Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.

This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China.Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was use...

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Published in:PLOS Neglected Tropical Diseases
Main Authors: Kangkang Liu, Yanshan Zhu, Yao Xia, Yingtao Zhang, Xiaodong Huang, Jiawei Huang, Enqiong Nie, Qinlong Jing, Guoling Wang, Zhicong Yang, Wenbiao Hu, Jiahai Lu
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2018
Subjects:
Online Access:https://doi.org/10.1371/journal.pntd.0006318
https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9
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spelling ftdoajarticles:oai:doaj.org/article:b675efc80b934f72b385f76d0efe7ea9 2023-05-15T15:08:22+02:00 Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China. Kangkang Liu Yanshan Zhu Yao Xia Yingtao Zhang Xiaodong Huang Jiawei Huang Enqiong Nie Qinlong Jing Guoling Wang Zhicong Yang Wenbiao Hu Jiahai Lu 2018-03-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0006318 https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC5880401?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0006318 https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9 PLoS Neglected Tropical Diseases, Vol 12, Iss 3, p e0006318 (2018) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2018 ftdoajarticles https://doi.org/10.1371/journal.pntd.0006318 2022-12-30T22:27:34Z This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China.Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF.Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01).The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 12 3 e0006318
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
Kangkang Liu
Yanshan Zhu
Yao Xia
Yingtao Zhang
Xiaodong Huang
Jiawei Huang
Enqiong Nie
Qinlong Jing
Guoling Wang
Zhicong Yang
Wenbiao Hu
Jiahai Lu
Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
topic_facet Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
description This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China.Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF.Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01).The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention.
format Article in Journal/Newspaper
author Kangkang Liu
Yanshan Zhu
Yao Xia
Yingtao Zhang
Xiaodong Huang
Jiawei Huang
Enqiong Nie
Qinlong Jing
Guoling Wang
Zhicong Yang
Wenbiao Hu
Jiahai Lu
author_facet Kangkang Liu
Yanshan Zhu
Yao Xia
Yingtao Zhang
Xiaodong Huang
Jiawei Huang
Enqiong Nie
Qinlong Jing
Guoling Wang
Zhicong Yang
Wenbiao Hu
Jiahai Lu
author_sort Kangkang Liu
title Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
title_short Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
title_full Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
title_fullStr Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
title_full_unstemmed Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
title_sort dynamic spatiotemporal analysis of indigenous dengue fever at street-level in guangzhou city, china.
publisher Public Library of Science (PLoS)
publishDate 2018
url https://doi.org/10.1371/journal.pntd.0006318
https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source PLoS Neglected Tropical Diseases, Vol 12, Iss 3, p e0006318 (2018)
op_relation http://europepmc.org/articles/PMC5880401?pdf=render
https://doaj.org/toc/1935-2727
https://doaj.org/toc/1935-2735
1935-2727
1935-2735
doi:10.1371/journal.pntd.0006318
https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9
op_doi https://doi.org/10.1371/journal.pntd.0006318
container_title PLOS Neglected Tropical Diseases
container_volume 12
container_issue 3
container_start_page e0006318
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