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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Bibliographic Details
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:
Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
Arctic
Online Access:https://doi.org/10.1371/journal.pntd.0006318
https://doaj.org/article/b675efc80b934f72b385f76d0efe7ea9
Description
Summary: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.

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