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A dataset of distribution and diversity of ticks in China
While tick-borne zoonoses, such as Lyme disease and tick-borne encephalitis, present an increasing global concern, knowledge of their vectors’ distribution remains limited, especially for China. In this paper, we present the first comprehensive dataset of known tick species and their distributions i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602924/ https://www.ncbi.nlm.nih.gov/pubmed/31263100 http://dx.doi.org/10.1038/s41597-019-0115-5 |
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author | Zhang, Guanshi Zheng, Duo Tian, Yuqin Li, Sen |
author_facet | Zhang, Guanshi Zheng, Duo Tian, Yuqin Li, Sen |
author_sort | Zhang, Guanshi |
collection | PubMed |
description | While tick-borne zoonoses, such as Lyme disease and tick-borne encephalitis, present an increasing global concern, knowledge of their vectors’ distribution remains limited, especially for China. In this paper, we present the first comprehensive dataset of known tick species and their distributions in China, derived from peer-reviewed literature published between 1960 and 2017. We searched for journal articles, conference papers and degree thesis published in both English and Chinese, extracted geographic information associated with tick occurrence, and applied quality-control procedures to remove duplicates and ensure accuracy. The dataset contains 5731 records of geo-referenced occurrences for 123 tick species distributed over 1141 locations distinguished at four levels of scale i.e., provincial, prefectural, county, and township and finer. The most frequently reported tick species include Haemaphysalis longicornis, Dermacentor silvarum, Ixodes persulcatus, Haemaphysalis conicinna, Rhipicephalus microplus, and Rhipicephalus sanguineus sensu lato. The geographical dataset provides an improved map of where ticks inhabit China and can be used for a variety of spatial analyses of ticks and the risk of zoonoses they transmit. |
format | Online Article Text |
id | pubmed-6602924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66029242019-07-02 A dataset of distribution and diversity of ticks in China Zhang, Guanshi Zheng, Duo Tian, Yuqin Li, Sen Sci Data Data Descriptor While tick-borne zoonoses, such as Lyme disease and tick-borne encephalitis, present an increasing global concern, knowledge of their vectors’ distribution remains limited, especially for China. In this paper, we present the first comprehensive dataset of known tick species and their distributions in China, derived from peer-reviewed literature published between 1960 and 2017. We searched for journal articles, conference papers and degree thesis published in both English and Chinese, extracted geographic information associated with tick occurrence, and applied quality-control procedures to remove duplicates and ensure accuracy. The dataset contains 5731 records of geo-referenced occurrences for 123 tick species distributed over 1141 locations distinguished at four levels of scale i.e., provincial, prefectural, county, and township and finer. The most frequently reported tick species include Haemaphysalis longicornis, Dermacentor silvarum, Ixodes persulcatus, Haemaphysalis conicinna, Rhipicephalus microplus, and Rhipicephalus sanguineus sensu lato. The geographical dataset provides an improved map of where ticks inhabit China and can be used for a variety of spatial analyses of ticks and the risk of zoonoses they transmit. Nature Publishing Group UK 2019-07-01 /pmc/articles/PMC6602924/ /pubmed/31263100 http://dx.doi.org/10.1038/s41597-019-0115-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Zhang, Guanshi Zheng, Duo Tian, Yuqin Li, Sen A dataset of distribution and diversity of ticks in China |
title | A dataset of distribution and diversity of ticks in China |
title_full | A dataset of distribution and diversity of ticks in China |
title_fullStr | A dataset of distribution and diversity of ticks in China |
title_full_unstemmed | A dataset of distribution and diversity of ticks in China |
title_short | A dataset of distribution and diversity of ticks in China |
title_sort | dataset of distribution and diversity of ticks in china |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602924/ https://www.ncbi.nlm.nih.gov/pubmed/31263100 http://dx.doi.org/10.1038/s41597-019-0115-5 |
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