Mapping the Potential Distribution of Major Tick Species in China

Xin Yang, Zheng Gao, Tianli Zhou, Jian Zhang, Luqi Wang, Lingjun Xiao, Hongjuan Wu and Sen Li
Additional contact information
Xin Yang: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China
Zheng Gao: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China
Tianli Zhou: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Jian Zhang: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Luqi Wang: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China
Lingjun Xiao: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China
Hongjuan Wu: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China
Sen Li: College of Environment Science and engineering, Huazhong University of Science and Technology, Wuhan 430070, China

IJERPH, 2020, vol. 17, issue 14, 1-15

Abstract: Ticks are known as the vectors of various zoonotic diseases such as Lyme borreliosis and tick-borne encephalitis. Though their occurrences are increasingly reported in some parts of China, our understanding of the pattern and determinants of ticks’ potential distribution over the country remain limited. In this study, we took advantage of the recently compiled spatial dataset of distribution and diversity of ticks in China, analyzed the environmental determinants of ten frequently reported tick species and mapped the spatial distribution of these species over the country using the MaxEnt model. We found that presence of urban fabric, cropland, and forest in a place are key determents of tick occurrence, suggesting ticks were likely inhabited close to where people live. Besides, precipitation in the driest month was found to have a relatively high contribution in mapping tick distribution. The model projected that theses ticks could be widely distributed in the Northwest, Central North, Northeast, and South China. Our results added new evidence on the potential distribution of a variety of major tick species in China and pinpointed areas with a high potential risk of tick bites and tick-borne diseases for raising public health awareness and prevention responses.

Keywords: tick; potential distribution; environmental factors; MaxEnt; machine learning (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/14/5145/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/14/5145/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:14:p:5145-:d:385641

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().