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.     

Optimal Lead Time for Dengue Forecast

Background

A dengue early warning system aims to prevent a dengue outbreak by providing an accurate prediction of a rise in dengue cases and sufficient time to allow timely decisions and preventive measures to be taken by local authorities. This study seeks to identify the optimal lead time for warning of dengue cases in Singapore given the duration required by a local authority to curb an outbreak.

Methodology and Findings

We developed a Poisson regression model to analyze relative risks of dengue cases as functions of weekly mean temperature and cumulative rainfall with lag times of 1–5 months using spline functions. We examined the duration of vector control and cluster management in dengue clusters > = 10 cases from 2000 to 2010 and used the information as an indicative window of the time required to mitigate an outbreak. Finally, we assessed the gap between forecast and successful control to determine the optimal timing for issuing an early warning in the study area. Our findings show that increasing weekly mean temperature and cumulative rainfall precede risks of increasing dengue cases by 4–20 and 8–20 weeks, respectively. These lag times provided a forecast window of 1–5 months based on the observed weather data. Based on previous vector control operations, the time needed to curb dengue outbreaks ranged from 1–3 months with a median duration of 2 months. Thus, a dengue early warning forecast given 3 months ahead of the onset of a probable epidemic would give local authorities sufficient time to mitigate an outbreak.

Conclusions

Optimal timing of a dengue forecast increases the functional value of an early warning system and enhances cost-effectiveness of vector control operations in response to forecasted risks. We emphasize the importance of considering the forecast-mitigation gaps in respective study areas when developing a dengue forecasting model.     

The Prevalence and Endemic Nature of Dengue Infections in Guangdong,South China: An Epidemiological,Serological, and Etiological Study from 2005–2011

Objectives

Frequent outbreaks of dengue are considered to be associated with an increased risk for endemicity of the disease. The occurrence of a large number of indigenous dengue cases in consecutive years indicates the possibility of a changing dengue epidemic pattern in Guangdong, China.

Methods

To have a clear understanding of the current dengue epidemic, a retrospective study of epidemiological profile, serological response, and virological features of dengue infections from 2005–2011 was conducted. Case data were collected from the National Notifiable Infectious Diseases Reporting Network. Serum samples were collected and prepared for serological verification and etiological confirmation. Incidence, temporal and spatial distribution, and the clinical manifestation of dengue infections were analyzed. Pearson''s Chi-Square test was used to compare incidences between different age groups. A seroprevalence survey was implemented in local healthy inhabitants to obtain the overall positive rate for the specific immunoglobulin (Ig) G antibody against dengue virus (DENV).

Results

The overall annual incidence rate was 1.87/100000. A significant difference was found in age-specific incidence (Pearson''s Chi-Square value 498.008, P<0.001). Children under 5 years of age had the lowest incidence of 0.28/100000. The vast majority of cases presented with a mild manifestation typical to dengue fever. The overall seroprevalence of dengue IgG antibody in local populations was 2.43% (range 0.28%–5.42%). DENV-1 was the predominant serotype in circulation through the years, while all 4 serotypes were identified in indigenous patients from different outbreak localities since 2009.

Conclusions

A gradual change in the epidemic pattern of dengue infection has been observed in recent years in Guangdong. With the endemic nature of dengue infections, the transition from a monotypic to a multitypic circulation of dengue virus in the last several years will have an important bearing on the prevention and control of dengue in the province and in the neighboring districts.     

Dengue Surveillance in Veterans Affairs Healthcare Facilities, 2007–2010

Background

Although dengue is endemic in Puerto Rico (PR), 2007 and 2010 were recognized as epidemic years. In the continental United States (US), outside of the Texas-Mexico border, there had not been a dengue outbreak since 1946 until dengue re-emerged in Key West, Florida (FL), in 2009–2010. The objective of this study was to use electronic and manual surveillance systems to identify dengue cases in Veterans Affairs (VA) healthcare facilities and then to clinically compare dengue cases in Veterans presenting for care in PR and in FL.

Methodology

Outpatient encounters from 1/2007–12/2010 and inpatient admissions (only available from 10/2009–12/2010) with dengue diagnostic codes at all VA facilities were identified using VA''s Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE). Additional case sources included VA data from Centers for Disease Control and Prevention BioSense and VA infection preventionists. Case reviews were performed. Categorical data was compared using Mantel-Haenszel or Fisher Exact tests and continuous variables using t-tests. Dengue case residence was mapped.

Findings

Two hundred eighty-eight and 21 PR and FL dengue cases respectively were identified. Of 21 FL cases, 12 were exposed in Key West and 9 were imported. During epidemic years, FL cases had significantly increased dengue testing and intensive care admissions, but lower hospitalization rates and headache or eye pain symptoms compared to PR cases. There were no significant differences in clinical symptoms, laboratory abnormalities or outcomes between epidemic and non-epidemic year cases in FL and PR. Confirmed/probable cases were significantly more likely to be hospitalized and have thrombocytopenia or leukopenia compared to suspected cases.

Conclusions

Dengue re-introduction in the continental US warrants increased dengue surveillance and education in VA. Throughout VA, under-testing of suspected cases highlights the need to emphasize use of diagnostic testing to better understand the magnitude of dengue among Veterans.     

Dengue Dynamics in Binh Thuan Province,Southern Vietnam: Periodicity,Synchronicity and Climate Variability

Background

Dengue is a major global public health problem with increasing incidence and geographic spread. The epidemiology is complex with long inter-epidemic intervals and endemic with seasonal fluctuations. This study was initiated to investigate dengue transmission dynamics in Binh Thuan province, southern Vietnam.

Methodology

Wavelet analyses were performed on time series of monthly notified dengue cases from January 1994 to June 2009 (i) to detect and quantify dengue periodicity, (ii) to describe synchrony patterns in both time and space, (iii) to investigate the spatio-temporal waves and (iv) to associate the relationship between dengue incidence and El Niño-Southern Oscillation (ENSO) indices in Binh Thuan province, southern Vietnam.

Principal Findings

We demonstrate a continuous annual mode of oscillation and a multi-annual cycle of around 2–3-years was solely observed from 1996–2001. Synchrony in time and between districts was detected for both the annual and 2–3-year cycle. Phase differences used to describe the spatio-temporal patterns suggested that the seasonal wave of infection was either synchronous among all districts or moving away from Phan Thiet district. The 2–3-year periodic wave was moving towards, rather than away from Phan Thiet district. A strong non-stationary association between ENSO indices and climate variables with dengue incidence in the 2–3-year periodic band was found.

Conclusions

A multi-annual mode of oscillation was observed and these 2–3-year waves of infection probably started outside Binh Thuan province. Associations with climatic variables were observed with dengue incidence. Here, we have provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam.     

International Dispersal of Dengue through Air Travel: Importation Risk for Europe

Background

The worldwide distribution of dengue is expanding, in part due to globalized traffic and trade. Aedes albopictus is a competent vector for dengue viruses (DENV) and is now established in numerous regions of Europe. Viremic travellers arriving in Europe from dengue-affected areas of the world can become catalysts of local outbreaks in Europe. Local dengue transmission in Europe is extremely rare, and the last outbreak occurred in 1927–28 in Greece. However, autochthonous transmission was reported from France in September 2010, and from Croatia between August and October 2010.

Methodology

We compiled data on areas affected by dengue in 2010 from web resources and surveillance reports, and collected national dengue importation data. We developed a hierarchical regression model to quantify the relationship between the number of reported dengue cases imported into Europe and the volume of airline travellers arriving from dengue-affected areas internationally.

Principal Findings

In 2010, over 5.8 million airline travellers entered Europe from dengue-affected areas worldwide, of which 703,396 arrived at 36 airports situated in areas where Ae. albopictus has been recorded. The adjusted incidence rate ratio for imported dengue into European countries was 1.09 (95% CI: 1.01–1.17) for every increase of 10,000 travellers; in August, September, and October the rate ratios were 1.70 (95%CI: 1.23–2.35), 1.46 (95%CI: 1.02–2.10), and 1.35 (95%CI: 1.01–1.81), respectively. Two Italian cities where the vector is present received over 50% of all travellers from dengue-affected areas, yet with the continuing vector expansion more cities will be implicated in the future. In fact, 38% more travellers arrived in 2013 into those parts of Europe where Ae. albopictus has recently been introduced, compared to 2010.

Conclusions

The highest risk of dengue importation in 2010 was restricted to three months and can be ranked according to arriving traveller volume from dengue-affected areas into cities where the vector is present. The presence of the vector is a necessary, but not sufficient, prerequisite for DENV onward transmission, which depends on a number of additional factors. However, our empirical model can provide spatio-temporal elements to public health interventions.     

Discriminating Malaria from Dengue Fever in Endemic Areas: Clinical and Biological Criteria,Prognostic Score and Utility of the C-Reactive Protein: A Retrospective Matched-Pair Study in French Guiana

Background

Dengue and malaria are two major public health concerns in tropical settings. Although the pathogeneses of these two arthropod-borne diseases differ, their clinical and biological presentations are unspecific. During dengue epidemics, several hundred patients with fever and diffuse pain are weekly admitted at the emergency room. It is difficult to discriminate them from patients presenting malaria attacks. Furthermore, it may be impossible to provide a parasitological microscopic examination for all patients. This study aimed to establish a diagnostic algorithm for communities where dengue fever and malaria occur at some frequency in adults.

Methodology/Principal Findings

A sub-study using the control groups of a case-control study in French Guiana – originally designed to compare dengue and malaria co-infected cases to single infected cases – was performed between 2004 and 2010. In brief, 208 patients with malaria matched to 208 patients with dengue fever were compared in the present study. A predictive score of malaria versus dengue was established using .632 bootstrap procedures. Multivariate analysis showed that male gender, age, tachycardia, anemia, thrombocytopenia, and CRP>5 mg/l were independently associated with malaria. The predictive score using those variables had an AUC of 0.86 (95%CI: 0.82–0.89), and the CRP was the preponderant predictive factor. The sensitivity and specificity of CRP>5 mg/L to discriminate malaria from dengue were of 0.995 (95%CI: 0.991–1) and 0.35 (95%CI 0.32–0.39), respectively.

Conclusions/Significance

The clinical and biological score performed relatively well for discriminating cases of dengue versus malaria. Moreover, using only the CRP level turned to be a useful biomarker to discriminate feverish patients at low risk of malaria in an area where both infections exist. It would avoid more than 33% of unnecessary parasitological examinations with a very low risk of missing a malaria attack.     

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.     

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.     

Climate Variability and Nonstationary Dynamics of Mycoplasma pneumoniae Pneumonia in Japan

Background

A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae) pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales.

Methods

We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO).

Results

Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1–2-year periodic mode in 2005–2007 and 2010–2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics.

Conclusions

Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.     

Allergies and Diabetes as Risk Factors for Dengue Hemorrhagic Fever: Results of a Case Control Study

Background

The physiopathology of dengue hemorrhagic fever (DHF), a severe form of Dengue Fever, is poorly understood. We are unable to identify patients likely to progress to DHF for closer monitoring and early intervention during epidemics, so most cases are sent home. This study explored whether patients with selected co-morbidities are at higher risk of developing DHF.

Methods

A matched case-control study was conducted in a dengue sero-positive population in two Brazilian cities. For each case of DHF, 7 sero-positive controls were selected. Cases and controls were interviewed and information collected on demographic and socio-economic status, reported co-morbidities (diabetes, hypertension, allergy) and use of medication. Conditional logistic regression was used to calculate the strength of the association between the co-morbidities and occurrence of DHF.

Results

170 cases of DHF and 1,175 controls were included. Significant associations were found between DHF and white ethnicity (OR = 4.70; 2.17–10.20), high income (OR = 6.84; 4.09–11.43), high education (OR = 4.67; 2.35–9.27), reported diabetes (OR = 2.75; 1.12–6.73) and reported allergy treated with steroids (OR = 2.94; 1.01–8.54). Black individuals who reported being treated for hypertension had 13 times higher risk of DHF then black individuals reporting no hypertension.

Conclusions

This is the first study to find an association between DHF and diabetes, allergy and hypertension. Given the high case fatality rate of DHF (1–5%), we believe that the evidence produced in this study, when confirmed in other studies, suggests that screening criteria might be used to identify adult patients at a greater risk of developing DHF with a recommendation that they remain under observation and monitoring in hospital.     

Predictive Tools for Severe Dengue Conforming to World Health Organization 2009 Criteria

Background

Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking.

Methods

We undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs).

Principal findings

Predictive tools compatible with well-resourced and resource-limited settings – not requiring laboratory measurements – performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27–47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD.

Conclusions

The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes.     

Can Human Movements Explain Heterogeneous Propagation of Dengue Fever in Cambodia?

Background

Determining the factors underlying the long-range spatial spread of infectious diseases is a key issue regarding their control. Dengue is the most important arboviral disease worldwide and a major public health problem in tropical areas. However the determinants shaping its dynamics at a national scale remain poorly understood. Here we describe the spatial-temporal pattern of propagation of annual epidemics in Cambodia and discuss the role that human movements play in the observed pattern.

Methods and Findings

We used wavelet phase analysis to analyse time-series data of 105,598 hospitalized cases reported between 2002 and 2008 in the 135 (/180) most populous districts in Cambodia. We reveal spatial heterogeneity in the propagation of the annual epidemic. Each year, epidemics are highly synchronous over a large geographic area along the busiest national road of the country whereas travelling waves emanate from a few rural areas and move slowly along the Mekong River at a speed of ∼11 km per week (95% confidence interval 3–18 km per week) towards the capital, Phnom Penh.

Conclusions

We suggest human movements – using roads as a surrogate – play a major role in the spread of dengue fever at a national scale. These findings constitute a new starting point in the understanding of the processes driving dengue spread.     

Imported Dengue Cases,Weather Variation and Autochthonous Dengue Incidence in Cairns,Australia

Background

Dengue fever (DF) outbreaks often arise from imported DF cases in Cairns, Australia. Few studies have incorporated imported DF cases in the estimation of the relationship between weather variability and incidence of autochthonous DF. The study aimed to examine the impact of weather variability on autochthonous DF infection after accounting for imported DF cases and then to explore the possibility of developing an empirical forecast system.

Methodology/principal finds

Data on weather variables, notified DF cases (including those acquired locally and overseas), and population size in Cairns were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics. A time-series negative-binomial hurdle model was used to assess the effects of imported DF cases and weather variability on autochthonous DF incidence. Our results showed that monthly autochthonous DF incidences were significantly associated with monthly imported DF cases (Relative Risk (RR):1.52; 95% confidence interval (CI): 1.01–2.28), monthly minimum temperature (^oC) (RR: 2.28; 95% CI: 1.77–2.93), monthly relative humidity (%) (RR: 1.21; 95% CI: 1.06–1.37), monthly rainfall (mm) (RR: 0.50; 95% CI: 0.31–0.81) and monthly standard deviation of daily relative humidity (%) (RR: 1.27; 95% CI: 1.08–1.50). In the zero hurdle component, the occurrence of monthly autochthonous DF cases was significantly associated with monthly minimum temperature (Odds Ratio (OR): 1.64; 95% CI: 1.01–2.67).

Conclusions/significance

Our research suggested that incidences of monthly autochthonous DF were strongly positively associated with monthly imported DF cases, local minimum temperature and inter-month relative humidity variability in Cairns. Moreover, DF outbreak in Cairns was driven by imported DF cases only under favourable seasons and weather conditions in the study.     

Effectiveness of the Viet Nam Produced,Mouse Brain-Derived,Inactivated Japanese Encephalitis Vaccine in Northern Viet Nam

Background

Japanese encephalitis (JE) is a flaviviral disease of public health concern in many parts of Asia. JE often occurs in large epidemics, has a high case-fatality ratio and, among survivors, frequently causes persistent neurological sequelae and mental disabilities. In 1997, the Vietnamese government initiated immunization campaigns targeting all children aged 1–5 years. Three doses of a locally-produced, mouse brain-derived, inactivated JE vaccine (MBV) were given. This study aims at evaluating the effectiveness of Viet Nam''s MBV.

Methodology

A matched case-control study was conducted in Northern Viet Nam. Cases were identified through an ongoing hospital-based surveillance. Each case was matched to four healthy controls for age, gender, and neighborhood. The vaccination history was ascertained through JE immunization logbooks maintained at local health centers.

Principal Findings

Thirty cases and 120 controls were enrolled. The effectiveness of the JE vaccine was 92.9% [95% CI: 66.6–98.5]. Confounding effects of other risk variables were not observed.

Conclusions

Our results strongly suggest that the locally-produced JE-MBV given to 1–5 years old Vietnamese children was efficacious.     

Risk of Dengue for Tourists and Teams during the World Cup 2014 in Brazil

Background

This year, Brazil will host about 600,000 foreign visitors during the 2014 FIFA World Cup. The concern of possible dengue transmission during this event has been raised given the high transmission rates reported in the past by this country.

Methodology/Principal Findings

We used dengue incidence rates reported by each host city during previous years (2001–2013) to estimate the risk of dengue during the World Cup for tourists and teams. Two statistical models were used: a percentile rank (PR) and an Empirical Bayes (EB) model. Expected IR''s during the games were generally low (<10/100,000) but predictions varied across locations and between models. Based on current ticket allocations, the mean number of expected symptomatic dengue cases ranged from 26 (PR, 10^th–100^th percentile: 5–334 cases) to 59 (EB, 95% credible interval: 30–77 cases) among foreign tourists but none are expected among teams. These numbers will highly depend on actual travel schedules and dengue immunity among visitors. Sensitivity analysis for both models indicated that the expected number of cases could be as low as 4 or 5 with 100,000 visitors and as high as 38 or 70 with 800,000 visitors (PR and EB, respectively).

Conclusion/Significance

The risk of dengue among tourists during the World Cup is expected to be small due to immunity among the Brazil host population provided by last year''s epidemic with the same DENV serotypes. Quantitative risk estimates by different groups and methodologies should be made routinely for mass gathering events.     

Long-Term and Seasonal Dynamics of Dengue in Iquitos,Peru

Introduction

Long-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world''s population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data.

Methods

We studied 10 years (2000–2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases.

Findings

Transmission was dominated by single serotypes, first DENV-3 (2001–2007) then DENV-4 (2008–2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season.

Conclusions

Dengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos.     

Do Intensive Care Data on Respiratory Infections Reflect Influenza Epidemics?

Objectives

Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics.

Methods

We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003–2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI.

Results

Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51.

Conclusions

ICU data was associated with ILI activity, with increases in ICU data often occurring earlier and for a longer time period. However, in the Netherlands, predicting influenza epidemics in the general population using ICU data was imprecise, with low positive predictive values and sensitivities.     

Use of saliva for early dengue diagnosis

Background

The necessity of a venous blood collection in all dengue diagnostic assays and the high cost of tests that are available for testing during the viraemic period hinder early detection of dengue cases and thus could delay cluster management. This study reports the utility of saliva in an assay that detects dengue virus (DENV)–specific immunoglobulin A (Ig A) early in the phase of a dengue infection.

Methods and Findings

Using an antigen capture anti-DENV IgA (ACA) ELISA technique, we tested saliva samples collected from dengue-confirmed patients. The sensitivity within 3 days from fever onset was over 36% in primary dengue infections. The performance is markedly better in secondary infections, with 100% sensitivity reported in saliva samples from day 1 after fever onset. Serum and salivary IgA levels showed good correlation (Pearson''s r = 0.69, p<0.001). Specificity was found to be 97%.

Conclusion

Our findings suggest that this technique would be very useful in dengue endemic regions, where the majority of dengue cases are secondary. The ACA-ELISA is easy to perform, cost effective, and especially useful in laboratories without sophisticated equipment. Our findings established the usefulness and reliability of saliva for early dengue diagnosis.