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Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis
Lyme borreliosis, recognized as one of the most important tick-borne diseases worldwide, has been increasing in incidence and spatial extent. Currently, there are few geographic studies about the distribution of Lyme borreliosis risk across China. Here we established a nationwide database that invol...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067995/ https://www.ncbi.nlm.nih.gov/pubmed/35411829 http://dx.doi.org/10.1080/22221751.2022.2065930 |
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author | Che, Tian-Le Jiang, Bao-Gui Xu, Qiang Zhang, Yu-Qi Lv, Chen-Long Chen, Jin-Jin Tian, Ying-Jie Yang, Yang Hay, Simon I. Liu, Wei Fang, Li-Qun |
author_facet | Che, Tian-Le Jiang, Bao-Gui Xu, Qiang Zhang, Yu-Qi Lv, Chen-Long Chen, Jin-Jin Tian, Ying-Jie Yang, Yang Hay, Simon I. Liu, Wei Fang, Li-Qun |
author_sort | Che, Tian-Le |
collection | PubMed |
description | Lyme borreliosis, recognized as one of the most important tick-borne diseases worldwide, has been increasing in incidence and spatial extent. Currently, there are few geographic studies about the distribution of Lyme borreliosis risk across China. Here we established a nationwide database that involved Borrelia burgdorferi sensu lato (B. burgdorferi) detected in humans, vectors, and animals in China. The eco-environmental factors that shaped the spatial pattern of B. burgdorferi were identified by using a two-stage boosted regression tree model and the model-predicted risks were mapped. During 1986−2020, a total of 2,584 human confirmed cases were reported in 25 provinces. Borrelia burgdorferi was detected from 35 tick species with the highest positive rates in Ixodes granulatus, Hyalomma asiaticum, Ixodes persulcatus, and Haemaphysalis concinna ranging 20.1%−24.0%. Thirteen factors including woodland, NDVI, rainfed cropland, and livestock density were determined as important drivers for the probability of B. burgdorferi occurrence based on the stage 1 model. The stage 2 model identified ten factors including temperature seasonality, NDVI, and grasslands that were the main determinants used to distinguish areas at high or low-medium risk of B. burgdorferi, interpreted as potential occurrence areas within the area projected by the stage 1 model. The projected high-risk areas were not only concentrated in high latitude areas, but also were distributed in middle and low latitude areas. These high-resolution evidence-based risk maps of B. burgdorferi was first created in China and can help as a guide to future surveillance and control and help inform disease burden and infection risk estimates. |
format | Online Article Text |
id | pubmed-9067995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-90679952022-05-05 Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis Che, Tian-Le Jiang, Bao-Gui Xu, Qiang Zhang, Yu-Qi Lv, Chen-Long Chen, Jin-Jin Tian, Ying-Jie Yang, Yang Hay, Simon I. Liu, Wei Fang, Li-Qun Emerg Microbes Infect Research Article Lyme borreliosis, recognized as one of the most important tick-borne diseases worldwide, has been increasing in incidence and spatial extent. Currently, there are few geographic studies about the distribution of Lyme borreliosis risk across China. Here we established a nationwide database that involved Borrelia burgdorferi sensu lato (B. burgdorferi) detected in humans, vectors, and animals in China. The eco-environmental factors that shaped the spatial pattern of B. burgdorferi were identified by using a two-stage boosted regression tree model and the model-predicted risks were mapped. During 1986−2020, a total of 2,584 human confirmed cases were reported in 25 provinces. Borrelia burgdorferi was detected from 35 tick species with the highest positive rates in Ixodes granulatus, Hyalomma asiaticum, Ixodes persulcatus, and Haemaphysalis concinna ranging 20.1%−24.0%. Thirteen factors including woodland, NDVI, rainfed cropland, and livestock density were determined as important drivers for the probability of B. burgdorferi occurrence based on the stage 1 model. The stage 2 model identified ten factors including temperature seasonality, NDVI, and grasslands that were the main determinants used to distinguish areas at high or low-medium risk of B. burgdorferi, interpreted as potential occurrence areas within the area projected by the stage 1 model. The projected high-risk areas were not only concentrated in high latitude areas, but also were distributed in middle and low latitude areas. These high-resolution evidence-based risk maps of B. burgdorferi was first created in China and can help as a guide to future surveillance and control and help inform disease burden and infection risk estimates. Taylor & Francis 2022-04-12 /pmc/articles/PMC9067995/ /pubmed/35411829 http://dx.doi.org/10.1080/22221751.2022.2065930 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Che, Tian-Le Jiang, Bao-Gui Xu, Qiang Zhang, Yu-Qi Lv, Chen-Long Chen, Jin-Jin Tian, Ying-Jie Yang, Yang Hay, Simon I. Liu, Wei Fang, Li-Qun Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title | Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title_full | Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title_fullStr | Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title_full_unstemmed | Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title_short | Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis |
title_sort | mapping the risk distribution of borrelia burgdorferi sensu lato in china from 1986 to 2020: a geospatial modelling analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067995/ https://www.ncbi.nlm.nih.gov/pubmed/35411829 http://dx.doi.org/10.1080/22221751.2022.2065930 |
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