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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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 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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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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1766339741424287744 |