Dengue prevention and 35 years of vector control in Singapore

Behavioral responses and life history traits of Taiwanese and Indonesian populations of Aedes aegypti surviving deltamethrin-clothianidin treatment

BACKGROUND

Indoor residual spraying (IRS) capitalizes on the natural behavior of mosquitoes because Aedes aegypti commonly seeks indoor resting sites after a blood meal. This behavior allows mosquitoes to be exposed to insecticide-treated surfaces and subsequently killed. Combinations of deltamethrin and clothianidin with different modes of action have shown promise in IRS, effectively targeting both susceptible and pyrethroid-resistant malaria vectors. However, the effects of this approach on Aedes mosquitoes remain unclear. The present study tested the effects of deltamethrin-clothianidin mixture treatment on behavioral responses and life history traits of Taiwanese and Indonesian populations of Ae. aegypti.

METHODS

We adopted an excito-repellent approach to explore the behavioral responses of pyrethroid-resistant Ae. aegypti populations from Indonesia and Taiwan to a deltamethrin-clothianidin mixture used in contact irritancy and non-contact repellency treatments. We further evaluated the life history traits of surviving mosquitoes (i.e., delayed mortality after 7-day post-treatment, longevity, fecundity, and egg hatching) and investigated the potential transgenerational hormetic effects of insecticide exposure (i.e., development rate and survival of immatures and adult mosquitos).

RESULTS

All tested field populations of Ae. aegypti displayed strong contact irritancy responses; the percentage of escape upon insecticide exposure ranged from 38.8% to 84.7%. However, repellent effects were limited, with the escape percentage ranging from 4.3% to 48.9%. We did not observe immediate knockdown or mortality after 24 h, and less than 15% of the mosquitoes exhibited delayed mortality after a 7-day exposure period. However, the carryover effects of insecticide exposure on the survival of immature mosquitoes resulted in approximately 25% higher immature mortality than that in the control. By contrast, we further documented stimulated survivor reproduction and accelerated transgenerational immature development resulting from the sublethal effects of the insecticide mixture. In particular, the number of eggs laid by treated (both treatments) female mosquitoes increased by at least 60% compared with that of eggs laid by control female mosquitoes.

CONCLUSIONS

IRS with deltamethrin-clothianidin effectively deters Aedes mosquitoes from entering residential areas and thereby reduces mosquito bites. However, the application rate (deltamethrin: 25 mg/m2; clothianidin: 200 mg/m2) may be insufficient to effectively kill Aedes mosquitoes. Insecticide response appears to vary across mosquito species; their behavioral and physiological responses to sublethal doses have crucial implications for mosquito control programs.

Preferences and Demand for Mosquito Control among Dengue-Endemic Communities in Peñuelas, Puerto Rico: An Application of the Best-Worst Choice Model

Aedes aegypti is the primary vector of dengue virus and threatens 3.9 billion people living in many tropical and subtropical countries. Prevention and reduction of dengue and other Aedes-borne viruses, including Zika and chikungunya, requires control of mosquito populations. Community mobilization and input are essential components of vector control efforts. Many vector control campaigns do not engage communities prior to implementation, leading to program failure. Those that do often conduct basic knowledge, attitude, and practice surveys that are not designed to explicitly elicit preferences. Here, we applied a novel stated preference elicitation tool, best-worst choice, to understand preferences, willingness to participate, and willingness to pay for mosquito control in dengue-endemic communities of Peñuelas, Puerto Rico. Findings revealed that the community preferred mosquito control programs that are 1) applied at the neighborhood level, 2) implemented by the local government, and 3) focused specifically on reducing disease transmission (e.g., dengue) instead of mosquito nuisance. Programs targeting the reduction of disease transmission and higher educational level of participants increased willingness to participate. Participants were willing to pay an average of $72 annually to have a program targeting the reduction of diseases such as dengue. This study serves as a model to engage communities in the design of mosquito control programs and improve stakeholders' decision-making.

Cell Type Variability in the Incorporation of Lipids in the Dengue Virus Virion

A lipid bilayer produced from the host membrane makes up around 20% of the weight of the dengue virus (DENV) virion and is crucial for virus entry. Despite its significance, the virion's lipid composition is still poorly understood. In tandem with lipid profiles of the cells utilised to generate the virions, this work determined a partial lipid profile of DENV virions derived from two cell lines (C6/36 and LLC-MK₂). The results showed distinctive profiles between the two cell types. In the mammalian LLC-MK₂ cells, 30.8% (73/237 identified lipid species; 31 upregulated, 42 downregulated) of lipid species were altered in response to infection, whilst in insect C6/36 cells only 12.0% (25/208; 19 upregulated, 6 downregulated) of lipid species showed alterations in response to infection. For virions from LLC-MK₂ cells, 14 lipids were detected specifically in virions with a further seven lipids being enriched (over mock controls). For virions from C6/36 cells, 43 lipids were detected that were not seen in mock preparations, with a further 16 being specifically enriched (over mock control). These results provide the first lipid description of DENV virions produced in mammalian and mosquito cells, as well as the lipid changes in the corresponding infected cells.

Geographical clusters of dengue outbreak in Singapore during the Covid-19 nationwide lockdown of 2020

Dengue, a mosquito-transmitted viral disease, has posed a public health challenge to Singaporean residents over the years. In 2020, Singapore experienced an unprecedented dengue outbreak. We collected a dataset of geographical dengue clusters reported by the National Environment Agency (NEA) from 15 February to 9 July in 2020, covering the nationwide lockdown associated with Covid-19 during the period from 7 April to 1 June. NEA regularly updates the dengue clusters during which an infected person may be tagged to one cluster based on the most probable infection location (residential apartment or workplace address), which is further matched to fine-grained spatial units with an average coverage of about 1.35 km². Such dengue cluster dataset helps not only reveal the dengue transmission patterns, but also reflect the effects of lockdown on dengue spreading dynamics. The resulting data records are released in simple formats for easy access to facilitate studies on dengue epidemics.

Measurement(s)	dengue infection locations
Technology Type(s)	NEA’s disclosured report
Factor Type(s)	Singapore’s dengue in in 2020

Anti-DENV-NS1 monoclonal antibody for the differential histopathological diagnosis of hemorrhagic fever caused by dengue

Dengue is the most prevalent arboviral disease in humans in tropical and subtropical regions, especially in urban areas, and can cause major epidemics. Although a self-limiting illness, it may sometimes have serious hemorrhagic manifestations, and the outcome of dengue hemorrhagic fever has similar clinical manifestations as in other infections, which could result in death. Therefore, autopsy procedures are required under certain circumstances such as in hemorrhagic fevers, sometimes to confirm or to clarify the diagnosis that may have epidemiological consequences. Normally, the Immunohistochemistry Laboratory of the Pathology Center of Adolfo Lutz Institute receives autopsy samples from different hospitals in Sao Paulo State to confirm a previous diagnosis, especially hemorrhagic fever of infectious etiology. For this diagnosis, we have been using a mouse polyclonal antibody to dengue virus that often does not provide a clear conclusion, because of background staining or no relevant immunostaining, which hampers the histopathological analysis. Accordingly, in the present study, anti-DENV-NS1 monoclonal antibody (4H2) was tested to determine its accuracy in immunohistochemical analysis. Twenty-four autopsy cases of hemorrhagic febrile syndrome showing histopathological alterations compatible with dengue disease were studied: twenty cases were confirmed by RT-PCR for DENV-2 and in four by RT-PCR for yellow fever virus. Samples from autopsied cases of deaths caused by other infectious diseases (two meningitis C and two severe acute respiratory syndrome caused by influenza A H1N1) were included as negative control cases. Positive immunostaining for DENV-NS1 was detected in 16/20 (80%) liver samples and 11/15 (73%) spleen samples from autopsied hemorrhagic dengue patients, whereas the polyclonal antibody detected DENV antigens in 12/20 (60%) liver and in 6/15 (40%) spleen samples from the same cases. Positive results were not obtained with liver biopsy samples from yellow fever or Neisseria meningitides and Flu-A cases. 4H2 mAb recognizes the native protein of the four DENV serotypes in infected cells and did not cross-react with native ZIKV- or CHKV-infected cells by immunohistochemical assay, so it is a useful tool for differential histopathological conclusion of acute febrile hemorrhagic deaths.

Adaptive Evolution as a Driving Force of the Emergence and Re-Emergence of Mosquito-Borne Viral Diseases

Emerging and re-emerging mosquito-borne viral diseases impose a significant burden on global public health. The most common mosquito-borne viruses causing recent epidemics include flaviviruses in the family Flaviviridae, including Dengue virus (DENV), Zika virus (ZIKV), Japanese encephalitis virus (JEV) and West Nile virus (WNV) and Togaviridae viruses, such as chikungunya virus (CHIKV). Several factors may have contributed to the recent re-emergence and spread of mosquito-borne viral diseases. Among these important causes are the evolution of mosquito-borne viruses and the genetic mutations that make them more adaptive and virulent, leading to widespread epidemics. RNA viruses tend to acquire genetic diversity due to error-prone RNA-dependent RNA polymerases, thus promoting high mutation rates that support adaptation to environmental changes or host immunity. In this review, we discuss recent findings on the adaptive evolution of mosquito-borne viruses and their impact on viral infectivity, pathogenicity, vector fitness, transmissibility, epidemic potential and disease emergence.

Dengue virus infection modifies mosquito blood-feeding behavior to increase transmission to the host

Because dengue viruses are spread by mosquitoes during biting, transmission capacity depends on mosquito-biting behavior. For this reason, it is critical to understand how infection in mosquitoes influences biting. To answer this question, we deployed a multidisciplinary approach including high-resolution, multivariate biting behavior monitoring on mice, in vivo transmission assay, and mathematical modeling. We demonstrated that infected mosquitoes are more attracted to mice and bite more often to get the same amount of blood as uninfected mosquitoes. While the effect of increased attraction to host on transmission capacity is trivial, we showed that increased number of bites results in successive transmission. Eventually, we calculated that the infection-induced behavior changes tripled transmission capacity of mosquitoes.

Mosquito blood-feeding behavior is a key determinant of the epidemiology of dengue viruses (DENV), the most-prevalent mosquito-borne viruses. However, despite its importance, how DENV infection influences mosquito blood-feeding and, consequently, transmission remains unclear. Here, we developed a high-resolution, video-based assay to observe the blood-feeding behavior of Aedes aegypti mosquitoes on mice. We then applied multivariate analysis on the high-throughput, unbiased data generated from the assay to ordinate behavioral parameters into complex behaviors. We showed that DENV infection increases mosquito attraction to the host and hinders its biting efficiency, the latter resulting in the infected mosquitoes biting more to reach similar blood repletion as uninfected mosquitoes. To examine how increased biting influences DENV transmission to the host, we established an in vivo transmission model with immuno-competent mice and demonstrated that successive short probes result in multiple transmissions. Finally, to determine how DENV-induced alterations of host-seeking and biting behaviors influence dengue epidemiology, we integrated the behavioral data within a mathematical model. We calculated that the number of infected hosts per infected mosquito, as determined by the reproduction rate, tripled when mosquito behavior was influenced by DENV infection. Taken together, this multidisciplinary study details how DENV infection modulates mosquito blood-feeding behavior to increase vector capacity, proportionally aggravating DENV epidemiology. By elucidating the contribution of mosquito behavioral alterations on DENV transmission to the host, these results will inform epidemiological modeling to tailor improved interventions against dengue.

Fine-scale estimation of effective reproduction numbers for dengue surveillance

The effective reproduction number R_t is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used R_t as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of R_t for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated R_t by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of R_t from each proposed method and determined exogenous temporal and spatial drivers for R_t in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R²_EpiEstim = 0.95, R²_EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE _EpiEstim = 1.23, MASE_EpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of R_t as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of R_t at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

The effective reproduction number R_t is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used R_t as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of R_t for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated R_t by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of R_t from each proposed method and determined exogenous temporal and spatial drivers for R_t in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved high accuracy, but disparities in performance were large at finer spatial scales when case counts are low. This study demonstrates the potential of R_t as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of R_t at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

Impact of environmental factors on the spread of dengue fever in Sri Lanka

Dengue fever is a mosquito-borne viral disease caused by the dengue virus of the Flaviviridae family and is responsible for colossal health and economic burden worldwide. This study aimed to investigate the effect of environmental, seasonal, and spatial variations on the spread of dengue fever in Sri Lanka. The study used secondary data of monthly dengue infection and the monthly average of environmental parameters of 26 Sri Lankan regions from January 2015 to December 2019. Besides the descriptive measurements, Kendall's tau_b, Spearman's rho, and Kruskal-Wallis H test have been performed as bivariate analyses. The multivariate generalized linear negative binomial regression model was applied to determine the impacts of meteorological factors on dengue transmission. The aggregate negative binomial regression model disclosed that precipitation (odds ratio: 0.97, p < 0.05), humidity (odds ratio: 1.05, p < 0.01), and air pressure (odds ratio: 1.46, p < 0.01) were significantly influenced the spread of dengue fever in Sri Lanka. The bioclimatic zone is the vital factor that substantially affects the dengue infection, and the wet zone (odds ratio: 6.41, p < 0.05) was more at-risk than the dry zone. The climate season significantly influenced dengue fever transmission, and a higher infection rate was found (odds ratio: 1.46, p < 0.01) in the northeast monsoon season. The findings of this study facilitate policymakers to improve the existing dengue control strategies focusing on the meteorological condition in the local as well as global perspectives.

Lipid Interactions Between Flaviviruses and Mosquito Vectors

Mosquito-borne flaviviruses, such as dengue (DENV), Zika (ZIKV), yellow fever (YFV), West Nile (WNV), and Japanese encephalitis (JEV) viruses, threaten a large part of the human populations. In absence of therapeutics and effective vaccines against each flaviviruses, targeting viral metabolic requirements in mosquitoes may hold the key to new intervention strategies. Development of metabolomics in the last decade opened a new field of research: mosquito metabolomics. It is now clear that flaviviruses rely on mosquito lipids, especially phospholipids, for their cellular cycle and propagation. Here, we review the biosyntheses of, biochemical properties of and flaviviral interactions with mosquito phospholipids. Phospholipids are structural lipids with a polar headgroup and apolar acyl chains, enabling the formation of lipid bilayer that form plasma- and endomembranes. Phospholipids are mostly synthesized through the de novo pathway and remodeling cycle. Variations in headgroup and acyl chains influence phospholipid physicochemical properties and consequently the membrane behavior. Flaviviruses interact with cellular membranes at every step of their cellular cycle. Recent evidence demonstrates that flaviviruses reconfigure the phospholipidome in mosquitoes by regulating phospholipid syntheses to increase virus multiplication. Identifying the phospholipids involved and understanding how flaviviruses regulate these in mosquitoes is required to design new interventions.

High resolution proteomics of Aedes aegypti salivary glands infected with either dengue, Zika or chikungunya viruses identify new virus specific and broad antiviral factors

Arboviruses such as dengue (DENV), Zika (ZIKV) and chikungunya (CHIKV) viruses infect close to half a billion people per year, and are primarily transmitted through Aedes aegypti bites. Infection-induced changes in mosquito salivary glands (SG) influence transmission by inducing antiviral immunity, which restricts virus replication in the vector, and by altering saliva composition, which influences skin infection. Here, we profiled SG proteome responses to DENV serotype 2 (DENV2), ZIKV and CHIKV infections by using high-resolution isobaric-tagged quantitative proteomics. We identified 218 proteins with putative functions in immunity, blood-feeding or related to the cellular machinery. We observed that 58, 27 and 29 proteins were regulated by DENV2, ZIKV and CHIKV infections, respectively. While the regulation patterns were mostly virus-specific, we separately depleted four uncharacterized proteins that were upregulated by all three viral infections to determine their effects on these viral infections. Our study suggests that gamma-interferon responsive lysosomal thiol-like (GILT-like) has an anti-ZIKV effect, adenosine deaminase (ADA) has an anti-CHIKV effect, salivary gland surface protein 1 (SGS1) has a pro-ZIKV effect and salivary gland broad-spectrum antiviral protein (SGBAP) has an antiviral effect against all three viruses. The comprehensive description of SG responses to three global pathogenic viruses and the identification of new restriction factors improves our understanding of the molecular mechanisms influencing transmission.

Aedes-AI: Neural network models of mosquito abundance

We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluate the networks in their ability to replicate the spatiotemporal features of mosquito populations predicted by the mechanistic model, and discuss how augmenting the training data with time series that emphasize specific dynamical behaviors affects model performance. We conclude with an outlook on how such equation-free models may facilitate vector control or the estimation of disease risk at arbitrary spatial scales.

Aedes aegypti mosquitoes affect millions of people each year through infectious diseases such as chikungunya, dengue, and Zika. Because local vector levels need to be sufficiently high for associated outbreaks to occur, the ability to estimate mosquito abundance is a central component of assessing disease risk. The mosquito landscape model (MoLS) is a mechanistic model that estimates Aedes aegypti abundance from local weather time series, and is able to reproduce trends observed in surveillance data. However, scaling this up to a large number of locations is resource intensive, requiring a high-performance computing system. In this article, we develop artificial neural network models that are significantly faster than MoLS and can produce abundance estimates directly from local weather data. This approach reduces the computational time associated with estimating local mosquito levels, thereby allowing for a corresponding increase in the spatiotemporal resolution of these predictions. We compare network design choices, including architecture and training data, in their ability to accurately reproduce MoLS estimates and analyze model performance in locations across the contiguous United States.

A Household-Based Survey to Understand Factors Influencing Awareness, Attitudes and Knowledge towards Wolbachia-Aedes Technology

In 2016, Singapore introduced the release of male Wolbachia-Aedes mosquitoes to complement vector control efforts and suppress Aedes aegypti mosquitoes in selected study sites. With ongoing expansion of Project Wolbachia-Singapore to cover larger areas, a household-based survey was conducted between July 2019 to February 2020 in two Project Wolbachia study sites using a structured questionnaire, to evaluate current sentiments and assess the need for enhanced public messaging and engagement. The association of factors that influence awareness, attitudes, and knowledge towards the use of Wolbachia-Aedes technology was analysed using Pearson's Chi-square test and binary logistic regression. Of 500 respondents, 74.8% were aware of Project Wolbachia-Singapore. Comparatively, the level of knowledge on Wolbachia-Aedes technology was lower, suggesting knowledge gaps that require enhanced communication and messaging to address misinformation. Longer exposure to the project predicted greater awareness, whereas higher education levels predicted higher knowledge levels. Younger age groups and higher education levels were associated with high acceptance towards the project. High levels of trust and acceptance towards the project were also observed across the population. The public's positive perception of the project is a testament to the effective public communication undertaken to date and will facilitate programme expansion.

Ovitrap surveillance of dengue vector mosquitoes in Bandung City, West Java Province, Indonesia

Larval surveillance is the central approach for monitoring dengue vector populations in Indonesia. However, traditional larval indices are ineffective for measuring mosquito population dynamics and predicting the dengue transmission risk. We conducted a 14-month ovitrap surveillance. Eggs and immature mosquitoes were collected on a weekly basis from an urban village of Bandung, namely Sekejati. Ovitrap-related indices, namely positive house index (PHI), ovitrap index (OI), and ovitrap density index (ODI), were generated and correlated with environmental variables, housing type (terraced or high-density housing), ovitrap placement location (indoor or outdoor; household or public place), and local dengue cases. Our results demonstrated that Aedes aegypti was significantly predominant compared with Aedes albopictus at each housing type and ovitrap placement location. Ovitrap placement locations and rainfall were the major factors contributing to variations in PHI, OI, and ODI, whereas the influences of housing type and temperature were subtle. Indoor site values were significantly positively correlated to outdoor sites’ values for both OI and ODI. OI and ODI values from households were best predicted with those from public places at 1- and 0-week lags, respectively. Weekly rainfall values at 4- and 3-week lags were the best predictors of OI and ODI for households and public places, respectively. Monthly mean PHI, OI, and ODI were significantly associated with local dengue cases. In conclusion, ovitrap may be an effective tool for monitoring the population dynamics of Aedes mosquitoes, predicting dengue outbreaks, and serving as an early indicator to initiate environmental clean-up. Ovitrap surveillance is easy for surveyors if they are tasked with a certain number of ovitraps at a designated area, unlike the existing larval surveillance methodology, which entails identifying potential breeding sites largely at the surveyors’ discretion. Ovitrap surveillance may reduce the influence of individual effort in larval surveillance that likely causes inconsistency in results.

The dengue virus, transmitted by Aedes vectors, has been continuously spreading in tropical and subtropical countries, causing illness and fatality. Given the lack of a cost-effective dengue vaccine, the vector control approach for reducing the Aedes population remains the key method for mitigating dengue transmission. For a successful vector control program, an effective vector surveillance system is crucial for precisely predicting the spatial and temporal risk of a dengue outbreak. The ovitrap system improves data collection efficiency, aiding long-term dengue vector monitoring activities. This study is one of the few long-term dengue vector surveillance programs in Indonesia and provides compelling evidence of the need to improve the existing conventional larval surveillance system. The results demonstrated that two dengue vector mosquitoes, A. aegypti and A. albopictus, were present in the study area, and A. aegypti was more prevalent than A. albopictus. We observed an interactive relationship between ovitrap placement and rainfall in the dynamics of ovitrap-related indices; understanding this relationship allows for timely initiation of vector control and intervention strategies. We conclude that the ovitrap surveillance system is a sensitive tool for monitoring the population dynamics of Aedes vectors, predicting dengue outbreaks, and potentially improving community-based conventional larval surveillance.

Case-area targeted interventions (CATI) for reactive dengue control: Modelling effectiveness of vector control and prophylactic drugs in Singapore

BACKGROUND

Targeting interventions to areas that have recently experienced cases of disease is one strategy to contain outbreaks of infectious disease. Such case-area targeted interventions (CATI) have become an increasingly popular approach for dengue control but there is little evidence to suggest how precisely targeted or how recent cases need to be, to mount an effective response. The growing interest in the development of prophylactic and therapeutic drugs for dengue has also given new relevance for CATI strategies to interrupt transmission or deliver early treatment.

METHODS/PRINCIPAL FINDINGS

Here we develop a patch-based mathematical model of spatial dengue spread and fit it to spatiotemporal datasets from Singapore. Simulations from this model suggest CATI strategies could be effective, particularly if used in lower density areas. To maximise effectiveness, increasing the size of the radius around an index case should be prioritised even if it results in delays in the intervention being applied. This is partially because large intervention radii ensure individuals receive multiple and regular rounds of drug dosing or vector control, and thus boost overall coverage. Given equivalent efficacy, CATIs using prophylactic drugs are predicted to be more effective than adult mosquito-killing vector control methods and may even offer the possibility of interrupting individual chains of transmission if rapidly deployed. CATI strategies quickly lose their effectiveness if baseline transmission increases or case detection rates fall.

CONCLUSIONS/SIGNIFICANCE

These results suggest CATI strategies can play an important role in dengue control but are likely to be most relevant for low transmission areas where high coverage of other non-reactive interventions already exists. Controlled field trials are needed to assess the field efficacy and practical constraints of large operational CATI strategies.

Severe Dengue Epidemic, Sri Lanka, 2017

In 2017, a dengue epidemic of unexpected magnitude occurred in Sri Lanka. A total of 186,101 suspected cases and 440 dengue-related deaths occurred. We conducted a comprehensive analysis of this epidemic by comparing national surveillance data for 2017 with data from the preceding 5 years. In all Sri Lanka districts, dengue incidence in 2017 increased significantly over incidence during the previous 5 years. Older schoolchildren and young adults were more clinically symptomatic than those at extremes of age. Limited virologic surveillance showed the dominant circulating variant was dengue virus type 2 cosmopolitan genotype in the most affected district. One quarter of total annual cases were reported 5 weeks after the southwest monsoon started. Changes in vector abundance were not predictive of the increased incidence. Direct government expenditures on dengue control activities in 2017 were US $12.7 million. The lessons learned from this outbreak are useful for other tropical nations facing increasing dengue incidence.

Serological biomarker for assessing human exposure to Aedes mosquito bites during a randomized vector control intervention trial in northeastern Thailand

Background

Aedes mosquitoes are vectors for several major arboviruses of public health concern including dengue viruses. The relationships between Aedes infestation and disease transmission are complex wherein the epidemiological dynamics can be difficult to discern because of a lack of robust and sensitive indicators for predicting transmission risk. This study investigates the use of anti-Aedes saliva antibodies as a serological biomarker for Aedes mosquito bites to assess small scale variations in adult Aedes density and dengue virus (DENV) transmission risk in northeastern Thailand. Individual characteristics, behaviors/occupation and socio-demographics, climatic and epidemiological risk factors associated with human-mosquito exposure are also addressed.

Methods

The study was conducted within a randomized clustered control trial in Roi Et and Khon Kaen provinces over a consecutive 19 months period. Thirty-six (36) clusters were selected, each of ten houses. Serological and entomological surveys were conducted in all houses every four months and monthly in three sentinel households per cluster between September 2017 and April 2019 for blood spot collections and recording concurrent immature and adult Aedes indices. Additionally, the human exposure to Aedes mosquito bites (i.e., Mosquito Exposure Index or MEI) was estimated by ELISA measuring levels of human antibody response to the specific Nterm-34 kDa salivary antigen. The relationships between the MEI, vector infestation indices (adult and immature stages) and vector DENV infection were evaluated using a two-level (house and individual levels) mixed model analysis with one-month lag autoregressive correlation.

Results

There was a strong positive relationship between the MEI and adult Aedes (indoor and outdoor) density. Individuals from households with a medium mosquito density (mean difference: 0.091, p<0.001) and households with a high mosquito density (mean difference: 0.131, p<0.001) had higher MEI’s compared to individuals from households without Aedes. On a similar trend, individuals from households with a low, medium or high indoor Aedes densities (mean difference: 0.021, p<0.007, 0.053, p<0.0001 and 0.037, p<0.0001 for low, medium and high levels of infestation, respectively) had higher MEI than individuals from houses without indoor Aedes. The MEI was driven by individual characteristics, such as gender, age and occupation/behaviors, and varied according to climatic, seasonal factors and vector control intervention (p<0.05). Nevertheless, the study did not demonstrate a clear correlation between MEI and the presence of DENV-infected Aedes.

Conclusion

This study represents an important step toward the validation of the specific IgG response to the Aedes salivary peptide Nterm-34kDa as a proxy measure for Aedes infestation levels and human-mosquito exposure risk in a dengue endemic setting. The use of the IgG response to the Nterm-34 kDa peptide as a viable diagnostic tool for estimating dengue transmission requires further investigations and validation in other geographical and transmission settings.

Aedes mosquitoes and the viruses they transmit are major public health concerns for over half of the global human population. However, the quantitative relationships between virus transmission and vector mosquito infestation remain unclear despite numerous indicators used to estimate transmission risk and predict dengue outbreaks. The aim of this study is to investigate the use of a salivary biomarker to assess the small-scale variation in human exposure to Aedes bites and the risk of dengue infection in the context of a vector control intervention in northeastern Thailand. A cohort of 539 persons visited every four months, including 161 individuals visited monthly, were recruited for routine serological and concurrent household entomological surveys during 19 consecutive months follow-up. Antibody response to Aedes bites was measured by enzyme-linked immunosorbent assays to assess the mosquito exposure index (MEI) and association with the Aedes adult and immature abundance as well as the presence of dengue virus (DENV) in adult mosquitoes (transmission risk). Additionally, the individual (cohort), climatic, and vector control intervention risk factors associated with MEI are explored. This study demonstrates that the MEI was strongly related to household adult Aedes density, particularly indoors resting mosquitoes. Additionally, the MEI was influenced by individual characteristics (i.e., person age, gender, staying indoors), and varied according to seasons and intervention. Nonetheless, no clear relationship between MEI and dengue transmission risk (i.e., vector infection) was detected. This study demonstrated the potential usefulness of the MEI to assess heterogeneity in adult Aedes infestation indices that could assist public health authorities to rapidly identify mosquito “hot spots” and the timeliness of effective vector control interventions.

Immune cell phenotypes associated with disease severity and long-term neutralizing antibody titers after natural dengue virus infection

Prior immunological exposure to dengue virus can be both protective and disease-enhancing during subsequent infections with different dengue virus serotypes. We provide here a systematic, longitudinal analysis of B cell, T cell, and antibody responses in the same patients. Antibody responses as well as T and B cell activation differentiate primary from secondary responses. Hospitalization is associated with lower frequencies of activated, terminally differentiated T cells and higher percentages of effector memory CD4 T cells. Patients with more severe disease tend to have higher percentages of plasmablasts. This does not translate into long-term antibody titers, since neutralizing titers after 6 months correlate with percentages of specific memory B cells, but not with acute plasmablast activation. Overall, our unbiased analysis reveals associations between cellular profiles and disease severity, opening opportunities to study immunopathology in dengue disease and the potential predictive value of these parameters.

Mosquito Control Based on Pesticides and Endosymbiotic Bacterium Wolbachia

Mosquito-borne diseases, such as dengue fever and Zika, have posed a serious threat to human health around the world. Controlling vector mosquitoes is an effective method to prevent these diseases. Spraying pesticides has been the main approach of reducing mosquito population, but it is not a sustainable solution due to the growing insecticide resistance. One promising complementary method is the release of Wolbachia-infected mosquitoes into wild mosquito populations, which has been proven to be a novel and environment-friendly way for mosquito control. In this paper, we incorporate consideration of releasing infected sterile mosquitoes and spraying pesticides to aim to reduce wild mosquito populations based on the population replacement model. We present the estimations for the number of wild mosquitoes or infection density in a normal environment and then discuss how to offset the effect of the heatwave, which can cause infected mosquitoes to lose Wolbachia infection. Finally, we give the waiting time to suppress wild mosquito population to a given threshold size by numerical simulations.

Original Article: Decline of notified dengue infections in Indonesia in 2017: Discussion of the possible determinants

This study was conducted to quantify the trend in dengue notifications in the country in 2017 and to explore the possible determinants. Annual nation-wide dengue notification data were obtained from the National Disease Surveillance of Ministry of Health of Indonesia. Annual incidence rate (IR) and case fatality rate (CFR) in 2017 and the previous years were quantified and compared. Correlations between annual larva free index (LFI), implementation coverage of integrated vector management (IVM), El Niño Southern Oscillation (Niño3.4), Dipole Mode Index (DMI), Zika virus seropositivity and the percent change in IR and CFR of dengue were examined. The change of dengue IR and CFRs were mapped. In 2017, dengue IR was declined by 71% (22.55 per 100,000 population) compared to 2016 (77.96 per 100,000 population) while the CFR was slightly reduced from 0.79% to 0.75%. Reduction in IR and CFR occurred in 94.1% and 70.1% out of 34 provinces, respectively. The trend of dengue IR seems to be influenced by Niño3.4 but there is no clear evidence that Niño3.4 is the main reason for dengue reduction in 2017. It is difficult to elucidate that the reduction of dengue in 2017 was associated with previous Zika outbreaks. In conclusion, there was a significant reduction on dengue notifications in Indonesia in 2017. Further investigation is needed to look at the role of climate on the decline of dengue IR at finer temporal scale. In addition, study on the role of cross-protective immunity generated by Zika infection on dengue incidence is also warranted.

Dengue virus induces PCSK9 expression to alter antiviral responses and disease outcomes

Dengue virus (DENV) infection requires cholesterol as a proviral factor, although statin treatment did not show antiviral efficacy in patients with dengue. Here, we show that DENV infection manipulated cholesterol metabolism in cells residing in low-oxygen microenvironments (hypoxia) such as in the liver, spleen, and lymph nodes. DENV infection induced expression of proprotein convertase subtilisin/kexin type 9 (PCSK9), which reduces low-density lipoprotein receptor (LDLR) recycling and hence cholesterol uptake. We found that, whereas LDLR uptake would have distributed cholesterol throughout the various cell compartments, de novo cholesterol synthesis enriched this lipid in the endoplasmic reticulum (ER). With cholesterol enrichment in the ER, ER-resident STING and type I IFN (IFN) activation was repressed during DENV infection. Our in vitro findings were further supported by the detection of elevated plasma PCSK9 levels in patients with dengue with high viremia and increased severity of plasma leakage. Our findings therefore suggest that PCSK9 plays a hitherto unrecognized role in dengue pathogenesis and that PCSK9 inhibitors could be a suitable host-directed treatment for patients with dengue.

Social and environmental risk factors for dengue in Delhi city: A retrospective study

Global urbanization is leading to an inexorable spread of several major diseases that need to be stemmed. Dengue is one of these major diseases spreading in cities today, with its principal mosquito vector superbly adapted to the urban environment. Current mosquito control strategies are proving inadequate, especially in the face of such urbanisation and novel, evidence-based targeted approaches are needed. Through combined epidemiological and entomological approaches, we aimed to identify a novel sanitation strategy to alleviate the burden of dengue through how the dengue virus spreads through the community. We combined surveillance case mapping, prospective serological studies, year-round mosquito surveys, socio-economic and Knowledge Attitudes and Practices surveys across Delhi. We identified lack of access to tap water (≤98%) as an important risk factor for dengue virus IgG sero-positivity (adjusted Odds Ratio 4.69, 95% C.I. 2.06–10.67) and not poverty per se. Wealthier districts had a higher dengue burden despite lower mosquito densities than the Intermediary income communities (adjusted Odds Ratio 2.92, 95% C.I. 1.26–6.72). This probably reflects dengue being introduced by people travelling from poorer areas to work in wealthier houses. These poorer, high density areas, where temperatures are also warmer, also had dengue cases during the winter. Control strategies based on improved access to a reliable supply of tap water plus focal intervention in intra-urban heat islands prior to the dengue season could not only lead to a reduction in mosquito abundance but also eliminate the reservoir of dengue virus clearly circulating at low levels in winter in socio-economically disadvantaged areas.

Identifying disease hotspots and individual risk factors for dengue can enable targeted intervention strategies. We conducted combined serological, entomological and socio-economic surveys across 18 areas within Delhi, taken from the total 1280 colonies (i.e. the administrative units of reference in Delhi) for which we classified their socio-economic typology. We additionally performed a Knowledge, Attitudes, Practices survey at a household level within the most socially disadvantaged sub-districts. Finally, we mapped all the winter dengue cases to 250 m x 250 m units along with their winter mean temperatures. We found that access to tap water was an important risk factor for exposure to dengue virus (DENV) and this was confirmed even within the socially disadvantaged sub-districts. The Wealthy colonies had a high burden of DENV infection despite low mosquito densities, likely linked to their connectedness through daily human mobility. The winter burden of dengue occurred majoritarily in the socio-economically disadvantaged colonies, which also have higher mean temperatures and urban heat islands. Improved access to tap water could lead to a reduction in dengue, not only for those directly affected but for the general population. Targeted intervention through mosquito control in winter in the socially disadvantaged areas could offer a rational strategy for optimising control efforts.

Spatial and temporal patterns of dengue incidence in Bhutan: a Bayesian analysis

Dengue is an important emerging vector-borne disease in Bhutan. This study aimed to quantify the spatial and temporal patterns of dengue and their relationship to environmental factors in dengue-affected areas at the sub-district level. A multivariate zero-inflated Poisson regression model was developed using a Bayesian framework with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure. The posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. A total of 708 dengue cases were notified through national surveillance between January 2016 and June 2019. Individuals aged ≤14 years were found to be 53% (95% CrI: 42%, 62%) less likely to have dengue infection than those aged >14 years. Dengue cases increased by 63% (95% CrI: 49%, 77%) for a 1°C increase in maximum temperature, and decreased by 48% (95% CrI: 25%, 64%) for a one-unit increase in normalized difference vegetation index (NDVI). There was significant residual spatial clustering after accounting for climate and environmental variables. The temporal trend was significantly higher than the national average in eastern sub-districts. The findings highlight the impact of climate and environmental variables on dengue transmission and suggests prioritizing high-risk areas for control strategies.

Enhancing fine-grained intra-urban dengue forecasting by integrating spatial interactions of human movements between urban regions

Background

As a mosquito-borne infectious disease, dengue fever (DF) has spread through tropical and subtropical regions worldwide in recent decades. Dengue forecasting is essential for enhancing the effectiveness of preventive measures. Current studies have been primarily conducted at national, sub-national, and city levels, while an intra-urban dengue forecasting at a fine spatial resolution still remains a challenging feat. As viruses spread rapidly because of a highly dynamic population flow, integrating spatial interactions of human movements between regions would be potentially beneficial for intra-urban dengue forecasting.

Methodology

In this study, a new framework for enhancing intra-urban dengue forecasting was developed by integrating the spatial interactions between urban regions. First, a graph-embedding technique called Node2Vec was employed to learn the embeddings (in the form of an N-dimensional real-valued vector) of the regions from their population flow network. As strongly interacting regions would have more similar embeddings, the embeddings can serve as “interaction features.” Then, the interaction features were combined with those commonly used features (e.g., temperature, rainfall, and population) to enhance the supervised learning–based dengue forecasting models at a fine-grained intra-urban scale.

Results

The performance of forecasting models (i.e., SVM, LASSO, and ANN) integrated with and without interaction features was tested and compared on township-level dengue forecasting in Guangzhou, the most threatened sub-tropical city in China. Results showed that models using both common and interaction features can achieve better performance than that using common features alone.

Conclusions

The proposed approach for incorporating spatial interactions of human movements using graph-embedding technique is effective, which can help enhance fine-grained intra-urban dengue forecasting.

Dengue fever, a mosquito-borne infectious disease, has become a serious public health problem in many tropical and subtropical regions worldwide, such as Southeast Asian countries and the Guangdong Province in China. In the absence of an effective vaccine at present, disease surveillance and mosquito control remain the primary means of controlling the spread of the disease. At an intra-urban setting, it is important to predict the spatial distribution of future patients, which can help government agencies to establish precise and targeted prevention measures beforehand. Considering the fast virus spread within a city because of a highly dynamic population flow, we proposed a novel approach to enhancing fine-grained intra-urban dengue forecasting by integrating spatial interactions of human movements between urban regions. First, using a graph-embedding model called Node2Vec, the embeddings of the regions were learned from their population interaction network so that strongly interacted regions would have more similar embeddings. Secondly, serving as interaction features, the embeddings were combined with the commonly used features as inputs of the forecasting models. The experimental results indicated that the performance of the models can be improved by incorporating the interaction features, confirming the effectiveness of our proposed strategy in enhancing fine-grained intra-urban dengue forecasting.

Irradiation induced inversions suppress recombination between the M locus and morphological markers in Aedes aegypti

BACKGROUND

Aedes aegypti is the primary vector of arthropod-borne viruses and one of the most widespread and invasive mosquito species. Due to the lack of efficient specific drugs or vaccination strategies, vector population control methods, such as the sterile insect technique, are receiving renewed interest. However, availability of a reliable genetic sexing strategy is crucial, since there is almost zero tolerance for accidentally released females. Development of genetic sexing strains through classical genetics is hindered by genetic recombination that is not suppressed in males as is the case in many Diptera. Isolation of naturally-occurring or irradiation-induced inversions can enhance the genetic stability of genetic sexing strains developed through genetically linking desirable phenotypes with the male determining region.

RESULTS

For the induction and isolation of inversions through irradiation, 200 male pupae of the 'BRA' wild type strain were irradiated at 30 Gy and 100 isomale lines were set up by crossing with homozygous 'red-eye' (re) mutant females. Recombination between re and the M locus and the white (w) gene (causing a recessive white eye phenotype when mutated) and the M locus was tested in 45 and 32 lines, respectively. One inversion (Inv35) reduced recombination between both re and the M locus, and wand the M locus, consistent with the presence of a rather extended inversion between the two morphological mutations, that includes the M locus. Another inversion (Inv5) reduced recombination only between w and the M locus. In search of naturally-occurring, recombination-suppressing inversions, homozygous females from the red eye and the white eye strains were crossed with seventeen and fourteen wild type strains collected worldwide, representing either recently colonized or long-established laboratory populations. Despite evidence of varying frequencies of recombination, no combination led to the elimination or substantial reduction of recombination.

CONCLUSION

Inducing inversions through irradiation is a feasible strategy to isolate recombination suppressors either on the M or the m chromosome for Aedes aegypti. Such inversions can be incorporated in genetic sexing strains developed through classical genetics to enhance their genetic stability and support SIT or other approaches that aim to population suppression through male-delivered sterility.

Use of Animal Models in Studying Roles of Antibodies and Their Secretion Cells in Dengue Vaccine Development

The cardinal feature of adaptive immunity is its ability to form memory responses that can be rapidly recalled to contain pathogens upon reencountering. Conferring a robust memory immune response to an infection is a key feature for a successful vaccination program. The plasmablasts are cells that not only can secret non-neutralizing antibodies but also can secrete the specific antibodies essential to neutralize and inactivate the invading pathogens. Dengue has been recognized as one of the most important vector-borne human viral diseases globally. Currently, supportive care with vigilant monitoring is the standard practice since there is as yet no approved therapeutic modality to treat dengue. Even though the approved vaccine has become available, its low efficacy with the potential to cause harm is the major hurdle to promote the widespread usage of the vaccine. Despite the decades of research on dengue, the major challenge in dengue vaccine development is the absence of suitable experimental animal models that reflect the pathological features and clinical symptoms, as seen in humans. Dengue is transmitted by the bite of mosquitoes carrying infectious dengue virus (DENV), which has four distinct serotypes. Recently, cases resulting from unconventional transmission routes, such as blood transfusion, organs as well as stem cells and bone marrow transplantations, and mother-to-infant vertical transmission, have been reported, suggesting an alternate route of DENV transmission exists in nature. This review discusses issues and challenges needing to be resolved to develop an effective dengue vaccine. Development of a robust and reliable dengue animal model that can reflect not only dynamic human clinical symptoms but also can answer around why preexisting neutralizing antibodies do not confer protection upon re-infection and immune protection marker for dengue vaccine efficacy evaluation.

Live vaccine infection burden elicits adaptive humoral and cellular immunity required to prevent Zika virus infection

BACKGROUND

The emergence of Zika virus (ZIKV) as an important cause of congenital and childhood developmental disorders presents another challenge to global health. Efforts to develop a Zika vaccine have begun although vaccine development against flaviviruses, of which ZIKV belongs to, has proven to be time-consuming and challenging. Defining the vaccine attributes that elicit adaptive immune response necessary for preventing ZIKV infection could provide an evidence-based guide to Zika vaccine development.

METHODS

We used a previously described attenuated ZIKV DN-2 strain in a type-I interferon receptor deficient mouse model and tested the hypothesis that duration of vaccine burden rather than peak level of infection, is a determinant of immunogenicity. We quantified both humoral and cellular responses against ZIKV using plaque reduction neutralisation test and flow cytometry with ELISPOT assays, respectively. Vaccinated mice were challenged with wild-type ZIKV (H/PF/2013 strain) to determine the level of protection against infection.

FINDINGS

We found that the overall vaccine burden is directly correlated with neutralising antibody titres. Reduced duration of vaccine burden lowered neutralising antibody titres that resulted in subclinical infection, despite unchanged peak vaccine viraemia levels. We also found that sterilising immunity is dependant on both neutralising antibody and CD8⁺T cell responses; depletion of CD8⁺T cells in vaccinated animals led to wild-type ZIKV infection, especially in the male reproductive tract.

INTERPRETATION

Our findings indicate that duration of attenuated virus vaccine burden is a determinant of humoral and cellular immunity and also suggest that vaccines that elicit both arms of the adaptive immune response are needed to fully prevent ZIKV transmission.

FUNDING

This study was supported by the National Medical Research Council through the Clinician-Scientist Award (Senior Investigator) to E.E.O. Salary support for S.W. was from a Competitive Research Programme grant awarded by the National Research Foundation of Singapore.

Complex relationships between Aedes vectors, socio-economics and dengue transmission-Lessons learned from a case-control study in northeastern Thailand

BACKGROUND/OBJECTIVES

Dengue fever is an important public health concern in most tropical and subtropical countries, and its prevention and control rest on vector surveillance and control. However, many aspects of dengue epidemiology remain unclear; in particular, the relationship between Aedes vector abundance and dengue transmission risk. This study aims to identify entomological and immunological indices capable of discriminating between dengue case and control (non-case) houses, based on the assessment of candidate indices, as well as individual and household characteristics, as potential risk factors for acquiring dengue infection.

METHODS

This prospective, hospital-based, case-control study was conducted in northeastern Thailand between June 2016 and August 2019. Immature and adult stage Aedes were collected at the houses of case and control patients, recruited from district hospitals, and at patients' neighboring houses. Blood samples were tested by RDT and PCR to detect dengue cases, and were processed with the Nterm-34 kDa salivary peptide to measure the human immune response to Aedes bites. Socioeconomic status, and other individual and household characteristics were analyzed as potential risk factors for dengue.

RESULTS

Study findings showed complex relationships between entomological indices and dengue risk. The presence of DENV-infected Aedes at the patient house was associated with 4.2-fold higher odds of dengue. On the other hand, Aedes presence (irrespective of infectious status) in the patient's house was negatively associated with dengue. In addition, the human immune response to Aedes bites, was higher in control than in case patients and Aedes adult abundance and immature indices were higher in control than in case houses at the household and the neighboring level. Multivariable analysis showed that children aged 10-14 years old and those aged 15-25 years old had respectively 4.5-fold and 2.9-fold higher odds of dengue infection than those older than 25 years.

CONCLUSION

DENV infection in female Aedes at the house level was positively associated with dengue infection, while adult Aedes presence in the household was negatively associated. This study highlights the potential benefit of monitoring dengue viruses in Aedes vectors. Our findings suggest that monitoring the presence of DENV-infected Aedes mosquitoes could be a better indicator of dengue risk than the traditional immature entomological indices.

Dengue and Zika Viruses: Epidemiological History, Potential Therapies, and Promising Vaccines

Dengue virus (DENV), which can lead to fatal hemorrhagic fever, affects 390 million people worldwide. The closely related Zika virus (ZIKV) causes microcephaly in newborns and Guillain-Barré syndrome in adults. Both viruses are mostly transmitted by Aedes albopictus and Aedes aegypti mosquitoes, which, due to globalization of trade and travel alongside climate change, are spreading worldwide, paving the way to DENV and ZIKV transmission and the occurrence of new epidemics. Local outbreaks have already occurred in temperate climates, even in Europe. As there are no specific treatments, these viruses are an international public health concern. Here, we analyze and discuss DENV and ZIKV outbreaks history, clinical and pathogenesis features, and modes of transmission, supplementing with information on advances on potential therapies and restraining measures. Taking advantage of the knowledge of the structure and biological function of the capsid (C) protein, a relatively conserved protein among flaviviruses, within a genus that includes DENV and ZIKV, we designed and patented a new drug lead, pep14-23 (WO2008/028939A1). It was demonstrated that it inhibits the interaction of DENV C protein with the host lipid system, a process essential for viral replication. Such an approach can be used to develop new therapies for related viruses, such as ZIKV.

Factors associated with thrombocytopenia in patients with dengue fever: a retrospective cohort study

OBJECTIVE

Some patients with dengue fever tend to develop thrombocytopenia during the course of infection and are thus vulnerable to haemorrhagic manifestations and other complications. However, the factors associated with the development of thrombocytopenia are unknown. We aimed to identify factors associated with an increased risk of thrombocytopenia and haematological changes in patients with confirmed dengue fever.

DESIGN

Retrospective cohort study.

SETTING

Brazilian multicentre primary care databases.

PARTICIPANTS

387 patients had positive laboratory serological confirmation of dengue infection during 2014. The data were identified from two databases: Notification of Injury Information System (SINAN) and Municipal Laboratory.

MAIN OUTCOME MEASURE

The presence of thrombocytopenia (platelet count <1 50×10⁹/L). The associations of factors that predisposed patients to thrombocytopenia and haematological changes were analysed using logistic regression. ORs and 95% CIs were calculated.

RESULTS

Among 387 patients, 156 had both dengue and thrombocytopenia. The risk factors associated with thrombocytopenia included male sex (OR: 1.77, 95% CI: 1.16 to 2.71, p=0.007), age of 46-64 years (OR: 2.20, 95% CI: 1.15 to 4.21, p=0.009) or ≥65 years (OR: 3.02, 95% CI: 1.40 to 6.50, p=0.002), presence of leucopenia (OR: 6.85, 95% CI: 4.27 to 10.99, p<0.001) and high mean corpuscular haemoglobin (MCH) levels (OR: 2.00, 95% CI: 1.29 to 3.12, p=0.005).

CONCLUSION

Older age, male sex, presence of leucopenia and high MCH levels were identified as risk factors associated with the development of thrombocytopenia in this population.

A greener vision for vector control: The example of the Singapore dengue control programme

Vector-borne diseases are a major cause of morbidity and mortality worldwide. Aedes-borne diseases, in particular, including dengue, chikungunya, yellow fever, and Zika, are increasing at an alarming rate due to urbanisation, population movement, weak vector control programmes, and climate change. The World Health Organization calls for strengthening of vector control programmes in line with the Global Vector Control Response (GVCR) strategy, and many vector control programmes are transitioning to this new approach. The Singapore dengue control programme, situated within the country’s larger vision of a clean, green, and sustainable environment for the health and well-being of its citizens, provides an excellent example of the GVCR approach in action. Since establishing vector control operations in the 1960s, the Singapore dengue control programme succeeded in reducing the dengue force of infection 10-fold by the 1990s and has maintained it at low levels ever since. Key to this success is consideration of dengue as an environmental disease, with a strong focus on source reduction and other environmental management methods as the dominant vector control strategy. The programme collaborates closely with other government ministries, as well as town councils, communities, the private sector, and academic and research institutions. Community engagement programmes encourage source reduction, and house-to-house inspections accompanied by a strong legislative framework with monetary penalties help to support compliance. Strong vector and epidemiological surveillance means that routine control activities can be heightened to specifically target dengue clusters. Despite its success, the programme continues to innovate to tackle challenges such as climate change, low herd immunity, and manpower constraints. Initiatives include development of novel vector controls such as Wolbachia-infected males and spatiotemporal models for dengue risk assessment. Lessons learnt from the Singapore programme can be applied to other settings, even those less well-resourced than Singapore, for more effective vector control.

Infections due to dengue and other viruses transmitted by Aedes mosquitoes are on the rise worldwide as a result of urbanisation, trade, population movement, and climate change. Contemporary vector control programmes have struggled to control Aedes-borne diseases, but the Singapore dengue control programme provides a success story. Key to the success is consideration of dengue as an environmental disease, with a corresponding focus on removal of water containers from in and around homes, solid waste management, and limited use of insecticides. The programme relies on close collaboration with other government and nongovernment actors including communities. Community engagement campaigns to ensure high awareness are supported by house-to-house inspections for mosquito habitats and a legislative framework including penalties for noncompliance. The Singapore dengue control programme provides important lessons that can be applied to other Aedes control programmes and vector control programmes more widely.

Larval Indices of Vector Mosquitoes as Predictors of Dengue Epidemics: An Approach to Manage Dengue Outbreaks Based on Entomological Parameters in the Districts of Colombo and Kandy, Sri Lanka

Background

Early detection of dengue epidemics is a vital aspect in control programmes. Predictions based on larval indices of disease vectors are widely used in dengue control, with defined threshold values. However, there is no set threshold in Sri Lanka at the national or regional levels for Aedes larval indices. Therefore, the current study aimed at developing threshold values for vector indices in two dengue high-risk districts in Sri Lanka.

Methods

Monthly vector indices (House Index [HI], Container Index [CI], Breteau Index for Aedes aegypti [BI_agp], and Ae. albopictus [BI_alb]), of ten selected dengue high-risk Medical Officer of Health (MOH) areas located in Colombo and Kandy districts, were collected from January 2010 to June 2019, along with monthly reported dengue cases. Receiver Operating Characteristic (ROC) curve analysis in SPSS (version 23) was used to assess the discriminative power of the larval indices in identifying dengue epidemics and to develop thresholds for the dengue epidemic management.

Results

Only HI and BI_agp denoted significant associations with dengue epidemics at lag periods of one and two months. Based on Ae. aegypti, average threshold values were defined for Colombo as Low Risk (2.4 ≤ BI_agp < 3.8), Moderate Risk (3.8 ≤ BI_agp < 5), High Risk (BI_agp ≥ 5), along with BI_agp 2.9 ≤ BI_agp < 4.2 (Low Risk), 4.2 ≤ BI_agp < 5.3 (Moderate Risk), and BI_agp ≥ 5.3 (High Risk) for Kandy. Further, 5.5 ≤ HI < 8.9, 8.9 ≤ HI < 11.9, and HI ≥ 11.9 were defined as Low Risk, Moderate Risk, and High Risk average thresholds for HI in Colombo, while 6.9 ≤ HI < 9.1 (Low Risk), 8.9 ≥ HI < 11.8 (Moderate Risk), and HI ≥ 11.8 (High Risk) were defined for Kandy.

Conclusions

The defined threshold values for Ae. aegypti and HI could be recommended as indicators for early detection of dengue epidemics and to drive vector management activities, with the objective of managing dengue epidemics with optimal usage of financial, technical, and human resources in Sri Lanka.

An Innovative, Prospective, Hybrid Cohort-Cluster Study Design to Characterize Dengue Virus Transmission in Multigenerational Households in Kamphaeng Phet, Thailand

Difficulties inherent in the identification of immune correlates of protection or severe disease have challenged the development and evaluation of dengue vaccines. There persist substantial gaps in knowledge about the complex effects of age and sequential dengue virus (DENV) exposures on these correlations. To address these gaps, we were conducting a novel family-based cohort-cluster study for DENV transmission in Kamphaeng Phet, Thailand. The study began in 2015 and is funded until at least 2023. As of May 2019, 2,870 individuals in 485 families were actively enrolled. The families comprise at least 1 child born into the study as a newborn, 1 other child, a parent, and a grandparent. The median age of enrolled participants is 21 years (range 0–93 years). Active surveillance is performed to detect acute dengue illnesses, and annual blood testing identifies subclinical seroconversions. Extended follow-up of this cohort will detect sequential infections and correlate antibody kinetics and sequence of infections with disease outcomes. The central goal of this prospective study is to characterize how different DENV exposure histories within multigenerational family units, from DENV-naive infants to grandparents with multiple prior DENV exposures, affect transmission, disease, and protection at the level of the individual, household, and community.

Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

BACKGROUND

Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful.

METHODS

We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R₀] of 1·5, 2·0, or 2·5) and assuming 7·5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R₀ value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22·7%, 30·0%, 40·0%, and 50·0%) to compare outbreak sizes under the same control measures.

FINDINGS

For the baseline scenario, when R₀ was 1·5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000-320 000), corresponding to 7·4% (IQR 6·5-8·5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000-776 000) when R₀ was 2·0, corresponding to 19·3% (17·8-20·6) of the Singaporean population, and 1 207 000 cases (1 164 000-1 249 000) when R₀ was 2·5, corresponding to 32% (30·9-33·1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99·3% (IQR 92·6-99·9) when R₀ was 1·5, by 93·0% (81·5-99·7) when R₀ was 2·0, and by 78·2% (59·0 -94·4) when R₀ was 2·5. Assuming increasing asymptomatic fractions up to 50·0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R₀ of 1·5.

INTERPRETATION

Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines.

FUNDING

Singapore Ministry of Health, Singapore Population Health Improvement Centre.

Urban mosquito management administration: Mosquito (Diptera: Culicidae) habitat surveillance and questionnaire survey in Wuhan, Central China

BACKGROUND

Creating National Sanitary City (CNSC) promotes appearance, environment sanitation and public health including vector management of cities in China. However, vector management especially mosquito management and the related administrative productivity of Patriotic Health Campaign System (PHCS) of National Sanitary Cities (NSCs) were questioned by many pest control professionals and citizens. In this study, we studied mosquito management of NSCs taking Wuhan as an example. The study aimed to (1) determine the distribution and abundance of immature mosquito habitats in built-up areas of Wuhan and (2) better understand the related administration procedure in CNSC.

METHODS

Immature mosquito habitat surveillance was carried out in randomly selected premises of driving schools (DSs), schools or kindergartens (SKs), property management residential areas (PMRAs), construction sites (CSs), wide roads with storm drains (WRSDs) and urban creeks (UCs) in built-up areas of Wuhan from July to October 2015 followed by questionnaire interviews with one each of premise occupants and district departments responsible for mosquito management in these premises.

RESULTS

Total of 64.1 km of route were inspected in 36 DSs, 36 SKs, 36 PMRAs, 36 CSs and 36 segments of WRSD and 2,158 potential mosquito habitats with 749 (35%) mosquito-positive habitats were found. The route index (RI) was 11.7, which was 14.6 times higher than the grade C criteria for vector density control (RI = 0.8 positive habitats/km) in CNSC. Occupants of 36 DSs, 36 SKs, 36 PMRAs, 34 CSs were interviewed and 77% of them reported no difference in mosquito infestation in their premises since 2013 and 80% of them knew about the responsibility and arrangements of PHCS of mosquito management in their premises. Only 15% had the awareness of larval source reduction strategy and 14% had implemented it. Receipt the electronic/paper edition of CNSC vector management specifications from the PHCS was very low (13%) and an official notification or bulletin for rectification mosquito-positive habitats was also very low (5%). Of the 75 responsible district departments interviewed, about half (55%) reported that they had held training courses/meetings related to CNSC vector management, the majority (96%) reported that they had not carried out independent on-site supervision of premises under their jurisdiction. No differences in larval indices were found between premises which were administrative intervened and with no administrative intervention.

CONCLUSIONS

The administrative intervention of PHCS had not evidently improved mosquito management of the premises in built-up areas in Wuhan. It is a violation of the original intention of the National Patriotic Health Campaign Committee in organizing CNSC programs. To combat mosquito borne diseases, and to improve the quality of life of residents, we recommend that PHCS honestly reveals defects in urban mosquito management and seriously takes those exposed defects. The PHCS should strengthen Patriotic Health Campaign activities by strict adherence to NSC standards. Further research on sustained promotion of urban mosquito management of NSCs, which focus on effective administration, as well as on improvement of related sectors of NSC standards should be carried out.

Dengue Fever and Severe Dengue in Barbados, 2008-2016

Analysis of the temporal, seasonal and demographic distribution of dengue virus (DENV) infections in Barbados was conducted using national surveillance data from a total of 3994 confirmed dengue cases. Diagnosis was confirmed either by DENV-specific real time reverse transcriptase polymerase chain reaction (rRT-PCR), or non-structural protein 1 (NS1) antigen or enzyme linked immunosorbent assay (ELISA) tests; a case fatality rate of 0.4% (10/3994) was observed. The prevalence rate of dengue fever (DF) varied from 27.5 to 453.9 cases per 100,000 population among febrile patients who sought medical attention annually. DF cases occurred throughout the year with low level of transmission observed during the dry season (December to June), then increased transmission during rainy season (July to November) peaking in October. Three major dengue epidemics occurred in Barbados during 2010, 2013 and possibly 2016 with an emerging three-year interval. DF prevalence rate among febrile patients who sought medical attention overall was highest among the 10-19 years old age group. The highest DF hospitalisation prevalence rate was observed in 2013. Multiple serotypes circulated during the study period and Dengue virus serotype 2 (DENV-2) was the most prevalent serotype during 2010, whilst DENV-1 was the most prevalent serotype in 2013. Two DENV-1 strains from the 2013 DENV epidemic were genetically more closely related to South East Asian strains, than Caribbean or South American strains, and represent the first ever sequencing of DENV strains in Barbados. However, the small sample size (n = 2) limits any meaningful conclusions. DF prevalence rates were not significantly different between females and males. Public health planning should consider DENV inter-epidemic periodicity, the current COVID-19 pandemic and similar clinical symptomology between DF and COVID-19. The implementation of routine sequencing of DENV strains to obtain critical data can aid in battling DENV epidemics in Barbados.

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.

Impact of Climate Variability and Abundance of Mosquitoes on Dengue Transmission in Central Vietnam

Dengue fever is an important arboviral disease in many countries. Its incidence has increased during the last decade in central Vietnam. Most dengue studies in Vietnam focused on the northern area (Hanoi) and southern regions but not on central Vietnam. Dengue transmission dynamics and relevant environmental risk factors in central Vietnam are not understood. This study aimed to evaluate spatiotemporal patterns of dengue fever in central Vietnam and effects of climatic factors and abundance of mosquitoes on its transmission. Dengue and mosquito surveillance data were obtained from the Department of Vector Control and Border Quarantine at Nha Trang Pasteur Institute. Geographic Information System and satellite remote sensing techniques were used to perform spatiotemporal analyses and to develop climate models using generalized additive models. During 2005-2018, 230,458 dengue cases were reported in central Vietnam. Da Nang and Khanh Hoa were two major hotspots in the study area. The final models indicated the important role of Indian Ocean Dipole, multivariate El Niño-Southern Oscillation index, and vector index in dengue transmission in both regions. Regional climatic variables and mosquito population may drive dengue transmission in central Vietnam. These findings provide important information for developing an early dengue warning system in central Vietnam.

RC, Perkins TA. Optimizing the deployment of ultra-low volume and targeted indoor residual spraying for dengue outbreak response

Recent years have seen rising incidence of dengue and large outbreaks of Zika and chikungunya, which are all caused by viruses transmitted by Aedes aegypti mosquitoes. In most settings, the primary intervention against Aedes-transmitted viruses is vector control, such as indoor, ultra-low volume (ULV) spraying. Targeted indoor residual spraying (TIRS) has the potential to more effectively impact Aedes-borne diseases, but its implementation requires careful planning and evaluation. The optimal time to deploy these interventions and their relative epidemiological effects are, however, not well understood. We used an agent-based model of dengue virus transmission calibrated to data from Iquitos, Peru to assess the epidemiological effects of these interventions under differing strategies for deploying them. Specifically, we compared strategies where spray application was initiated when incidence rose above a threshold based on incidence in recent years to strategies where spraying occurred at the same time(s) each year. In the absence of spraying, the model predicted 361,000 infections [inter-quartile range (IQR): 347,000-383,000] in the period 2000-2010. The ULV strategy with the fewest median infections was spraying twice yearly, in March and October, which led to a median of 172,000 infections [IQR: 158,000-183,000], a 52% reduction from baseline. Compared to spraying once yearly in September, the best threshold-based strategy utilizing ULV had fewer median infections (254,000 vs. 261,000), but required more spraying (351 vs. 274 days). For TIRS, the best strategy was threshold-based, which led to the fewest infections of all strategies tested (9,900; [IQR: 8,720-11,400], a 94% reduction), and required fewer days spraying than the equivalent ULV strategy (280). Although spraying twice each year is likely to avert the most infections, our results indicate that a threshold-based strategy can become an alternative to better balance the translation of spraying effort into impact, particularly if used with a residual insecticide.

Key Findings and Comparisons From Analogous Case-Cluster Studies for Dengue Virus Infection Conducted in Machala, Ecuador, and Kamphaeng Phet, Thailand

Dengue viruses (DENV) pose a significant and increasing threat to human health across broad regions of the globe. Currently, prevention, control, and treatment strategies are limited. Promising interventions are on the horizon, including multiple vaccine candidates under development and a renewed and innovative focus on controlling the vector, Aedes aegypti. However, significant gaps persist in our understanding of the similarities and differences in DENV epidemiology across regions of potential implementation and evaluation. In this manuscript, we highlight and compare findings from two analogous cluster-based studies for DENV transmission and pathogenesis conducted in Thailand and Ecuador to identify key features and questions for further pursuit. Despite a remarkably similar incidence of DENV infection among enrolled neighborhood contacts at the two sites, we note a higher occurrence of secondary infection and severe illness in Thailand compared to Ecuador. A higher force of infection in Thailand, defined as the incidence of infection among susceptible individuals, is suggested by the higher number of captured Aedes mosquitoes per household, the increasing proportion of asymptomatic infections with advancing age, and the high proportion of infections identified as secondary-type infections by serology. These observations should be confirmed in long-term, parallel prospective cohort studies conducted across regions, which would advantageously permit characterization of baseline immune status (susceptibility) and contemporaneous assessment of risks and risk factors for dengue illness.

Patterns, Drivers, and Challenges of Vector-Borne Disease Emergence

Vector-borne diseases are emerging at an increasing rate and comprise a disproportionate share of all emerging infectious diseases. Yet, the key ecological and evolutionary dimensions of vector-borne disease that facilitate their emergence have not been thoroughly explored. This study reviews and synthesizes the existing literature to explore global patterns of emerging vector-borne zoonotic diseases (VBZDs) under changing global conditions. We find that the vast majority of emerging VBZDs are transmitted by ticks (Ixodidae) and mosquitoes (Culicidae) and the pathogens transmitted are dominated by Rickettsiaceae bacteria and RNA viruses (Flaviviridae, Bunyaviridae, and Togaviridae). The most common potential driver of these emerging zoonoses is land use change, but for many diseases, the driver is unknown, revealing a critical research gap. While most reported VBZDs are emerging in the northern latitudes, after correcting for sampling bias, Africa is clearly a region with the greatest share of emerging VBZD. We highlight critical gaps in our understanding of VBZD emergence and emphasize the importance of interdisciplinary research and consideration of deeper evolutionary processes to improve our capacity for anticipating where and how such diseases have and will continue to emerge.

Designing effective control of dengue with combined interventions

Viruses transmitted by Aedes mosquitoes, such as dengue, Zika, and chikungunya, have expanding ranges and seem unabated by current vector control programs. Effective control of these pathogens likely requires integrated approaches. We evaluated dengue management options in an endemic setting that combine novel vector control and vaccination using an agent-based model for Yucatán, Mexico, fit to 37 y of data. Our intervention models are informed by targeted indoor residual spraying (TIRS) experiments; trial outcomes and World Health Organization (WHO) testing guidance for the only licensed dengue vaccine, CYD-TDV; and preliminary results for in-development vaccines. We evaluated several implementation options, including varying coverage levels; staggered introductions; and a one-time, large-scale vaccination campaign. We found that CYD-TDV and TIRS interfere: while the combination outperforms either alone, performance is lower than estimated from their separate benefits. The conventional model hypothesized for in-development vaccines, however, performs synergistically with TIRS, amplifying effectiveness well beyond their independent impacts. If the preliminary performance by either of the in-development vaccines is upheld, a one-time, large-scale campaign followed by routine vaccination alongside aggressive new vector control could enable short-term elimination, with nearly all cases avoided for a decade despite continuous dengue reintroductions. If elimination is impracticable due to resource limitations, less ambitious implementations of this combination still produce amplified, longer-lasting effectiveness over single-approach interventions.

Assessing the interplay between human mobility and mosquito borne diseases in urban environments

Urbanization drives the epidemiology of infectious diseases to many threats and new challenges. In this research, we study the interplay between human mobility and dengue outbreaks in the complex urban environment of the city-state of Singapore. We integrate both stylized and mobile phone data-driven mobility patterns in an agent-based transmission model in which humans and mosquitoes are represented as agents that go through the epidemic states of dengue. We monitor with numerical simulations the system-level response to the epidemic by comparing our results with the observed cases reported during the 2013 and 2014 outbreaks. Our results show that human mobility is a major factor in the spread of vector-borne diseases such as dengue even on the short scale corresponding to intra-city distances. We finally discuss the advantages and the limits of mobile phone data and potential alternatives for assessing valuable mobility patterns for modeling vector-borne diseases outbreaks in cities.

Immunogenicity and safety of a dengue vaccine given as a booster in Singapore: a randomized Phase II, placebo-controlled trial evaluating its effects 5-6 years after completion of the primary series

The tetravalent dengue vaccine (CYD-TDV; Dengvaxia®) is administered on a three-dose schedule, 6 months apart in those aged ≥9 years in a number of dengue-endemic countries in Asia and Latin America. In this study, CYD63 (NCT02824198), participants aged 9–45 years at first vaccination, and who had received three doses of CYD-TDV in the CYD28 study more than 5 years previously, were randomized 3:1 to receive a booster CYD-TDV dose (Group 1) or placebo (Group 2). Dengue neutralizing antibody geometric mean titres (PRNT₅₀ GMTs) for each of the four dengue serotypes were assessed in sera collected before and 28 days after booster injections. Non-inferiority of the booster immune response versus that induced after the third dose was demonstrated for each serotype if the lower limit of the two-sided 95% confidence interval (CI) was >0.5 for the GMT ratios (GMTRs) between post-booster CYD-TDV dose and post-dose 3 in Group 1. Overall, 118 participants received CYD-TDV booster or placebo and 116 (98.3%) completed the study; two participants were withdrawn because of noncompliance. GMTs in the booster CYD-TDV group increased across all serotypes post-booster injection by 1.74- (serotype 1) to 3.58-fold (serotype 4). No discernible increases were observed in the placebo group. Non-inferiority was demonstrated for serotypes 1, 3, and 4, but not for serotype 2 (GMTR; 0.603 [95% CI, 0.439– 0.829]). No safety issues were observed. These data show that the CYD-TDV booster given 5 or more years later tended to restore GMTs back to levels observed post-dose 3.

Mathematical analysis of a Wolbachia invasive model with imperfect maternal transmission and loss of Wolbachia infection

Arboviral infections, especially dengue, continue to cause significant health burden in their endemic regions. One of the strategies to tackle these infections is to replace the main vector agent, Ae. aegypti, with the ones incapable of transmitting the virus. Wolbachia, an intracellular bacterium, has shown promise in achieving this goal. However, key factors such as imperfect maternal transmission, loss of Wolbachia infection, reduced reproductive capacity and shortened life-span affect the dynamics of Wolbachia in different forms in the Ae. aegypti population. In this study, we developed a Wolbachia transmission dynamic model adjusting for imperfect maternal transmission and loss of Wolbachia infection. The invasive reproductive number that determines the likelihood of replacement of the Wolbachia-uninfected (WU) population is derived and with it, we established the local and global stability of the equilibrium points. This analysis clearly shows that cytoplasmic incompatibility (CI) does not guarantee establishment of the Wolbachia-infected (WI) mosquitoes as imperfect maternal transmission and loss of Wolbachia infection could outweigh the gains from CI. Optimal release programs depending on the level of imperfect maternal transmission and loss of Wolbachia infection are shown. Hence, it is left to decision makers to either aim for replacement or co-existence of both populations.

Spatial and temporal patterns of dengue incidence in northeastern Thailand 2006-2016

Background

Dengue, a viral disease transmitted by Aedes mosquitoes, is an important public health concern throughout Thailand. Climate variables are potential predictors of dengue transmission. Associations between climate variables and dengue have usually been performed on large-scale first-level national administrative divisions, i.e. provinces. Here we analyze data on a finer spatial resolution in one province, which is often more relevant for effective disease control design. The objective of this study was to investigate the effect of seasonal variations, monthly climate variability, and to identify local clusters of symptomatic disease at the sub-district level based on reported dengue cases.

Methods

Data on dengue cases were retrieved from the national communicable disease surveillance system in Thailand. Between 2006 and 2016, 15,167 cases were recorded in 199 sub-districts of Khon Kaen Province, northeastern Thailand. Descriptive analyses included demographic characteristics and temporal patterns of disease and climate variables. The association between monthly disease incidence and climate variations was analyzed at the sub-district level using Bayesian Poisson spatial regression. A hotspot analysis was used to assess the spatial patterns (clustered/dispersed/random) of dengue incidence.

Results

Dengue was predominant in the 5–14 year-old age group (51.1%). However, over time, dengue incidence in the older age groups (> 15 years) gradually increased and was the most affected group in 2013. Dengue outbreaks coincide with the rainy season. In the spatial regression model, maximum temperature was associated with higher incidence. The hotspot analysis showed clustering of cases around the urbanized area of Khon Kaen city and in rural areas in the southwestern portion of the province.

Conclusions

There was an increase in the number of reported dengue cases in older age groups over the study period. Dengue incidence was highly seasonal and positively associated with maximum ambient temperature. However, climatic variables did not explain all the spatial variation of dengue in the province. Further analyses are needed to clarify the detailed effects of urbanization and other potential environmental risk factors. These results provide useful information for ongoing prediction modeling and developing of dengue early warning systems to guide vector control operations.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4379-3) contains supplementary material, which is available to authorized users.

Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China

Background

The number of dengue fever (DF) cases and the number of dengue outbreaks have increased in recent years in Zhejiang Province, China. An unexpected dengue outbreak was reported in Hangzhou in 2017 and caused more than one thousand dengue cases. This study was undertaken to evaluate the effectiveness of the actual control measures, estimate the proportion of inapparent infections during this outbreak and simulate epidemic development based on different levels of control measures taking inapparent infections into consideration.

Methods

The epidemic data of dengue cases in Hangzhou, Zhejiang Province, in 2017 and the number of the people exposed to the outbreaks were obtained from the China Information Network System of Disease Prevention and Control. The epidemic without intervention measures was used to estimate the unknown parameters. A susceptible-exposed-infectious/inapparent-recovered (SEIAR) model was used to estimate the effectiveness of the control interventions. The inapparent infections were also evaluated at the same time.

Results

In total, 1137 indigenous dengue cases were reported in Hangzhou in 2017. The number of indigenous dengue cases was estimated by the SEIAR model. This number was predicted to reach 6090 by the end of November 2, 2017, if no control measures were implemented. The total number of reported cases was reduced by 81.33% in contrast to the estimated incidence without intervention. The number of average daily inapparent cases was 10.18 times higher than the number of symptomatic cases. The earlier and more rigorously the vector control interventions were implemented, the more effective they were. The results showed that implementing vector control continuously for more than twenty days was more effective than every few days of implementation. Case isolation is not sufficient enough for epidemic control and only reduced the incidence by 38.10% in contrast to the estimated incidence without intervention, even if case isolation began seven days after the onset of the first case.

Conclusions

The practical control interventions in the outbreaks that occurred in Hangzhou City were highly effective. The proportion of inapparent infections was large, and it played an important role in transmitting the disease during this epidemic. Early, continuous and high efficacy vector control interventions are necessary to limit the development of a dengue epidemic. Timely diagnosis and case reporting are important in the intervention at an early stage of the epidemic.

Multiple introductions of dengue virus strains contribute to dengue outbreaks in East Kalimantan, Indonesia, in 2015-2016

BACKGROUND

Dengue fever is a febrile disease caused by dengue virus (DENV), which affects people throughout the tropical and subtropical regions of the world, including Indonesia. East Kalimantan (Borneo) province suffered a dramatic increase in dengue cases in 2015 and 2016, making it the province with the second highest incidence of dengue in Indonesia. Despite this, dengue in East Kalimantan is understudied; leaving transmission dynamics of the disease in the area are mostly unknown. In this study, we investigate the factors contributing to the outbreaks in East Kalimantan.

METHODS

Prospective clinical and molecular virology study was conducted in two main cities in the province, namely Samarinda and Balikpapan, in 2015-2016. Patients' clinical, hematological, and demographic data were recorded. Dengue detection and confirmation was performed using NS1-antigen and IgG/IgM antibody detection. RT-PCR was conducted to determine the serotypes of the virus. Phylogenetic analysis was performed based on envelope gene sequences.

RESULTS

Three hundred patients with suspected dengue were recruited. Among these, 132 (44%) were diagnosed with dengue by NS1 antigen and/or nucleic acid detection. The majority of the infections (60%) were primary, with dengue hemorrhagic fever (DHF) the predominant manifestation (71.9%). Serotyping detected all four DENV serotypes in 112 (37.3%) cases, with the majority of patients (58.9%) infected by DENV-3. Phylogenetic analysis based on envelope gene sequences revealed the genotypes of the viruses as DENV-1 Genotype I, DENV-2 Cosmopolitan, and DENV-3 Genotype I. Most virus strains were closely-related to strains from cities in Indonesia.

CONCLUSIONS

Our observations indicate that multiple introductions of endemic DENV from surrounding cities in Indonesia, coupled with relatively low herd immunity, were likely responsible for the outbreak of the dominant viruses. The study provides information on the clinical spectrum of the disease, together with serology, viral genetics, and demographic data, which will be useful for better understanding of dengue disease in Borneo.

Contrasting the value of targeted versus area-wide mosquito control scenarios to limit arbovirus transmission with human mobility patterns based on different tropical urban population centers

Vector control is still our primary intervention for both prevention and mitigation of epidemics of many vector-borne diseases. Efficiently targeting control measures is important since control can involve substantial economic costs. Targeting is not always straightforward, as transmission of vector-borne diseases is affected by various types of host movement. Here we assess how taking daily commuting patterns into consideration can help improve vector control efforts. We examine three tropical urban centers (San Juan, Recife, and Jakarta) that have recently been exposed to Zika and/or dengue infections and consider whether the distribution of human populations and resulting commuting flows affects the optimal scale at which control interventions should be implemented. We developed a stochastic, spatial model and investigated four control scenarios. The scenarios differed in the spatial extent of their implementation and were: 1) a response at the level of an individual neighborhood; 2) a response targeted at a neighborhood in which infected humans were detected and the one with which it was most strongly connected by human movement; 3) a limited area-wide response where all neighborhoods within a certain radius of the focal area were included; and 4) a collective response where all participating neighborhoods implemented control. The relative effectiveness of the scenarios varied only slightly between different settings, with the number of infections averted over time increasing with the scale of implementation. This difference depended on the efficacy of control at the neighborhood level. At low levels of efficacy, the scenarios mirrored each other in infections averted. At high levels of efficacy, impact increased with the scale of the intervention. As a result, the choice between scenarios will not only be a function of the amount of effort decision-makers are willing to invest, but largely epend on the overall effectiveness of vector control approaches.

Control and prevention of Aedes-transmitted viruses, such as dengue, chikungunya, or Zika relies heavily on vector control approaches. Given the effort and cost involved in implementation of vector control, targeting of control measures is highly desirable. However, it is unclear to what extent the effectiveness of highly focal and reactive control measures depends on the commuting and movement patterns of humans. To investigate this question, we developed a model and four control scenarios that ranged from highly focal to area-wide larval control. The distribution of humans and their commuting patterns were modelled after three major tropical urban centers, San Juan, Recife, and Jakarta. We show that as implementation is applied across a wider area, a greater number of infections is averted. Critically, this only occurs if the efficacy of control at the neighborhood level is sufficiently high. A consistent outcome across the three settings was that the focal strategy was most likely to provide the best outcome at lower levels of effort, and when the efficacy of control was low. These outcomes suggest that optimal control strategies will likely have to be tailored to individual settings by decision makers and would benefit from localized cost-effectiveness modelling studies.