dynamic is therefore critical for public health risk assessment. Here we present a focused dataset of questing nymph density, comprising 3579 records from 136 publications from 1980 to 2024. The dataset includes three tick species that represent major Lyme disease risk in the Northern Hemisphere. Records were compiled through systematic literature review and preserved original density measurements with their respective units (e.g., nymphs/m², nymphs/100 m²). Each record contains detailed metadata including tick species, geographical coordinates, temporal resolution and collection methods. This resource provides transparent and structured tick surveillance data essential for ecological modelling, disease risk prediction, and public health risk mapping.</p>

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Geographical dataset of questing nymphal density for three key tick vector species of Lyme disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月9日

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  • Yinsheng Zhang,
  • Yifan Sun,
  • Jinchen Wang,
  • Xiaolong Wu,
  • Luqi Wang,
  • Xin Yang,
  • Yiyang Guo,
  • Ruying Fang,
  • Linxuan Miao,
  • Man Yang,
  • Bingjie Peng,
  • Sophie O. Vanwambeke,
  • Sen Li

摘要

Nymphal ticks of Ixodes pacificus, Ixodes scapularis, Ixodes ricinus, and Ixodes persulcatus are primary vectors of Lyme disease, which affects both animal and human health. Understanding their population dynamic is therefore critical for public health risk assessment. Here we present a focused dataset of questing nymph density, comprising 3579 records from 136 publications from 1980 to 2024. The dataset includes three tick species that represent major Lyme disease risk in the Northern Hemisphere. Records were compiled through systematic literature review and preserved original density measurements with their respective units (e.g., nymphs/m², nymphs/100 m²). Each record contains detailed metadata including tick species, geographical coordinates, temporal resolution and collection methods. This resource provides transparent and structured tick surveillance data essential for ecological modelling, disease risk prediction, and public health risk mapping.