Qinlong Jing

Epidemiological, Virological, and Entomological Characteristics of Dengue from 1978 to 2009 in Guangzhou, China

ABSTRACT: To understand its unprecedented resurgence, we examined the epidemiological, virological, and entomological features of dengue in Guangzhou during 1978–2009. Cases reported to the Guangzhou Centre for Disease Control and Prevention and data from virological and entomological surveillance were analyzed from three periods: 1978–1988, 1989–1999, and 2000–2009. Although cases decreased over time: 6,649 (1978–1988) to 6,479 (1989–1999) to 2,526 (2000–2009), geographical expansion resulted in districts with an average incidence >2.5/100,000, increasing from five (1978–1988, 1989–1999) to seven (2000–2009). Age distribution (mean age: 34.9 years) provided a trend of increasing dengue incidence among adults, and there was a significantly higher incidence among men with a sex ratio of 1.15:1 (P<0.001). Cases occurred from May through November with a peak between August and October, and a long-term trend was characterized by a three to five-year cyclical pattern. The most frequently isolated serotypes were DENV-2 (1978–1988) and DENV-1 (1989–1999 and 2000–2009). Seasonal fluctuations in immature densities of Aedes albopictus (sole transmission vector in Guangzhou) were consistent with the dengue seasonality. After a 30-year apparent absence, DENV-3 had reemerged in 2009. The current epidemiological situation is highly conducive to periodic dengue resurgences. Thus, a high degree of surveillance and strict control measures in source reduction should be maintained.

Emergence of dengue virus 4 genotype II in Guangzhou, China, 2010: Survey and molecular epidemiology of one community outbreak

BackgroundThe re-emergence of dengue virus 4 (DENV-4) has become a public health concern in South America, Southeast Asia and South Asia. However, it has not been known to have caused a local outbreak in China for the past 20 years. The purpose of this study was to elucidate the epidemiology of one local community outbreak caused by DENV-4 in Guangzhou city, China, in 2010; and to determine the molecular characteristics of the genotype II virus involved.Case presentationsDuring September and October of 2010, one imported case, a Guangzhou resident who travelled back from Thailand, resulted in 18 secondary autochthonous cases in Guangzhou City, with an incidence rate of 5.53 per 10,000 residents. In indigenous cases, 14 serum samples tested positive for IgM against DENV and 7 for IgG from a total of 15 submitted serum samples, accompanied by 5 DENV-4 isolates. With identical envelope gene nucleotide sequences, the two isolates (D10168-GZ from the imported index case and Guangzhou 10660 from the first isolate in the autochthonous cases) were grouped into DENV-4 genotype II after comparison to 32 previous DENV-4 isolates from GenBank that originated from different areas.ConclusionsBased on epidemiological and phylogenetic analyses, the outbreak, which was absent for 20 years after the DENV-4 genotype I outbreak in 1990, was confirmed as DENV-4 genotype II and initially traced to the imported index case, a Guangzhou resident who travelled back from Thailand.

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

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.

Surface water areas significantly impacted 2014 dengue outbreaks in Guangzhou, China

Dengue transmission in urban areas is strongly influenced by a range of biological and environmental factors, yet the key drivers still need further exploration. To better understand mechanisms of environment-mosquito-urban dengue transmission, we propose an empirical model parameterized and cross-validated from a unique dataset including viral gene sequences, vector dynamics and human dengue cases in Guangzhou, China, together with a 36-year urban environmental change maps investigated by spatiotemporal satellite image fusion. The dengue epidemics in Guangzhou are highly episodic and were not associated with annual rainfall over time. Our results indicate that urban environmental changes, especially variations in surface area covered by water in urban areas, can substantially alter the virus population and dengue transmission. The recent severe dengue outbreaks in Guangzhou may be due to the surge in an artificial lake construction, which could increase infection force between vector (mainly Aedes albopictus) and host when urban water area significantly increased. Impacts of urban environmental change on dengue dynamics may not have been thoroughly investigated in the past studies and more work needs to be done to better understand the consequences of urbanization processes in our changing world.

Re-Emergence of Dengue Virus Type 3 in Canton, China, 2009–2010, Associated with Multiple Introductions through Different Geographical Routes

Background Endemic dengue virus type 3 (DENV-3) infections have not been reported in Canton, China, since 1980. In March 2009, DENV-3 was isolated for the second time, occurring about 30 years after the previous circulation. In August, 3 other cases emerged. One much larger outbreak occurred again in 2010. To address the origin and particularly to determine whether the outbreaks were caused by the same viral genotype, we investigated the epidemiological and molecular characteristics of the introduction, spread and genetic microevolution of DENV-3 involved. Methodology/Principal Findings Three imported cases (index-1,2,3) separately traveled back from Vietnam, India and Tanzania, resulted in 1, 3 and 60 secondary autochthonous cases, respectively. In autochthonous cases, 64.6% positive in IgM anti-DENV and 18.6% in IgG from a total of 48 submitted serum samples, accompanied by 7 DENV-3 isolates. With 99.8%, 99.7%, and 100% envelope gene nucleotidic identity, 09/GZ/1081 from index-1 and endemic strain (09/GZ/1483) belonged to genotype V; 09/GZ/10616 from index-2 and endemic strains (09/GZ/11144 and 09/GZ/11194) belonged to genotype III Clade-A; and 10/GZ/4898 from index-3 and all four 2010 endemic DENV-3 strains belonged to genotype III Clade-B, respectively. Conclusions/Significance Both epidemiological and phylogenetic analyses showed that the 2010 outbreak of dengue was not a reemergence of the 2009 strain. Introductions of different genotypes following more than one route were important contributory factors for the 2009–2010 dengue epidemics/outbreaks in Canton. These findings underscore the importance of early detection and case management of imported case in preventing large-scale dengue epidemics among indigenous peoples of Canton.

Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

Background Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information. Methods We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation. Results Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845–2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938–0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance. Conclusion Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Using Baidu search index to predict dengue outbreak in China

This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1–3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1–5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1–3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1–5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.

A city park as a potential epidemic site of scrub typhus: a case–control study of an outbreak in Guangzhou, China

BackgroundScrub typhus is an important public health problem in China, especially in Guangzhou city. Typical outbreaks of scrub typhus have been previously reported in rural areas, affecting mainly farmers. We describe an atypical outbreak of the disease with case fatalities, from a park in Haizhu District, Guangzhou, that could turn out to be a potential scrub typhus epidemic site.MethodsFrom May 2012 to June 2012, a case–control study was conducted to identify source and risk factors of this outbreak. Reported cases of scrub typhus in Xiaogang Park were confirmed by Weil–Felix test or a nested polymerase chain reaction (NPCR). Controls were matched with their neighbors by gender and age. Multivariate conditional logistic regression was used to identify risk factors and protective factors.ResultsA total of 29 cases were confirmed by Weil–Felix test, including 4 deaths by both Weil–Felix test and NPCR. All patients presented with fever (100%), while 28 (96.6%) cases had eschars, 10 (34.5%) headache, 10 (34.5%) chills, 6 (20.7%) lymphadenopathy, 5 (17.2%) rash, 2 (6.9%) vomiting and 1 (3.5%) presented with conjunctival congestion. The proportion of cases with activity history in Xiaogang Park was much higher than the control group (72.4% vs 24.1%, P < 0.001), and morning exercise in park or field was also as a risk factor for scrub typhus (adjusted OR = 3.0, 95% CI: 1.1 - 8.2). Four factors were significantly associated with the risk of developing scrub typhus: sitting on the lawn (adjusted OR = 8.0, 95% CI: 1.4 - 44.5), close contact with rats (adjusted OR = 3.3, 95% CI: 1.2 -9.6), sitting near the rat holes (OR = 6.8, 95% CI: 1.2 - 38.1) and wearing long-sleeved clothing when outside (adjusted OR = 0.3, 95% CI: 0.1 - 0.7).ConclusionsWe confirmed an atypical outbreak of scrub typhus in a park in Guangzhou city, which has the potential to develop into an important epidemic site. This public health risk should not be neglected and requires more attention from authorities.

The interplay of climate, intervention and imported cases as determinants of the 2014 dengue outbreak in Guangzhou

Dengue is a fast spreading mosquito-borne disease that affects more than half of the population worldwide. An unprecedented outbreak happened in Guangzhou, China in 2014, which contributed 52 percent of all dengue cases that occurred in mainland China between 1990 and 2015. Our previous analysis, based on a deterministic model, concluded that the early timing of the first imported case that triggered local transmission and the excessive rainfall thereafter were the most important determinants of the large final epidemic size in 2014. However, the deterministic model did not allow us to explore the driving force of the early local transmission. Here, we expand the model to include stochastic elements and calculate the successful invasion rate of cases that entered Guangzhou at different times under different climate and intervention scenarios. The conclusion is that the higher number of imported cases in May and June was responsible for the early outbreak instead of climate. Although the excessive rainfall in 2014 did increase the success rate, this effect was offset by the low initial water level caused by interventions in late 2013. The success rate is strongly dependent on mosquito abundance during the recovery period of the imported case, since the first step of a successful invasion is infecting at least one local mosquito. The average final epidemic size of successful invasion decreases exponentially with introduction time, which means if an imported case in early summer initiates the infection process, the final number infected can be extremely large. Therefore, dengue outbreaks occurring in Thailand, Singapore, Malaysia and Vietnam in early summer merit greater attention, since the travel volumes between Guangzhou and these countries are large. As the climate changes, destroying mosquito breeding sites in Guangzhou can mitigate the detrimental effects of the probable increase in rainfall in spring and summer.

Meteorological Factors for Dengue Fever Control and Prevention in South China.

Dengue fever (DF) is endemic in Guangzhou and has been circulating for decades, causing significant economic loss. DF prevention mainly relies on mosquito control and change in lifestyle. However, alert fatigue may partially limit the success of these countermeasures. This study investigated the delayed effect of meteorological factors, as well as the relationships between five climatic variables and the risk for DF by boosted regression trees (BRT) over the period of 2005–2011, to determine the best timing and strategy for adapting such preventive measures. The most important meteorological factor was daily average temperature. We used BRT to investigate the lagged relationship between dengue clinical burden and climatic variables, with the 58 and 62 day lag models attaining the largest area under the curve. The climatic factors presented similar patterns between these two lag models, which can be used as references for DF prevention in the early stage. Our results facilitate the development of the Mosquito Breeding Risk Index for early warning systems. The availability of meteorological data and modeling methods enables the extension of the application to other vector-borne diseases endemic in tropical and subtropical countries.