The impact of COVID–19 lockdown on dengue transmission in Sri Lanka; A natural experiment for understanding the influence of human mobility

BackgroundDengue is one of the major public health problems in Sri Lanka. Its outbreak pattern depends on a multitude of drivers, including human mobility. Here we evaluate the impact of COVID–19 related mobility restriction (lockdown) on the risk of dengue in Sri Lanka.MethodologyTwo-stage hierarchical models were fitted using an interrupted time-series design based on the notified dengue cases, January 2015 to July 2020. In the first stage model, the district level impact was estimated using quasi-Poisson regression models while accounting for temporal trends. Estimates were pooled at zonal and national levels in the second stage model using meta-analysis. The influence of the extended period of school closure on dengue in children in the western province was compared to adults.FindingsStatistically significant and homogeneous reduction of dengue risk was observed at all levels during the lockdown. Overall an 88% reduction in risk (RR 0.12; 95% CI from 0.08 to 0.17) was observed at the national level. The highest impact was observed among children aged less than 19 years showing a 92% reduction (RR 0.8; 95% CI from 0.03 to 0.25). We observed higher impact in the dry zone having 91% reduction (RR 0.09; 95% CI from 0.05 to 0.15) compared to wet zone showing 83% reduction (RR 0.17; 95% CI from 0.09 to 0.30). There was no indication that the overall health-seeking behaviour for dengue had a substantial influence on these estimates.SignificanceThis study offers a broad understanding of the change in risk of dengue during the COVID–19 pandemic and associated mobility restrictions in Sri Lanka. The analysis using the mobility restrictions as a natural experiment suggests mobility patterns to be a very important driver of dengue transmission.     

Rapid testing requires clinical evaluation for accurate diagnosis of dengue disease: A passive surveillance study in Southern Malaysia

BackgroundDengue fever is the most common mosquito-borne infection worldwide where an expanding surveillance and characterization of this infection are needed to better inform the healthcare system. In this surveillance-based study, we explored the prevalence and distinguishing features of dengue fever amongst febrile patients in a large community-based health facility in southern peninsular Malaysia.MethodsOver six months in 2018, we recruited 368 adults who met the WHO 2009 criteria for probable dengue infection. They underwent the following blood tests: full blood count, dengue virus (DENV) rapid diagnostic test (RDT), ELISA (dengue IgM and IgG), nested RT-PCR for dengue, multiplex qRT-PCR for Zika, Chikungunya and dengue as well as PCR tests for Leptopspira spp., Japanese encephalitis and West Nile virus.ResultsLaboratory-confirmed dengue infections (defined by positive tests in NS1, IgM, high-titre IgG or nested RT-PCR) were found in 167 (45.4%) patients. Of these 167 dengue patients, only 104 (62.3%) were positive on rapid diagnostic testing. Dengue infection was significantly associated with the following features: family or neighbours with dengue in the past week (AOR: 3.59, 95% CI:2.14–6.00, p<0.001), cutaneous rash (AOR: 3.58, 95% CI:1.77–7.23, p<0.001), increased temperature (AOR: 1.33, 95% CI:1.04–1.70, p = 0.021), leucopenia (white cell count < 4,000/μL) (AOR: 3.44, 95% CI:1.72–6.89, p<0.001) and thrombocytopenia (platelet count <150,000/μL)(AOR: 4.63, 95% CI:2.33–9.21, p<0.001). Dengue infection was negatively associated with runny nose (AOR: 0.47, 95% CI:0.29–0.78, p = 0.003) and arthralgia (AOR: 0.42, 95% CI:0.24–0.75, p = 0.004). Serotyping by nested RT-PCR revealed mostly mono-infections with DENV-2 (n = 64), DENV-1 (n = 32) and DENV-3 (n = 17); 14 co-infections occurred with DENV-1/DENV-2 (n = 13) and DENV-1/DENV-4 (n = 1). Besides dengue, none of the pathogens above were found in patients’ serum.ConclusionsAcute undifferentiated febrile infections are a diagnostic challenge for community-based clinicians. Rapid diagnostic tests are increasingly used to diagnose dengue infection but negative tests should be interpreted with caution as they fail to detect a considerable proportion of dengue infection. Certain clinical features and haematological parameters are important in the clinical diagnosis of dengue infection.     

Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles

BackgroundWith enough advanced notice, dengue outbreaks can be mitigated. As a climate-sensitive disease, environmental conditions and past patterns of dengue can be used to make predictions about future outbreak risk. These predictions improve public health planning and decision-making to ultimately reduce the burden of disease. Past approaches to dengue forecasting have used seasonal climate forecasts, but the predictive ability of a system using different lead times in a year-round prediction system has been seldom explored. Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare.Methods and findingsWe introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. Bayesian spatiotemporal models were fit to 19 years (2002–2020) of dengue data at the province level across Vietnam. A superensemble of these models then makes probabilistic predictions of dengue incidence at various future time points aligned with key Vietnamese decision and planning deadlines. We demonstrate that the superensemble generates more accurate predictions of dengue incidence than the individual models it incorporates across a suite of time horizons and transmission settings. Using historical data, the superensemble made slightly more accurate predictions (continuous rank probability score [CRPS] = 66.8, 95% CI 60.6–148.0) than a baseline model which forecasts the same incidence rate every month (CRPS = 79.4, 95% CI 78.5–80.5) at lead times of 1 to 3 months, albeit with larger uncertainty. The outbreak detection capability of the superensemble was considerably larger (69%) than that of the baseline model (54.5%). Predictions were most accurate in southern Vietnam, an area that experiences semi-regular seasonal dengue transmission. The system also demonstrated added value across multiple areas compared to previous practice of not using a forecast. We use the system to make a prospective prediction for dengue incidence in Vietnam for the period May to October 2020. Prospective predictions made with the superensemble were slightly more accurate (CRPS = 110, 95% CI 102–575) than those made with the baseline model (CRPS = 125, 95% CI 120–168) but had larger uncertainty. Finally, we propose a framework for the evaluation of probabilistic predictions. Despite the demonstrated value of our forecasting system, the approach is limited by the consistency of the dengue case data, as well as the lack of publicly available, continuous, and long-term data sets on mosquito control efforts and serotype-specific case data.ConclusionsThis study shows that by combining detailed Earth observation data, seasonal climate forecasts, and state-of-the-art models, dengue outbreaks can be predicted across a broad range of settings, with enough lead time to meaningfully inform dengue control. While our system omits some important variables not currently available at a subnational scale, the majority of past outbreaks could be predicted up to 3 months ahead. Over the next 2 years, the system will be prospectively evaluated and, if successful, potentially extended to other areas and other climate-sensitive disease systems.     

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.     

Major acute cardiovascular events after dengue infection–A population-based observational study

BackgroundDengue virus (DENV) infection may be associated with increased risks of major adverse cardiovascular effect (MACE), but a large-scale study evaluating the association between DENV infection and MACEs is still lacking.Methods and findingsAll laboratory confirmed dengue cases in Taiwan during 2009 and 2015 were included by CDC notifiable database. The self-controlled case-series design was used to evaluate the association between DENV infection and MACE (including acute myocardial infarction [AMI], heart failure and stroke). The "risk interval" was defined as the first 7 days after the diagnosis of DENV infection and the "control interval" as 1 year before and 1 year after the risk interval. The incidence rate ratio (IRR) and 95% confidence interval (CI) for MACE were estimated by conditional Poisson regression. Finally, the primary outcome of the incidence of MACEs within one year of dengue was observed in 1,247 patients. The IRR of MACEs was 17.9 (95% CI 15.80–20.37) during the first week after the onset of DENV infection observed from 1,244 eligible patients. IRR were significantly higher for hemorrhagic stroke (10.9, 95% CI 6.80–17.49), ischemic stroke (15.56, 95% CI 12.44–19.47), AMI (13.53, 95% CI 10.13–18.06), and heart failure (27.24, 95% CI 22.67–32.73). No increased IRR was observed after day 14.ConclusionsThe risks for MACEs are significantly higher in the immediate time period after dengue infection. Since dengue infection is potentially preventable by early recognition and vaccination, the dengue-associated MACE should be taken into consideration when making public health management policies.     

Multiyear Climate Variability and Dengue—El Ni?o Southern Oscillation,Weather, and Dengue Incidence in Puerto Rico,Mexico, and Thailand: A Longitudinal Data Analysis

Background

The mosquito-borne dengue viruses are a major public health problem throughout the tropical and subtropical regions of the world. Changes in temperature and precipitation have well-defined roles in the transmission cycle and may thus play a role in changing incidence levels. The El Niño Southern Oscillation (ENSO) is a multiyear climate driver of local temperature and precipitation worldwide. Previous studies have reported varying degrees of association between ENSO and dengue incidence.

Methods and Findings

We analyzed the relationship between ENSO, local weather, and dengue incidence in Puerto Rico, Mexico, and Thailand using wavelet analysis to identify time- and frequency-specific association. In Puerto Rico, ENSO was transiently associated with temperature and dengue incidence on multiyear scales. However, only local precipitation and not temperature was associated with dengue on multiyear scales. In Thailand, ENSO was associated with both temperature and precipitation. Although precipitation was associated with dengue incidence, the association was nonstationary and likely spurious. In Mexico, no association between any of the variables was observed on the multiyear scale.

Conclusions

The evidence for a relationship between ENSO, climate, and dengue incidence presented here is weak. While multiyear climate variability may play a role in endemic interannual dengue dynamics, we did not find evidence of a strong, consistent relationship in any of the study areas. The role of ENSO may be obscured by local climate heterogeneity, insufficient data, randomly coincident outbreaks, and other, potentially stronger, intrinsic factors regulating transmission dynamics. Please see later in the article for the Editors'' Summary     

The performance of the SD BIOLINE Dengue DUO? rapid immunochromatographic test kit for the detection of NS1 antigen,IgM and IgG antibodies during a dengue type 1 epidemic in Jamaica

Background

Dengue is an important mosquito-borne viral infection that affects millions of persons worldwide. Early diagnosis is necessary to effect appropriate management and decrease mortality. Immunochromatographic tests are advantageous in producing dengue test results within 30 min but these results should be sensitive and specific. In this study we evaluated the diagnostic performance of the SD BIOLINE Dengue DUO® rapid immunochromatographic test kit. A panel of 309 dengue and 30 non-dengue single serum samples characterized by using reference enzyme-linked immunosorbent assays (ELISAs) was used. These samples were received in the virology laboratory for routine testing during a dengue type 1 outbreak between October to December, 2012.

Results

The overall diagnostic sensitivities of the SD BIOLINE Dengue DUO® rapid testfor IgM, IgG and NSI were 49.3 % (95 % CI: 41.3-57.4), 39.1 % (95 % CI: 33.3-45.2) and 90 % (95 % CI: 82.1-94.7), respectively. The IgM and IgG detection rates were significantly lower than that of the NSI (p < 0.001). However the combination of the IgM detection with NS1 detection or both NS1 and IgG resulted in a significant (p < 0.001) increase in sensitivity to 97.5 % (95 % CI: 92.9-99.2) and 98.9 % (95 % CI: 96.0-99.7), respectively. These higher sensitivities were achieved without any decrease in specificities.

Conclusions

This study revealed that combining two or more parameters of the SD BIOLINE Dengue DUO® rapid kit significantly improved the sensitivity of diagnosis of dengue virus infection and supports its usefulness in the Jamaican setting.     

Developing a Social Autopsy Tool for Dengue Mortality: A Pilot Study

BackgroundDengue fever is a public health problem in the tropical and sub-tropical world. Dengue cases have grown dramatically in recent years as well as dengue mortality. Colombia has experienced periodic dengue outbreaks with numerous dengue related-deaths, where the Santander department has been particularly affected. Although social determinants of health (SDH) shape health outcomes, including mortality, it is not yet understood how these affect dengue mortality. The aim of this pilot study was to develop and pre-test a social autopsy (SA) tool for dengue mortality.ConclusionsThe SA tool is based on the scientific literature, a validated conceptual framework, researchers’ and health professionals’ expertise, and a pilot study. It is the first time that a SA tool has been created for the dengue mortality context. Our work furthers the study on SDH and how these are applied to neglected tropical diseases, like dengue. This tool could be integrated in surveillance systems to provide complementary information on the modifiable and avoidable death-related factors and therefore, be able to formulate interventions for dengue mortality reduction.     

Diagnostic accuracy of the WHO clinical definitions for dengue and implications for surveillance: A systematic review and meta-analysis

BackgroundDengue is the world’s most common mosquito-borne virus but remains diagnostically challenging due to its nonspecific presentation. Access to laboratory confirmation is limited and thus most reported figures are based on clinical diagnosis alone, the accuracy of which is uncertain. This systematic review assesses the diagnostic accuracy of the traditional (1997) and revised (2009) WHO clinical case definitions for dengue fever, the basis for most national guidelines.Methodology/Principal findingsPubMed, EMBASE, Scopus, OpenGrey, and the annual Dengue Bulletin were searched for studies assessing the diagnostic accuracy of the unmodified clinical criteria. Two reviewers (NR/SL) independently assessed eligibility, extracted data, and evaluated risk of bias using a modified QUADAS-2. Additional records were found by citation network analysis. A meta-analysis was done using a bivariate mixed-effects regression model. Studies that modified criteria were analysed separately. This systematic review protocol was registered on PROSPERO (CRD42020165998). We identified 11 and 12 datasets assessing the 1997 and 2009 definition, respectively, and 6 using modified criteria. Sensitivity was 93% (95% CI: 77–98) and 93% (95% CI: 86–96) for the 1997 and 2009 definitions, respectively. Specificity was 29% (95% CI: 8–65) and 31% (95% CI: 18–48) for the 1997 and 2009 definitions, respectively. Diagnostic performance suffered at the extremes of age. No modification significantly improved accuracy.Conclusions/SignificanceDiagnostic accuracy of clinical criteria is poor, with significant implications for surveillance and public health responses for dengue control. As the basis for most reported figures, this has relevance to policymakers planning resource allocation and researchers modelling transmission, particularly during COVID-19.     

Estimating the Burden of Leptospirosis among Febrile Subjects Aged below 20 Years in Kampong Cham Communities,Cambodia, 2007-2009

BackgroundLeptospirosis is an emerging but neglected public health challenge in the Asia/Pacific Region with an annual incidence estimated at 10–100 per 100,000 population. No accurate data, however, are available for at-risk rural Cambodian communities.MethodWe conducted anonymous, unlinked testing for IgM antibodies to Leptospira spp. on paired sera of Cambodian patients <20 years of age between 2007–2009 collected through active, community-based surveillance for febrile illnesses in a convenience sample of 27 rural and semi-rural villages in four districts of Kampong Cham province, Cambodia. Leptospirosis testing was done on paired serological samples negative for Dengue, Japanese encephalitis and Chikungunya viruses after random selection. Convalescent samples found positive while initial samples were negative were considered as proof of acute infection. We then applied a mathematical model to estimate the risk of fever caused by leptospirosis, dengue or other causes in rural Cambodia.ResultsA total of 630 samples are coming from a randomly selected subset of 2358 samples. IgM positive were found on the convalescent serum sample, among which 100 (15.8%) samples were IgM negative on an earlier sample. Seventeen of these 100 seroconversions were confirmed using a Microagglutination Test. We estimated the probability of having a fever due to leptospirosis at 1. 03% (95% Credible Interval CI: 0. 95%–1. 22%) per semester. In comparison, this probability was 2. 61% (95% CI: 2. 55%, 2. 83%) for dengue and 17. 65% (95% CI: 17. 49%, 18. 08%) for other causes.ConclusionOur data from febrile cases aged below 20 years suggest that the burden of leptospirosis is high in rural Cambodian communities. This is especially true during the rainy season, even in the absence of identified epidemics.     

Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City,northeastern China, 2007–2018

BackgroundHemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS.ObjectiveHuludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City.MethodsOur researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors.ResultsDuring the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5^th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5^th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5^th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5^th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level.ConclusionsOur study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.     

Characteristics of a Dengue Outbreak in a Remote Pacific Island Chain – Republic of the Marshall Islands, 2011–2012

Dengue is a potentially fatal acute febrile illness caused by four mosquito-transmitted dengue viruses (DENV-1–4). Although dengue outbreaks regularly occur in many regions of the Pacific, little is known about dengue in the Republic of the Marshall Islands (RMI). To better understand dengue in RMI, we investigated an explosive outbreak that began in October 2011. Suspected cases were reported to the Ministry of Health, serum specimens were tested with a dengue rapid diagnostic test (RDT), and confirmatory testing was performed using RT-PCR and IgM ELISA. Laboratory-positive cases were defined by detection of DENV nonstructural protein 1 by RDT, DENV nucleic acid by RT-PCR, or anti-DENV IgM antibody by RDT or ELISA. Secondary infection was defined by detection of anti-DENV IgG antibody by ELISA in a laboratory-positive acute specimen. During the four months of the outbreak, 1,603 suspected dengue cases (3% of the RMI population) were reported. Of 867 (54%) laboratory-positive cases, 209 (24%) had dengue with warning signs, six (0.7%) had severe dengue, and none died. Dengue incidence was highest in residents of Majuro and individuals aged 10–29 years, and ∼95% of dengue cases were experiencing secondary infection. Only DENV-4 was detected by RT-PCR, which phylogenetic analysis demonstrated was most closely related to a virus previously identified in Southeast Asia. Cases of vertical DENV transmission, and DENV/Salmonella Typhi and DENV/Mycobacterium leprae co-infection were identified. Entomological surveys implicated water storage containers and discarded tires as the most important development sites for Aedes aegypti and Ae. albopictus, respectively. Although this is the first documented dengue outbreak in RMI, the age groups of cases and high prevalence of secondary infection demonstrate prior DENV circulation. Dengue surveillance should continue to be strengthened in RMI and throughout the Pacific to identify and rapidly respond to future outbreaks.     

Anomalously warm weather and acute care visits in patients with multiple sclerosis: A retrospective study of privately insured individuals in the US

BackgroundAs the global climate changes in response to anthropogenic greenhouse gas emissions, weather and temperature are expected to become increasingly variable. Although heat sensitivity is a recognized clinical feature of multiple sclerosis (MS), a chronic demyelinating disorder of the central nervous system, few studies have examined the implications of climate change for patients with this disease.Methods and findingsWe conducted a retrospective cohort study of individuals with MS ages 18–64 years in a nationwide United States patient-level commercial and Medicare Advantage claims database from 2003 to 2017. We defined anomalously warm weather as any month in which local average temperatures exceeded the long-term average by ≥1.5°C. We estimated the association between anomalously warm weather and MS-related inpatient, outpatient, and emergency department visits using generalized log-linear models. From 75,395,334 individuals, we identified 106,225 with MS. The majority were women (76.6%) aged 36–55 years (59.0%). Anomalously warm weather was associated with increased risk for emergency department visits (risk ratio [RR] = 1.043, 95% CI: 1.025–1.063) and inpatient visits (RR = 1.032, 95% CI: 1.010–1.054). There was limited evidence of an association between anomalously warm weather and MS-related outpatient visits (RR = 1.010, 95% CI: 1.005–1.015). Estimates were similar for men and women, strongest among older individuals, and exhibited substantial variation by season, region, and climate zone. Limitations of the present study include the absence of key individual-level measures of socioeconomic position (i.e., race/ethnicity, occupational status, and housing quality) that may determine where individuals live—and therefore the extent of their exposure to anomalously warm weather—as well as their propensity to seek treatment for neurologic symptoms.ConclusionsOur findings suggest that as global temperatures rise, individuals with MS may represent a particularly susceptible subpopulation, a finding with implications for both healthcare providers and systems.     

Short Report: Adult Aedes abundance and risk of dengue transmission

Dengue is transmitted mainly by the adult female Aedes aegypti mosquito. However, little is known about the impact of adult Aedes abundance on the risk of dengue transmission. Here we analysed nationally representative dengue case and vector surveillance data collected from Singapore, to determine the effect of adult Aedes abundance on the risk of dengue transmission. A case was an area with active dengue transmission as indicated by the presence of dengue cluster. A control was an area where no dengue cluster was reported. Using multivariate logistic regression, we analysed 88 cases and 602 controls and estimated the odds of dengue cluster formation at various adult Aedes abundance levels, estimated by the mean number of adult female Aedes per Gravitrap per week and categorised into Low, Moderate, High and Very High abundance level. We found that the risk of dengue cluster formation was positively associated with adult Ae. aegypti abundance. We observed a three to four-fold increase in the odds of dengue clusters forming in areas with High (AOR: 3.40, 95% CI: 2.09, 5.52) and Very High (AOR: 3.99, 95% CI: 2.46, 6.46) adult Aedes aegypti abundance level compared to those with low Ae. aegypti abundance level. Our study strengthens the evidence for the use of adult Aedes indices for dengue risk assessment and early warning for dengue outbreaks. Entomological indicators of adult Ae. aegypti could be used to anticipate and prioritize areas for dengue control.     

Climate-based models for understanding and forecasting dengue epidemics

Background

Dengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia), and to provide an early warning system.

Methodology/Principal Findings

Epidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March–April) lagged the warmest temperature by 1–2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January–February–March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October–November–December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively.

Conclusions/Significance

The epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was also crucial. An operational model that will enable health authorities to anticipate the outbreak risk was successfully developed. Similar models may be developed to improve dengue management in other countries.     

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.     

Incidence of lab-confirmed dengue fever in a pediatric cohort in Delhi,India

BackgroundOur aim was to estimate the overall and age-specific incidence of lab-confirmed dengue fever using ELISA based assays among children 6 months to 15 years in Delhi.MethodsWe enrolled a cohort of 984 children aged 6 months to <14 years in South Delhi and followed-up weekly for fever for 24 months or till 15 completed years of child-age. Households of the enrolled children were geo-tagged. NS1, IgM and IgG assays were conducted using ELISA method to confirm dengue fever in children with ≥3 consecutive days of fever. Molecular typing was done in a subset of NS1 positive cases to identify the circulating serotypes.Principal findingsWe had a total of 1953 person-years (PY) of follow up. Overall, there were 4208 episodes of fever with peaks during June to November. The overall incidence (95%CI) of fever was 215/100 PY (209 to 222). A total of 74/1250 3-day fever episodes were positive for acute dengue fever (NS1 and/or IgM positive). The overall incidence (95%CI) of acute dengue fever was 37.9 (29.8 to 47.6) per 1000 PY; highest among children aged 5 to 10 years (50.4 per 1000 PY, 95% CI 36.5 to 67.8). Spatial autocorrelation analysis suggested a clustering pattern for the dengue fever cases (Moran’s Index 0.35, z-score 1.8, p = 0.06). Dengue PCR was positive in 16 of the 24 specimens tested; DEN 3 was the predominant serotype identified in 15/24 specimens.ConclusionsWe found a high incidence of dengue fever among under 15-year children with clustering of cases in the community. DEN 3 was the most commonly circulating strain encountered. The findings underscore the need for development of affordable pre-vaccination screening strategy as well as newer dengue vaccines for young children while continuing efforts in vector control.     

Nutritional Manipulation for the Primary Prevention of Gestational Diabetes Mellitus: A Meta-Analysis of Randomised Studies

IntroductionThe rise in gestational diabetes (GDM), defined as first onset or diagnosis of diabetes in pregnancy, is a global problem. GDM is often associated with unhealthy diet and is a major contributor to adverse outcomes maternal and fetal outcomes. Manipulation of nutrition has the potential to prevent GDM.MethodsWe assessed the effects of nutritional manipulation in pregnancy on GDM and relevant maternal and fetal outcomes by a systematic review of the literature. We searched MEDLINE, EMBASE, and Cochrane Database from inception to March 2014 without any language restrictions. Randomised controlled trials (RCT) of nutritional manipulation to prevent GDM were included. We summarised dichotomous data as relative risk (RR) and continuous data as standardised mean difference (SMD) with 95% confidence interval (CI).ResultsFrom 1761 citations, 20 RCTs (6,444 women) met the inclusion criteria. We identified the following interventions: diet-based (n = 6), mixed approach (diet and lifestyle) interventions (n = 13), and nutritional supplements (myo-inositol n = 1, diet with probiotics n = 1). Diet based interventions reduced the risk of GDM by 33% (RR 0.67; 95% CI 0.39, 1.15). Mixed approach interventions based on diet and lifestyle had no effect on GDM (RR 0.95; 95% CI 0.89, 1.22). Nutritional supplements probiotics combined with diet (RR 0.40; 95% CI 0.20, 0.78) and myo-inositol (RR 0.40; 95% CI 0.16, 0.99) were assessed in one trial each and showed a beneficial effect. We observed a significant interaction between the groups based on BMI for diet-based intervention. The risk of GDM was reduced in obese and overweight pregnant women for GDM (RR 0.40, 95% CI 0.18, 0.86).ConclusionsNutritional manipulation in pregnancy based on diet or mixed approach do not appear to reduce the risk of GDM. Nutritional supplements show potential as agents for primary prevention of GDM.     

Clinical and epidemiologic characteristics associated with dengue fever in 2011–2016 in Bang Phae district,Ratchaburi province,Thailand

BackgroundDengue is a major public health problem in Thailand, but data are often focused on certain dengue-endemic areas. Methods: To better understand dengue epidemiology and clinical characteristics in Thailand, a fever surveillance study was conducted among patients aged 1–55 years, who presented with non-localized febrile illness at Bang Phae Community Hospital in Ratchaburi province, Thailand from October 2011 to September 2016.ResultsAmong 951 febrile episodes, 130 were dengue-confirmed. Individuals aged 10–14 years were mostly affected, followed by those 15–19 years-of-age, with about 15% of dengue-confirmed cases from adults 25 years and older. There were annual peaks of dengue occurrence between June-November. Most prevalent serotype in circulation was DENV-2 in 2012, DENV-3 in 2014, and DENV-4 & -3 in 2015. Among dengue cases, 65% were accurately detected using the dengue NS1 RDT. Detection rate was similar between secondary and primary dengue cases where 66% of secondary vs. 60% of primary dengue cases had positive results on the NS1 RDT. Among dengue cases, 66% were clinically diagnosed with suspected dengue or DHF, prior to lab confirmation. Dengue was positively associated with rash, headache, hematemesis and alterations to consciousness, when compared to non-dengue. Dengue patients were 10.6 times more likely to be hospitalized, compared to non-dengue cases. Among dengue cases, 95 were secondary and 35 were primary infections. There were 8 suspected DHF cases and all were identified to be secondary dengue. Secondary dengue cases were 3.5 times more likely to be hospitalized compared to primary dengue cases. Although the majority of our dengue-positive patients were secondary dengue cases, with few patients showing manifestations of DHF, our dengue cases were mostly mild disease. Even among children < 10 years-of-age, 61% had secondary infection and the rate of secondary infection increased with age.ConclusionWhile the majority of dengue-confirmed cases were children, almost three-quarters of dengue-confirmed cases in this study were secondary dengue. Our study results consistent with previous data from the country confirm the hyperendemic transmission of DENV in Thailand, even in the non-epidemic years. With various interventions becoming available for dengue prevention and control, including dengue vaccines, decision-making on future implementation strategies should be based on such burden of disease data.     

Evaluation of two new commercial tests for the diagnosis of acute dengue virus infection using NS1 antigen detection in human serum

Background

We compared the performance of two new commercial tests for the detection of dengue NS1 protein during the clinical phase of dengue virus (DENV) infection—an immunochromatographic test allowing rapid detection of the NS1 antigen, Dengue NS1 Ag STRIP (Bio-Rad Laboratories - Marnes La Coquette, France), and a two-step sandwich-format microplate enzyme-linked immunosorbent assay (ELISA), pan-E Dengue Early ELISA (Panbio - Brisbane, Australia)—with a one-step sandwich-format microplate ELISA, the Platelia Dengue NS1 Ag test (Bio-Rad).

Methods

We tested 272 serum samples from patients with dengue disease. Of these, 222 were from patients with acute infection of one of the four dengue serotypes, detected by RT-PCR and/or virus isolation. Forty-eight acute-phase serum samples from patients not infected with dengue virus were also included.

Results

The sensitivity of the Platelia Dengue NS1 Ag test on acute serum samples (n = 222) was 87.4% (95% confidence interval: 82.3% to 91.5%); that of Dengue NS1 Ag STRIP was 81.5% (95% CI: 75.8% to 86.4%) after 15 minutes and 82.4% (95% CI: 76.8% to 87.2%) after 30 minutes. Both tests had a specificity of 100% (97.5% CI, one-sided test: 92.6% to 100.0%). The pan-E Dengue Early ELISA had a sensitivity of 60.4% (95% CI: 53.4% to 66.8%) and a specificity of 97.9% (95% CI: 88.9% to 99.9%).

Conclusion

Our findings support the use of diagnostic tools based on the NS1 antigen detection for the diagnosis of acute DENV infection. The immunochromatographic test, Dengue NS1 Ag STRIP—the first rapid diagnostic test for DENV infection—was highly sensitive and specific, and would therefore be a suitable first-line test in the field. The pan-E Dengue Early ELISA was less sensitive than the Platelia test; this two-step ELISA should be combined with DENV IgM antibody detection for the diagnosis of DENV infection.