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

Applying fuzzy logic to assess the biogeographical risk of dengue in South America

BACKGROUND

Over the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affecting both the vector species and the virus.

METHODS

We contribute with a methodology based on fuzzy logic that is helpful to disentangle the main factors that determine favorable environmental conditions for vectors and diseases. Using favorability functions as fuzzy logic modelling technique and the fuzzy intersection, union and inclusion as fuzzy operators, we were able to specify the territories at biogeographical risk of dengue outbreaks in South America.

RESULTS

Our results indicate that the distribution of Ae. aegypti mostly encompasses the biogeographical framework of dengue in South America, which suggests that this species is the principal vector responsible for the geographical extent of dengue cases in the continent. Nevertheless, the intersection between the favorability for dengue cases and the union of the favorability for any of the vector species provided a comprehensive map of the biogeographical risk for dengue.

CONCLUSIONS

Fuzzy logic is an appropriate conceptual and operational tool to tackle the nuances of the vector-illness biogeographical interaction. The application of fuzzy logic may be useful in decision-making by the public health authorities to prevent, control and mitigate vector-borne diseases.

Developing a dengue prediction model based on climate in Tawau, Malaysia

Dengue is fast becoming the most urgent health issue in Malaysia, recording close to a 10-fold increase in cases over the last decade. With much uncertainty hovering over the recently introduced tetravalent vaccine and no effective antiviral drugs, vector control remains the most important strategy in combating dengue. This study analyses the relationship between weather predictors including its lagged terms, and dengue incidence in the District of Tawau over a period of 12 years, from 2006 to 2017. A forecasting model purposed to predict future outbreaks in Tawau was then developed using this data. Monthly dengue incidence data, mean temperature, maximum temperature, minimum temperature, mean relative humidity and mean rainfall over a period of 12 years from 2006 to 2017 in Tawau were retrieved from Tawau District Health Office and the Malaysian Meteorological Department. Cross-correlation analysis between weather predictors, lagged terms of weather predictors and dengue incidences established statistically significant cross-correlation between lagged periods of weather predictors-namely maximum temperature, mean relative humidity and mean rainfall with dengue incidence at time lags of 4-6 months. These variables were then employed into 3 different methods: a multivariate Poisson regression model, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a SARIMA with external regressors for selection. Three models were selected but the SARIMA with external regressors model utilising maximum temperature at a lag of 6 months (p-value:0.001), minimum temperature at a lag of 4 months (p-value:0.01), mean relative humidity at a lag of 2 months (p-value:0.001), and mean rainfall at a lag of 6 months (p-value:0.001) produced an AIC of 841.94, and a log-likelihood score of -413.97 establishing it as the best fitting model of the methodologies utilised. In validating the models, they were utilised to develop forecasts with the model selected with the highest accuracy of predictions being the SARIMA model predicting 1 month in advance (MAE: 7.032, MSE: 83.977). This study establishes the effect of weather on the intensity and magnitude of dengue incidence as has been previously studied. A prediction model remains a novel method of evidence-based forecasting in Tawau, Sabah. The model developed in this study, demonstrated an ability to forecast potential dengue outbreaks 1 to 4 months in advance. These findings are not dissimilar to what has been previously studied in many different countries- with temperature and humidity consistently being established as powerful predictors of dengue incidence magnitude. When used in prognostication, it can enhance- decision making and allow judicious use of resources in public health setting. Nevertheless, the model remains a work in progress- requiring larger and more diverse data.

The effect of global change on mosquito-borne disease

More than 80% of the global population is at risk of a vector-borne disease, with mosquito-borne diseases being the largest contributor to human vector-borne disease burden. Although many global processes, such as land-use and socioeconomic change, are thought to affect mosquito-borne disease dynamics, research to date has strongly focused on the role of climate change. Here, we show, through a review of contemporary modelling studies, that no consensus on how future changes in climatic conditions will impact mosquito-borne diseases exists, possibly due to interacting effects of other global change processes, which are often excluded from analyses. We conclude that research should not focus solely on the role of climate change but instead consider growing evidence for additional factors that modulate disease risk. Furthermore, future research should adopt new technologies, including developments in remote sensing and system dynamics modelling techniques, to enable a better understanding and mitigation of mosquito-borne diseases in a changing world.

Temperature impacts on dengue emergence in the United States: Investigating the role of seasonality and climate change

Tropical mosquito-borne viruses have been expanding into more temperate regions in recent decades. This is partly due to the coupled effects of temperature on mosquito life history traits and viral infection dynamics and warming surface temperatures, resulting in more suitable conditions for vectors and virus transmission. In this study, we use a deterministic ordinary differential equations model to investigate how seasonal and diurnal temperature fluctuations affect the potential for dengue transmission in six U.S. cities. We specifically consider temperature-dependent mosquito larval development, adult mosquito mortality, and the extrinsic incubation period of the virus. We show that the ability of introductions to lead to outbreaks depends upon the relationship between a city's temperature profile and the time of year at which the initial case is introduced. We also investigate how the potential for outbreaks changes with predicted future increases in mean temperatures due to climate change. We find that climate change will likely lead to increases in suitability for dengue transmission and will increase the periods of the year in which introductions may lead to outbreaks, particularly in cities that typically have mild winters and warm summers, such as New Orleans, Louisiana, and El Paso, Texas. We discuss our results in the context of temperature heterogeneity within and across cities and how these differences may impact the potential for dengue emergence given present day and predicted future temperatures.

Climate drives spatial variation in Zika epidemics in Latin America

Between 2015 and 2017, Zika virus spread rapidly through populations in the Americas with no prior exposure to the disease. Although climate is a known determinant of many Aedes-transmitted diseases, it is currently unclear whether climate was a major driver of the Zika epidemic and how climate might have differentially impacted outbreak intensity across locations within Latin America. Here, we estimated force of infection for Zika over time and across provinces in Latin America using a time-varying susceptible–infectious–recovered model. Climate factors explained less than 5% of the variation in weekly transmission intensity in a spatio-temporal model of force of infection by province over time, suggesting that week to week transmission within provinces may be too stochastic to predict. By contrast, climate and population factors were highly predictive of spatial variation in the presence and intensity of Zika transmission among provinces, with pseudo-R² values between 0.33 and 0.60. Temperature, temperature range, rainfall and population size were the most important predictors of where Zika transmission occurred, while rainfall, relative humidity and a nonlinear effect of temperature were the best predictors of Zika intensity and burden. Surprisingly, force of infection was greatest in locations with temperatures near 24°C, much lower than previous estimates from mechanistic models, potentially suggesting that existing vector control programmes and/or prior exposure to other mosquito-borne diseases may have limited transmission in locations most suitable for Aedes aegypti, the main vector of Zika, dengue and chikungunya viruses in Latin America.

Impact of Temperature Variant on Survival of Aedes albopictus Skuse (Diptera: Culicidae): Implications on Thermotolerance and Acclimation

Aedes albopictus (Skuse 1894) is prevalent in the urban/peri-urban Port Blair, posing a public health threat, during past outbreaks of chikungunya (2006) and dengue (2010). Despite its vector potential, information on the biology is scanty. Therefore, impact of temperature on survival of immature stages, under laboratory conditions, was studied on F₁ population of Andamans. Ae. albopictus larvae were exposed to static temperatures viz. 37°C, 39°C, 41°C, 43°C and 45°C, and the lethal time to cause 50% (LT₅₀) and 90% mortality (LT₉₀) was computed. To assess adaptive thermotolerance, larvae exposed (37°C and 39°C) were re-exposed to higher temperatures (43°C and 45°C). All larvae survived at 37°C and 39°C for the entire exposure period of 420 min, while variable mortality was observed at 41°C, 43°C and 45°C. Larvae re-exposed to 43°C and 45°C showed an increase in thermotolerance with respect to non-adapted larvae. The results are discussed in the context of survival, development and distribution.

MVSE: An R-package that estimates a climate-driven mosquito-borne viral suitability index

Viruses, such as dengue, Zika, yellow fever and chikungunya, depend on mosquitoes for transmission. Their epidemics typically present periodic patterns, linked to the underlying mosquito population dynamics, which are known to be driven by natural climate fluctuations. Understanding how climate dictates the timing and potential of viral transmission is essential for preparedness of public health systems and design of control strategies. While various alternative approaches have been proposed to estimate local transmission potential of such viruses, few open-source, ready to use and freely available software tools exist.We developed the Mosquito-borne Viral Suitability Estimator (MVSE) software package for the R programming environment. MVSE estimates the index P, a novel suitability index based on a climate-driven mathematical expression for the basic reproductive number of mosquito-borne viruses. By accounting for local humidity and temperature, as well as viral, vector and human priors, the index P can be estimated for specific host and viral species in different regions of the globe.We describe the background theory, empirical support and biological interpretation of the index P. Using real-world examples spanning multiple epidemiological contexts, we further demonstrate MVSE's basic functionality, research and educational potentials.

Preliminary Screening of Mosquito Spatial Distribution in Togo: With Special Focus on the Aedes (Diptera: Culicidae) Species

The Togolese Republic has a tropical and humid climate which constitutes an ideal environment for mosquitoes to breed and transmit diseases. The Aedes mosquito is known to transmit yellow fever (YF), dengue, chikungunya, and Zika viruses in West Africa. Togo has been suffering from YF virus transmission, despite vaccination efforts. Unfortunately, there is scarcity in the data that reflect mosquito spatial distribution in Togo, specifically possible YF vectors. In the current study, mosquito surveillance efforts targeted areas with confirmed YF cases between July and August 2012. Indoor mosquitoes were collected using knockdown insecticide spraying, whereas Biogents (BG) traps were used to collect outdoor mosquito adults. Mosquito larval surveillance was conducted as well. In total, 17 species were identified. This investigation revealed the presence of medically important vectors in Togo, especially the Aedes aegypti (Linnaeus) (Diptera: Culicidae) which was collected in the four regions. Screening of all pools of female Aedes mosquitoes for YF, by real-time PCR, showed negative results. This is the first record for Coquillettidia flavocincta (Edwards) (Diptera: Culicidae) species in West Africa. This preliminary work serves as a baseline for further mosquito distribution studies in Togo.

Changing Climatic Factors Favor Dengue Transmission in Lahore, Pakistan

Dengue fever (DF) is a national health problem in Pakistan. It has become endemic in Lahore after its recent reemergence in 2016. This study investigates the impacts of climatic factors (temperature and rainfall) on DF transmission in the district of Lahore through statistical approaches. Initially, the climatic variability was explored using a time series analysis on climatic factors from 1970 to 2012. Furthermore, ordinary and multiple linear regression analyses were used to measure the simulating effect of climatic factors on dengue incidence from 2007 to 2012. The time series analysis revealed significant annual and monthly variability in climatic factors, which shaped a dengue-supporting environment. It also showed a positive temporal relationship between climatic factors and DF. Moreover, the regression analyses revealed a substantial monthly relationship between climatic factors and dengue incidence. The ordinary linear regression of rainfall versus dengue showed monthly R2 = 34.2%, whereas temperature versus dengue presented R2 = 38.0%. The multiple regression analysis showed a monthly significance of R2 = 44.6%. Consequently, our study shows a substantial synergism between dengue and climatic factors in Lahore. The present study could help in unveiling new ways for health prediction modeling of dengue and might be applicable in other subtropical and temperate climates.

Use of Twitter data to improve Zika virus surveillance in the United States during the 2016 epidemic

BACKGROUND

Zika virus (ZIKV) is an emerging mosquito-borne arbovirus that can produce serious public health consequences. In 2016, ZIKV caused an epidemic in many countries around the world, including the United States. ZIKV surveillance and vector control is essential to combating future epidemics. However, challenges relating to the timely publication of case reports significantly limit the effectiveness of current surveillance methods. In many countries with poor infrastructure, established systems for case reporting often do not exist. Previous studies investigating the H1N1 pandemic, general influenza and the recent Ebola outbreak have demonstrated that time- and geo-tagged Twitter data, which is immediately available, can be utilized to overcome these limitations.

METHODS

In this study, we employed a recently developed system called Cloudberry to filter a random sample of Twitter data to investigate the feasibility of using such data for ZIKV epidemic tracking on a national and state (Florida) level. Two auto-regressive models were calibrated using weekly ZIKV case counts and zika tweets in order to estimate weekly ZIKV cases 1 week in advance.

RESULTS

While models tended to over-predict at low case counts and under-predict at extreme high counts, a comparison of predicted versus observed weekly ZIKV case counts following model calibration demonstrated overall reasonable predictive accuracy, with an R2 of 0.74 for the Florida model and 0.70 for the U.S.

MODEL

Time-series analysis of predicted and observed ZIKV cases following internal cross-validation exhibited very similar patterns, demonstrating reasonable model performance. Spatially, the distribution of cumulative ZIKV case counts (local- & travel-related) and zika tweets across all 50 U.S. states showed a high correlation (r = 0.73) after adjusting for population.

CONCLUSIONS

This study demonstrates the value of utilizing Twitter data for the purposes of disease surveillance. This is of high value to epidemiologist and public health officials charged with protecting the public during future outbreaks.

The current and future global distribution and population at risk of dengue

Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world’s population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

Statistical mapping techniques provide insights into the current geographical spread of the mosquito-borne dengue virus infection and predict changes in the areas that will be environmentally suitable to the virus for the years 2020, 2050 and 2080.

Estimating the impact of city-wide Aedes aegypti population control: An observational study in Iquitos, Peru

During the last 50 years, the geographic range of the mosquito Aedes aegypti has increased dramatically, in parallel with a sharp increase in the disease burden from the viruses it transmits, including Zika, chikungunya, and dengue. There is a growing consensus that vector control is essential to prevent Aedes-borne diseases, even as effective vaccines become available. What remains unclear is how effective vector control is across broad operational scales because the data and the analytical tools necessary to isolate the effect of vector-oriented interventions have not been available. We developed a statistical framework to model Ae. aegypti abundance over space and time and applied it to explore the impact of citywide vector control conducted by the Ministry of Health (MoH) in Iquitos, Peru, over a 12-year period. Citywide interventions involved multiple rounds of intradomicile insecticide space spray over large portions of urban Iquitos (up to 40% of all residences) in response to dengue outbreaks. Our model captured significant levels of spatial, temporal, and spatio-temporal variation in Ae. aegypti abundance within and between years and across the city. We estimated the shape of the relationship between the coverage of neighborhood-level vector control and reductions in female Ae. aegypti abundance; i.e., the dose-response curve. The dose-response curve, with its associated uncertainties, can be used to gauge the necessary spraying effort required to achieve a desired effect and is a critical tool currently absent from vector control programs. We found that with complete neighborhood coverage MoH intra-domicile space spray would decrease Ae. aegypti abundance on average by 67% in the treated neighborhood. Our framework can be directly translated to other interventions in other locations with geolocated mosquito abundance data. Results from our analysis can be used to inform future vector-control applications in Ae. aegypti endemic areas globally.

Despite the growing threat of arboviruses, there is a dearth of ‘best practices’ for the primary vector control tools used in the field. In the absence of cluster randomized control trials, evidence on the utility (or lack thereof) of vector control interventions must be gleaned from ongoing control programs. Motivated by 12 years of household-level Ae. aegypti abundance surveys and neighborhood-level space-spray campaign data from Iquitos, Peru, we developed a new framework to model mosquito abundance. In spite of significant spatial and temporal heterogeneity, we identified a statistically significant and practically important impact of the local Ministry of Health space-spray campaign, specifically, a reduction of mosquito abundance of 67% when coverage was optimal. Our framework can be directly applied to other locations with geolocated mosquito abundance data and our findings can be used to both optimize resources within Iquitos as well as inform future vector-control interventions in Ae. aegypti endemic areas globally.

Climate change may enable Aedes aegypti infestation in major European cities by 2100

BACKGROUND

Climate change allows Aedes aegypti to infest new areas. Consequently, it enables the arboviruses the mosquito transmits -- e.g., dengue, chikungunya, Zika and yellow fever - to emerge in previously uninfected areas. An example is the Portuguese island of Madeira during 2012-13.

OBJECTIVE

We aim to understand how climate change will affect the future spread of this potent vector, as an aid in assessing the risk of disease outbreaks and effectively allocating resources for vector control.

METHODS

We used an empirically-informed, process-based mathematical model to study the feasibility of Aedes aegypti infestation into continental Europe. Based on established global climate-change scenario data, we assess the potential of Aedes aegypti to establish in Europe over the 21st century by estimating the vector population growth rate for five climate models (GCM5).

RESULTS

In a low carbon emission future (RCP2.6), we find minimal change to the current situation throughout the whole of the 21st century. In a high carbon future (RCP8.5), a large parts of southern Europe risks being invaded by Aedes aegypti.

CONCLUSION

Our results show that successfully enforcing the Paris Agreement by limiting global warming to below 2 °C significantly lowers the risk for infestation of Aedes aegypti and consequently of potential large-scale arboviral disease outbreaks in Europe within the 21st century.

Climate change and the rising infectiousness of dengue

The disease burden of dengue has been steadily rising over the last half-century due to a multitude of factors, including global trade and travel, urbanization, population growth, and climate variability and change, that facilitate conductive conditions for the proliferation of dengue vectors and viruses. This review describes how climate, specifically temperature, affects the vectors’ ability to cause and sustain outbreaks, and how the infectiousness of dengue is influenced by climatic change. The review is focused on the core concepts and frameworks derived in the area of epidemiology of mosquito-borne diseases and outlines the sensitivity of vectorial capacity and vector-to-human transmission on climatic conditions. It further reviews studies linking mathematical or statistical models of disease transmission to scenarios of projected climate change and provides recommendations for future research directions.

Interpreting mosquito feeding patterns in Australia through an ecological lens: an analysis of blood meal studies

Background

Mosquito-borne pathogens contribute significantly to the global burden of disease, infecting millions of people each year. Mosquito feeding is critical to the transmission dynamics of pathogens, and thus it is important to understanding and interpreting mosquito feeding patterns. In this paper we explore mosquito feeding patterns and their implications for disease ecology through a meta-analysis of published blood meal results collected across Australia from more than 12,000 blood meals from 22 species. To assess mosquito-vertebrate associations and identify mosquitoes on a spectrum of generalist or specialist feeders, we analysed blood meal data in two ways; first using a novel odds ratio analysis, and secondly by calculating Shannon’s diversity scores.

Results

We find that each mosquito species had a unique feeding association with different vertebrates, suggesting species-specific feeding patterns. Broadly, mosquito species could be grouped broadly into those that were primarily ornithophilic and those that fed more often on livestock. Aggregated feeding patterns observed across Australia were not explained by intrinsic variables such as mosquito genetics or larval habitats. We discuss the implications for disease transmission by vector mosquito species classified as generalist-feeders (such as Aedes vigilax and Culex annulirostris), or specialists (such as Aedes aegypti) in light of potential influences on mosquito host choice.

Conclusions

Overall, we find that whilst existing blood meal studies in Australia are useful for investigating mosquito feeding patterns, standardisation of blood meal study methodologies and analyses, including the incorporation of vertebrate surveys, would improve predictions of the impact of vector-host interactions on disease ecology. Our analysis can also be used as a framework to explore mosquito-vertebrate associations, in which host availability data is unavailable, in other global systems.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3405-z) contains supplementary material, which is available to authorized users.

Global expansion and redistribution of Aedes-borne virus transmission risk with climate change

Forecasting the impacts of climate change on Aedes-borne viruses-especially dengue, chikungunya, and Zika-is a key component of public health preparedness. We apply an empirically parameterized model of viral transmission by the vectors Aedes aegypti and Ae. albopictus, as a function of temperature, to predict cumulative monthly global transmission risk in current climates, and compare them with projected risk in 2050 and 2080 based on general circulation models (GCMs). Our results show that if mosquito range shifts track optimal temperature ranges for transmission (21.3-34.0°C for Ae. aegypti; 19.9-29.4°C for Ae. albopictus), we can expect poleward shifts in Aedes-borne virus distributions. However, the differing thermal niches of the two vectors produce different patterns of shifts under climate change. More severe climate change scenarios produce larger population exposures to transmission by Ae. aegypti, but not by Ae. albopictus in the most extreme cases. Climate-driven risk of transmission from both mosquitoes will increase substantially, even in the short term, for most of Europe. In contrast, significant reductions in climate suitability are expected for Ae. albopictus, most noticeably in southeast Asia and west Africa. Within the next century, nearly a billion people are threatened with new exposure to virus transmission by both Aedes spp. in the worst-case scenario. As major net losses in year-round transmission risk are predicted for Ae. albopictus, we project a global shift towards more seasonal risk across regions. Many other complicating factors (like mosquito range limits and viral evolution) exist, but overall our results indicate that while climate change will lead to increased net and new exposures to Aedes-borne viruses, the most extreme increases in Ae. albopictus transmission are predicted to occur at intermediate climate change scenarios.

Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China

Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005-2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Statistical mapping techniques provide insights into the spread of two key arbovirus vectors in Europe and the United States, and predict the future distributions of both mosquitoes in response to accelerating urbanization, connectivity and climate change.

The association between Zika virus infection and microcephaly in Brazil 2015-2017: An observational analysis of over 4 million births

BACKGROUND

In 2015, high rates of microcephaly were reported in Northeast Brazil following the first South American Zika virus (ZIKV) outbreak. Reported microcephaly rates in other Zika-affected areas were significantly lower, suggesting alternate causes or the involvement of arboviral cofactors in exacerbating microcephaly rates.

METHODS AND FINDINGS

We merged data from multiple national reporting databases in Brazil to estimate exposure to 9 known or hypothesized causes of microcephaly for every pregnancy nationwide since the beginning of the ZIKV outbreak; this generated between 3.6 and 5.4 million cases (depending on analysis) over the time period 1 January 2015-23 May 2017. The association between ZIKV and microcephaly was statistically tested against models with alternative causes or with effect modifiers. We found no evidence for alternative non-ZIKV causes of the 2015-2017 microcephaly outbreak, nor that concurrent exposure to arbovirus infection or vaccination modified risk. We estimate an absolute risk of microcephaly of 40.8 (95% CI 34.2-49.3) per 10,000 births and a relative risk of 16.8 (95% CI 3.2-369.1) given ZIKV infection in the first or second trimester of pregnancy; however, because ZIKV infection rates were highly variable, most pregnant women in Brazil during the ZIKV outbreak will have been subject to lower risk levels. Statistically significant associations of ZIKV with other birth defects were also detected, but at lower relative risks than that of microcephaly (relative risk < 1.5). Our analysis was limited by missing data prior to the establishment of nationwide ZIKV surveillance, and its findings may be affected by unmeasured confounding causes of microcephaly not available in routinely collected surveillance data.

CONCLUSIONS

This study strengthens the evidence that congenital ZIKV infection, particularly in the first 2 trimesters of pregnancy, is associated with microcephaly and less frequently with other birth defects. The finding of no alternative causes for geographic differences in microcephaly rate leads us to hypothesize that the Northeast region was disproportionately affected by this Zika outbreak, with 94% of an estimated 8.5 million total cases occurring in this region, suggesting a need for seroprevalence surveys to determine the underlying reason.

Global warming and arboviral infections

Climate change is already expanding the geographic footprint of arboviral infections. In this article we consider the impact of climate change on three arboviruses with particular consideration of the effect on Europe.

A combination of climatic conditions determines major within-season dengue outbreaks in Guangdong Province, China

Background

China’s Guangdong Province experienced a major dengue outbreak in 2014. Here we investigate if the weather conditions contributing to the outbreak can be elucidated by multi-scale models.

Methods

A multi-scale modelling framework, parameterized by available weather, vector and human case data, was used to examine the integrative effect of temperature and precipitation variation on the effective reproduction number (ERN) of dengue fever.

Results

With temperature in the range of 25–30 °C, increasing precipitation leads to an increase in the ERN with an average lag of 10 days. With monthly precipitation fixed, the more regular the pattern of rainfall (i.e. higher numbers of rainy days), the larger is the total number of adult mosquitoes. A rainfall distribution peaking in June and July produces a large ERN, beneficial to transmission. Climate conditions conducive to major outbreaks within a season are a combination of relatively high temperature, high precipitation peaking in June and July, and uninterrupted drizzle or regular rainfall.

Conclusions

Evaluating a set of weather conditions favourable to a future major dengue outbreak requires near-future prediction of temperature variation, total rainfall and its peaking times. Such information permits seasonal rapid response management decisions due to the lags between the precipitation events and the realisation of the ERN.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3295-0) contains supplementary material, which is available to authorized users.

Mapping the global potential distributions of two arboviral vectors Aedes aegypti and Ae. albopictus under changing climate

BACKGROUND

Aedes aegypti and Ae. albopictus are the primary vectors that transmit several arboviral diseases, including dengue, chikungunya, and Zika. The world is presently experiencing a series of outbreaks of these diseases, so, we still require to better understand the current distributions and possible future shifts of their vectors for successful surveillance and control programs. Few studies assessed the influences of climate change on the spatial distributional patterns and abundance of these important vectors, particularly using the most recent climatic scenarios. Here, we updated the current potential distributions of both vectors and assessed their distributional changes under future climate conditions.

METHODS

We used ecological niche modeling approach to estimate the potential distributions of Ae. aegypti and Ae. albopictus under present-day and future climate conditions. This approach fits ecological niche model from occurrence records of each species and environmental variables. For each species, future projections were based on climatic data from 9 general circulation models (GCMs) for each representative concentration pathway (RCP) in each time period, with a total of 72 combinations in four RCPs in 2050 and 2070. All ENMs were tested using the partial receiver operating characteristic (pROC) and a set of 2,048 and 2,003 additional independent records for Ae. aegypti and Ae. albopictus, respectively. Finally, we used background similarity test to assess the similarity between the ENMs of Ae. aegypti and Ae. albopictus.

RESULTS

The predicted potential distribution of Ae. aegypti and Ae. albopictus coincided with the current and historical known distributions of both species. Aedes aegypti showed a markedly broader distributional potential across tropical and subtropical regions than Ae. albopictus. Interestingly, Ae. albopictus was markedly broader in distributional potential across temperate Europe and the United States. All ecological niche models (ENMs) were statistically robust (P < 0.001). ENMs successfully anticipated 98% (1,999/2,048) and 99% (1,985/2,003) of additional independent records for both Ae. aegypti and Ae. albopictus, respectively (P < 0.001). ENMs based on future conditions showed similarity between the overall distributional patterns of future-day and present-day conditions; however, there was a northern range expansion in the continental USA to include parts of Southern Canada in case of Ae. albopictus in both 2050 and 2070. Future models also anticipated further expansion of Ae. albopictus to the East to include most of Europe in both time periods. Aedes aegypti was anticipated to expand to the South in East Australia in 2050 and 2070. The predictions showed differences in distributional potential of both species between diverse RCPs in 2050 and 2070. Finally, the background similarity test comparing the ENMs of Ae. aegypti and Ae. albopictus was unable to reject the null hypothesis of niche similarity between both species (P > 0.05).

CONCLUSION

These updated maps provided details to better guide surveillance and control programs of Ae. aegypti and Ae. albopictus. They have also significant public health importance as a baseline for predicting the emergence of arboviral diseases transmitted by both vectors in new areas across the world.

Cytoplasmic incompatibility management to support Incompatible Insect Technique against Aedes albopictus

Background

The transinfection of the endosymbiotic bacterium Wolbachia provides a method to produce functionally sterile males to be used to suppress mosquito vectors. ARwP is a wPip Wolbachia infected Aedes albopictus which exhibits a bidirectional incompatibility pattern with wild-types. We coupled a modelistic approach with laboratory experiments to test ARwP as a control tool and evaluate the possible occurrence of population replacement following the release of ARwP females in a wild-type (S_ANG) population. Repeated male-only releases were simulated and tested in the laboratory in comparison with releases contaminated with 1% ARwP females. Model simulations also investigated how migration affects the outcome of contaminated releases. Finally, the mean level of egg fertility and the long-term evolution of populations constituted by two Wolbachia infection types were studied by testing S_ANG and ARwP Ae. albopictus and performing more general model simulations.

Results

The model was parametrized with laboratory data and simulations were compared with results of biological trials. Small populations of ARwP males and females were theoretically and experimentally demonstrated to rapidly become extinct when released in larger S_ANG populations. Male-only releases at a 5:1 ratio with respect to the wild-type males led to a complete suppression of the S_ANG population in a few generations. Contaminated releases were efficient as well but led to population replacement in the long term, when the wild-type population approached eradication. Migration significantly contrasted this trend as a 5% population turnover was sufficient to avoid any risk of population replacement. At equal frequencies between ARwP and S_ANG individuals, the mean egg fertility of the overall population was more than halved and suppression was self-sustaining until one of the two infection types extinguished.

Conclusions

In the case of bidirectional incompatibility patterns, the repeated release of incompatible males with small percentages of contaminant females could lead to population replacement in confined environments while it could be managed to target high efficiency and sustainability in wild-type suppression when systems are open to migration. This possibility is discussed based on various contexts and taking into consideration the possibility of integration with other control methods such as SIT and the use of larvicides.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-3208-7) contains supplementary material, which is available to authorized users.

Cross-reactive dengue virus-derived monoclonal antibodies to Zika virus envelope protein: Panacea or Pandora's box?

Background

Dengue Virus (DENV) and Zika Virus (ZIKV) are closely related flaviviruses, circulating in overlapping geographical regions. The recent ZIKV epidemic has been linked to an explosion in reports of microcephaly and neurological defects. It is conceivable that our knowledge of DENV might potentiate the development of a ZIKV vaccine due to the close phylogenetic relationship between these flaviviruses and cross-reactive antibodies, principally to the envelope protein (E protein). Alternatively, cross-reactive antibodies that are generated following vaccination or infection, might become damaging during subsequent infections.

Main body

The aims of this review are to collate and analyse data from a recent series of DENV-derived monoclonal antibody (mAb) panels from different research groups. These panels measured DENV-mAb activity against ZIKV in terms of antibody-dependent enhancement (ADE) and neutralisation. Methodology used across groups was compared and critiqued. Furthermore, the specific antibody targets on E protein were considered and their therapeutic potential evaluated. Shortcomings of hmAb panels suggest ADE may be over-estimated and neutralisation underestimated, as compared to clinical situations. It remains unknown whether preference of enhancement or neutralisation by antibodies to ZIKV E protein is dictated by quantitative aspects of antibody titre or epitope specific variation. Additionally, little is known about how duration between flavivirus reinfections affect secondary antibody response.

Conclusion

This review concludes that our current knowledge of cross-reactive antibodies to E protein is inadequate to anticipate the outcome of deploying an E protein based vaccine to regions co-infected by DENV and ZIKV.

Robustness of the reproductive number estimates in vector-borne disease systems

BACKGROUND

The required efforts, feasibility and predicted success of an intervention strategy against an infectious disease are partially determined by its basic reproduction number, R0. In its simplest form R0 can be understood as the product of the infectious period, the number of infectious contacts and the per-contact transmission probability, which in the case of vector-transmitted diseases necessarily extend to the vector stages. As vectors do not usually recover from infection, they remain infectious for life, which places high significance on the vector's life expectancy. Current methods for estimating the R0 for a vector-borne disease are mostly derived from compartmental modelling frameworks assuming constant vector mortality rates. We hypothesised that some of the assumptions underlying these models can lead to unrealistic high vector life expectancies with important repercussions for R0 estimates.

METHODOLOGY AND PRINCIPAL FINDINGS

Here we used a stochastic, individual-based model which allowed us to directly measure the number of secondary infections arising from one index case under different assumptions about vector mortality. Our results confirm that formulas based on age-independent mortality rates can overestimate R0 by nearly 100% compared to our own estimate derived from first principles. We further provide a correction factor that can be used with a standard R0 formula and adjusts for the discrepancies due to erroneous vector age distributions.

CONCLUSION

Vector mortality rates play a crucial role for the success and general epidemiology of vector-transmitted diseases. Many modelling efforts intrinsically assume these to be age-independent, which, as clearly demonstrated here, can lead to severe over-estimation of the disease's reproduction number. Our results thus re-emphasise the importance of obtaining field-relevant and species-dependent vector mortality rates, which in turn would facilitate more realistic intervention impact predictions.

Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment

Mathematical modeling has an extensive history in vector-borne disease epidemiology, and is increasingly used for prediction, intervention design, and understanding mechanisms. Many studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings. However, few studies have formally evaluated whether vector-borne disease models can properly estimate the parameters of interest given the constraints of a particular dataset. Identifiability analysis allows us to examine whether model parameters can be estimated uniquely-a lack of consideration of such issues can result in misleading or incorrect parameter estimates and model predictions. Here, we evaluate both structural (theoretical) and practical identifiability of a commonly used compartmental model of mosquito-borne disease, using the 2010 dengue epidemic in Taiwan as a case study. We show that while the model is structurally identifiable, it is practically unidentifiable under a range of human and mosquito time series measurement scenarios. In particular, the transmission parameters form a practically identifiable combination and thus cannot be estimated separately, potentially leading to incorrect predictions of the effects of interventions. However, in spite of the unidentifiability of the individual parameters, the basic reproduction number was successfully estimated across the unidentifiable parameter ranges. These identifiability issues can be resolved by directly measuring several additional human and mosquito life-cycle parameters both experimentally and in the field. While we only consider the simplest case for the model, we show that a commonly used model of vector-borne disease is unidentifiable from human and mosquito incidence data, making it difficult or impossible to estimate parameters or assess intervention strategies. This work illustrates the importance of examining identifiability when linking models with data to make predictions and inferences, and particularly highlights the importance of combining laboratory, field, and case data if we are to successfully estimate epidemiological and ecological parameters using models.

Association of dengue fever with Aedes spp. abundance and climatological effects

OBJECTIVE

To analyze the association of dengue fever incidence with Aedes mosquito's abundance, and the effect of climatological and geographical variables, in a region in Morelos State, Mexico.

MATERIALS AND METHODS

Weekly data during the period 2010 to 2014 was used. Mosquito abundance was determined using ovitraps. Confirmed dengue cases were obtained from the Epidemiological Surveillance System. Climatic variables were obtained from weather monitoringstations. The correlation between climate variables and ovitraps data was estimated using a multivariate regression model.

RESULTS

A correlation of mosquito abundance with dengue fever incidence, and a yearly pattern with seasonal variations were observed. The daily mean temperature, relative humidity and rainfall parameters were associated with mosquito egg abundance. Time lags of three and four weeks between egg counts and dengue fever incidence were observed.

CONCLUSION

Time lags between egg counts and dengue incidence could be useful for prevention and control interventions.

Effects of the Environmental Temperature on Aedes aegypti and Aedes albopictus Mosquitoes: A Review

The temperature of the environment is one of the most important abiotic factors affecting the life of insects. As poikilotherms, their body temperature is not constant, and they rely on various strategies to minimize the risk of thermal stress. They have been thus able to colonize a large spectrum of habitats. Mosquitoes, such as Ae. aegypti and Ae. albopictus, vector many pathogens, including dengue, chikungunya, and Zika viruses. The spread of these diseases has become a major global health concern, and it is predicted that climate change will affect the mosquitoes’ distribution, which will allow these insects to bring new pathogens to naïve populations. We synthesize here the current knowledge on the impact of temperature on the mosquito flight activity and host-seeking behavior (1); ecology and dispersion (2); as well as its potential effect on the pathogens themselves and how climate can affect the transmission of some of these pathogens (3).

Projecting the end of the Zika virus epidemic in Latin America: a modelling analysis

BACKGROUND

Zika virus (ZIKV) emerged in Latin America and the Caribbean (LAC) region in 2013, with serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and the lack of a comprehensive collation of data from affected countries.

METHODS

Our analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 90 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vectorial capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.

RESULTS

There was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 would present within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p < 0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.

CONCLUSIONS

The findings suggest that the ZIKV epidemic is by and large over within LAC, with incidence projected to be low in most cities in 2018. Local low levels of transmission are probable, but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.

Changes in temperature alter the potential outcomes of virus host shifts

Host shifts-where a pathogen jumps between different host species-are an important source of emerging infectious disease. With on-going climate change there is an increasing need to understand the effect changes in temperature may have on emerging infectious disease. We investigated whether species' susceptibilities change with temperature and ask if susceptibility is greatest at different temperatures in different species. We infected 45 species of Drosophilidae with an RNA virus and measured how viral load changes with temperature. We found the host phylogeny explained a large proportion of the variation in viral load at each temperature, with strong phylogenetic correlations between viral loads across temperature. The variance in viral load increased with temperature, while the mean viral load did not. This suggests that as temperature increases the most susceptible species become more susceptible, and the least susceptible less so. We found no significant relationship between a species' susceptibility across temperatures, and proxies for thermal optima (critical thermal maximum and minimum or basal metabolic rate). These results suggest that whilst the rank order of species susceptibilities may remain the same with changes in temperature, some species may become more susceptible to a novel pathogen, and others less so.

Determining environmental and anthropogenic factors which explain the global distribution of Aedes aegypti and Ae. albopictus

Background

Responsible for considerable global human morbidity and mortality, Aedes aegypti and Ae. albopictus are the primary vectors of several important human diseases, including dengue and yellow fever. Although numerous variables that affect mosquito survival and reproduction have been recorded at the local and regional scales, many remain untested at the global level, potentially confounding mapping efforts to date.

Methods

We develop a modelling ensemble of boosted regression trees and maximum entropy models using sets of variables previously untested at the global level to examine their performance in predicting the global distribution of these two vectors. The results show that accessibility, absolute humidity and annual minimum temperature are consistently the strongest predictors of mosquito presence. Both vectors are similar in their response to accessibility and humidity, but exhibit individual profiles for temperature. Their mapped ranges are therefore similar except at peripheral latitudes, where the range of Ae. albopictus extends further, a finding consistent with ongoing trapping studies. We show that variables previously identified as being relevant, including maximum and mean temperatures, enhanced vegetation index, relative humidity and population density, are comparatively weak performers.

Results

The variables identified represent three key biological mechanisms. Cold tolerance is a critical biological parameter, controlling both species' distribution northwards, and to a lesser degree for Ae. albopictus which has consequent greater inland suitability in North America, Europe and East Asia. Absolute humidity restricts the distribution of both vectors from drier areas, where moisture availability is very low, and increases their suitability in coastal areas. The latter is exacerbated by accessibility with increased likelihood of vector importation due to greater potential for human and trade movement.

Conclusion

Accessibility, absolute humidity and annual minimum temperatures were the strongest and most robust global predictors of Ae. aegypti and Ae. albopictus presence, which should be considered in control efforts and future distribution projections.

Mapping the transmission risk of Zika virus using machine learning models

Zika virus, which has been linked to severe congenital abnormalities, is exacerbating global public health problems with its rapid transnational expansion fueled by increased global travel and trade. Suitability mapping of the transmission risk of Zika virus is essential for drafting public health plans and disease control strategies, which are especially important in areas where medical resources are relatively scarce. Predicting the risk of Zika virus outbreak has been studied in recent years, but the published literature rarely includes multiple model comparisons or predictive uncertainty analysis. Here, three relatively popular machine learning models including backward propagation neural network (BPNN), gradient boosting machine (GBM) and random forest (RF) were adopted to map the probability of Zika epidemic outbreak at the global level, pairing high-dimensional multidisciplinary covariate layers with comprehensive location data on recorded Zika virus infection in humans. The results show that the predicted high-risk areas for Zika transmission are concentrated in four regions: Southeastern North America, Eastern South America, Central Africa and Eastern Asia. To evaluate the performance of machine learning models, the 50 modeling processes were conducted based on a training dataset. The BPNN model obtained the highest predictive accuracy with a 10-fold cross-validation area under the curve (AUC) of 0.966 [95% confidence interval (CI) 0.965-0.967], followed by the GBM model (10-fold cross-validation AUC = 0.964[0.963-0.965]) and the RF model (10-fold cross-validation AUC = 0.963[0.962-0.964]). Based on training samples, compared with the BPNN-based model, we find that significant differences (p = 0.0258* and p = 0.0001***, respectively) are observed for prediction accuracies achieved by the GBM and RF models. Importantly, the prediction uncertainty introduced by the selection of absence data was quantified and could provide more accurate fundamental and scientific information for further study on disease transmission prediction and risk assessment.

Estimating air temperature using MODIS surface temperature images for assessing Aedes aegypti thermal niche in Bangkok, Thailand

Dengue, the most widespread urban vector-borne disease, is transmitted to human by the mosquito Aedes aegypti. Its distribution in urban areas is heterogeneous over time and space. In time, it is linked to seasonal variations such as warm and cold seasons, as well as rainy and dry seasons. In space, it is linked to social and environmental conditions, which alternate between rich and deprived neighborhoods, vegetated and densely built areas. These variations in terms of land cover can affect surface and air temperature. As a result of its influence on the mosquito's life cycle, temperature plays a crucial part in dengue epidemics potential. Thus, deciphering the thermal variations effects within cities could lead to the identification of precise thermal comfort zones, favorable to the survival of mosquito populations during inter-epidemic periods. The maps that could be produced as a result would enable health authorities to target specific areas. Most cities are equipped with meteorological stations. However, the network is generally not dense enough to precisely identify thermal comfort zones. Remote sensing can be used as a tool to solve this issue. The methodological objective of this paper is to assess the potential of the TVX (Temperature-Vegetation indeX) approach applied to MODIS thermal images for the purpose of estimating daily minimum and maximum air temperatures in the city of Bangkok, Thailand. The TVX approach has been seldom used over urban areas due to the heterogeneous nature of cities in terms of land cover. However, our study shows that in vegetated cities such as Bangkok, the TVX method provides valuable results which can be used to assess thermal niche of A. aegypti.

Insecticide Resistance Associated with kdr Mutations in Aedes albopictus: An Update on Worldwide Evidences

Insecticide resistance is an increasing problem worldwide that limits the efficacy of control methods against several pests of health interest. Among them, Aedes albopictus mosquitoes are efficient vectors of relevant pathogens causing animal and human diseases worldwide, including yellow fever, chikungunya, dengue, and Zika. Different mechanisms are associated in conferring resistance to chemical insecticides. One of the most widespread and analysed mechanisms is the knockdown resistance (kdr) causing resistance to DDT and pyrethroids. The mechanism is associated with mutations in the voltage sensitive sodium channel, which is involved in beginning and propagation of action potentials in nervous cells. The mechanism was originally discovered in the housefly and then it was found in a large number of arthropods. In 2011, a kdr associated mutation was evidenced for the first time in A. albopictus and afterward several evidences were reported in the different areas of the world, including China, USA, Brazil, India, and Mediterranean Countries. This review aims to update and summarize current evidences on kdr in A. albopictus, in order to stimulate further researches to analyse in depth A. albopictus resistance status across the world, especially in countries where the presence of this vector is still an emerging issue. Such information is currently needed given the well-known vector role of A. albopictus in the transmission of severe infectious diseases. Furthermore, the widespread use of chemical insecticides for control strategies against A. albopictus progressively lead to pressure selection inducing the rise of insecticide resistance-related mutations in the species. Such event is especially evident in some countries as China, often related to a history of uncontrolled use of chemical insecticides. Thus, a careful picture on the diffusion of kdr mutations worldwide represents a milestone for the implementation of control plans and the triggering of novel research on alternative strategies for mosquito-borne infections.

Combining Wolbachia-induced sterility and virus protection to fight Aedes albopictus-borne viruses

Among the strategies targeting vector control, the exploitation of the endosymbiont Wolbachia to produce sterile males and/or invasive females with reduced vector competence seems to be promising. A new Aedes albopictus transinfection (ARwP-M) was generated by introducing wMel Wolbachia in the ARwP line which had been established previously by replacing wAlbA and wAlbB Wolbachia with the wPip strain. Various infection and fitness parameters were studied by comparing ARwP-M, ARwP and wild-type (SANG population) Ae. albopictus sharing the same genetic background. Moreover, the vector competence of ARwP-M related to chikungunya, dengue and zika viruses was evaluated in comparison with ARwP. ARwP-M showed a 100% rate of maternal inheritance of wMel and wPip Wolbachia. Survival, female fecundity and egg fertility did not show to differ between the three Ae. albopictus lines. Crosses between ARwP-M males and SANG females were fully unfertile regardless of male age while egg hatch in reverse crosses increased from 0 to about 17% with SANG males aging from 3 to 17 days. When competing with SANG males for SANG females, ARwP-M males induced a level of sterility significantly higher than that expected for an equal mating competitiveness (mean Fried index of 1.71 instead of 1). The overall Wolbachia density in ARwP-M females was about 15 fold higher than in ARwP, mostly due to the wMel infection. This feature corresponded to a strongly reduced vector competence for chikungunya and dengue viruses (in both cases, 5 and 0% rates of transmission at 14 and 21 days post infection) with respect to ARwP females. Results regarding Zika virus did not highlight significant differences between ARwP-M and ARwP. However, none of the tested ARwP-M females was capable at transmitting ZIKV. These findings are expected to promote the exploitation of Wolbachia to suppress the wild-type Ae. albopictus populations.

The spread of mosquito-borne viruses in modern times: A spatio-temporal analysis of dengue and chikungunya

Since the 1970s, mosquito-borne pathogens have spread to previously disease-free areas, as well as causing increased illness in endemic areas. In particular, dengue and chikungunya viruses, transmitted primarily by Aedes aegypti and secondarily by Aedes albopictus mosquitoes, represent a threat for up to a third of the world population, and are a growing public health concern. In this study, we assess the spatial and temporal factors related to the occurrences of historic dengue and chikungunya outbreaks in 76 nations focused geographically on the Indian Ocean, with outbreak data from 1959 to 2009. First, we describe the historical spatial and temporal patterns of outbreaks of dengue and chikungunya in the focal nations. Second, we use a boosted regression tree approach to assess the statistical relationships of nations' concurrent outbreak occurrences and annual occurrences with their spatial proximity to prior infections and climatic and socio-economic characteristics. We demonstrate that higher population density and shorter distances among nations with outbreaks are the dominant factors that characterize both dengue and chikungunya outbreaks. In conclusion, our analysis provides crucial insights, which can be applied to improve nations' surveillance and preparedness for future vector-borne disease epidemics.

Mapping Disease Transmission Risk of Nipah Virus in South and Southeast Asia

Since 1998, Nipah virus (NiV) (genus: Henipavirus; family: Paramyxoviridae), an often-fatal and highly virulent zoonotic pathogen, has caused sporadic outbreak events. Fruit bats from the genus Pteropus are the wildlife reservoirs and have a broad distribution throughout South and Southeast Asia, and East Africa. Understanding the disease biogeography of NiV is critical to comprehending the potential geographic distribution of this dangerous zoonosis. This study implemented the R packages ENMeval and BIOMOD2 as a means of modeling regional disease transmission risk and additionally measured niche similarity between the reservoir Pteropus and the ecological characteristics of outbreak localities with the Schoener's D index and I statistic. Results indicate a relatively high degree of niche overlap between models in geographic and environmental space (D statistic, 0.64; and I statistic, 0.89), and a potential geographic distribution encompassing 19% (2,963,178 km²) of South and Southeast Asia. This study should contribute to current and future efforts to understand the critical ecological contributors and geography of NiV. Furthermore, this study can be used as a geospatial guide to identify areas of high disease transmission risk and to inform national public health surveillance programs.

Effects of desiccation stress on adult female longevity in Aedes aegypti and Ae. albopictus (Diptera: Culicidae): results of a systematic review and pooled survival analysis

Background

Transmission dynamics of mosquito-borne viruses such as dengue, Zika and chikungunya are affected by the longevity of the adult female mosquito. Environmental conditions influence the survival of adult female Aedes mosquitoes, the primary vectors of these viruses. While the association of temperature with Aedes mortality has been relatively well-explored, the role of humidity is less established. The current study’s goals were to compile knowledge of the influence of humidity on adult survival in the important vector species Aedes aegypti and Ae. albopictus, and to quantify this relationship while accounting for the modifying effect of temperature.

Methods

We performed a systematic literature review to identify studies reporting experimental results informing the relationships among temperature, humidity and adult survival in Ae. aegypti and Ae. albopictus. Using a novel simulation approach to harmonize disparate survival data, we conducted pooled survival analyses via stratified and mixed effects Cox regression to estimate temperature-dependent associations between humidity and mortality risk for these species across a broad range of temperatures and vapor pressure deficits.

Results

After screening 1517 articles, 17 studies (one in semi-field and 16 in laboratory settings) met inclusion criteria and collectively reported results for 192 survival experiments. We review and synthesize relevant findings from these studies. Our stratified model estimated a strong temperature-dependent association of humidity with mortality in both species, though associations were not significant for Ae. albopictus in the mixed effects model. Lowest mortality risks were estimated around 27.5 °C and 21.5 °C for Ae. aegypti and Ae. albopictus, respectively, and mortality increased non-linearly with decreasing humidity. Aedes aegypti had a survival advantage relative to Ae. albopictus in the stratified model under most conditions, but species differences were not significant in the mixed effects model.

Conclusions

Humidity is associated with mortality risk in adult female Ae. aegypti in controlled settings. Data are limited at low humidities, temperature extremes, and for Ae. albopictus, and further studies should be conducted to reduce model uncertainty in these contexts. Desiccation is likely an important factor in Aedes population dynamics and viral transmission in arid regions. Models of Aedes-borne virus transmission may be improved by more comprehensively representing humidity effects.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2808-6) contains supplementary material, which is available to authorized users.

The seasonal influence of climate and environment on yellow fever transmission across Africa

Background

Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports.

Methodology/Principal findings

We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike’s Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission.

Conclusions/Significance

The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of large outbreaks, such as those seen in Angola, the Democratic Republic of the Congo and Brazil.

In this article, we describe the development of a model to quantify the seasonal dynamics of yellow fever virus (YFV) transmission across Africa. YFV is a flavivirus transmitted, within Africa, primarily by Aedes spp where it causes an estimated 78,000 deaths a year despite the presence of a safe and effective vaccine. The importance of sufficient vaccination, made difficult by a global shortage, has been highlighted by recent large scale, devastating, outbreaks in Angola, the Democratic Republic of the Congo and Brazil. Here we describe a novel way of parameterising the effect of temperature on YFV transmission and implement statistical models to predict both the geographic and temporal heterogeneities in transmissions, while demonstrating their robustness in comparison to models simply predicting geographic distribution. We believe this quantification of seasonality could lead to more precise applications of vaccination campaigns and vector-control programmes. In turn this would help maximise their impact, especially vital with limited resources, and could contribute to lessening the risk of large scale outbreaks. Not only this, but the methods described here could be applied to other Aedes-borne diseases and as such provide a useful tool in understanding, and combatting, several other important diseases such as dengue and zika.

Modeling the spread of the Zika virus using topological data analysis

Zika virus (ZIKV), a disease spread primarily through the Aedes aegypti mosquito, was identified in Brazil in 2015 and was declared a global health emergency by the World Health Organization (WHO). Epidemiologists often use common state-level attributes such as population density and temperature to determine the spread of disease. By applying techniques from topological data analysis, we believe that epidemiologists will be able to better predict how ZIKV will spread. We use the Vietoris-Rips filtration on high-density mosquito locations in Brazil to create simplicial complexes, from which we extract homology group generators. Previously epidemiologists have not relied on topological data analysis to model disease spread. Evaluating our model on ZIKV case data in the states of Brazil demonstrates the value of these techniques for the improved assessment of vector-borne diseases.

Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis

Background

Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease's contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies.

Methods

We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide.

Findings

Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur.

Interpretation

Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events.

Funding

Bill & Melinda Gates Foundation.

Mapping the spatial distribution of Aedes aegypti and Aedes albopictus

Mosquito-borne infectious diseases, such as Rift Valley fever, Dengue, Chikungunya and Zika, have caused mass human death with the transnational expansion fueled by economic globalization. Simulating the distribution of the disease vectors is of great importance in formulating public health planning and disease control strategies. In the present study, we simulated the global distribution of Aedes aegypti and Aedes albopictus at a 5×5km spatial resolution with high-dimensional multidisciplinary datasets and machine learning methods Three relatively popular and robust machine learning models, including support vector machine (SVM), gradient boosting machine (GBM) and random forest (RF), were used. During the fine-tuning process based on training datasets of A. aegypti and A. albopictus, RF models achieved the highest performance with an area under the curve (AUC) of 0.973 and 0.974, respectively, followed by GBM (AUC of 0.971 and 0.972, respectively) and SVM (AUC of 0.963 and 0.964, respectively) models. The simulation difference between RF and GBM models was not statistically significant (p>0.05) based on the validation datasets, whereas statistically significant differences (p<0.05) were observed for RF and GBM simulations compared with SVM simulations. From the simulated maps derived from RF models, we observed that the distribution of A. albopictus was wider than that of A. aegypti along a latitudinal gradient. The discriminatory power of each factor in simulating the global distribution of the two species was also analyzed. Our results provided fundamental information for further study on disease transmission simulation and risk assessment.

Characterizing environmental suitability of Aedes albopictus (Diptera: Culicidae) in Mexico based on regional and global niche models

The Asian tiger mosquito, Aedes albopictus (Skuse) (Diptera: Culicidae), is an invasive species and a vector of numerous human pathogens, including chikungunya, dengue, yellow fever, and Zika viruses. This mosquito had been reported from 36 geographic locations in Mexico by 2005, increasing to 101 locations by 2010 and 501 locations (spanning 16 states) by 2016. Here we modeled the occupied niche for Ae. albopictus in Mexico to characterize the environmental conditions related to its presence, and to generate updated environmental suitability maps. The predictors with the greatest contribution to characterizing the occupied niche for Ae. albopictus were NDVI and annual mean temperature. We also estimated the environmental suitability for Ae. albopictus in regions of the country where it has not been documented yet, by means of: 1) transferring its occupied niche model to these regions and 2) modeling its fundamental niche using global data. Our models will help vector control and public health institutions to identify areas where Ae. albopictus has not yet been recorded but where it may be present. We emphasize that most of Mexico has environmental conditions that potentially allow the survival of Ae. albopictus, which underscores the need for systematic mosquito monitoring in all states of the country.

Assessment of a trap based Aedes aegypti surveillance program using mathematical modeling

The goal of this study was to assess the goodness-of-fit of theoretical models of population dynamics of Aedes aegypti to trap data collected by a long term entomological surveillance program. The carrying capacity K of this vector was estimated at city and neighborhood level. Adult mosquito abundance was measured via adults collected weekly by a network of sticky traps (Mosquitraps) from January 2008 to December 2011 in Vitória, Espírito Santo, Brazil. K was the only free parameter estimated by the model. At the city level, the model with temperature as a driver captured the seasonal pattern of mosquito abundance. At the local level, we observed a spatial heterogeneity in the estimated carrying capacity between neighborhoods, weakly associated with environmental variables related to poor infrastructure. Model goodness-of-fit was influenced by the number of sticky traps, and suggests a minimum of 16 traps at the neighborhood level for surveillance.

Inferences about spatiotemporal variation in dengue virus transmission are sensitive to assumptions about human mobility: a case study using geolocated tweets from Lahore, Pakistan

Billions of users of mobile phones, social media platforms, and other technologies generate an increasingly large volume of data that has the potential to be leveraged towards solving public health challenges. These and other big data resources tend to be most successful in epidemiological applications when utilized within an appropriate conceptual framework. Here, we demonstrate the importance of assumptions about host mobility in a framework for dynamic modeling of infectious disease spread among districts within a large urban area. Our analysis focused on spatial and temporal variation in the transmission of dengue virus (DENV) during a series of large seasonal epidemics in Lahore, Pakistan during 2011-2014. Similar to many directly transmitted diseases, DENV transmission occurs primarily where people spend time during daytime hours, given that DENV is transmitted by a day-biting mosquito. We inferred spatiotemporal variation in DENV transmission under five different assumptions about mobility patterns among ten districts of Lahore: no movement among districts, movement following patterns of geo-located tweets, movement proportional to district population size, and movement following the commonly used gravity and radiation models. Overall, we found that inferences about spatiotemporal variation in DENV transmission were highly sensitive to this range of assumptions about intra-urban human mobility patterns, although the three assumptions that allowed for a modest degree of intra-urban mobility all performed similarly in key respects. Differing inferences about transmission patterns based on our analysis are significant from an epidemiological perspective, as they have different implications for where control efforts should be targeted and whether conditions for transmission became more or less favorable over time.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (10.1140/epjds/s13688-018-0144-x) contains supplementary material.

Population genomics of the Asian tiger mosquito, Aedes albopictus: insights into the recent worldwide invasion

Aedes albopictus, the "Asian tiger mosquito," is an aggressive biting mosquito native to Asia that has colonized all continents except Antarctica during the last ~30-40 years. The species is of great public health concern as it can transmit at least 26 arboviruses, including dengue, chikungunya, and Zika viruses. In this study, using double-digest Restriction site-Associated DNA (ddRAD) sequencing, we developed a panel of ~58,000 single nucleotide polymorphisms (SNPs) based on 20 worldwide Ae. albopictus populations representing both the invasive and the native range. We used this genomic-based approach to study the genetic structure and the differentiation of Ae. albopictus populations and to understand origin(s) and dynamics of the recent invasions. Our analyses indicated the existence of two major genetically differentiated population clusters, each one including both native and invasive populations. The detection of additional genetic structure within each major cluster supports that these SNPs can detect differentiation at a global and local scale, while the similar levels of genomic diversity between native and invasive range populations support the scenario of multiple invasions or colonization by a large number of propagules. Finally, our results revealed the possible source(s) of the recent invasion in Americas, Europe, and Africa, a finding with important implications for vector-control strategies.

Global risk mapping for major diseases transmitted by Aedes aegypti and Aedes albopictus

OBJECTIVES

The objective of this study was to map the global risk of the major arboviral diseases transmitted by Aedes aegypti and Aedes albopictus by identifying areas where the diseases are reported, either through active transmission or travel-related outbreaks, as well as areas where the diseases are not currently reported but are nonetheless suitable for the vector.

METHODS

Data relating to five arboviral diseases (Zika, dengue fever, chikungunya, yellow fever, and Rift Valley fever (RVF)) were extracted from some of the largest contemporary databases and paired with data on the known distribution of their vectors, A. aegypti and A. albopictus. The disease occurrence data for the selected diseases were compiled from literature dating as far back as 1952 to as recent as 2017. The resulting datasets were aggregated at the country level, except in the case of the USA, where state-level data were used. Spatial analysis was used to process the data and to develop risk maps.

RESULTS

Out of the 250 countries/territories considered, 215 (86%) are potentially suitable for the survival and establishment of A. aegypti and/or A. albopictus. A. albopictus has suitability foci in 197 countries/territories, while there are 188 that are suitable for A. aegypti. There is considerable variation in the suitability range among countries/territories, but many of the tropical regions of the world provide high suitability over extensive areas. Globally, 146 (58.4%) countries/territories reported at least one arboviral disease, while 123 (49.2%) reported more than one of the above diseases. The overall numbers of countries/territories reporting autochthonous vector-borne occurrences of Zika, dengue, chikungunya, yellow fever, and RVF, were 85, 111, 106, 43, and 39, respectively.

CONCLUSIONS

With 215 countries/territories potentially suitable for the most important arboviral disease vectors and more than half of these reporting cases, arboviral diseases are indeed a global public health threat. The increasing proportion of reports that include multiple arboviral diseases highlights the expanding range of their common transmission vectors. The shared features of these arboviral diseases should motivate efforts to combine interventions against these diseases.

The importance of human population characteristics in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases

Background

The mosquito Aedes aegypti has long been a vector for human illness in the Southeastern United States. In the past, it has been responsible for outbreaks of dengue, chikungunya, and yellow fever and, very recently, the Zika virus that has been introduced to the region. Multiple studies have modeled the geographic distribution of Ae. aegypti as a function of climate factors; however, this ignores the importance of humans to the anthropophilic biter. Furthermore, Ae. aegypti thrives in areas where humans have created standing water sites, such as water storage containers and trash. As models are developed to examine the potential impact of climate change, it becomes increasingly important to include the most comprehensive set of predictors possible.

Results

This study uses Maxent, a species distribution model, to evaluate the effects of adding poverty and population density to climate-only models. Performance was evaluated through model fit statistics, such as AUC, omission, and commission, as well as individual variable contributions and response curves. Models which included both population density and poverty exhibited better predictive power and produced more precise distribution maps. Furthermore, the two human population characteristics accounted for much of the model contribution-more so than climate variables.

Conclusions

Modeling mosquito distributions without accounting for their dependence on local human populations may miss factors that are very important to niche realization and subsequent risk of infection for humans. Further research is needed to determine if additional human characteristics should be evaluated for model inclusion.

Genomic and epidemiological characterisation of a dengue virus outbreak among blood donors in Brazil

Outbreaks caused by Dengue, Zika and Chikungunya viruses can spread rapidly in immunologically naïve populations. By analysing 92 newly generated viral genome sequences from blood donors and recipients, we assess the dynamics of dengue virus serotype 4 during the 2012 outbreak in Rio de Janeiro. Phylogenetic analysis indicates that the outbreak was caused by genotype II, although two isolates of genotype I were also detected for the first time in Rio de Janeiro. Evolutionary analysis and modelling estimates are congruent, indicating a reproduction number above 1 between January and June, and at least two thirds of infections being unnoticed. Modelling analysis suggests that viral transmission started in early January, which is consistent with multiple introductions, most likely from the northern states of Brazil, and with an increase in within-country air travel to Rio de Janeiro. The combination of genetic and epidemiological data from blood donor banks may be useful to anticipate epidemic spread of arboviruses.

Management of Arthropod Pathogen Vectors in North America: Minimizing Adverse Effects on Pollinators

Tick and mosquito management is important to public health protection. At the same time, growing concerns about declines of pollinator species raise the question of whether vector control practices might affect pollinator populations. We report the results of a task force of the North American Pollinator Protection Campaign (NAPPC) that examined potential effects of vector management practices on pollinators, and how these programs could be adjusted to minimize negative effects on pollinating species. The main types of vector control practices that might affect pollinators are landscape manipulation, biocontrol, and pesticide applications. Some current practices already minimize effects of vector control on pollinators (e.g., short-lived pesticides and application-targeting technologies). Nontarget effects can be further diminished by taking pollinator protection into account in the planning stages of vector management programs. Effects of vector control on pollinator species often depend on specific local conditions (e.g., proximity of locations with abundant vectors to concentrations of floral resources), so planning is most effective when it includes collaborations of local vector management professionals with local experts on pollinators. Interventions can then be designed to avoid pollinators (e.g., targeting applications to avoid blooming times and pollinator nesting habitats), while still optimizing public health protection. Research on efficient targeting of interventions, and on effects on pollinators of emerging technologies, will help mitigate potential deleterious effects on pollinators in future management programs. In particular, models that can predict effects of integrated pest management on vector-borne pathogen transmission, along with effects on pollinator populations, would be useful for collaborative decision-making.