Global temperature constraints on Aedes aegypti and Ae. albopictus persistence and competence for dengue virus transmission

Seasonal Synchronization of Diapause Phases in Aedes albopictus (Diptera: Culicidae)

In temperate areas, population dynamics of the invasive Asian tiger mosquito Aedes albopictus are strongly affected by winter. The work we present here analyzes the adaptive synchronization of the diapause process in the wintry generation of A. albopictus, where the egg stage is exposed to adverse winter conditions. The seasonal pattern of egg laying activity of a French Mediterranean population of the Asian tiger mosquito was monitored weekly for 2 years with ovitraps. The field diapause incidence and the critical photoperiod (CPP, i.e. the maternal day length inducing diapause in 50% of the eggs), were determined by hatching experiments on the collected eggs. The period of diapause termination was estimated by a field survey of the first hatchings for both years. The CPP is equal to 13.5 hours of light and occurs in the field on the 25th of August. Thus, it is on September 11th, 17 days after the CPP, that 50% of the eggs are in a prediapause stage in the field. The egg diapause rate increases rapidly during September, whereas the mean number of eggs laid decreases sharply after mid-September. Surprisingly, after having reached a peak of 95% at the end of September, from mid-October the diapause incidence declined and stayed below 50%. Indeed, both years the diapause initiates before the rapid decrease of the environmental temperature. This leaves a sufficient period of time to the complete development of one generation of A. albopictus with effective induction of diapause in the laid eggs. The very first larvae hatched were sampled both years in the first half of March. With 20 to 26 weeks in the egg stage and about 7 weeks in the larval stages, the first annual generation spends a long time in immature stages. On a practical point of view, this long development time represents a wide window for eggs and larvae control in early spring.

Modeling the habitat suitability for the arbovirus vector Aedes albopictus (Diptera: Culicidae) in Germany

Climatic changes raise the risk of re-emergence of arthropod-borne virus outbreaks globally. These viruses are transmitted by arthropod vectors, often mosquitoes. Due to increasing worldwide trade and tourism, these vector species are often accidentally introduced into many countries beyond their former distribution range. Aedes albopictus, a well-known disease vector, was detected for the first time in Germany in 2007, but seems to have failed establishment until today. However, the species is known to occur in other temperate regions and a risk for establishment in Germany remains, especially in the face of predicted climate change. Thus, the goal of the study was to estimate the potential distribution of Ae. albopictus in Germany. We used ecological niche modeling in order to estimate the potential habitat suitability for this species under current and projected future climatic conditions. According to our model, there are already two areas in western and southern Germany that appear suitable for Ae. albopictus under current climatic conditions. One of these areas lies in Baden-Wuerttemberg, the other in North-Rhine Westphalia in the Ruhr region. Furthermore, projections under future climatic conditions show an increase of the modeled habitat suitability throughout Germany. Ae. albopictus is supposed to be better acclimated to colder temperatures than other tropical vectors and thus, might become, triggered by climate change, a serious threat to public health in Germany. Our modeling results can help optimizing the design of monitoring programs currently in place in Germany.

The epidemiological characteristics and genetic diversity of dengue virus during the third largest historical outbreak of dengue in Guangdong, China, in 2014

OBJECTIVES

The third largest historical outbreak of dengue occurred during July to December 2014, in 20 of 21 cities of Guangdong, China. The epidemiological and molecular characteristics of the introduction, expansion and phylogeny of the DENV isolates involved in this outbreak were investigated.

METHODS

A combination analyses of epidemiological characteristics and genetic diversity of dengue virus was performed in this study.

RESULTS

In total, 45,236 cases and 6 fatalities were reported. Unemployed individuals, retirees and retailers were the most affected populations. A total of 6024 cases were verified to have DENV infections by nucleic acid detection, of which 5947, 74 and 3 were confirmed to have DENV-1, -2, and -3 infections, respectively. Phylogenetic analyses of DENV-1 isolates were assigned into three genotypes (I, IV, and V). Genotype V was the predominant genotype that likely originated from Singapore. The DENV-2 isolates were assigned to the Cosmopolitan and Asian I genotypes. A unique DENV-3 isolate (genotype III) shared high similarity with isolates obtained from Guangdong in 2013.

CONCLUSIONS

A combination analyses demonstrated the multiple geographical origins of this outbreak, and highlight the importance of early detection, the case management and vector surveillance for preventing further dengue epidemics in Guangdong.

Progress and Challenges in Infectious Disease Cartography

Quantitatively mapping the spatial distributions of infectious diseases is key to both investigating their epidemiology and identifying populations at risk of infection. Important advances in data quality and methodologies have allowed for better investigation of disease risk and its association with environmental factors. However, incorporating dynamic human behavioural processes in disease mapping remains challenging. For example, connectivity among human populations, a key driver of pathogen dispersal, has increased sharply over the past century, along with the availability of data derived from mobile phones and other dynamic data sources. Future work must be targeted towards the rapid updating and dissemination of appropriately designed disease maps to guide the public health community in reducing the global burden of infectious disease.

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes

Background

Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather.

Methodology/Principal Findings

We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution.

Conclusions/Significance

Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning.

Timing and spatial-extent of diseases such as dengue and malaria that result from transmission between humans and mosquitoes are regulated by weather in complicated ways. For Aedes aegypti mosquitoes, the primary vector of dengue, slight changes in different components of weather have important effects on population dynamics, lifespan, biting-frequency, virus incubation period and capacity to transmit the virus, thus inducing changes in transmission probability. These complicated dynamics produce a weather-disease connection that is not well-defined for different ecological settings. Understanding this connection is important to critical elements of policy development and operational control of dengue such as predicting risk, developing human-vector transmission models, and planning surveillance-intervention strategies locally and globally. The empirical profile of the weather-disease connection for dengue developed in this study provides a needed understanding of how temperature and humidity work together in regulating human-mosquito transmission. The observed likelihood of low to epidemic-level transmission was highly sensitive to local seasonal duration in limited areas of this two-dimensional weather-space. Data presented represent a resource for estimating where and when transmission-potential supports epidemics of varying magnitude. This high-resolution weather-disease profile for dengue reveals systematic relationships that are informative for mosquito-borne diseases in general and discussions of consequences of global warming.

The global compendium of Aedes aegypti and Ae. albopictus occurrence

Aedes aegypti and Ae. albopictus are the main vectors transmitting dengue and chikungunya viruses. Despite being pathogens of global public health importance, knowledge of their vectors’ global distribution remains patchy and sparse. A global geographic database of known occurrences of Ae. aegypti and Ae. albopictus between 1960 and 2014 was compiled. Herein we present the database, which comprises occurrence data linked to point or polygon locations, derived from peer-reviewed literature and unpublished studies including national entomological surveys and expert networks. We describe all data collection processes, as well as geo-positioning methods, database management and quality-control procedures. This is the first comprehensive global database of Ae. aegypti and Ae. albopictus occurrence, consisting of 19,930 and 22,137 geo-positioned occurrence records respectively. Both datasets can be used for a variety of mapping and spatial analyses of the vectors and, by inference, the diseases they transmit.

The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus

Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.

Prioritising Infectious Disease Mapping

Background

Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available.

Methodology/Principal Findings

Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites.

Conclusions/Significance

A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited.

Maps have long been used to not only visualise, but also to inform infectious disease control efforts, identify and predict areas of greatest risk of specific diseases, and better understand the epidemiology of disease over various spatial scales. In spite of the utilities of such outputs, globally comprehensive maps have been produced for only a handful of infectious diseases. Due to limited resources, it is necessary to define a framework to prioritise which diseases to consider mapping globally. This paper outlines a framework which compares each disease’s global burden with its associated interest from the policy community in a data-driven manner which can be used to determine the relative priority of each condition. Malaria, HIV and TB are, unsurprisingly, ranked highest due to their considerable health burden, while the other priority diseases are dominated by neglected tropical diseases and vector-borne diseases. For some conditions, global mapping efforts are already in place, however, for many neglected conditions there still remains a need for high resolution spatial surveys.

Predicting unprecedented dengue outbreak using imported cases and climatic factors in Guangzhou, 2014

INTRODUCTION

Dengue is endemic in more than 100 countries, mainly in tropical and subtropical regions, and the incidence has increased 30-fold in the past 50 years. The situation of dengue in China has become more and more severe, with an unprecedented dengue outbreak hitting south China in 2014. Building a dengue early warning system is therefore urgent and necessary for timely and effective response.

METHODOLOGY AND PRINCIPAL FINDINGS

In the study we developed a time series Poisson multivariate regression model using imported dengue cases, local minimum temperature and accumulative precipitation to predict the dengue occurrence in four districts of Guangzhou, China. The time series data were decomposed into seasonal, trend and remainder components using a seasonal-trend decomposition procedure based on loess (STL). The time lag of climatic factors included in the model was chosen based on Spearman correlation analysis. Autocorrelation, seasonality and long-term trend were controlled in the model. A best model was selected and validated using Generalized Cross Validation (GCV) score and residual test. The data from March 2006 to December 2012 were used to develop the model while the data from January 2013 to September 2014 were employed to validate the model. Time series Poisson model showed that imported cases in the previous month, minimum temperature in the previous month and accumulative precipitation with three month lags could project the dengue outbreaks occurred in 2013 and 2014 after controlling the autocorrelation, seasonality and long-term trend.

CONCLUSIONS

Together with the sole transmission vector Aedes albopictus, imported cases, monthly minimum temperature and monthly accumulative precipitation may be used to develop a low-cost effective early warning system.

The changing epidemiology of dengue in China, 1990-2014: a descriptive analysis of 25 years of nationwide surveillance data

BACKGROUND

Dengue has been a notifiable disease in China since 1 September 1989. Cases have been reported each year during the past 25 years of dramatic socio-economic changes in China, and reached a historical high in 2014. This study describes the changing epidemiology of dengue in China during this period, to identify high-risk areas and seasons and to inform dengue prevention and control activities.

METHODS

We describe the incidence and distribution of dengue in mainland China using notifiable surveillance data from 1990-2014, which includes classification of imported and indigenous cases from 2005-2014.

RESULTS

From 1990-2014, 69,321 cases of dengue including 11 deaths were reported in mainland China, equating to 2.2 cases per one million residents. The highest number was recorded in 2014 (47,056 cases). The number of provinces affected has increased, from a median of three provinces per year (range: 1 to 5 provinces) during 1990-2000 to a median of 14.5 provinces per year (range: 5 to 26 provinces) during 2001-2014. During 2005-2014, imported cases were reported almost every month and 28 provinces (90.3%) were affected. However, 99.8% of indigenous cases occurred between July and November. The regions reporting indigenous cases have expanded from the coastal provinces of southern China and provinces adjacent to Southeast Asia to the central part of China. Dengue virus serotypes 1, 2, 3, and 4 were all detected from 2009-2014.

CONCLUSIONS

In China, the area affected by dengue has expanded since 2000 and the incidence has increased steadily since 2012, for both imported and indigenous dengue. Surveillance and control strategies should be adjusted to account for these changes, and further research should explore the drivers of these trends.

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

Background

Transmission of dengue viruses (DENV), the most common arboviral pathogens globally, is influenced by many climatic and socioeconomic factors. However, the relative contributions of these factors on a global scale are unclear.

Methods

We randomly selected 94 islands stratified by socioeconomic and geographic characteristics. With a Bayesian model, we assessed factors contributing to the probability of islands having a history of any dengue outbreaks and of having frequent outbreaks.

Results

Minimum temperature was strongly associated with suitability for DENV transmission. Islands with a minimum monthly temperature of greater than 14.8°C (95% CI: 12.4–16.6°C) were predicted to be suitable for DENV transmission. Increased population size and precipitation were associated with increased outbreak frequency, but did not capture all of the variability. Predictions for 48 testing islands verified these findings.

Conclusions

This analysis clarified two key components of DENV ecology: minimum temperature was the most important determinant of suitability; and endemicity was more likely in areas with high precipitation and large, but not necessarily dense, populations. Wealth and connectivity, in contrast, had no discernable effects. This model adds to our knowledge of global determinants of dengue risk and provides a basis for understanding the ecology of dengue endemicity.

Dengue is still an imported disease in China: a case study in Guangzhou

Dengue virus and its four serotypes (DENV 1-4) infect approximately 390 million people worldwide each year, with most cases in tropical and subtropical regions. Because of repeated introduction of DENV from epidemic regions and suitable weather conditions, many regions have shifted from hypo-endemicity to hyper-endemicity over recent decades. Since the first dengue outbreak in 1978, it is crucial to understand the current situation in China over nearly 40 years. The purpose of the study was to examine whether dengue in China was endemic or not, which is essential for relevant dengue control and prevention strategy implementation in China. The study, combining epidemiological characteristics of dengue from the disease notification system, phylogenetic and phylogeographic analyses, showed that all four serotypes had been detected in Guangzhou, China, which was dominated by DENV 1-2. The Maximum Likelihood tree analytic results showed that the virus detected in Guangzhou localized in different clades, except of virus of 2002 and 2003 clustered together. There existed the mutual introductions between Guangzhou and Southeast Asia. Most of the viruses were imported from Southeast Asia and the sources of outbreaks in Guangzhou mainly originated from Thailand, Indonesia, and the Philippines. The study indicates that dengue in China still remains as an imported disease, with the possibility of localization.

The many projected futures of dengue

Dengue is a vector-borne disease that causes a substantial public health burden within its expanding range. Several modelling studies have attempted to predict the future global distribution of dengue. However, the resulting projections are difficult to compare and are sometimes contradictory because the models differ in their approach, in the quality of the disease data that they use and in the choice of variables that drive disease distribution. In this Review, we compare the main approaches that have been used to model the future global distribution of dengue and propose a set of minimum criteria for future projections that, by analogy, are applicable to other vector-borne diseases.

Estimating drivers of autochthonous transmission of chikungunya virus in its invasion of the americas

Background Chikungunya is an emerging arbovirus that has caused explosive outbreaks in Africa and Asia for decades and invaded the Americas just over a year ago. During this ongoing invasion, it has spread to 45 countries where it has been transmitted autochthonously, infecting nearly 1.3 million people in total. Methods Here, we made use of weekly, country-level case reports to infer relationships between transmission and two putative climatic drivers: temperature and precipitation averaged across each country on a monthly basis. To do so, we used a TSIR model that enabled us to infer a parametric relationship between climatic drivers and transmission potential, and we applied a new method for incorporating a probabilistic description of the serial interval distribution into the TSIR framework. Results We found significant relationships between transmission and linear and quadratic terms for temperature and precipitation and a linear term for log incidence during the previous pathogen generation. The lattermost suggests that case numbers three to four weeks ago are largely predictive of current case numbers. This effect is quite nonlinear at the country level, however, due to an estimated mixing parameter of 0.74. Relationships between transmission and the climatic variables that we estimated were biologically plausible and in line with expectations. Conclusions Our analysis suggests that autochthonous transmission of Chikungunya in the Americas can be correlated successfully with putative climatic drivers, even at the coarse scale of countries and using long-term average climate data. Overall, this provides a preliminary suggestion that successfully forecasting the future trajectory of a Chikungunya outbreak and the receptivity of virgin areas may be possible. Our results also provide tentative estimates of timeframes and areas of greatest risk, and our extension of the TSIR model provides a novel tool for modeling vector-borne disease transmission.

Daily forecast of dengue fever incidents for urban villages in a city

Background

Instead of traditional statistical models for large spatial areas and weekly or monthly temporal units, what public health workers urgently need is a timely risk prediction method for small areas. This risk prediction would provide information for early warning, target surveillance and intervention.

Methods

Daily dengue cases in the 457 urban villages of Kaohsiung City, Taiwan from 2009 to 2012 were used for model development and evaluation. There were in total 2,997 confirmed dengue cases during this period. A logistic regression model was fitted to the daily incidents occurring in the villages for the past 30 days. The fitted model was then used to predict the incidence probabilities of dengue outbreak for the villages the next day. A percentile of the 457*30 fitted incidence probabilities was chosen to determine a cut-point for issuing the alerts. The covariates included three different levels of spatial effect, and with four lag time periods. The population density and the meteorological conditions were also included for the prediction.

Results

The performance of the prediction models was evaluated on 122 consecutive days from September 1 to December 31, 2012. With the 80th percentile threshold, the median sensitivity was 83% and the median false positive rate was 23%. We found that most of the coefficients of the predictors of having cases at the same village in the previous 14 days were positive and significant for the 122 daily updated models. The estimated coefficients of population density were significant during the peak of the epidemic in 2012.

Conclusions

The proposed method can provide near real-time dengue risk prediction for a small area. This can serve as a useful decision making tool for front-line public health workers to control dengue epidemics. The precision of the spatial and temporal units can be easily adjusted to different settings for different cities.

The burden of dengue and chikungunya worldwide: implications for the southern United States and California

BACKGROUND

Dengue virus (DENV) spreads to humans through the bite of an infected Aedes aegypti or Aedes albopictus mosquito and is a growing public health threat to both industrialized and developing nations worldwide. Outbreaks of autochthonous dengue in the United States occurred extensively in the past but over the past 3 decades have again taken place in Florida, Hawaii, and Texas as well as in American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and the US Virgin Islands. As the Aedes vectors spread worldwide it is anticipated that DENV as well as other viruses also transmitted by these vectors, such as Chikungunya virus (CHKV), will invade new areas of the world, including the United States.

OBJECTIVES

In this review, we describe the current burden of dengue disease worldwide and the potential introduction of DENV and CHKV into different areas of the United States. Of these areas, the state of California saw the arrival and spread of the Aedes aegypti vector beginning in 2013. This invasion presents a developing situation when considering the state's number of imported dengue cases and proximity to northern Mexico as well as the rising specter of chikungunya in the Western hemisphere.

FINDINGS

In light of the recent arrival of Aedes aegypti mosquito vectors to California, there is now a small but appreciable risk for endemic transmission of dengue and chikungunya within the State. It is likely, however, that if DENV or CHKV were to become endemic that the public health situation would be similar to that currently found along the Texas-Mexico border. The distribution of Aedes vectors in California as well as a discussion of several factors contributing to the risk for dengue importation are discussed and evaluated.

CONCLUSIONS

Dengue and chikungunya viruses present real risks to states where the Aedes vector is now established. Scientists, physicians, and public health authorities should familiarize themselves with these risks and prepare appropriately.

Dengue outbreaks in Divinopolis, south-eastern Brazil and the geographic and climatic distribution of Aedes albopictus and Aedes aegypti in 2011-2012

OBJECTIVE

To entomologically monitor Aedes spp. and correlate the presence of these vectors with the recent epidemic of dengue in Divinopolis, Minas Gerais State, Brazil.

METHODS

Ovitraps were installed at 44 points in the city, covering six urban areas, from May 2011 to May 2012. After collection, the eggs were incubated until hatching. In the 4th stage of development, the larvae were classified as Ae. aegypti or Ae. albopictus.

RESULTS

In total, 25 633 Aedes spp. eggs were collected. February was the month with the highest incidence, with 5635 eggs collected and a hatching rate of 46.7%. Ae. aegypti eggs had the highest hatching rate, at 72.3%, whereas Ae. albopictus eggs had 27.7%. Climate and population density influenced the number of eggs found. Indicators of vector presence were positively correlated with the occurrence of dengue cases.

CONCLUSION

These data reinforce the need for entomological studies, highlight the relevance of Ae. albopictus as a possible disease vector and demonstrate its adaptation. Ae. albopictus, most commonly found in forested areas, comprised a substantial proportion of the urban mosquito population.