Dengue on islands: a Bayesian approach to understanding the global ecology of dengue viruses

A scoping literature review of global dengue age-stratified seroprevalence data: estimating dengue force of infection in endemic countries

BACKGROUND

Dengue poses a significant burden worldwide, and a more comprehensive understanding of the heterogeneity in the intensity of dengue transmission within endemic countries is necessary to evaluate the potential impact of public health interventions.

METHODS

This scoping literature review aimed to update a previous study of dengue transmission intensity by collating global age-stratified dengue seroprevalence data published in the Medline, Embase and Web of Science databases from 2014 to 2023. These data were then utilised to calibrate catalytic models and estimate the force of infection (FOI), which is the yearly per-capita risk of infection for a typical susceptible individual.

FINDINGS

We found a total of 66 new publications containing 219 age-stratified seroprevalence datasets across 30 endemic countries. Together with the previously available average FOI estimates, there are now more than 250 dengue average FOI estimates obtained from seroprevalence studies from across the world.

INTERPRETATION

The results show large heterogeneities in average dengue FOI both across and within countries. These new estimates can be used to inform ongoing modelling efforts to improve our understanding of the drivers of the heterogeneity in dengue transmission globally, which in turn can help inform the optimal implementation of public health interventions.

FUNDING

UK Medical Research Council, Wellcome Trust, Community Jameel, Drugs for Neglected Disease initiative (DNDi) funded by the French Development Agency, Médecins Sans Frontières International; Swiss Agency for Development and Cooperation and UK aid.

Age-specific case data reveal varying dengue transmission intensity in US states and territories

Dengue viruses (DENV) are endemic in the US territories of Puerto Rico, American Samoa, and the US Virgin Islands, with focal outbreaks also reported in the states of Florida and Hawaii. However, little is known about the intensity of dengue virus transmission over time and how dengue viruses have shaped the level of immunity in these populations, despite the importance of understanding how and why levels of immunity against dengue may change over time. These changes need to be considered when responding to future outbreaks and enacting dengue management strategies, such as guiding vaccine deployment. We used catalytic models fitted to case surveillance data stratified by age from the ArboNET national arboviral surveillance system to reconstruct the history of recent dengue virus transmission in Puerto Rico, American Samoa, US Virgin Islands, Florida, Hawaii, and Guam. We estimated average annual transmission intensity (i.e., force of infection) of DENV between 2010 and 2019 and the level of seroprevalence by age group in each population. We compared models and found that assuming all reported cases are secondary infections generally fit the surveillance data better than assuming all cases are primary infections. Using the secondary case model, we found that force of infection was highly heterogeneous between jurisdictions and over time within jurisdictions, ranging from 0.00008 (95% CrI: 0.00002-0.0004) in Florida to 0.08 (95% CrI: 0.044-0.14) in American Samoa during the 2010-2019 period. For early 2020, we estimated that seropositivity in 10 year-olds ranged from 0.09% (0.02%-0.54%) in Florida to 56.3% (43.7%-69.3%) in American Samoa. In the absence of serological data, age-specific case notification data collected through routine surveillance combined with mathematical modeling are powerful tools to monitor arbovirus circulation, estimate the level of population immunity, and design dengue management strategies.

The effect of temperature on dengue virus transmission by Aedes mosquitoes

Dengue is prevalent in tropical and subtropical regions. As an arbovirus disease, it is mainly transmitted by Aedes aegypti and Aedes albopictus. According to the previous studies, temperature is closely related to the survival of Aedes mosquitoes, the proliferation of dengue virus (DENV) and the vector competence of Aedes to transmit DENV. This review describes the correlations between temperature and dengue epidemics, and explores the potential reasons including the distribution and development of Aedes mosquitoes, the structure of DENV, and the vector competence of Aedes mosquitoes. In addition, the immune and metabolic mechanism are discussed on how temperature affects the vector competence of Aedes mosquitoes to transmit DENV.

Spatial, Sociodemographic, and Weather Analysis of the Zika Virus Outbreak: U.S. Virgin Islands, January 2016-January 2018

Background: The first Zika virus outbreak in U.S. Virgin Islands identified 1031 confirmed noncongenital Zika disease (n = 967) and infection (n = 64) cases during January 2016-January 2018; most cases (89%) occurred during July-December 2016. Methods and Results: The epidemic followed a continued point-source outbreak pattern. Evaluation of sociodemographic risk factors revealed that estates with higher unemployment, more houses connected to the public water system, and more newly built houses were significantly less likely to have Zika virus disease and infection cases. Increased temperature was associated with higher case counts, which suggests a seasonal association of this outbreak. Conclusion: Vector surveillance and control measures are needed to prevent future outbreaks.

Quantifying the future risk of dengue under climate change in Japan

Background

In metropolitan Tokyo in 2014, Japan experienced its first domestic dengue outbreak since 1945. The objective of the present study was to quantitatively assess the future risk of dengue in Japan using climate change scenarios in a high-resolution geospatial environment by building on a solid theory as a baseline in consideration of future adaptation strategies.

Methods

Using climate change scenarios of the Model for Interdisciplinary Research on Climate version 6 (MIROC6), representative concentration pathway (RCP) 2.6, 4.5, and 8.5, we computed the daily average temperature and embedded this in the effective reproduction number of dengue, R(T), to calculate the extinction probability and interepidemic period across Japan.

Results

In June and October, the R(T) with daily average temperature T, was <1 as in 2022; however, an elevation in temperature increased the number of days with R(T) >1 during these months under RCP8.5. The time period with a risk of dengue transmission gradually extended to late spring (April–May) and autumn (October–November). Under the RCP8.5 scenario in 2100, the possibility of no dengue-free months was revealed in part of southernmost Okinawa Prefecture, and the epidemic risk extended to the entire part of northernmost Hokkaido Prefecture.

Conclusion

Each locality in Japan must formulate action plans in response to the presented scenarios. Our geographic analysis can help local governments to develop adaptation policies that include mosquito breeding site elimination, distribution of adulticides and larvicides, and elevated situation awareness to prevent transmission via bites from Aedes vectors.

American Mammals Susceptibility to Dengue According to Geographical, Environmental, and Phylogenetic Distances

Many human emergent and re-emergent diseases have a sylvatic cycle. Yet, little effort has been put into discovering and modeling the wild mammal reservoirs of dengue (DENV), particularly in the Americas. Here, we show a species-level susceptibility prediction to dengue of wild mammals in the Americas as a function of the three most important biodiversity dimensions (ecological, geographical, and phylogenetic spaces), using machine learning protocols. Model predictions showed that different species of bats would be highly susceptible to DENV infections, where susceptibility mostly depended on phylogenetic relationships among hosts and their environmental requirement. Mammal species predicted as highly susceptible coincide with sets of species that have been reported infected in field studies, but it also suggests other species that have not been previously considered or that have been captured in low numbers. Also, the environment (i.e., the distance between the species' optima in bioclimatic dimensions) in combination with geographic and phylogenetic distance is highly relevant in predicting susceptibility to DENV in wild mammals. Our results agree with previous modeling efforts indicating that temperature is an important factor determining DENV transmission, and provide novel insights regarding other relevant factors and the importance of considering wild reservoirs. This modeling framework will aid in the identification of potential DENV reservoirs for future surveillance efforts.

Space-Time Conditional Autoregressive Modeling to Estimate Neighborhood-Level Risks for Dengue Fever in Cali, Colombia

Vector-borne diseases affect more than 1 billion people a year worldwide, causing more than 1 million deaths, and cost hundreds of billions of dollars in societal costs. Mosquitoes are the most common vectors responsible for transmitting a variety of arboviruses. Dengue fever (DENF) has been responsible for nearly 400 million infections annually. Dengue fever is primarily transmitted by female Aedes aegypti and Aedes albopictus mosquitoes. Because both Aedes species are peri-domestic and container-breeding mosquitoes, dengue surveillance should begin at the local level—where a variety of local factors may increase the risk of transmission. Dengue has been endemic in Colombia for decades and is notably hyperendemic in the city of Cali. For this study, we use weekly cases of DENF in Cali, Colombia, from 2015 to 2016 and develop space–time conditional autoregressive models to quantify how DENF risk is influenced by socioeconomic, environmental, and accessibility risk factors, and lagged weather variables. Our models identify high-risk neighborhoods for DENF throughout Cali. Statistical inference is drawn under Bayesian paradigm using Markov chain Monte Carlo techniques. The results provide detailed insight about the spatial heterogeneity of DENF risk and the associated risk factors (such as weather, proximity to Aedes habitats, and socioeconomic classification) at a fine level, informing public health officials to motivate at-risk neighborhoods to take an active role in vector surveillance and control, and improving educational and surveillance resources throughout the city of Cali.

Entomological Investigation Detects Dengue Virus Type 1 in Aedes (Stegomyia) albopictus (Skuse) during the 2015-16 Outbreak in Hawaii

A dengue outbreak occurred on Hawaii Island between September 2015 and March 2016. Entomological investigations were undertaken between December 2015 and February 2016 to determine which Aedes mosquito species were responsible for the outbreak. A total of 3,259 mosquitoes were collected using a combination of CDC autocidal gravid ovitraps, Biogents BG-Sentinel traps, and hand-nets; immature mosquitoes were collected during environmental surveys. The composition of species was Aedes albopictus (58%), Aedes aegypti (25%), Wyeomyia mitchelli (7%), Aedes vexans (5%), Culex quinquefasciatus (4%), and Aedes japonicus (1%). Adult mosquitoes were analyzed by real-time reverse transcription polymerase chain reaction (PCR) for the presence of dengue virus (DENV) RNA. Of the 185 pools of female mosquitoes tested, 15 containing Ae. albopictus were positive for the presence of DENV type 1 RNA. No virus was detected in pools of the remaining species. Phylogenetic analysis showed the virus strain belonged to genotype I and was closely related to strains that were circulating in the Pacific between 2008 and 2014. This is the first report of detection of DENV in Ae. albopictus from Hawaii.

Socio-Ecological Factors Associated with Dengue Risk and Aedes aegypti Presence in the Galápagos Islands, Ecuador

Dengue fever is an emerging infectious disease in the Galápagos Islands of Ecuador, with the first cases reported in 2002 and subsequent periodic outbreaks. We report results of a 2014 pilot study conducted in Puerto Ayora (PA) on Santa Cruz Island, and Puerto Baquerizo Moreno (PB) on San Cristobal Island. To assess the socio-ecological risk factors associated with dengue and mosquito vector presence at the household level, we conducted 100 household surveys (50 on each island) in neighborhoods with prior reported dengue cases. Adult mosquitoes were collected inside and outside the home, larval indices were determined through container surveys, and heads of households were interviewed to determine demographics, self-reported prior dengue infections, housing conditions, and knowledge, attitudes, and practices regarding dengue. Multi-model selection methods were used to derive best-fit generalized linear regression models of prior dengue infection, and Aedes aegypti presence. We found that 24% of PB and 14% of PA respondents self-reported a prior dengue infection, and more PB homes than PA homes had Ae. aegypti. The top-ranked model for prior dengue infection included several factors related to human movement, household demographics, access to water quality issues, and dengue awareness. The top-ranked model for Ae. aegypti presence included housing conditions, mosquito control practices, and dengue risk perception. This is the first study of dengue risk and Ae. aegypti presence in the Galápagos Islands.

Economic analysis of dengue prevention and case management in the Maldives

As tourism is the mainstay of the Maldives' economy, this country recognizes the importance of controlling mosquito-borne diseases in an environmentally responsible manner. This study sought to estimate the economic costs of dengue in this Small Island Developing State of 417,492 residents. The authors reviewed relevant available documents on dengue epidemiology and conducted site visits and interviews with public health offices, health centers, referral hospitals, health insurers, and drug distribution organizations. An average of 1,543 symptomatic dengue cases was reported annually from 2011 through 2016. Intensive waste and water management on a resort island cost $1.60 per occupied room night. Local vector control programs on inhabited islands cost $35.93 for waste collection and $7.89 for household visits by community health workers per person per year. Ambulatory care for a dengue episode cost $49.87 at a health center, while inpatient episodes averaged $127.74 at a health center, $1,164.78 at a regional hospital, and $1,655.50 at a tertiary referral hospital. Overall, the cost of dengue illness in the Maldives in 2015 was $2,495,747 (0.06% of gross national income, GNI, or $6.10 per resident) plus $1,338,141 (0.03% of GNI or $3.27 per resident) for dengue surveillance. With tourism generating annual income of $898 and tax revenues of $119 per resident, results of an international analysis suggest that the risk of dengue lowers the country's gross annual income by $110 per resident (95% confidence interval $50 to $160) and its annual tax receipts by $14 per resident (95% confidence interval $7 to $22). Many innovative vector control efforts are affordable and could decrease future costs of dengue illness in the Maldives.

Low socioeconomic condition and the risk of dengue fever: A direct relationship

This study aimed to characterize the first dengue fever epidemic in Várzea Paulista, São Paulo, Brazil, and its spatial and spatio-temporal distribution in order to assess the association of socioeconomic factors with dengue occurrence. We used autochthonous dengue cases confirmed in a 2007 epidemic, the first reported in the city, available in the Information System on Diseases of Compulsory Declaration database. These cases where geocoded by address. We identified spatial and spatio-temporal clusters of high- and low-risk dengue areas using scan statistics. To access the risk of dengue occurrence and to evaluate its relationship with socioeconomic level we used a population-based case-control design. Firstly, we fitted a generalized additive model (GAM) to dengue cases and controls without considering the non-spatial covariates to estimate the odds ratios of the occurrence of the disease. The controls were drawn considering the spatial distribution of the household of the study area and represented the source population of the dengue cases. After that, we assessed the relationship between socioeconomic variables and dengue using the GAM and obtained the effect of these covariates in the occurrence of dengue adjusted by the spatial localization of the cases and controls. Cluster analysis and GAM indicated that northeastern area of Várzea Paulista was the most affected area during the epidemic. The study showed a positive relationship between low socioeconomic condition and increased risk of dengue. We studied the first dengue epidemic in a highly susceptible population at the beginning of the outbreak and therefore it may have allowed to identify an association between low socioeconomic conditions and increased risk of dengue. These results may be useful to predict the occurrence and to identify priority areas to develop control measures for dengue, and also for Zika and Chikungunya; diseases that recently reached Latin America, especially Brazil.

After the epidemic: Zika virus projections for Latin America and the Caribbean

Background

Zika is one of the most challenging emergent vector-borne diseases, yet its future public health impact remains unclear. Zika was of little public health concern until recent reports of its association with congenital syndromes. By 3 August 2017 ∼217,000 Zika cases and ∼3,400 cases of associated congenital syndrome were reported in Latin America and the Caribbean. Some modelling exercises suggest that Zika virus infection could become endemic in agreement with recent declarations from the The World Health Organisation.

Methodology/Principal findings

We produced high-resolution spatially-explicit projections of Zika cases, associated congenital syndromes and monetary costs for Latin America and the Caribbean now that the epidemic phase of the disease appears to be over. In contrast to previous studies which have adopted a modelling approach to map Zika potential, we project case numbers using a statistical approach based upon reported dengue case data as a Zika surrogate. Our results indicate that ∼12.3 (0.7–162.3) million Zika cases could be expected across Latin America and the Caribbean every year, leading to ∼64.4 (0.2–5159.3) thousand cases of Guillain-Barré syndrome and ∼4.7 (0.0–116.3) thousand cases of microcephaly. The economic burden of these neurological sequelae are estimated to be USD ∼2.3 (USD 0–159.3) billion per annum.

Conclusions/Significance

Zika is likely to have significant public health consequences across Latin America and the Caribbean in years to come. Our projections inform regional and federal health authorities, offering an opportunity to adapt to this public health challenge.

In February 2016 the World Health Organisation (WHO) declared Zika virus infection in the Americas as a Public Health Emergency of International Concern (PHEIC). By November 2016, Zika was declared a long-term public health challenge. This change of status implies that Zika is likely to become an endemic problem in the region. Due to the PHEIC status of Zika, most current research has rightly focused on the epidemic stage of the disease; however, it is timely and critical to consider the public health consequences after such epidemic phase. We used one of the largest and most spatially diverse panels of epidemiological surveillance data comprising 12 years of dengue case observations from Brazil and Mexico, and covering an area of over ten million km². State-of-the-art statistical models, and high-resolution (0.5 × 0.5 degrees) climate and demographic data were used to produce spatially-explicit projections of Zika infection for Latin America and the Caribbean. Model projections were then used to estimate the number of cases with neurological sequelae and their economic cost. Our findings indicate that the potential health and economic burden of Zika could be considerably large for the region should it become endemic. The estimated burden of Zika under an endemic state highlights the need for health authorities in the countries at risk to promote preventive and control measures.

Epidemiological and ecological determinants of Zika virus transmission in an urban setting

The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting.

Mosquitoes can transmit viruses that cause Zika, dengue and several other tropical diseases that affect humans. Zika virus usually causes mild symptoms, but it is thought that infection during pregnancy can lead to brain abnormalities, including microcephaly, where babies are born with an abnormally small head. Recent studies have shed light on how the Zika virus spread from Africa to reach South America, the Caribbean and North America. However, much less is known about the ecological factors that contribute to the spread of the virus within towns, cities and other local areas.

In 2015, Brazil was struck by an outbreak of the Zika virus that led to an international public health emergency. Lourenço et al. used a mathematical model to explore the local conditions within Feira de Santana (a major urban center in Brazil) that contributed to the outbreak. The model took into account numerous factors, including temperature, humidity, rainfall and the mosquito life-cycle, which made it possible to reconstruct the history of the virus over the past three years and to make projections for the next decades.

It revealed that most of the infections occured during 2015, with approximately 65% of the population infected. The incidences of new infections declined in 2016, as increasing numbers of local people had already been exposed to the virus and became immune. Temperature and humidity appeared to have played a critical role in sustaining the mosquito population carrying the Zika virus.

Further analysis suggests that the risk of Zika virus causing microcephaly is very low – only 0.3–0.5% of the pregnant women in Feira de Santana who were infected with Zika gave birth to a baby with the condition. What therefore makes Zika a public health concern is the combination of a low risk with very high infection rates, which can affect a large number of pregnancies.

This study will help researchers and policy makers to predict how the Zika virus will behave in the coming years. It also highlights the limitations and successes of the current system of surveillance. Moreover, it will help to identify critical time periods in the year when mosquito control strategies should be implemented to limit the spread of this virus. In future, this could help shape new local strategies to control Zika virus, dengue and other diseases carried by mosquitoes.

Climate change and human infectious diseases: A synthesis of research findings from global and spatio-temporal perspectives

The life cycles and transmission of most infectious agents are inextricably linked with climate. In spite of a growing level of interest and progress in determining climate change effects on infectious disease, the debate on the potential health outcomes remains polarizing, which is partly attributable to the varying effects of climate change, different types of pathogen-host systems, and spatio-temporal scales. We summarize the published evidence and show that over the past few decades, the reported negative or uncertain responses of infectious diseases to climate change has been growing. A feature of the research tendency is the focus on temperature and insect-borne diseases at the local and decadal scale. Geographically, regions experiencing higher temperature anomalies have been given more research attention; unfortunately, the Earth's most vulnerable regions to climate variability and extreme events have been less studied. From local to global scales, agreements on the response of infectious diseases to climate change tend to converge. So far, an abundance of findings have been based on statistical methods, with the number of mechanistic studies slowly growing. Research gaps and trends identified in this study should be addressed in the future.

Modeling Mosquito-Borne Disease Spread in U.S. Urbanized Areas: The Case of Dengue in Miami

Expansion of mosquito-borne pathogens into more temperate regions of the world necessitates tools such as mathematical models for understanding the factors that contribute to the introduction and emergence of a disease in populations naïve to the disease. Often, these models are not developed and analyzed until after a pathogen is detected in a population. In this study, we develop a spatially explicit stochastic model parameterized with publicly available U.S. Census data for studying the potential for disease spread in Urbanized Areas of the United States. To illustrate the utility of the model, we specifically study the potential for introductions of dengue to lead to autochthonous transmission and outbreaks in a population representative of the Miami Urbanized Area, where introductions of dengue have occurred frequently in recent years. We describe seasonal fluctuations in mosquito populations by fitting a population model to trap data provided by the Miami-Dade Mosquito Control Division. We show that the timing and location of introduced cases could play an important role in determining both the probability that local transmission occurs as well as the total number of cases throughout the entire region following introduction. We show that at low rates of clinical presentation, small outbreaks of dengue could go completely undetected during a season, which may confound mitigation efforts that rely upon detection. We discuss the sensitivity of the model to several critical parameter values that are currently poorly characterized and motivate the collection of additional data to strengthen the predictive power of this and similar models. Finally, we emphasize the utility of the general structure of this model in studying mosquito-borne diseases such as chikungunya and Zika virus in other regions.

Epidemiology of Chikungunya Virus in Bahia, Brazil, 2014-2015

Chikungunya is an emerging arbovirus that is characterized into four lineages. One of these, the Asian genotype, has spread rapidly in the Americas after its introduction in the Saint Martin island in October 2013. Unexpectedly, a new lineage, the East-Central-South African genotype, was introduced from Angola in the end of May 2014 in Feira de Santana (FSA), the second largest city in Bahia state, Brazil, where over 5,500 cases have now been reported. Number weekly cases of clinically confirmed CHIKV in FSA were analysed alongside with urban district of residence of CHIKV cases reported between June 2014 and October collected from the municipality's surveillance network. The number of cases per week from June 2014 until September 2015 reveals two distinct transmission waves. The first wave ignited in June and transmission ceased by December 2014. However, a second transmission wave started in January and peaked in May 2015, 8 months after the first wave peak, and this time in phase with Dengue virus and Zika virus transmission, which ceased when minimum temperature dropped to approximately 15°C. We find that shorter travelling times from the district where the outbreak first emerged to other urban districts of FSA were strongly associated with incidence in each district in 2014 (R(2)).

Epidemiology of Chikungunya Virus in Bahia, Brazil, 2014-2015

Chikungunya is an emerging arbovirus that is characterized into four lineages. One of these, the Asian genotype, has spread rapidly in the Americas after its introduction in the Saint Martin island in October 2013. Unexpectedly, a new lineage, the East-Central-South African genotype, was introduced from Angola in the end of May 2014 in Feira de Santana (FSA), the second largest city in Bahia state, Brazil, where over 5,500 cases have now been reported. Number weekly cases of clinically confirmed CHIKV in FSA were analysed alongside with urban district of residence of CHIKV cases reported between June 2014 and October collected from the municipality's surveillance network. The number of cases per week from June 2014 until September 2015 reveals two distinct transmission waves. The first wave ignited in June and transmission ceased by December 2014. However, a second transmission wave started in January and peaked in May 2015, 8 months after the first wave peak, and this time in phase with Dengue virus and Zika virus transmission, which ceased when minimum temperature dropped to approximately 15°C. We find that shorter travelling times from the district where the outbreak first emerged to other urban districts of FSA were strongly associated with incidence in each district in 2014 (R(2)).

A dengue outbreak on a floating village at Cat Ba Island in Vietnam

Background

A dengue outbreak in an ecotourism destination spot in Vietnam, from September to November 2013, impacted a floating village of fishermen on the coastal island of Cat Ba. The outbreak raises questions about how tourism may impact disease spread in rural areas.

Methods

Epidemiological data were obtained from the Hai Phong Preventive Medical Center (PMC), including case histories and residential location from all notified dengue cases from this outbreak. All household addresses were geo-located. Knox test, a spatio-temporal analysis that enables inference dengue clustering constrained by space and time, was performed on the geocoded locations. From the plasma available from two patients, positive for Dengue serotype 3 virus (DENV3), the Envelope (E) gene was sequenced, and their genetic relationships compared to other E sequences in the region.

Results

Of 192 dengue cases, the odds ratio of contracting dengue infections for people living in the floating villages compared to those living on the island was 4.9 (95 % CI: 3.6-6.7). The space-time analyses on 111 geocoded dengue residences found the risk of dengue infection to be the highest within 4 days and a radius of 20 m of a given case. Of the total of ten detected clusters with an excess risk greater than 2, the cluster with the highest number of cases was in the floating village area (24 patients for a total duration of 31 days). Phylogenetic analysis revealed a high homology of the two DENV3 strains (genotype III) from Cat Ba with DENV3 viruses circulating in Hanoi in the same year (99.1 %).

Conclusions

Our study showed that dengue transmission is unlikely to be sustained on Cat Ba Island and that the 2013 epidemic likely originated through introduction of viruses from the mainland, potentially Hanoi. These findings suggest that prevention efforts should be focused on mainland rather than on the island.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-2235-y) contains supplementary material, which is available to authorized users.

Understanding the relative importance of global dengue risk factors

Dengue is a mosquito-transmitted viral infection of major international public health concern. Global environmental and socio-economic change has created ideal conditions for the global expansion of dengue transmission. Innovative modelling tools help in understanding the global determinants of dengue risk and the relative impact of environmental and socio-economic factors on dengue transmission and spread. While climatic factors may act as a limiting factor on the global scale, other processes may play a dominant role at the local level. Understanding the spatial scales at which environmental and socio-economic factors dominate can help to target appropriate dengue control and prevention strategies.