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The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors
In mainland China, a geographic northward expansion of scrub typhus has been seen, highlighting the need to understand the factors and identify the risk for disease prevention. Incidence data from 1980 to 2013 were used. A Cox proportional hazard model was used to identify drivers for spatial spread...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598543/ https://www.ncbi.nlm.nih.gov/pubmed/31233387 http://dx.doi.org/10.1080/22221751.2019.1631719 |
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author | Yao, Hongwu Wang, Yixing Mi, Xianmiao Sun, Ye Liu, Kun Li, Xinlou Ren, Xiang Geng, Mengjie Yang, Yang Wang, Liping Liu, Wei Fang, Liqun |
author_facet | Yao, Hongwu Wang, Yixing Mi, Xianmiao Sun, Ye Liu, Kun Li, Xinlou Ren, Xiang Geng, Mengjie Yang, Yang Wang, Liping Liu, Wei Fang, Liqun |
author_sort | Yao, Hongwu |
collection | PubMed |
description | In mainland China, a geographic northward expansion of scrub typhus has been seen, highlighting the need to understand the factors and identify the risk for disease prevention. Incidence data from 1980 to 2013 were used. A Cox proportional hazard model was used to identify drivers for spatial spread, and a boosted regression tree (BRT) model was constructed to predict potential risk areas. Since the 1980s, an invasive expansion from South Natural Foci towards North Natural Foci was clearly identified, with the epidemiological heterogeneity observed between two regions, mainly in spatial distribution, seasonality, and demographic characteristics. Survival analysis disclosed significant factors contributing to the spatial expansion as following: being intersected by freeway (HR = 1.31, 95% CI: 1.11–1.54), coverage percentage of broadleaf forest (HR = 1.10, 95% CI: 1.06–1.15), and monthly average temperature (HR = 1.27, 95% CI: 1.25–1.30). The BRT models showed that precipitation, sunshine hour, temperature, crop field, and relative humidity contributed substantially to the spatial distribution of scrub typhus. A county-scale risk map was created to predict the regions with high probability of the disease. The current study enabled a comprehensive overview of epidemiological characteristics of scrub typhus in mainland China. |
format | Online Article Text |
id | pubmed-6598543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-65985432019-07-03 The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors Yao, Hongwu Wang, Yixing Mi, Xianmiao Sun, Ye Liu, Kun Li, Xinlou Ren, Xiang Geng, Mengjie Yang, Yang Wang, Liping Liu, Wei Fang, Liqun Emerg Microbes Infect Article In mainland China, a geographic northward expansion of scrub typhus has been seen, highlighting the need to understand the factors and identify the risk for disease prevention. Incidence data from 1980 to 2013 were used. A Cox proportional hazard model was used to identify drivers for spatial spread, and a boosted regression tree (BRT) model was constructed to predict potential risk areas. Since the 1980s, an invasive expansion from South Natural Foci towards North Natural Foci was clearly identified, with the epidemiological heterogeneity observed between two regions, mainly in spatial distribution, seasonality, and demographic characteristics. Survival analysis disclosed significant factors contributing to the spatial expansion as following: being intersected by freeway (HR = 1.31, 95% CI: 1.11–1.54), coverage percentage of broadleaf forest (HR = 1.10, 95% CI: 1.06–1.15), and monthly average temperature (HR = 1.27, 95% CI: 1.25–1.30). The BRT models showed that precipitation, sunshine hour, temperature, crop field, and relative humidity contributed substantially to the spatial distribution of scrub typhus. A county-scale risk map was created to predict the regions with high probability of the disease. The current study enabled a comprehensive overview of epidemiological characteristics of scrub typhus in mainland China. Taylor & Francis 2019-06-24 /pmc/articles/PMC6598543/ /pubmed/31233387 http://dx.doi.org/10.1080/22221751.2019.1631719 Text en © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd http://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/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Yao, Hongwu Wang, Yixing Mi, Xianmiao Sun, Ye Liu, Kun Li, Xinlou Ren, Xiang Geng, Mengjie Yang, Yang Wang, Liping Liu, Wei Fang, Liqun The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title | The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title_full | The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title_fullStr | The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title_full_unstemmed | The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title_short | The scrub typhus in mainland China: spatiotemporal expansion and risk prediction underpinned by complex factors |
title_sort | scrub typhus in mainland china: spatiotemporal expansion and risk prediction underpinned by complex factors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598543/ https://www.ncbi.nlm.nih.gov/pubmed/31233387 http://dx.doi.org/10.1080/22221751.2019.1631719 |
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