Prevalence and prediction of Lyme disease in Hainan province.
Lyme disease (LD) is one of the most important vector-borne diseases worldwide. However, there is limited information on the prevalence and risk analysis using correlated factors in the tropical areas. A total of 1583 serum samples, collected from five hospitals of Hainan Province, were tested by im...
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ftdoajarticles:oai:doaj.org/article:9021998de80f4c09bc465bab57e72ea5 2023-05-15T15:13:47+02:00 Prevalence and prediction of Lyme disease in Hainan province. Lin Zhang Xiong Zhu Xuexia Hou Huan Li Xiaona Yang Ting Chen Xiaoying Fu Guangqing Miao Qin Hao Sha Li 2021-03-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0009158 https://doaj.org/article/9021998de80f4c09bc465bab57e72ea5 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0009158 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009158 https://doaj.org/article/9021998de80f4c09bc465bab57e72ea5 PLoS Neglected Tropical Diseases, Vol 15, Iss 3, p e0009158 (2021) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2021 ftdoajarticles https://doi.org/10.1371/journal.pntd.0009158 2022-12-31T05:03:46Z Lyme disease (LD) is one of the most important vector-borne diseases worldwide. However, there is limited information on the prevalence and risk analysis using correlated factors in the tropical areas. A total of 1583 serum samples, collected from five hospitals of Hainan Province, were tested by immunofluorescence assay (IFA) and western blot (WB) analyses using anti-Borrelia burgdorferi antibodies. Then, we mapped the distribution of positive rate (by IFA) and the spread of confirmed Lyme patients (by WB). Using ArcGIS, we compiled host-vector-human interactions and correlated data as risk factor layers to predict LD risk in Hainan Province. There are three LD hotspots, designated hotspot I, which is located in central Hainan, hotspot II, which contains Sanya district, and hotspot III, which lies in the Haikou-Qiongshan area. The positive rate (16.67% by IFA) of LD in Qiongzhong, located in hotspot I, was higher than that in four other areas. Of confirmed cases of LD, 80.77% of patients (42/52) whose results had been confirmed by WB were in hotspots I and III. Hotspot II, with unknowed prevalence of LD, need to be paid more attention considering human-vector interaction. Wuzhi and Limu mountains might be the most important areas for the prevalence of LD, as the severe host-vector and human-vector interactions lead to a potential origin site for LD. Qiongzhong is the riskiest area and is located to the east of Wuzhi Mountain. In the Sanya and Haikou-Qiongshan area, intervening in the human-vector interaction would help control the prevalence of LD. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 15 3 e0009158 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Lin Zhang Xiong Zhu Xuexia Hou Huan Li Xiaona Yang Ting Chen Xiaoying Fu Guangqing Miao Qin Hao Sha Li Prevalence and prediction of Lyme disease in Hainan province. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Lyme disease (LD) is one of the most important vector-borne diseases worldwide. However, there is limited information on the prevalence and risk analysis using correlated factors in the tropical areas. A total of 1583 serum samples, collected from five hospitals of Hainan Province, were tested by immunofluorescence assay (IFA) and western blot (WB) analyses using anti-Borrelia burgdorferi antibodies. Then, we mapped the distribution of positive rate (by IFA) and the spread of confirmed Lyme patients (by WB). Using ArcGIS, we compiled host-vector-human interactions and correlated data as risk factor layers to predict LD risk in Hainan Province. There are three LD hotspots, designated hotspot I, which is located in central Hainan, hotspot II, which contains Sanya district, and hotspot III, which lies in the Haikou-Qiongshan area. The positive rate (16.67% by IFA) of LD in Qiongzhong, located in hotspot I, was higher than that in four other areas. Of confirmed cases of LD, 80.77% of patients (42/52) whose results had been confirmed by WB were in hotspots I and III. Hotspot II, with unknowed prevalence of LD, need to be paid more attention considering human-vector interaction. Wuzhi and Limu mountains might be the most important areas for the prevalence of LD, as the severe host-vector and human-vector interactions lead to a potential origin site for LD. Qiongzhong is the riskiest area and is located to the east of Wuzhi Mountain. In the Sanya and Haikou-Qiongshan area, intervening in the human-vector interaction would help control the prevalence of LD. |
format |
Article in Journal/Newspaper |
author |
Lin Zhang Xiong Zhu Xuexia Hou Huan Li Xiaona Yang Ting Chen Xiaoying Fu Guangqing Miao Qin Hao Sha Li |
author_facet |
Lin Zhang Xiong Zhu Xuexia Hou Huan Li Xiaona Yang Ting Chen Xiaoying Fu Guangqing Miao Qin Hao Sha Li |
author_sort |
Lin Zhang |
title |
Prevalence and prediction of Lyme disease in Hainan province. |
title_short |
Prevalence and prediction of Lyme disease in Hainan province. |
title_full |
Prevalence and prediction of Lyme disease in Hainan province. |
title_fullStr |
Prevalence and prediction of Lyme disease in Hainan province. |
title_full_unstemmed |
Prevalence and prediction of Lyme disease in Hainan province. |
title_sort |
prevalence and prediction of lyme disease in hainan province. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doi.org/10.1371/journal.pntd.0009158 https://doaj.org/article/9021998de80f4c09bc465bab57e72ea5 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 15, Iss 3, p e0009158 (2021) |
op_relation |
https://doi.org/10.1371/journal.pntd.0009158 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009158 https://doaj.org/article/9021998de80f4c09bc465bab57e72ea5 |
op_doi |
https://doi.org/10.1371/journal.pntd.0009158 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
15 |
container_issue |
3 |
container_start_page |
e0009158 |
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1766344301601619968 |