Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Yao, Hongwu, Wang, Yixing, Mi, Xianmiao, Sun, Ye, Liu, Kun, Li, Xinlou, Ren, Xiang, Geng, Mengjie, Yang, Yang, Wang, Liping, Liu, Wei, Fang, Liqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2019
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
_version_ 1783430794170073088
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
work_keys_str_mv AT yaohongwu thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT wangyixing thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT mixianmiao thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT sunye thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT liukun thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT lixinlou thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT renxiang thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT gengmengjie thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT yangyang thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT wangliping thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT liuwei thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT fangliqun thescrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT yaohongwu scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT wangyixing scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT mixianmiao scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT sunye scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT liukun scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT lixinlou scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT renxiang scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT gengmengjie scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT yangyang scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT wangliping scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT liuwei scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors
AT fangliqun scrubtyphusinmainlandchinaspatiotemporalexpansionandriskpredictionunderpinnedbycomplexfactors