Increasing Dengue Incidence in Singapore over the Past 40 Years: Population Growth, Climate and Mobility

Net benefit of smaller human populations to environmental integrity and individual health and wellbeing

Introduction

The global human population is still growing such that our collective enterprise is driving environmental catastrophe. Despite a decline in average population growth rate, we are still experiencing the highest annual increase of global human population size in the history of our species-averaging an additional 84 million people per year since 1990. No review to date has accumulated the available evidence describing the associations between increasing population and environmental decline, nor solutions for mitigating the problems arising.

Methods

We summarize the available evidence of the relationships between human population size and growth and environmental integrity, human prosperity and wellbeing, and climate change. We used PubMed, Google Scholar, and Web of Science to identify all relevant peer-reviewed and gray-literature sources examining the consequences of human population size and growth on the biosphere. We reviewed papers describing and quantifying the risks associated with population growth, especially relating to climate change.

Results

These risks are global in scale, such as greenhouse-gas emissions, climate disruption, pollution, loss of biodiversity, and spread of disease-all potentially catastrophic for human standards of living, health, and general wellbeing. The trends increasing the risks of global population growth are country development, demographics, maternal education, access to family planning, and child and maternal health.

Conclusion

Support for nations still going through a demographic transition is required to ensure progress occurs within planetary boundaries and promotes equity and human rights. Ensuring the wellbeing for all under this aim itself will lower population growth and further promote environmental sustainability.

Ocular Autoimmune Systemic Inflammatory Infectious Study (OASIS) - Report 6: Dengue Uveitis at a Tertiary Eye Institution in Singapore

OBJECTIVES

To identify the characteristics, treatment, and visual outcomes of dengue uveitis at a tertiary eye care centre in Singapore.

METHODS

Retrospective case record review of all consecutive dengue uveitis patients (2004 to 2015) from the Ocular Autoimmune Systemic Inflammatory and Infectious Study (OASIS) database.

RESULTS

Fifty-four patients were identified from the OASIS database. The most common ocular symptom was blurring of vision (n = 41, 75.9%), followed by floaters (n = 9, 17.0%), scotoma (n = 5, 9.3%), and metamorphopsia (n = 3, 5.7%). Scotoma based on history, Amsler grid, and perimetry accounted for 27 (50%) patients. Majority presented with either a posterior uveitis or retinal vasculitis (n = 51, 94.4%). Treatments ranged from close observation for spontaneous improvement, to the use of high-dose corticosteroids.

CONCLUSIONS

Dengue uveitis may present with a spectrum of disease manifestations including posterior uveitis, vasculitis, and macula edema. Scotoma is significant and may be found on history taking, Amsler charting, and perimetry.

Entomological risk assessment for transmission of arboviral diseases by Aedes mosquitoes in a domestic and forest site in Accra, Ghana

Dengue, Zika and chikungunya are Aedes-borne viral diseases that have become great global health concerns in the past years. Several countries in Africa have reported outbreaks of these diseases and despite Ghana sharing borders with some of these countries, such outbreaks are yet to be detected. Viral RNA and antibodies against dengue serotype-2 have recently been reported among individuals in some localities in the regional capital of Ghana. This is an indication of a possible silent transmission ongoing in the population. This study, therefore, investigated the entomological transmission risk of dengue, Zika and chikungunya viruses in a forest and domestic population in the Greater Accra Region, Ghana. All stages of the Aedes mosquito (egg, larvae, pupae and adults) were collected around homes and in the forest area for estimation of risk indices. All eggs were hatched and reared to larvae or adults for morphological identification together with larvae and adults collected from the field. The forest population had higher species richness with 7 Aedes species. The predominant species of Aedes mosquitoes identified from both sites was Aedes aegypti (98%). Aedes albopictus, an important arbovirus vector, was identified only in the peri-domestic population at a prevalence of 1.5%, significantly higher than previously reported. All risk indices were above the WHO threshold except the House Index for the domestic site which was moderate (19.8). The forest population recorded higher Positive Ovitrap (34.2% vs 26.6%) and Container (67.9% vs 36.8%) Indices than the peri-domestic population. Although none of the mosquito pools showed the presence of dengue, chikungunya or Zika viruses, all entomological risk indicators showed that both sites had a high potential arboviral disease transmission risk should any of these viruses be introduced. Continuous surveillance is recommended in these and other sites in the Metropolis to properly map transmission risk areas to inform outbreak preparedness strategies.

Associations between Dengue Incidence, Ecological Factors, and Anthropogenic Factors in Singapore

Singapore experiences endemic dengue. Vector control remains the primary means to reduce transmission due to the lack of available therapeutics. Resource limitations mean that vector-control tools need to be optimized, which can be achieved by studying risk factors related to disease transmission. We developed a statistical modelling framework which can account for a high-resolution and high-dimensional set of covariates to delineate spatio-temporal characteristics that are associated with dengue transmission from 2014 to 2020 in Singapore. We applied the proposed framework to two distinct datasets, stratified based on the primary type of housing within each spatial unit. Generalized additive models reveal non-linear exposure responses between a large range of ecological and anthropogenic factors as well as dengue incidence rates. At values below their mean, lesser mean total daily rainfall (Incidence rate ratio (IRR): 3.75, 95% CI: 1.00-14.05, Mean: 4.40 mm), decreased mean windspeed (IRR: 3.65, 95% CI: 1.87-7.10, Mean: 4.53 km/h), and lower building heights (IRR: 2.62, 95% CI: 1.44-4.77, Mean: 6.5 m) displayed positive associations, while higher than average annual NO2 concentrations (IRR: 0.35, 95% CI: 0.18-0.66, Mean: 13.8 ppb) were estimated to be negatively associated with dengue incidence rates. Our study provides an understanding of associations between ecological and anthropogenic characteristics with dengue transmission. These findings help us understand high-risk areas of dengue transmission, and allows for land-use planning and formulation of vector control policies.

Projecting the future incidence and burden of dengue in Southeast Asia

The recent global expansion of dengue has been facilitated by changes in urbanisation, mobility, and climate. In this work, we project future changes in dengue incidence and case burden to 2099 under the latest climate change scenarios. We fit a statistical model to province-level monthly dengue case counts from eight countries across Southeast Asia, one of the worst affected regions. We project that dengue incidence will peak this century before declining to lower levels with large variations between and within countries. Our findings reveal that northern Thailand and Cambodia will show the biggest decreases and equatorial areas will show the biggest increases. The impact of climate change will be counterbalanced by income growth, with population growth having the biggest influence on increasing burden. These findings can be used for formulating mitigation and adaptation interventions to reduce the immediate growing impact of dengue virus in the region.

Impact of regional climate change on the mosquito vector Aedes albopictus in a tropical island environment: La Réunion

The recent expansion of Aedes albopictus across continents in both tropical and temperate regions and the exponential growth of dengue cases over the past 50 years represent a significant risk to human health. Although climate change is not the only factor responsible for the increase and spread of dengue cases worldwide, it might increase the risk of disease transmission at global and regional scale. Here we show that regional and local variations in climate can induce differential impacts on the abundance of Ae. albopictus. We use the instructive example of Réunion Island with its varied climatic and environmental conditions and benefiting from the availability of meteorological, climatic, entomological and epidemiological data. Temperature and precipitation data based on regional climate model simulations (3 km × 3 km) are used as inputs to a mosquito population model for three different climate emission scenarios. Our objective is to study the impact of climate change on the life cycle dynamics of Ae. albopictus in the 2070-2100 time horizon. Our results show the joint influence of temperature and precipitation on Ae. albopictus abundance as a function of elevation and geographical subregion. At low-elevations areas, decreasing precipitation is expected to have a negative impact on environmental carrying capacity and, consequently, on Ae. albopictus abundance. At mid- and high-elevations, decreasing precipitation is expected to be counterbalanced by a significant warming, leading to faster development rates at all life stages, and consequently increasing the abundance of this important dengue vector in 2070-2100.

PICTUREE-Aedes: A Web Application for Dengue Data Visualization and Case Prediction

Dengue fever remains a significant public health concern in many tropical and subtropical countries, and there is still a need for a system that can effectively combine global risk assessment with timely incidence forecasting. This research describes an integrated application called PICTUREE-Aedes, which can collect and analyze dengue-related data, display simulation results, and forecast outbreak incidence. PICTUREE-Aedes automatically updates global temperature and precipitation data and contains historical records of dengue incidence (1960-2012) and Aedes mosquito occurrences (1960-2014) in its database. The application utilizes a mosquito population model to estimate mosquito abundance, dengue reproduction number, and dengue risk. To predict future dengue outbreak incidence, PICTUREE-Aedes applies various forecasting techniques, including the ensemble Kalman filter, recurrent neural network, particle filter, and super ensemble forecast, which are all based on user-entered case data. The PICTUREE-Aedes' risk estimation identifies favorable conditions for potential dengue outbreaks, and its forecasting accuracy is validated by available outbreak data from Cambodia.

Effects of high temperatures and heatwaves on dengue fever: a systematic review and meta-analysis

BACKGROUND

Studies have shown that dengue virus transmission increases in association with ambient temperature. We performed a systematic review and meta-analysis to assess the effect of both high temperatures and heatwave events on dengue transmission in different climate zones globally.

METHODS

A systematic literature search was conducted in PubMed, Scopus, Embase, and Web of Science from January 1990 to September 20, 2022. We included peer reviewed original observational studies using ecological time series, case crossover, or case series study designs reporting the association of high temperatures and heatwave with dengue and comparing risks over different exposures or time periods. Studies classified as case reports, clinical trials, non-human studies, conference abstracts, editorials, reviews, books, posters, commentaries; and studies that examined only seasonal effects were excluded. Effect estimates were extracted from published literature. A random effects meta-analysis was performed to pool the relative risks (RRs) of dengue infection per 1 °C increase in temperature, and further subgroup analyses were also conducted. The quality and strength of evidence were evaluated following the Navigation Guide systematic review methodology framework. The review protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO).

FINDINGS

The study selection process yielded 6367 studies. A total of 106 studies covering more than four million dengue cases fulfilled the inclusion criteria; of these, 54 studies were eligible for meta-analysis. The overall pooled estimate showed a 13% increase in risk of dengue infection (RR = 1.13; 95% confidence interval (CI): 1.11-1.16, I² = 98.0%) for each 1 °C increase in high temperatures. Subgroup analyses by climate zones suggested greater effects of temperature in tropical monsoon climate zone (RR = 1.29, 95% CI: 1.11-1.51) and humid subtropical climate zone (RR = 1.20, 95% CI: 1.15-1.25). Heatwave events showed association with an increased risk of dengue infection (RR = 1.08; 95% CI: 0.95-1.23, I² = 88.9%), despite a wide confidence interval. The overall strength of evidence was found to be "sufficient" for high temperatures but "limited" for heatwaves. Our results showed that high temperatures increased the risk of dengue infection, albeit with varying risks across climate zones and different levels of national income.

INTERPRETATION

High temperatures increased the relative risk of dengue infection. Future studies on the association between temperature and dengue infection should consider local and regional climate, socio-demographic and environmental characteristics to explore vulnerability at local and regional levels for tailored prevention.

FUNDING

Australian Research Council Discovery Program.

Dengue determinants: Necessities and challenges for universal dengue vaccine development

Dengue illness can range from mild illness to life-threatening haemorrhage. It is an Aedes-borne infectious disease caused by the dengue virus, which has four serotypes. Each serotype acts as an independent infectious agent. The antibodies against one serotype confer homotypic immunity but temporary protection against heterotypic infection. Dengue has become a growing health concern for up to one third of the world's population. Currently, there is no potent anti-dengue medicine, and treatment for severe dengue relies on intravenous fluid management and pain medications. The burden of dengue dramatically increases despite advances in vector control measures. These factors underscore the need for a vaccine. Various dengue vaccine strategies have been demonstrated, that is, live attenuated vaccine, inactivated vaccine, DNA vaccine, subunit vaccine, and viral-vector vaccines, some of which are at the stage of clinical testing. Unfortunately, the forefront candidate vaccine is less than satisfactory, and its performance depends on serostatus and age factors. The lessons from clinical studies depicted ambiguity concerning the efficacy of dengue vaccine. Our study highlighted that viral structural heterogeneity, epitope accessibility, autoimmune complications, genetic variants, genetic diversities, antigen competition, virulence variation, host-pathogen specific interaction, antibody-dependent enhancement, cross-reactive immunity among Flaviviruses, and host-susceptibility determinants not only influence infection outcomes but also hampered successful vaccine development. This review integrates dengue determinants allocated necessities and challenges, which would provide insight for universal dengue vaccine development.

Increasing Dengue Burden and Severe Dengue Risk in Bangladesh: An Overview

Dengue is a prevalent and rapidly spreading mosquito-borne viral disease affecting humans. The geographic range of dengue is expanding, and much like in many other tropical regions of the world, dengue has become a major public health issue in Bangladesh. Until a large epidemic dengue outbreak in 2000, sporadic outbreaks have occurred in Bangladesh since 1964. After 2000, varying intensities of dengue activity were observed each year until 2018. However, in 2019, Bangladesh experienced the largest dengue epidemic in its history, with 101,354 dengue cases and 164 dengue-related deaths. Notably, this outbreak occurred in many regions that were previously considered free of the disease. As of 10 December 2022, a total of 60,078 dengue cases and 266 dengue-related deaths were reported in Bangladesh, with the 2022 outbreak being the second largest since 2000. There is an increased genetic diversity of the dengue virus (DENV) in Bangladesh and all four DENV serotypes are prevalent and co-circulating, which increases the risk for severe dengue owing to the antibody-dependent enhancement effect. Vector control remains the mainstay of dengue outbreak prevention; however, the vector control programs adopted in Bangladesh seem inadequate, requiring improved vector control strategies. In this review, we provide an overview of the epidemiology of DENV infection and the risks for a severe dengue outbreak in Bangladesh. Additionally, we discuss different dengue vector control strategies, from which the most suitable and effective measures can be applied in the context of Bangladesh for tackling future dengue epidemics.

C-reactive protein: An easy marker for early differentiation between leptospirosis and dengue fever in endemic area

In tropical regions, leptospirosis and dengue fever (DF) are infectious diseases of epidemiological importance and have overlapping symptomatic features. The objective of this study was to identify the factors associated to diagnosing leptospirosis that differentiate it to DF at the initial hospital evaluation. A multicenter retrospective study was conducted comparing confirmed leptospirosis to DF cases. Clinical/laboratory findings were compiled at hospital admission on Reunion Island between 2018 and 2019. Multivariable logistic regression was used to identify the predictors of leptospirosis. In total, 98 leptospirosis and 673 DF patients were included with a mean age of 47.8 (±17.1) and 48.9 (±23.3) years, respectively. In the multivariate analyses, the main parameters associated with leptospirosis were: i) increased neutrophil counts, ii) C-reactive protein values, iii) the absence of prolonged partial thromboplastin time, and iv) a decrease of platelets. The most discriminating parameter was C-reactive protein (CRP). With a threshold of 50mg/L, CRP taken alone had a sensitivity of 94% and a specificity of 93.5%. The positive and negative likelihood ratios were 14.5 and 0.06, respectively. In the setting of an early presumptive diagnosis, we found that an increased CRP value (>50 mg/L) could help diagnose leptospirosis and aid the decision process for hospital surveillance and/or a potential antibiotic treatment regimen.

Dengue Incidence Trends and Its Burden in Major Endemic Regions from 1990 to 2019

BACKGROUND

Dengue has become one of the major vector-borne diseases, which has been an important public health concern. We aimed to estimate the disease burden of dengue in major endemic regions from 1990 to 2019, and explore the impact pattern of the socioeconomic factors on the burden of dengue based on the global burden of diseases, injuries, and risk factors study 2019 (GBD 2019).

METHODS

Using the analytical strategies and data from the GBD 2019, we described the incidence and disability-adjusted life years (DALYs) of dengue in major endemic regions from 1990 to 2019. Furthermore, we estimated the correlation between dengue burden and socioeconomic factors, and then established an autoregressive integrated moving average (ARIMA) model to predict the epidemic trends of dengue in endemic regions. All estimates were proposed as numbers and age-standardized rates (ASR) per 100,000 population, with uncertainty intervals (UIs). The ASRs of dengue incidence were compared geographically and five regions were stratified by a sociodemographic index (SDI).

RESULTS

A significant rise was observed on a global scale between 1990 and 2019, with the overall age-standardized rate (ASR) increasing from 557.15 (95% UI 243.32-1212.53) per 100,000 in 1990 to 740.4 (95% UI 478.2-1323.1) per 100,000 in 2019. In 2019, the Oceania region had the highest age-standardized incidence rates per 100,000 population (3173.48 (95% UI 762.33-6161.18)), followed by the South Asia region (1740.79 (95% UI 660.93-4287.12)), and then the Southeast Asia region (1153.57 (95% UI 1049.49-1281.59)). In Oceania, South Asia, and Southeast Asia, increase trends were found in the burden of dengue fever measured by ASRs of DALY which were consistent with ASRs of dengue incidence at the national level. Most of the countries with the heaviest burden of dengue fever occurred in areas with low and medium SDI regions. However, the burden in high-middle and high-SDI countries is relatively low, especially the Solomon Islands and Tonga in Oceania, the Maldives in South Asia and Indonesia in Southeast Asia. The age distribution results of the incidence rate and disease burden of dengue fever of major endemic regions showed that the higher risk and disease burden are mainly concentrated in people under 14 or over 70 years old. The prediction by ARIMA showed that the risk of dengue fever in South and Southeast Asia is on the rise, and further prevention and control is warranted.

CONCLUSIONS

In view of the rapid population growth and urbanization in many dengue-endemic countries, our research results are of great significance for presenting the future trend in dengue fever. It is recommended to policy makers that specific attention needs to be paid to the negative impact of urbanization on dengue incidence and allocate more resources to the low-SDI areas and people under 14 or over 70 years old to reduce the burden of dengue fever.

Forecasting the incidence of dengue in Bangladesh—Application of time series model

Background

Dengue is an alarming public health concern in terms of its preventive and curative measures among people in Bangladesh; moreover, its sudden outbreak created a lot of suffering among people in 2018. Considering the greater burden of disease in larger epidemic years and the difficulty in understanding current and future needs, it is highly needed to address early warning systems to control epidemics from the earliest.

Objective

The study objective was to select the most appropriate model for dengue incidence and using the selected model, the authors forecast the future dengue outbreak in Bangladesh.

Methods and Materials

This study considered a secondary data set of monthly dengue occurrences over the period of January 2008 to January 2020. Initially, the authors found the suitable model from Autoregressive Integrated Moving Average (ARIMA), Error, Trend, Seasonal (ETS) and Trigonometric seasonality, Box‐Cox transformation, ARMA errors, Trend and Seasonal (TBATS) models with the help of selected model selection criteria and finally employing the selected model make forecasting of dengue incidences in Bangladesh.

Results

Among ARIMA, ETS, and TBATS models, the ARIMA model performs better than others. The Box‐Jenkin's procedure is applicable here and it is found that the best‐selected model to forecast the dengue outbreak in the context of Bangladesh is ARIMA (2,1,2).

Conclusion

Before establishing a comprehensive plan for future combating strategies, it is vital to understand the future scenario of dengue occurrence. With this in mind, the authors aimed to select an appropriate model that might predict dengue fever outbreaks in Bangladesh. The findings revealed that dengue fever is expected to become more frequent in the future. The authors believe that the study findings will be helpful to take early initiatives to combat future dengue outbreaks.

Urban Scaling of Health Outcomes: a Scoping Review

Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. We found several historical studies that examined the dynamic relationships between city size and mortality occurring during the nineteenth and early twentieth centuries. In more recent years, we documented heterogeneity in the relation between city size and health. Measles and influenza are influenced by city size in conjunction with other factors like geographic proximity, while STIs, HIV, and dengue tend to occur more frequently in larger cities. NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.

Introgression of the Aedes aegypti Red-Eye Genetic Sexing Strains Into Different Genomic Backgrounds for Sterile Insect Technique Applications

Aedes aegypti is an invasive mosquito species and major vector of human arboviruses. A wide variety of control methods have been employed to combat mosquito populations. One of them is the sterile insect technique (SIT) that has recently attracted considerable research efforts due to its proven record of success and the absence of harmful environmental footprints. The efficiency and cost-effectiveness of SIT is significantly enhanced by male-only releases. For mosquito SIT, male-only releases are ideally needed since females bite, blood-feed and transmit the pathogens. Ae. aegypti genetic sexing strains (GSS) have recently become available and are based on eye colour mutations that were chosen as selectable markers. These genetic sexing strains were developed through classical genetics and it was shown to be subjected to genetic recombination, a phenomenon that is not suppressed in males as is the case in many Diptera. The genetic stability of these GSS was strengthened by the induction and isolation of radiation-induced inversions. In this study, we used the red eye mutation and the inversion Inv35 line of the Ae. aegypti red-eye GSS s and introgressed them in six different genomic backgrounds to develop GSS with the respective local genomic backgrounds. Our goal was to assess whether the recombination frequencies in the strains with and without the inversion are affected by the different genomic backgrounds. In all cases the recombination events were suppressed in all Inv35 GSS strains, thus indicating that the genomic background does not negatively affect the inversion result. Absence of any effect that could be ascribed to genetic differences, enables the introgression of the key elements of the GSS into the local genomic background prior to release to the target areas. Maintaining the local background increases the chances for successful matings between released males and wild females and addresses potential regulatory concerns regarding biosafety and biosecurity.

Weather Factors Associated with Reduced Risk of Dengue Transmission in an Urbanized Tropical City

This study assessed the impact of weather factors, including novel predictors-pollutant standards index (PSI) and wind speed-on dengue incidence in Singapore between 2012 and 2019. Autoregressive integrated moving average (ARIMA) model was fitted to explore the autocorrelation in time series and quasi-Poisson model with a distributed lag non-linear term (DLNM) was set up to assess any non-linear association between climatic factors and dengue incidence. In DLNM, a PSI level of up to 111 was positively associated with dengue incidence; incidence reduced as PSI level increased to 160. A slight rainfall increase of up to 7 mm per week gave rise to higher dengue risk. On the contrary, heavier rainfall was protective against dengue. An increase in mean temperature under around 28.0 °C corresponded with increased dengue cases whereas the association became negative beyond 28.0 °C; the minimum temperature was significantly positively associated with dengue incidence at around 23-25 °C, and the relationship reversed when temperature exceed 27 °C. An overall positive association, albeit insignificant, was observed between maximum temperature and dengue incidence. Wind speed was associated with decreasing relative risk (RR). Beyond prevailing conclusions on temperature, this study observed that extremely poor air quality, high wind speed, minimum temperature ≥27 °C, and rainfall volume beyond 12 mm per week reduced the risk of dengue transmission in an urbanized tropical environment.

Cocculus hirsutus-Derived Phytopharmaceutical Drug Has Potent Anti-dengue Activity

Dengue is a serious public health concern worldwide, with ∼3 billion people at risk of contracting dengue virus (DENV) infections, with some suffering severe consequences of disease and leading to death. Currently, there is no broad use vaccine or drug available for the prevention or treatment of dengue, which leaves only anti-mosquito strategies to combat the dengue menace. The present study is an extension of our earlier study aimed at determining the in vitro and in vivo protective effects of a plant-derived phytopharmaceutical drug for the treatment of dengue. In our previous report, we had identified a methanolic extract of aerial parts of Cissampelos pareira to exhibit in vitro and in vivo anti-dengue activity against all the four DENV serotypes. The dried aerial parts of C. pareira supplied by local vendors were often found to be mixed with aerial parts of another plant of the same Menispermaceae family, Cocculus hirsutus, which shares common homology with C. pareira. In the current study, we have found C. hirsutus to have more potent anti-dengue activity as compared with C. pareira. The stem part of C. hirsutus was found to be more potent (∼25 times) than the aerial part (stem and leaf) irrespective of the extraction solvent used, viz., denatured spirit, hydro-alcohol (50:50), and aqueous. Moreover, the anti-dengue activity of stem extract in all the solvents was comparable. Hence, an aqueous extract of the stem of C. hirsutus (AQCH) was selected due to greater regulatory compliance. Five chemical markers, viz., Sinococuline, 20-Hydroxyecdysone, Makisterone-A, Magnoflorine, and Coniferyl alcohol, were identified in fingerprinting analysis. In a test of primary dengue infection in the AG129 mice model, AQCH extract at 25 mg/kg body weight exhibited protection when administered four and three times a day. The AQCH was also protective in the secondary DENV-infected AG129 mice model at 25 mg/kg/dose when administered four and three times a day. Additionally, the AQCH extract reduced serum viremia and small intestinal pathologies, viz., viral load, pro-inflammatory cytokines, and vascular leakage. Based on these findings, we have undertaken the potential preclinical development of C. hirsutus-based phytopharmaceutical, which could be studied further for its clinical development for treating dengue.

Are Temperature Suitability and Socioeconomic Factors Reliable Predictors of Dengue Transmission in Brazil?

Dengue is an ongoing problem, especially in tropical countries. Like many other vector-borne diseases, the spread of dengue is driven by a myriad of climate and socioeconomic factors. Within developing countries, heterogeneities on socioeconomic factors are expected to create variable conditions for dengue transmission. However, the relative role of socioeconomic characteristics and their association with climate in determining dengue prevalence are poorly understood. Here we assembled essential socioeconomic factors over 5570 municipalities across Brazil and assessed their effect on dengue prevalence jointly with a previously predicted temperature suitability for transmission. Using a simultaneous autoregressive approach (SAR), we showed that the variability in the prevalence of dengue cases across Brazil is primarily explained by the combined effect of climate and socioeconomic factors. At some dengue seasons, the effect of temperature on transmission potential showed to be a more significant proxy of dengue cases. Still, socioeconomic factors explained the later increase in dengue prevalence over Brazil. In a heterogeneous country such as Brazil, recognizing the transmission drivers by vectors is a fundamental issue in effectively predicting and combating tropical diseases like dengue. Ultimately, it indicates that not considering socioeconomic factors in disease transmission predictions might compromise efficient surveillance strategies. Our study shows that sanitation, urbanization, and GDP are regional indicators that should be considered along with temperature suitability on dengue transmission, setting effective directions to mosquito-borne disease control.

Novel Sterile Insect Technology Program Results in Suppression of a Field Mosquito Population and Subsequently to Reduced Incidence of Dengue

BACKGROUND

There is a steady rise in the global incidence of Aedes-borne arbovirus disease. It has become urgent to develop alternative solutions for mosquito vector control. We developed a new method of sterilization of male mosquitoes with the goal to suppress a local Aedes aegypti population and to prevent the spread of dengue.

METHODS

Sterile male mosquitoes were produced from a locally acquired Ae. aegypti colony by using a treatment that includes double-stranded RNA and thiotepa. A field study was conducted with sterile mosquito releases being performed on a weekly basis in predefined areas. There were 2 intervention periods (INT1 and INT2), with treatment and control areas reversed between INT1 and INT2.

RESULTS

During INT1, releases in the treated area resulted in up to 91.4% reduction of live progeny of field Ae. aegypti mosquitoes recorded over time, while the control neighborhoods (no releases of sterile male mosquitoes) remained highly infested. The successful implementations of the program during INT1 and INT2 were associated with 15.9-fold and 13.7-fold lower incidences of dengue in the treated area compared to the control areas, respectively.

CONCLUSIONS

Our data show the success of this new sterile insect technology-based program in preventing the spread of dengue.

Recent Insights Into the Molecular Mechanism of Toll-Like Receptor Response to Dengue Virus Infection

Dengue is the most prevalent and rapidly spreading mosquito-borne viral disease caused by dengue virus (DENV). Recently, DENV has been affecting humans within an expanding geographic range due to the warming of the earth. Innate immune responses play a significant role in antiviral defense, and Toll-like receptors (TLRs) are key regulators of innate immunity. Therefore, a detailed understanding of TLR and DENV interactions is important for devising therapeutic and preventive strategies. Several studies have indicated the ability of DENV to modulate the TLR signaling pathway and host immune response. Vaccination is considered one of the most successful medical interventions for preventing viral infections. However, only a partially protective dengue vaccine, the first licensed dengue vaccine CYD-TDV, is available in some dengue-endemic countries to protect against DENV infection. Therefore, the development of a fully protective, durable, and safe DENV vaccine is a priority for global health. Here, we demonstrate the progress made in our understanding of the host response to DENV infection, with a particular focus on TLR response and how DENV avoids the response toward establishing infection. We also discuss dengue vaccine candidates in late-stage development and the issues that must be overcome to enable their success.

The role of urbanisation in the spread of Aedes mosquitoes and the diseases they transmit-A systematic review

Background

This systematic review aims to assess how different urbanisation patterns related to rapid urban growth, unplanned expansion, and human population density affect the establishment and distribution of Aedes aegypti and Aedes albopictus and create favourable conditions for the spread of dengue, chikungunya, and Zika viruses.

Methods and findings

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was conducted using the PubMed, Virtual Health Library, Cochrane, WHO Library Database (WHOLIS), Google Scholar, and and the Institutional Repository for Information Sharing (IRIS) databases. From a total of 523 identified studies, 86 were selected for further analysis, and 29 were finally analysed after applying all inclusion and exclusion criteria. The main explanatory variables used to associate urbanisation with epidemiological/entomological outcomes were the following: human population density, urban growth, artificial geographical space, urban construction, and urban density. Associated with the lack of a global definition of urbanisation, several studies provided their own definitions, which represents one of the study’s limitations. Results were based on 8 ecological studies/models, 8 entomological surveillance studies, 7 epidemiological surveillance studies, and 6 studies consisting of spatial and predictive models. According to their focus, studies were categorised into 2 main subgroups, namely “Aedes ecology” and “transmission dynamics.” There was a consistent association between urbanisation and the distribution and density of Aedes mosquitoes in 14 of the studies and a strong relationship between vector abundance and disease transmission in 18 studies. Human population density of more than 1,000 inhabitants per square kilometer was associated with increased levels of arboviral diseases in 15 of the studies.

Conclusions

The use of different methods in the included studies highlights the interplay of multiple factors linking urbanisation with ecological, entomological, and epidemiological parameters and the need to consider a variety of these factors for designing effective public health approaches.

The expansion of urbanisation is often associated with the emergence and spread of vector-borne diseases by creating favourable conditions for the survival of Aedes species and the spread of dengue, chikungunya, and Zika viruses. This systematic review examined the relationship of urbanisation to the emergence and spread of Aedes mosquito–borne diseases and epidemics. From a total of 523 identified studies, 29 were included in the analysis. Studies were categorised into 2 main subgroups, namely “Aedes ecology” and “transmission dynamics” according to the main influence factors posed by urbanisation. Selected articles showed a clear relationship of urbanisation with distribution and density of Aedes mosquitoes and a robust association between vector production, human population density, and disease transmission. Differing definitions of ’urbanisation’ and the interplay of numerous factors linking urbanisation with ecological, entomological, and epidemiological parameters highlight the need for a multidimensional perspective when assessing the impacts of rapid and unplanned urban expansion and when designing effective control programmes.

Development and Comparison of Dengue Vulnerability Indices Using GIS-Based Multi-Criteria Decision Analysis in Lao PDR and Thailand

Dengue is a continuous health burden in Laos and Thailand. We assessed and mapped dengue vulnerability in selected provinces of Laos and Thailand using multi-criteria decision approaches. An ecohealth framework was used to develop dengue vulnerability indices (DVIs) that explain links between population, social and physical environments, and health to identify exposure, susceptibility, and adaptive capacity indicators. Three DVIs were constructed using two objective approaches, Shannon's Entropy (SE) and the Water-Associated Disease Index (WADI), and one subjective approach, the Best-Worst Method (BWM). Each DVI was validated by correlating the index score with dengue incidence for each spatial unit (district and subdistrict) over time. A Pearson's correlation coefficient (r) larger than 0.5 and a p-value less than 0.05 implied a good spatial and temporal performance. Spatially, DVIWADI was significantly correlated on average in 19% (4-40%) of districts in Laos (mean r = 0.5) and 27% (15-53%) of subdistricts in Thailand (mean r = 0.85). The DVISE was validated in 22% (12-40%) of districts in Laos and in 13% (3-38%) of subdistricts in Thailand. The DVIBWM was only developed for Laos because of lack of data in Thailand and was significantly associated with dengue incidence on average in 14% (0-28%) of Lao districts. The DVIWADI indicated high vulnerability in urban centers and in areas with plantations and forests. In 2019, high DVIWADI values were observed in sparsely populated areas due to elevated exposure, possibly from changes in climate and land cover, including urbanization, plantations, and dam construction. Of the three indices, DVIWADI was the most suitable vulnerability index for the study area. The DVIWADI can also be applied to other water-associated diseases, such as Zika and chikungunya, to highlight priority areas for further investigation and as a tool for prevention and interventions.

Implementation strategies for the first licensed dengue vaccine: A meeting report

Dengue vaccination would enhance the control of dengue, one of the most frequent vector-borne viral diseases globally. CYD-TDV is the first dengue vaccine to be licensed, but global uptake has been hampered due to its use being limited to seropositive persons aged 9 years and above, and the need for a 3-dose schedule. The Partnership for Dengue Control (PDC) organized a meeting with key opinion leaders and stakeholders to deliberate on implementation strategies for the use of CYD-TDV. New data have emerged that support the shortening of the primary schedule from a 3 to 2 dose schedule, extending the age range below 9 to 6 years of age, and expanding the indication from endemic populations to also include travelers to endemic areas. Cost-effectiveness may improve with the modified 2-dose regimen and with multiple testing. Strategies to implement a dengue vaccination program have been developed, in particular school-based strategies. A range of delivery scenarios can then be considered, using various settings for each step of the intervention. However, several challenges remain, including communication about limiting the use of this vaccine to seropositive individuals only. Affordability will vary from country to country, as will government commitment and community acceptance. Well-tailored communication strategies that target key stakeholders are expected to make up a significant part of any future dengue vaccination program.

Dengue fever and insecticide resistance in Aedes mosquitoes in Southeast Asia: a review

Dengue fever is the most important mosquito-borne viral disease in Southeast Asia. Insecticides remain the most effective vector control approach for Aedes mosquitoes. Four main classes of insecticides are widely used for mosquito control: organochlorines, organophosphates, pyrethroids and carbamates. Here, we review the distribution of dengue fever from 2000 to 2020 and its associated mortality in Southeast Asian countries, and we gather evidence on the trend of insecticide resistance and its distribution in these countries since 2000, summarising the mechanisms involved. The prevalence of resistance to these insecticides is increasing in Southeast Asia, and the mechanisms of resistance are reported to be associated with target site mutations, metabolic detoxification, reduced penetration of insecticides via the mosquito cuticle and behavioural changes of mosquitoes. Continuous monitoring of the status of resistance and searching for alternative control measures will be critical for minimising any unpredicted outbreaks and improving public health. This review also provides improved insights into the specific use of insecticides for effective control of mosquitoes in these dengue endemic countries.

Dynamic dengue haemorrhagic fever calculators as clinical decision support tools in adult dengue

BACKGROUND

The objective of this study was to develop multiple prediction tools that calculate the risk of developing dengue haemorrhagic fever.

METHODS

Training data consisted of 1771 individuals from 2006-2008 admitted with dengue fever whereby 304 developed dengue haemorrhagic fever during hospitalisation. Least absolute shrinkage and selection operator regression was used to construct three types of calculators, static admission calculators and dynamic calculators that predict the risk of developing dengue haemorrhagic fever for a subsequent day (DAily Risk Tomorrow [DART]) or for any future point after a specific day since fever onset (DAily Risk Ever [DARE]).

RESULTS

From 119 admission covariates, 35 were in at least one of the calculators, which reported area under the curve (AUC) values of at least 0.72. Addition of person-time data for DART improved AUC to 0.76. DARE calculators displayed a large increase in AUC to 0.79 past day 7 with the inclusion of a strong predictor, maximum temperature on day 6 since onset, indicative of a saddleback fever.

CONCLUSIONS

All calculators performed well when validated with 2005 data. Addition of daily variables further improved the accuracy. These calculators can be used in tandem to assess the risk of dengue haemorrhagic fever upon admission and updated daily to obtain more precise risk estimates.

Analysis of climate factors and dengue incidence in the metropolitan region of Rio de Janeiro, Brazil

Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.

Climate variability, socio-ecological factors and dengue transmission in tropical Queensland, Australia: A Bayesian spatial analysis

BACKGROUND

Dengue is a wide-spread mosquito-borne disease globally with a likelihood of becoming endemic in tropical Queensland, Australia. The aim of this study was to analyse the spatial variation of dengue notifications in relation to climate variability and socio-ecological factors in the tropical climate zone of Queensland, Australia.

METHODS

Data on the number of dengue cases and climate variables including minimum temperature, maximum temperature and rainfall for the period of January 1^st, 2010 to December 31^st, 2015 were obtained for each Statistical Local Area (SLA) from Queensland Health and Australian Bureau of Meteorology, respectively. Socio-ecological data including estimated resident population, percentage of Indigenous population, housing structure (specifically terrace house), socio-economic index and land use types for each SLA were obtained from Australian Bureau of Statistics, and Australian Bureau of Agricultural and Resource Economics and Sciences, respectively. To quantify the relationship between dengue, climate and socio-ecological factors, multivariate Poisson regression models in a Bayesian framework were developed with a conditional autoregressive prior structure. Posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling.

RESULTS

In the tropical climate zone of Queensland, the estimated number of dengue cases was predicted to increase by 85% [95% Credible Interval (CrI): 25%, 186%] and 7% (95% CrI: 0.1%, 14%) for a 1-mm increase in average annual rainfall and 1% increase in the proportion of terrace houses, respectively. The estimated spatial variation (structured random effects) was small compared to the remaining unstructured variation, suggesting that the inclusion of covariates resulted in no residual spatial autocorrelation in dengue data.

CONCLUSIONS

Climate and socio-ecological factors explained much of the heterogeneity of dengue transmission dynamics in the tropical climate zone of Queensland. Results will help to further understand the risk factors of dengue transmission and will provide scientific evidence in designing effective local dengue control programs in the most needed areas.

Molecular evolution of dengue virus types 1 and 4 in Korean travelers

Dengue virus (DV) is a mosquito-borne virus that is endemic to many tropical and subtropical areas. Recently, the annual incidence of DV infection has increased worldwide, including in Korea, due to global warming and increased global travel. We therefore sought to characterize the molecular and evolutionary features of DV-1 and DV-4 isolated from Korean overseas travelers. We used phylogenetic analysis based on the full coding region to classify isolates of DV-1 in Korea into genotype I (43251, KP406802), genotype IV (KP406803), and genotype V (KP406801). In addition, we found that strains of DV-4 belonged to genotype I (KP406806) and genotype II (43257). Evidence of positive selection in DV-1 strains was identified in the C, prM, NS2A, and NS5 proteins, whereas DV-4 showed positive selection only in the non-structural proteins NS2A, NS3, and NS5. The substitution rates per site per year were 5.58 × 10^-4 and 6.72 × 10^-4 for DV-1 and DV-4, respectively, and the time of the most recent common ancestor was determined using the Bayesian skyline coalescent method. In this study, the molecular, phylogenetic, and evolutionary characteristics of Korean DV-1 and DV-4 isolates were evaluated for the first time.

Global, regional, and national dengue burden from 1990 to 2017: A systematic analysis based on the global burden of disease study 2017

BACKGROUND

Dengue is one of the most common vector-borne diseases globally, however, its burden is poorly quantified. Hence, we aimed to report the dengue burden in 195 countries and territories between 1990 and 2017, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017.

METHODS

Following the methodology framework and analytical strategies used in the Global Burden of Disease Study 2017, we analysed the incidence, mortality, and disability-adjusted life years (DALYs) of dengue in geographically defined populations worldwide between 1990 and 2017. We also determined the association between development levels and dengue burden. All estimates were reported as numbers and rates per 100 000 population, with 95% uncertainty intervals.

FINDINGS

Globally, the total number of dengue cases increased from 23 283 274 (95% UI 453 180.7-51 840 670) in 1990 to 104 771 911 (95% UI 63 759 019-158 870 031) in 2017. The age-standardised incidence rate increased from 431.6 (8.4-961.0) per 100 000 population in 1990 to 1371.3 (834.5-2079.3) per 100 000 population in 2017. In addition, the number of deaths due to dengue increased from approximately16 957 (7 613-30 091) in 1990 to 40 467 (17 620-49 778) in 2017. Meanwhile, the global age-standardised death rate increased from 0.31 (0.14-0•56) per 100 000 population in 1990 to 0.53 (0.23-0•65) per 100 000 population in 2017. Overall, there were 2 922 630 DALYs (1 629 424-3 967 492) attributed to dengue in 2017 globally, an increase of 107.6% since 1990 (1 407 571 DALYs [624 016.4-2 510 025]), and the age-standardised DALY rate increased from 26.10 (11.57-46.53) per 100 000 population to 38.25 (21.33-51.93) per 100 000 population between 1990 and 2017. The association between socio-demographic index (SDI) and dengue-related DALYs suggested that the lowest age-standardised DALY rates were found in countries in the low and high-SDI quintile in 2017, and from 1990 to 2017, the age-standardized DALY rate tended to increase in regions with the lowest SDI but declined in regions with the highest SDI. There was a nonlinear association between the socio-demographic index and the healthcare access and quality index and age-standardised DALY rates.

INTERPRETATION

Dengue is a major public health challenge worldwide. While there is remarkable international variation in its incidence, the dengue burden is increasing globally. The results of this study could be useful for policy makers to implement cost-effective interventions and reduce the dengue burden, particularly in countries with high incidence or increasing burden.

FUNDING

This work was supported by a grant from the National Natural Science Foundation of China (NSFC) (grant numbers 81,800,041 and 82,000,078).

COVID-19 in comparison with other emerging viral diseases: risk of geographic spread via travel

PURPOSE OF REVIEW

The COVID-19 pandemic poses a major global health threat. The rapid spread was facilitated by air travel although rigorous travel bans and lockdowns were able to slow down the spread. How does COVID-19 compare with other emerging viral diseases of the past two decades?

RECENT FINDINGS

Viral outbreaks differ in many ways, such as the individuals most at risk e.g. pregnant women for Zika and the elderly for COVID-19, their vectors of transmission, their fatality rate, and their transmissibility often measured as basic reproduction number. The risk of geographic spread via air travel differs significantly between emerging infectious diseases. COVID-19 is not associated with the highest case fatality rate compared with other emerging viral diseases such as SARS and Ebola, but the combination of a high reproduction number, superspreading events and a globally immunologically naïve population has led to the highest global number of deaths in the past 20 decade compared to any other pandemic.

Prediction of dengue outbreak in Selangor Malaysia using machine learning techniques

Dengue fever is a mosquito-borne disease that affects nearly 3.9 billion people globally. Dengue remains endemic in Malaysia since its outbreak in the 1980's, with its highest concentration of cases in the state of Selangor. Predictors of dengue fever outbreaks could provide timely information for health officials to implement preventative actions. In this study, five districts in Selangor, Malaysia, that demonstrated the highest incidence of dengue fever from 2013 to 2017 were evaluated for the best machine learning model to predict Dengue outbreaks. Climate variables such as temperature, wind speed, humidity and rainfall were used in each model. Based on results, the SVM (linear kernel) exhibited the best prediction performance (Accuracy = 70%, Sensitivity = 14%, Specificity = 95%, Precision = 56%). However, the sensitivity for SVM (linear) for the testing sample increased up to 63.54% compared to 14.4% for imbalanced data (original data). The week-of-the-year was the most important predictor in the SVM model. This study exemplifies that machine learning has respectable potential for the prediction of dengue outbreaks. Future research should consider boosting, or using, nature inspired algorithms to develop a dengue prediction model.

What Is the Impact of Lockdowns on Dengue?

PURPOSE OF REVIEW

Societal lockdowns in response to the COVID-19 pandemic have led to unprecedented disruption to daily life across the globe. A collateral effect of these lockdowns may be a change to transmission dynamics of a wide range of infectious diseases that are all highly dependent on rates of contact between humans. With timing, duration and intensity of lockdowns varying country-to-country, the wave of lockdowns in 2020 present a unique opportunity to observe how changes in human contact rates, disease control and surveillance affect dengue virus transmission in a global natural experiment. We explore the theoretical basis for the impact of lockdowns on dengue transmission and surveillance then summarise the current evidence base from country reports.

RECENT FINDINGS

We find considerable variation in the intensity of dengue epidemics reported so far in 2020 with some countries experiencing historic low levels of transmission while others are seeing record outbreaks. Despite many studies warning of the risks of lockdown for dengue transmission, few empirically quantify the impact and issues such as the specific timing of the lockdowns and multi-annual cycles of dengue are not accounted for. In the few studies where such issues have been accounted for, the impact of lockdowns on dengue appears to be limited.

SUMMARY

Studying the impact of lockdowns on dengue transmission is important both in how we deal with the immediate COVID-19 and dengue crisis, but also over the coming years in the post-pandemic recovery period. It is clear lockdowns have had very different impacts in different settings. Further analyses might ultimately allow this unique natural experiment to provide insights into how to better control dengue that will ultimately lead to better long-term control.

Spatiotemporal dynamics, risk areas and social determinants of dengue in Northeastern Brazil, 2014-2017: an ecological study

Background

Dengue fever is an arthropod-borne viral disease caused by dengue virus (DENV) and transmitted by Aedes mosquitoes. The Northeast region of Brazil is characterized by having one of the highest dengue rates in the country, in addition to being considered the poorest region. Here, we aimed to identify spatial clusters with the highest dengue risk, as well as to analyze the temporal behavior of the incidence rate and the effects of social determinants on the disease transmission dynamic in Northeastern Brazil.

Methods

This is an ecological study carried out with all confirmed cases of dengue in the Northeast Brazil between 2014 and 2017. Data were extracted from the National Notifiable Diseases Information System (SINAN) and the Brazilian Institute of Geography and Statistics (IBGE). Local empirical Bayesian model, Moran statistics and spatial scan statistics were applied. The association between dengue incidence rate and social determinants was tested using Moran’s bivariate correlation.

Results

A total of 509 261 cases of dengue were confirmed in the Northeast during the study period, 53.41% of them were concentrated in Pernambuco and Ceará states. Spatial analysis showed a heterogeneous distribution of dengue cases in the region, with the highest rates in the east coast. Four risk clusters were observed, involving 815 municipalities (45.45%). Moreover, social indicators related to population density, education, income, housing, and social vulnerability showed a spatial correlation with the dengue incidence rate.

Conclusions

This study provides information on the spatial dynamics of dengue in northeastern Brazil and its relationship with social determinants and can be used in the formulation of public health policies to reduce the impact of the disease in vulnerable populations.

Modeling the relative role of human mobility, land-use and climate factors on dengue outbreak emergence in Sri Lanka

BACKGROUND

More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission.

METHODS

We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1 km × 1 km spatial resolution and a weekly temporal resolution.

RESULTS

Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions.

CONCLUSIONS

Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.

Epidemiological and clinical analysis of the outbreak of dengue fever in Zhangshu City, Jiangxi Province, in 2019

This study analyzed the epidemiological and clinical features of dengue fever in Zhangshu, Jiangxi Province, in 2019 and provided evidence for the diagnosis, treatment, prevention, and control of dengue fever. A total of 718 dengue fever patients in Zhangshu in 2019 were involved. ELISA and qRT-PCR were used for pathogenic detection of dengue virus. Multiple adjuvant therapies were applied, and the condition of patients after treatment was examined. Patients were between the ages of 0.75 and 92 years old, and all of them had a fever. A total of 519 cases had fatigue, and 413 cases had generalized myalgia and bone ache; 356 cases had dry mouth, 289 cases had bitter taste, and 167 cases felt dry and bitter taste; 279 cases had rash, and 93 cases had pruritus; 587 cases had decreased leukocyte, among which, 7 cases had leukocyte lower than 1 × 10 [9]/L; 380 cases had a low platelet count, and the platelet count of 29 cases was lower than 50 × 10 [9]/L; 488 cases had increased aspartic transaminase, and 460 cases had increased alanine aminotransferase; 5 cases had a severe disease. It proved that the majority of dengue fever sufferers were adults, with the main clinical features being fever and rash and the chief injured organs being the blood system, liver, heart, and gastrointestinal tract. Besides, over 40% of patients had dry and bitter taste, and 12 cases had alopecia after discharge. It indicates that the incidence of dengue fever in Zhangshu is closely related to the sudden population flow and imported cases.

From the threat to the large outbreak: dengue on Reunion Island, 2015 to 2018

Background

With more than 300 million infections estimated annually worldwide, dengue is the most prevalent arboviral infection. On Reunion Island, after a large outbreak in 1977–78, only limited episodes of viral circulation or sporadic cases were reported till 2015.

Aim

Our objective was to document and report on the circulation of dengue virus after the occurrence of a small outbreak during austral summer 2015/16 and until the large outbreak of 2018.

Methods

Beside the mandatory notification of biologically confirmed dengue cases, additional systems of surveillance were set up: estimation of dengue-like syndrome in people seeking care by their family doctor, surveillance of emergency department visits related to dengue, surveillance of hospitalised dengue patients and deaths classifications.

Results

After a moderate outbreak during summer 2015/16 with 231 cases, 2017 was characterised by limited viral circulation (97 cases) which, however, persisted during the austral winter. By February 2018, the number of cases had increased and led to a peak at the beginning of May 2018. More than 6,000 cases were reported this year (dengue virus type 2 only). In addition, six deaths of dengue patients were notified.

Conclusion

In 2017, the persistence of transmission during winter created favourable conditions for the emergence of an epidemic during summer 2018. After this moderate epidemic wave, the viral circulation persisted during winter 2018 for the second year, opening the door for the second wave in 2019 and for potential endemisation of the disease on Reunion Island in the near future.

Aedes Mosquito Salivary Components and Their Effect on the Immune Response to Arboviruses

Vector-borne diseases are responsible for over a billion infections each year and nearly one million deaths. Mosquito-borne dengue virus, West Nile, Japanese encephalitis, Zika, Chikungunya, and Rift Valley Fever viruses constitute major public health problems in regions with high densities of arthropod vectors. During the initial step of the transmission cycle, vector, host, and virus converge at the bite site, where local immune cells interact with the vector's saliva. Hematophagous mosquito saliva is a mixture of bioactive components known to modulate vertebrate hemostasis, immunity, and inflammation during the insect's feeding process. The capacity of mosquito saliva to modulate the host immune response has been well-studied over the last few decades and has led to the consensus that the presence of saliva is linked to the enhancement of virus transmission, host susceptibility, disease progression, viremia levels, and mortality. We review some of the major aspects of the interactions between mosquito saliva and the host immune response that may be useful for future studies on the control of arboviruses.

Modeling and prediction of dengue occurrences in Kolkata, India, based on climate factors

Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.

Transmission dynamics of dengue and chikungunya in a changing climate: do we understand the eco-evolutionary response?

INTRODUCTION

We are witnessing an alarming increase in the burden and range of mosquito-borne arboviral diseases. The transmission dynamics of arboviral diseases is highly sensitive to climate and weather and is further affected by non-climatic factors such as human mobility, urbanization, and disease control. As evidence also suggests, climate-driven changes in species interactions may trigger evolutionary responses in both vectors and pathogens with important consequences for disease transmission patterns.

AREAS COVERED

Focusing on dengue and chikungunya, we review the current knowledge and challenges in our understanding of disease risk in a rapidly changing climate. We identify the most critical research gaps that limit the predictive skill of arbovirus risk models and the development of early warning systems, and conclude by highlighting the potentially important research directions to stimulate progress in this field.

EXPERT OPINION

Future studies that aim to predict the risk of arboviral diseases need to consider the interactions between climate modes at different timescales, the effects of the many non-climatic drivers, as well as the potential for climate-driven adaptation and evolution in vectors and pathogens. An important outcome of such studies would be an enhanced ability to promulgate early warning information, initiate adequate response, and enhance preparedness capacity.

The first licensed dengue vaccine: can it be used in travelers?

PURPOSE OF REVIEW

The first dengue vaccine (Dengvaxia) was endorsed by the European Medicine Agency and the US Food and Drug Administration. Given the excess risk of severe dengue in seronegative vaccinees, use is restricted to seropositive individuals. Dengvaxia confers high protection against severe dengue in seropositive vaccinees.

RECENT FINDINGS

With increasing global travel, the probability of travelers being seropositive increases. Such seropositive travelers may be at increased risk of severe dengue as a result of a second dengue infection during repeat travel. Nevertheless, the use of Dengvaxia in travelers requires a careful analysis of all the factors. Seropositive travelers only present a minority of all travelers. A validated rapid diagnostic test to screen for dengue serostatus is not yet available. Such a test should be highly specific to avoid inadvertent vaccination of seronegative individuals. The three-dose regimen precludes the use in most travelers who tend to present at travel clinics less than 6 weeks prior to departure. Furthermore, questions about potential sub-optimal immunogenicity in seropositives in nonendemic settings, and the need and timing of boosters remain unanswered.

SUMMARY

Although there could potentially be substantial protection against severe dengue in seropositive travelers, Dengvaxia is far from an ideal travel vaccine.

A spatial-temporal study for the spread of dengue depending on climate factors in Pakistan (2006-2017)

BACKGROUND

In Pakistan, dengue fever has become a major concerning factor, given that it is a relatively new disease compared to malaria. The number of people affected by dengue fever has increased at least 10-fold in the last 15 years in specific areas of Pakistan. Therefore, it is necessary to analyse this disease to reduce or prevent the effects of dengue fever in the region.

METHODS

Geographical information system (GIS) maps are used to identify the intensity of the spread according to the count of affected people in our study area. Generalised linear modelling (GLM) is used to study the significance of factors associated with dengue fever.

RESULTS

The dengue virus is present throughout the year in specific areas of Pakistan. Karachi and Lahore are most significantly affected with cases in these two most populous cities of Pakistan reported every year. In the study period (2006-2017), 2011 was the most devastating year for Pakistan. Lahore recorded more than 17,000 confirmed cases with 290 deaths in a single year. The GLM analysis shows rainfall, the average maximum temperature, and hospitals to be significant factors in the prevalence of dengue fever.

CONCLUSION

This study finds that Sindh and Khyber Pakhtunkhwa are two of the primarily vulnerable provinces for the spread of dengue fever. Punjab has observed sporadic increases in dengue fever cases. In Pakistan, dengue cases increase in the rainfall season, especially during monsoon season. Lack of proper hospitals and clinics are another major factor, and mobile hospitals are needed in remote hotspot regions often affected by dengue fever. Finally, improved sanitation systems in metropoles would facilitate reducing breeding grounds for Aedes Aegypti larvae.

Predicting re-emergence times of dengue epidemics at low reproductive numbers: DENV1 in Rio de Janeiro, 1986-1990

Predicting arbovirus re-emergence remains challenging in regions with limited off-season transmission and intermittent epidemics. Current mathematical models treat the depletion and replenishment of susceptible (non-immune) hosts as the principal drivers of re-emergence, based on established understanding of highly transmissible childhood diseases with frequent epidemics. We extend an analytical approach to determine the number of ‘skip’ years preceding re-emergence for diseases with continuous seasonal transmission, population growth and under-reporting. Re-emergence times are shown to be highly sensitive to small changes in low R₀ (secondary cases produced from a primary infection in a fully susceptible population). We then fit a stochastic Susceptible–Infected–Recovered (SIR) model to observed case data for the emergence of dengue serotype DENV1 in Rio de Janeiro. This aggregated city-level model substantially over-estimates observed re-emergence times either in terms of skips or outbreak probability under forward simulation. The inability of susceptible depletion and replenishment to explain re-emergence under ‘well-mixed’ conditions at a city-wide scale demonstrates a key limitation of SIR aggregated models, including those applied to other arboviruses. The predictive uncertainty and high skip sensitivity to epidemiological parameters suggest a need to investigate the relevant spatial scales of susceptible depletion and the scaling of microscale transmission dynamics to formulate simpler models that apply at coarse resolutions.

Inference on dengue epidemics with Bayesian regime switching models

Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific autoregressive processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Posterior predictive checks indicate that BRS replicates temporal trends in Dengue transmissions well and nowcast accuracy assessed using a post-hoc classification scheme showed that BRS classification accuracy is robust even under limited data with the AUC-ROC at 0.935. LASSO-based regression and bootstrapping was used to account for plausibly high dimensions of climatic factors affecting Dengue transmissions, which was then estimated using cross-validation to conduct statistical inference on long-run climatic effects on the estimated regimes. BRS estimates epidemic and endemic regimes of dengue in Singapore which are characterized by persistence across time, lasting an average of 20 weeks and 66 weeks respectively, with a low probability of transitioning away from their regimes. Climate analysis with LASSO indicates that long-run climatic effects up to 20 weeks ago do not differentiate epidemic and endemic regimes. Lastly, by fitting BRS to simulated disease data generated from a stochastic Susceptible-Infected-Recovered model, mechanistic links between infectivity and regimes classified using BRS were provided. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected.

Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Assessments against various baseline showed that BRS performs better in characterizing dengue transmissions. The dengue regimes estimated by BRS are characterized by their persistent nature. Next, climate analysis showed no short nor long term associations between classified regimes with climate. Lastly, fitting BRS to simulated disease data generated from a mechanistic model, we showed links between disease infectivity and regimes classified using BRS. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected.

The time series seasonal patterns of dengue fever and associated weather variables in Bangkok (2003-2017)

Background

In Thailand, dengue fever is one of the most well-known public health problems. The objective of this study was to examine the epidemiology of dengue and determine the seasonal pattern of dengue and its associate to climate factors in Bangkok, Thailand, from 2003 to 2017.

Methods

The dengue cases in Bangkok were collected monthly during the study period. The time-series data were extracted into the trend, seasonal, and random components using the seasonal decomposition procedure based on loess. The Spearman correlation analysis and artificial neuron network (ANN) were used to determine the association between climate variables (humidity, temperature, and rainfall) and dengue cases in Bangkok.

Results

The seasonal-decomposition procedure showed that the seasonal component was weaker than the trend component for dengue cases during the study period. The Spearman correlation analysis showed that rainfall and humidity played a role in dengue transmission with correlation efficiency equal to 0.396 and 0.388, respectively. ANN showed that precipitation was the most crucial factor. The time series multivariate Poisson regression model revealed that increasing 1% of rainfall corresponded to an increase of 3.3% in the dengue cases in Bangkok. There were three models employed to forecast the dengue case, multivariate Poisson regression, ANN, and ARIMA. Each model displayed different accuracy, and multivariate Poisson regression was the most accurate approach in this study.

Conclusion

This work demonstrates the significance of weather in dengue transmission in Bangkok and compares the accuracy of the different mathematical approaches to predict the dengue case. A single model may insufficient to forecast precisely a dengue outbreak, and climate factor may not only indicator of dengue transmissibility.

Reviewing estimates of the basic reproduction number for dengue, Zika and chikungunya across global climate zones

BACKGROUND

Globally, dengue, Zika virus, and chikungunya are important viral mosquito-borne diseases that infect millions of people annually. Their geographic range includes not only tropical areas but also sub-tropical and temperate zones such as Japan and Italy. The relative severity of these arboviral disease outbreaks can vary depending on the setting. In this study we explore variation in the epidemiologic potential of outbreaks amongst these climatic zones and arboviruses in order to elucidate potential reasons behind such differences.

METHODOLOGY

We reviewed the peer-reviewed literature (PubMed) to obtain basic reproduction number (R₀) estimates for dengue, Zika virus, and chikungunya from tropical, sub-tropical and temperate regions. We also computed R₀ estimates for temperate and sub-tropical climate zones, based on the outbreak curves in the initial outbreak phase. Lastly we compared these estimates across climate zones, defined by latitude.

RESULTS

Of 2115 studies, we reviewed the full text of 128 studies and included 65 studies in our analysis. Our results suggest that the R₀ of an arboviral outbreak depends on climate zone, with lower R₀ estimates, on average, in temperate zones (R₀ = 2.03) compared to tropical (R₀ = 3.44) and sub-tropical zones (R₀ = 10.29). The variation in R₀ was considerable, ranging from 0.16 to 65. The largest R₀ was for dengue (65) and was estimated by the Ross-Macdonald model in the tropical zone, whereas the smallest R₀ (0.16) was for Zika virus and was estimated statistically from an outbreak curve in the sub-tropical zone.

CONCLUSIONS

The results indicate climate zone to be an important determinant of the basic reproduction number, R₀, for dengue, Zika virus, and chikungunya. The role of other factors as determinants of R₀, such as methods, environmental and social conditions, and disease control, should be further investigated. The results suggest that R₀ may increase in temperate regions in response to global warming, and highlight the increasing need for strengthening preparedness and control activities.

Severe dengue in travellers: pathogenesis, risk and clinical management

RATIONALE FOR REVIEW

Dengue is a frequent cause of febrile illness among travellers and has overtaken malaria as the leading cause of febrile illness for those traveling to Southeast Asia. The purpose is to review the risk of dengue and severe dengue in travellers with a particular focus on the pathogenesis and clinical management of severe dengue.

RISK, PATHOGENESIS AND CLINICAL MANAGEMENT

The risk of travel-acquired dengue depends on destination, season and duration of travel and activities during travel. Seroconversion rates reported in travellers, therefore, vary between <1% and >20%. The most common life-threatening clinical response to dengue infection is the dengue vascular permeability syndrome, epidemiologically linked to secondary infection, but can also occur in primary infection. Tertiary and quaternary infections are usually associated with mild or no disease. Antibody-dependent enhancement, viral factors, age, host factors and clinical experience of the managing physician modulate the risk of progressing to severe dengue. The relative risk of severe dengue in secondary versus primary infection ranges from 2 to 7. The absolute risk of severe dengue in children in highly endemic areas is ~0.1% per year for primary infections and 0.4% for secondary infections. About 2-4% of secondary infections lead to severe dengue. Severe dengue and death are both relatively rare in general travellers but more frequently in those visiting friends and relatives. Clinical management of severe dengue depends on judicious use of fluid rehydration.

CONCLUSIONS

Although dengue is a frequent cause of travel illness, severe dengue and deaths are rare. Nevertheless, dengue infections can interrupt travel and lead to evacuation and major out-of-pocket costs. Dengue is more frequent than many other travel-related vaccine preventable diseases, such as hepatitis A, hepatitis B, rabies, Japanese encephalitis and yellow fever, indicating a need for a dengue vaccine for travellers.