Dataset Information

Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model.

ABSTRACT: As the world's fastest spreading vector-borne disease, dengue was estimated to infect more than 390 million people in 2010, a 30-fold increase in the past half century. Although considered to be a non-endemic country, mainland China had 55,114 reported dengue cases from 2005 to 2014, of which 47,056 occurred in 2014. Furthermore, 94% of the indigenous cases in this time period were reported in Guangdong Province, 83% of which were in Guangzhou City. In order to determine the possible determinants of the unprecedented outbreak in 2014, a population-based deterministic model was developed to describe dengue transmission dynamics in Guangzhou. Regional sensitivity analysis (RSA) was adopted to calibrate the model and entomological surveillance data was used to validate the mosquito submodel. Different scenarios were created to investigate the roles of the timing of an imported case, climate, vertical transmission from mosquitoes to their offspring, and intervention. The results suggested that an early imported case was the most important factor in determining the 2014 outbreak characteristics. Precipitation and temperature can also change the transmission dynamics. Extraordinary high precipitation in May and August, 2014 appears to have increased vector abundance. Considering the relatively small number of cases in 2013, the effect of vertical transmission was less important. The earlier and more frequent intervention in 2014 also appeared to be effective. If the intervention in 2014 was the same as that in 2013, the outbreak size may have been over an order of magnitude higher than the observed number of new cases in 2014.The early date of the first imported and locally transmitted case was largely responsible for the outbreak in 2014, but it was influenced by intervention, climate and vertical transmission. Early detection and response to imported cases in the spring and early summer is crucial to avoid large outbreaks in the future.

SUBMITTER: Cheng Q

PROVIDER: S-EPMC4749339 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model.

Cheng Qu Q Jing Qinlong Q Spear Robert C RC Marshall John M JM Yang Zhicong Z Gong Peng P

PLoS neglected tropical diseases 20160210 2

As the world's fastest spreading vector-borne disease, dengue was estimated to infect more than 390 million people in 2010, a 30-fold increase in the past half century. Although considered to be a non-endemic country, mainland China had 55,114 reported dengue cases from 2005 to 2014, of which 47,056 occurred in 2014. Furthermore, 94% of the indigenous cases in this time period were reported in Guangdong Province, 83% of which were in Guangzhou City. In order to determine the possible determinant ...[more]

PMID: 26863623

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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

Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model.

Publications

Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model.

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