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Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014.

ABSTRACT: INTRODUCTION:Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response. METHODOLOGY AND PRINCIPAL FINDINGS:In the study we developed a time series Poisson multivariate regression model using imported dengue cases, local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou, China. The time series data were decomposed into seasonal, trend and remainder components using a seasonal-trend decomposition procedure based on loess (STL). The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis. Autocorrelation, seasonality and long-term trend were controlled in the model. A best model was selected and validated using Generalized Cross Validation (GCV) score and residual test. The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model. Time series Poisson model showed that imported cases in the previous month, minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation, seasonality and long-term trend. CONCLUSIONS:Together with the sole transmission vector Aedes albopictus, imported cases, monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system.

SUBMITTER: Sang S

PROVIDER: S-EPMC4447292 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014.

Sang Shaowei S Gu Shaohua S Bi Peng P Yang Weizhong W Yang Zhicong Z Xu Lei L Yang Jun J Liu Xiaobo X Jiang Tong T Wu Haixia H Chu Cordia C Liu Qiyong Q

PLoS neglected tropical diseases 20150528 5

<h4>Introduction</h4>Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response.<h4>Methodology and principal findings</h4>In the study we developed a time series Pois ...[more]

PMID: 26020627

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Project description:IntroductionEach year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose.Methodology and principal findingsThree traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags.ConclusionsImported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.

Project description:BackgroundDengue was regarded as a mild epidemic in mainland China transmitted by Aedes albopictus. However, the 2014 record-breaking outbreak in Guangzhou could change the situation. In order to provide an early warning of epidemic trends and provide evidence for prevention and control strategies, we seek to characterize the 2014 outbreak through application of detailed cases and entomological data, as well as phylogenetic analysis of viral envelope (E) gene.MethodsWe used case survey data identified through the Notifiable Infectious Disease Report System, entomological surveillance and population serosurvey, along with laboratory testing for IgM/IgG, NS1, and isolation of viral samples followed by E gene sequencing and phylogenetic analysis to examine the epidemiological and molecular characteristics of the outbreak.ResultsThe 2014 dengue outbreak in Guangzhou accounted for nearly 80% of total reported cases that year in mainland China; a total of 37,376 cases including 37,340 indigenous cases with incidence rate 2908.3 per million and 36 imported cases were reported in Guangzhou, with 14,055 hospitalized and 5 deaths. The epidemic lasted for 193 days from June 11 to December 21, with the highest incidence observed in domestic workers, the unemployed and retirees. The inapparent infection rate was 18.00% (135/750). In total, 96 dengue virus 1 (DENV-1) and 11 dengue virus 2 (DENV-2) strains were isolated. Phylogenetic analysis indicated that the DENV-1 strains were divided into genotype I and V, similar to the strains isolated in Guangzhou and Dongguan in 2013. The DENV-2 strains isolated were similar to those imported from Thailand on May 11 in 2014 and that imported from Indonesia in 2012.ConclusionsThe 2014 dengue epidemic was confirmed to be the first co-circulation of DENV-1 and DENV-2 in Guangzhou. The DENV-1 strain was endemic, while the DENV-2 strain was imported, being efficiently transmitted by the Aedes albopictus vector species at levels as high as Aedes aegypti.

Dataset Information

Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014.

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Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014.

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