Community Involvement in Dengue Outbreak Control: An Integrated Rigorous Intervention Strategy

BackgroundAn explosive outbreak of dengue fever occurred in Guangdong Province, China in 2014. A community-based integrated intervention was applied to control this outbreak in the capital city Guangzhou, where dengue epidemic was mainly caused by imported cases.ConclusionsThis study suggests that an integrated dengue intervention program has significant effects to control a dengue outbreak in areas where dengue epidemic was mainly caused by imported dengue cases.     

Predicting Unprecedented Dengue Outbreak Using Imported Cases and Climatic Factors in Guangzhou, 2014

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.     

Analysis of a Dengue Model with Vertical Transmission and Application to the 2014 Dengue Outbreak in Guangdong Province,China

There is evidence showing that vertical transmission of dengue virus exists in Aedes mosquitoes. In this paper, we propose a deterministic dengue model with vertical transmission in mosquitoes by including aquatic mosquitoes (eggs, larvae and pupae), adult mosquitoes (susceptible, exposed and infectious) and human hosts (susceptible, exposed, infectious and recovered). We first analyze the existence and stability of disease-free equilibria, calculate the basic reproduction number and discuss the existence of the disease-endemic equilibrium. Then, we study the impact of vertical transmission of the virus in mosquitoes on the spread dynamics of dengue. We also use the model to simulate the reported infected human data from the 2014 dengue outbreak in Guangdong Province, China, carry out sensitivity analysis of the basic reproduction number in terms of the model parameters, and seek for effective control measures for the transmission of dengue virus.     

Molecular epidemiology demonstrates that imported and local strains circulated during the 2014 dengue outbreak in Guangzhou,China

The dengue virus(DENV) is a vital global public health issue. The 2014 dengue epidemic in Guangzhou, China, caused approximately 40,000 cases of infection and five deaths. We carried out a comprehensive investigation aimed at identifying the transmission sources in this dengue epidemic. To analyze the phylogenetics of the 2014 dengue strains, the envelope(E) gene sequences from 17 viral strains isolated from 168 dengue patient serum samples were sequenced and a phylogenetic tree was reconstructed. All 17 strains were serotype Ⅰ strains, including 8genotype Ⅰ and 9 genotype V strains. Additionally, 6 genotype Ⅰ strains that were probably introduced to China from Thailand before 2009 were widely transmitted in the 2013 and 2014 epidemics, and they continued to circulate until 2015, with one affinis strain being found in Singapore. The other 2 genotype Ⅰ strains were introduced from the Malaya Peninsula in 2014. The transmission source of the 9 genotype Ⅴ strains was from Malaysia in 2014. DENVs of different serotypes and genotypes co-circulated in the 2014 dengue outbreak in Guangzhou. Moreover, not only had DENV been imported to Guangzhou, but it had also been gradually exported, as the viruses exhibited an enzootic transmission cycle in Guangzhou.     

Evaluation of Inapparent Dengue Infections During an Outbreak in Southern China

Few studies evaluating inapparent dengue virus (DENV) infections have been conducted in China. In 2013, a large outbreak of DENV occurred in the city of Zhongshan, located in Southern China, which provided an opportunity to assess the clinical spectrum of disease. During the outbreak, an investigation of 887 index case contacts was conducted to evaluate inapparent and symptomatic DENV infections. Post-outbreak, an additional 815 subjects from 4 towns with, and 350 subjects from 2 towns without reported autochthonous DENV transmission, as determined by clinical diagnosis, were evaluated for serological evidence of dengue IgG antibodies. Between July and November 2013, there were 19 imported and 809 autochthonous dengue cases reported in Zhongshan. Of 887 case contacts enrolled during the outbreak, 13 (1.5%) exhibited symptomatic DENV infection, while 28 (3.2%) were inapparent. The overall I:S ratio was 2.2:1 (95% CI: 1.1-4.2:1). Post-outbreak serological data showed that the proportion of DENV IgG antibody detection from the 4 towns with and the 2 towns without reported DENV transmission was 2.7% (95% CI: 1.6%-3.8%) and 0.6% (95% CI: 0-1.4%), respectively. The I:S ratio in the 3 towns where clinical dengue cases were predominately typed as DENV-1 was 11.0:1 (95% CI: 3.7-∞:1). The ratio in the town where DENV-3 was predominately typed was 1.0:1 (95% CI: 0.5-∞:1). In this cross-sectional study, data suggests a high I:S ratio during a documented outbreak in Zhongshan, Southern China. These results have important implications for dengue control, implying that inapparent cases might influence DENV transmission more than previously thought.     

Predicting Local Dengue Transmission in Guangzhou,China, through the Influence of Imported Cases,Mosquito Density and Climate Variability

Introduction

Each 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 Findings

Three 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.

Conclusions

Imported 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.     

Assessing the suitability for Aedes albopictus and dengue transmission risk in China with a delay differential equation model

Dengue is considered non-endemic to mainland China. However, travellers frequently import the virus from overseas and local mosquito species can then spread the disease in the population. As a consequence, mainland China still experiences large dengue outbreaks. Temperature plays a key role in these outbreaks: it affects the development and survival of the vector and the replication rate of the virus. To better understand its implication in the transmission risk of dengue, we developed a delay differential equation model that explicitly simulates temperature-dependent development periods and tested it with collected field data for the Asian tiger mosquito, Aedes albopictus. The model predicts mosquito occurrence locations with a high accuracy (Cohen’s κ of 0.78) and realistically replicates mosquito population dynamics. Analysing the infection dynamics during the 2014 dengue outbreak that occurred in Guangzhou showed that the outbreak could have lasted for another four weeks if mosquito control interventions had not been undertaken. Finally, we analyse the dengue transmission risk in mainland China. We find that southern China, including Guangzhou, can have more than seven months of dengue transmission per year while even Beijing, in the temperate north, can have dengue transmission during hot summer months. The results demonstrate the importance of using detailed vector and infection ecology, especially when vector-borne disease transmission risk is modelled over a broad range of climatic zones.     

Investigation of the First Case of Dengue Virus Infection Acquired in Western Australia in Seven Decades: Evidence of Importation of Infected Mosquitoes?

In October 2013, a locally-acquired case of dengue virus (DENV) infection was reported in Western Australia (WA) where local dengue transmission has not occurred for over 70 years. Laboratory testing confirmed recent DENV infection and the case demonstrated a clinically compatible illness. The infection was most likely acquired in the Pilbara region in the northwest of WA. Follow up investigations did not detect any other locally-acquired dengue cases or any known dengue vector species in the local region, despite intensive adult and larval mosquito surveillance, both immediately after the case was notified in October 2013 and after the start of the wet season in January 2014. The mechanism of infection with DENV in this case cannot be confirmed. However, it most likely followed a bite from a single infected mosquito vector that was transiently introduced into the Pilbara region but failed to establish a local breeding population. This case highlights the public health importance of maintaining surveillance efforts to ensure that any incursions of dengue vectors into WA are promptly identified and do not become established, particularly given the large numbers of viraemic dengue fever cases imported into WA by travellers returning from dengue-endemic regions.     

The epidemiological characteristics of dengue in high-risk areas of China, 2013–2016

IntroductionDengue has become a more serious human health concern in China, with increased incidence and expanded outbreak regions. The knowledge of the cross-sectional and longitudinal epidemiological characteristics and the evolutionary dynamics of dengue in high-risk areas of China is limited.MethodsRecords of dengue cases from 2013 to 2016 were obtained from the China Notifiable Disease Surveillance System. Full envelope gene sequences of dengue viruses detected from the high-risk areas of China were collected. Maximum Likelihood tree and haplotype network analyses were conducted to explore the phylogenetic relationship of viruses from high-risk areas of China.ResultsA total of 56,520 cases was reported in China from 2013 to 2016. During this time, Yunnan, Guangdong and Fujian provinces were the high-risk areas. Imported cases occurred almost year-round, and were mainly introduced from Southeast Asia. The first indigenous case usually occurred in June to August, and the last one occurred before December in Yunnan and Fujian provinces but in December in Guangdong Province. Seven genotypes of DENV 1–3 were detected in the high-risk areas, with DENV 1-I the main genotype and DENV 2-Cosmopolitan the secondary one. The Maximum Likelihood trees show that almost all the indigenous viruses separated into different clusters. DENV 1-I viruses were found to be clustered in Guangdong Province, but not in Fujian and Yunnan, from 2013 to 2015. The ancestors of the Guangdong viruses in the cluster in 2013 and 2014 were most closely related to strains from Thailand or Singapore, and the Guangdong virus in 2015 was most closely related to the Guangdong virus of 2014. Based on closest phylogenetic relationships, viruses from Myanmar possibly initiated further indigenous cases in Yunnan, those from Indonesia in Fujian, while viruses from Thailand, Malaysia, Singapore and Indonesia were predominant in Guangdong Province.ConclusionsDengue is still an imported disease in China, although some genotypes continued to circulate in successive years. Viral phylogenies based on the envelope gene suggested periodic introductions of dengue strains into China, primarily from Southeast Asia, with occasional sustained, multi-year transmission in some regions of China.     

Isolation and characterization of dengue virus serotype 2 from the large dengue outbreak in Guangdong,China in 2014

Dengue has been well recognized as a global public health threat,but only sporadic epidemics and imported cases were reported in recent decades in China.Since July 2014,an unexpected large dengue outbreak has occurred in Guangdong province,China,resulting in more than 40000 patients including six deaths.To clarify and characterize the causative agent of this outbreak,the acute phase serum from a patient diagnosed with severe dengue was subjected to virus isolation and high-throughput sequencing(HTS).Traditional real-time RT-PCR and HTS with Ion Torrent PGM detected the presence of dengue virus serotype 2(DENV-2).A clinical DENV-2 isolate GZ05/2014 was obtained by culturing the patient serum in mosquito C6/36 cells.The complete genome of GZ05/2014 was determined and deposited in Gen Bank under the access number KP012546.Phylogenetic analysis based on the complete envelope gene showed that the newly DENV-2 isolate belonged to Cosmopolitan genotype and clustered closely with other Guangdong strains isolated in the past decade.No amino acid mutations that are obviously known to increase virulence or replication were identified throughout the genome of GZ05/2014.The high homology of Guangdong DENV-2 strains indicated the possibility of establishment of local DENV-2 circulation in Guangdong,China.These results help clarify the origin of this epidemic and predict the future status of dengue in China.     

Prevention of Malaria Resurgence in Greece through the Association of Mass Drug Administration (MDA) to Immigrants from Malaria-Endemic Regions and Standard Control Measures

Greece was declared malaria-free in 1974 after a long antimalarial fight. In 2011–2012, an outbreak of P. vivax malaria was reported in Evrotas, an agricultural area in Southern Greece, where a large number of immigrants from endemic countries live and work. A total of 46 locally acquired and 38 imported malaria cases were detected. Despite a significant decrease of the number of malaria cases in 2012, a mass drug administration (MDA) program was considered as an additional measure to prevent reestablishment of the disease in the area. During 2013 and 2014, a combination of 3-day chloroquine and 14-day primaquine treatment was administered under direct observation to immigrants living in the epicenter of the 2011 outbreak in Evrotas. Adverse events were managed and recorded on a daily basis. The control measures implemented since 2011 continued during the period of 2013–2014 as a part of a national integrated malaria control program that included active case detection (ACD), vector control measures and community education. The MDA program was started prior to the transmission periods (from May to December). One thousand ninety four (1094) immigrants successfully completed the treatment, corresponding to 87.3% coverage of the target population. A total of 688 adverse events were recorded in 397 (36.2%, 95% C.I.: 33.4–39.1) persons, the vast majority minor, predominantly dizziness and headache for chloroquine (284 events) and abdominal pain (85 events) for primaquine. A single case of primaquine-induced hemolysis was recorded in a person whose initial G6PD test proved incorrect. No malaria cases were recorded in Evrotas, Laconia, in 2013 and 2014, though three locally acquired malaria cases were recorded in other regions of Greece in 2013. Preventive antimalarial MDA to a high-risk population in a low transmission setting appears to have synergized with the usual antimalarial activities to achieve malaria elimination. This study suggests that judicious use of MDA can be a useful addition to the antimalarial armamentarium in areas threatened with the reintroduction of the disease.     

Dengue Virus 1 in Buenos Aires from 1999 to 2010: Towards Local Spread

Dengue virus (DENV) is a public health problem representing the most important arthropod-borne viral disease in humans. In Argentina, Northern provinces have reported autochthonous cases since 1997, though these outbreaks have originated in bordering countries, where co-circulation of more than one serotype has been reported. In the last decade, imported dengue cases have been reported in Buenos Aires, the urban area of Argentina with the highest population density. In 2009, a dengue outbreak affected Buenos Aires and, for the first time, local transmission was detected. All cases of this outbreak were caused by DENV-1. In this report, we present the full-length sequences of 27 DENV-1 isolates, corresponding to imported cases of 1999–2000, as well as local and imported cases of the 2009 and 2010 outbreaks. We analyzed their phylogenetic and phylodynamic relationships and their global and local spread. Additionally, we characterized their genomic and phenotypic features. All cases belonged to DENV-1 genotype V. The most recent ancestor for this genotype was dated ∼1934, whereas that for the 2009 outbreak was dated ∼2007. The mean rates of nucleotide substitution were 4.98E-4 and 8.53E-4 subs./site/yr, respectively. We inferred an introduction from Paraguay in 1999–2000 and mainly from Venezuela during 2009–2010. Overall, the number of synonymous substitutions per synonymous site significantly exceeded the number of non-synonymous substitutions per site and 12 positively selected sites were detected. These analyses could contribute to a better understanding regarding spread and evolution of this pathogen in the Southern Cone of South America.     

Dengue Sentinel Traveler Surveillance: Monthly and Yearly Notification Trends among Japanese Travelers, 2006–2014

BackgroundDengue is becoming an increasing threat to non-endemic countries. In Japan, the reported number of imported cases has been rising, and the first domestic dengue outbreak in nearly 70 years was confirmed in 2014, highlighting the need for greater situational awareness and better-informed risk assessment.MethodsUsing national disease surveillance data and publically available traveler statistics, we compared monthly and yearly trends in the destination country-specific dengue notification rate per 100,000 Japanese travelers with those of domestic dengue cases in the respective country visited during 2006–2014. Comparisons were made for countries accounting for the majority of importations; yearly comparisons were restricted to countries where respective national surveillance data were publicly available.ResultsThere were 1007 imported Japanese dengue cases (Bali, Indonesia (n = 202), the Philippines (n = 230), Thailand (n = 160), and India (n = 152)). Consistent with historic local dengue seasonality, monthly notification rate among travelers peaked in August in Thailand, September in the Philippines, and in Bali during April with a smaller peak in August. While the number of travelers to Bali was greatest in August, the notification rate was highest in April. Annually, trends in the notification rate among travelers to the Philippines and Thailand also closely reflected local notification trends.ConclusionTravelers to dengue-endemic countries appear to serve as reliable “sentinels”, with the trends in estimated risk of dengue infection among Japanese travelers closely reflecting local dengue trends, both seasonally and annually. Sentinel traveler surveillance can contribute to evidence-based pretravel advice, and help inform risk assessments and decision-making for importation and potentially for subsequent secondary transmission. As our approach takes advantage of traveler data that are readily available as a proxy denominator, sentinel traveler surveillance can be a practical surveillance tool that other countries could consider for implementation.     

The Role of Imported Cases and Favorable Meteorological Conditions in the Onset of Dengue Epidemics

Background

Travelers who acquire dengue infection are often routes for virus transmission to other regions. Nevertheless, the interplay between infected travelers, climate, vectors, and indigenous dengue incidence remains unclear. The role of foreign-origin cases on local dengue epidemics thus has been largely neglected by research. This study investigated the effect of both imported dengue and local meteorological factors on the occurrence of indigenous dengue in Taiwan.

Methods and Principal Findings

Using logistic and Poisson regression models, we analyzed bi-weekly, laboratory-confirmed dengue cases at their onset dates of illness from 1998 to 2007 to identify correlations between indigenous dengue and imported dengue cases (in the context of local meteorological factors) across different time lags. Our results revealed that the occurrence of indigenous dengue was significantly correlated with temporally-lagged cases of imported dengue (2–14 weeks), higher temperatures (6–14 weeks), and lower relative humidity (6–20 weeks). In addition, imported and indigenous dengue cases had a significant quantitative relationship in the onset of local epidemics. However, this relationship became less significant once indigenous epidemics progressed past the initial stage.

Conclusions

These findings imply that imported dengue cases are able to initiate indigenous epidemics when appropriate weather conditions are present. Early detection and case management of imported cases through rapid diagnosis may avert large-scale epidemics of dengue/dengue hemorrhagic fever. The deployment of an early-warning surveillance system, with the capacity to integrate meteorological data, will be an invaluable tool for successful prevention and control of dengue, particularly in non-endemic countries.     

An Explosive Epidemic of DENV-3 in Cairns,Australia

From November 2008-May 2009 Cairns Queensland Australia was struck by an explosive epidemic of DENV-3 that exceeded the capacity of highly skilled dengue control team to control it. We describe the environmental, virological and entomological factors associated with this outbreak to better understand the circumstances leading to its occurrence. Patient interviews, serological results and viral sequencing strongly suggest that the imported index case was infected in Kalimantan, Indonesia. A delay in notification of 27 days from importation of the index case until Queensland Health was notified of dengue transmission allowed the virus to amplify and spread unchecked through November 2008. Unseasonably warm weather, with daily mean temperatures exceeding 30°C, occurred in late November and would have shortened the extrinsic incubation period of the virus and enhanced transmission. Analysis of case movements early in the outbreak indicated that the total incubation period was as low as 9–11 days. This was supported by laboratory vector competence studies that found transmission by Aedes aegypti occurred within 5 days post exposure at 28°C. Effective vector competence rates calculated from these transmission studies indicate that early transmission contributed to the explosive dengue transmission observed in this outbreak. Collections from BG sentinel traps and double sticky ovitraps showed that large populations of the vector Ae. aegypti occurred in the transmission areas from November – December 2008. Finally, the seasonal movement of people around the Christmas holiday season enhanced the spread of DENV-3. These results suggest that a strain of DENV-3 with an unusually rapid transmission cycle was able to outpace vector control efforts, especially those reliant upon delayed action control such as lethal ovitraps.     

Re-assess Vector Indices Threshold as an Early Warning Tool for Predicting Dengue Epidemic in a Dengue Non-endemic Country

BackgroundDespite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic.Conclusion/SignificanceThere was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model.     

The 2012 Madeira Dengue Outbreak: Epidemiological Determinants and Future Epidemic Potential

Dengue, a vector-borne viral disease of increasing global importance, is classically associated with tropical and sub-tropical regions around the world. Urbanisation, globalisation and climate trends, however, are facilitating the geographic spread of its mosquito vectors, thereby increasing the risk of the virus establishing itself in previously unaffected areas and causing large-scale epidemics. On 3 October 2012, two autochthonous dengue infections were reported within the Autonomous Region of Madeira, Portugal. During the following seven months, this first ‘European’ dengue outbreak caused more than 2000 local cases and 81 exported cases to mainland Europe. Here, using an ento-epidemiological mathematical framework, we estimate that the introduction of dengue to Madeira occurred around a month before the first official cases, during the period of maximum influx of airline travel, and that the naturally declining temperatures of autumn were the determining factor for the outbreak''s demise in early December 2012. Using key estimates, together with local climate data, we further propose that there is little support for dengue endemicity on this island, but a high potential for future epidemic outbreaks when seeded between May and August—a period when detection of imported cases is crucial for Madeira''s public health planning.     

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 1^st January, 2005 to 31^st 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.     

Evaluation of the public health risk for autochthonous transmission of mosquito-borne viruses in southern Switzerland

Epidemics of mosquito-borne diseases such as chikungunya and dengue fever are becoming more frequent around the world. In Switzerland, autochthonous cases have not been reported so far, although the presence of the vector Aedes albopictus in urban areas of southern Switzerland increases the risk of indigenous transmissions subsequent to imported cases. In 2018, the potential risk of an outbreak of arboviral diseases was assessed in five municipalities of southern Switzerland. The population abundance of Ae. albopictus was evaluated during the mosquito active season by the mean number of Ae. albopictus bites per day per person (estimated using the human landing collection method) and the risk of outbreak in the case of the introduction of chikungunya, dengue or Zika viruses was estimated. In the five localities investigated, no epidemic risk appeared to be present for any of the arboviruses taken into consideration in the initial months (i.e. mid-May to end of July) of Ae. albopictus activity. In the case of the introduction of chikungunya (mutated or not), dengue (serotype 1) or Zika (African lineage) viruses during mid-end August, an epidemic could have occurred in all the municipalities investigated. In mid-end September, the introduction of same arboviruses could have led to an epidemic in three of the five municipalities investigated.     

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011–2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.