ArticlePLoS neglected tropical diseases2018
Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China.
Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Land use and land cover change and its impacts on dengue dynamics in China: A systematic review.PLoS neglected tropical diseases · 2021Pooled it
- Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China.PloS one · 2019Trial
- Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia.BMC public health · 2025Article
- Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan.International journal of environmental research and public health · 2021Article
- Facilitating fine-grained intra-urban dengue forecasting by integrating urban environments measured from street-view images.Infectious diseases of poverty · 2021Article
- Enhancing fine-grained intra-urban dengue forecasting by integrating spatial interactions of human movements between urban regions.PLoS neglected tropical diseases · 2020Article
- Determination of Factors Affecting Dengue Occurrence in Representative Areas of China: A Principal Component Regression Analysis.Frontiers in public health · 2020Article
- A dynamic neural network model for predicting risk of Zika in real time.BMC medicine · 2019Article
- Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China.Nature communications · 2019Article
- Neighbourhood level real-time forecasting of dengue cases in tropical urban Singapore.BMC medicine · 2018Article
- Dengue Infection Spectrum in Guangzhou: A Cross-Sectional Seroepidemiology Study among Community Residents between 2013 and 2015.International journal of environmental research and public health · 2018Article
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Authors and funding
12 authors.
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Abstract
backgroundThis 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.
methodsSpatiotemporal 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.
resultsSpatial 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).
conclusionsThe 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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