Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse)

Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model

Various modelling techniques are available to understand the temporal and spatial variations of the phenology of species. Scientists often rely on correlative models, which establish a statistical relationship between a response variable (such as species abundance or presence-absence) and a set of predominantly abiotic covariates. The choice of the modeling approach, i.e., the algorithm, is itself a significant source of variability, as different algorithms applied to the same dataset can yield disparate outcomes. This inter-model variability has led to the adoption of ensemble modelling techniques, among which stacked generalisation, which has recently demonstrated its capacity to produce robust results. Stacked ensemble modelling incorporates predictions from multiple base learners or models as inputs for a meta-learner. The meta-learner, in turn, assimilates these predictions and generates a final prediction by combining the information from all the base learners. In our study, we utilized a recently published dataset documenting egg abundance observations of Aedes albopictus collected using ovitraps. and a set of environmental predictors to forecast the weekly median number of mosquito eggs using a stacked machine learning model. This approach enabled us to (i) unearth the seasonal egg-laying dynamics of Ae. albopictus for 12 years; (ii) generate spatio-temporal explicit forecasts of mosquito egg abundance in regions not covered by conventional monitoring initiatives. Our work establishes a robust methodological foundation for forecasting the spatio-temporal abundance of Ae. albopictus, offering a flexible framework that can be tailored to meet specific public health needs related to this species.

Present and future suitability of invasive and urban vectors through an environmentally driven mosquito reproduction number

Temperature and water availability significantly influence mosquito population dynamics. We have developed a method, integrating experimental data with insights from mosquito and thermal biology, to calculate the basic reproduction number ([Formula: see text]) for urban mosquito species Aedes albopictus and Aedes aegypti. [Formula: see text] represents the number of female mosquitoes produced by one female during her lifespan, indicating suitability for growth. Environmental conditions, including temperature, rainfall and human density, influence [Formula: see text] by altering key mosquito life cycle traits. Validation using data from Spain and Europe confirms the approach's reliability. Our analysis suggests that temperature increases may not uniformly benefit Ae. albopictus proliferation but could boost Ae. aegypti expansion. We suggest using vector [Formula: see text] maps, leveraging climate and environmental data, to predict areas susceptible to invasive mosquito population growth. These maps aid resource allocation for intervention strategies, supporting effective vector surveillance and management efforts.

The effect of climate change and temperature extremes on Aedes albopictus populations: a regional case study for Italy

The Asian tiger mosquito, Aedes albopictus, has spread widely throughout Italy since its introduction, with significant public health implications. We examine how decadal temperature trends and sub-monthly heatwave events affect its climate-driven geographical distribution and temporal dynamics using a new regional-scale dynamical Aedes model. The model is calibrated using [Formula: see text] years of ovitrap data for Emilia-Romagna and reproduces the vector seasonality and, to a lesser extent, its inter-annual variability. Simulated vector density hotspots overlap with densely populated areas in Rome, Milan, Naples, Foggia, Catania, Palermo, Lecce, Cagliari, Genoa, Turin and large urban centres in Emilia-Romagna. Lower risk is simulated over the Central Apennine mountains and the Alps. At decadal time scale, we simulate a lengthening of the active mosquito season by 0.5-3 weeks per decade, with the vector becoming homodynamic in southern Italy. Depending on the climatic setting, heatwaves can increase or reduce vector populations and, in some locations, can temporarily decrease mosquito populations. Such decreases can be followed by a population rebound and overshoot. Given the model's skill in reproducing key spatio-temporal Ae. albopictus features, there is potential to develop an early warning system to inform control efforts at a national scale.

Human-Environment Interactions Shape Mosquito Seasonal Population Dynamics

Mosquito species, including the Asian tiger mosquito, can transmit disease-causing pathogens such as dengue, Zika, and chikungunya, with their population dynamics influenced by a variety of factors including climate shifts, human activity, and local environmental conditions. Understanding these dynamics is vital for effective control measures. Our study, conducted in Jardí Botanic Marimurtra from May to November 2021, monitored Ae. albopictus activity using BG-Traps and investigated larval control effects. We employed Generalized Linear Mixed Models to analyze variables like weather, human presence, and larvicidal control on adult mosquito abundance. Adults of Ae. albopictus exhibited a seasonal pattern influenced by temperature but with bimodal peaks linked to cumulative rainfall. Proximity to stagnant water and visitor influx directly affected mosquito captures. Additionally, the effectiveness of larvicide treatments depended on interactions between preceding rainfall levels and treatment timing. Our research emphasizes the significance of studying vector ecology at local scales to enhance the efficacy of control programs and address the escalating burden of vector-borne diseases. Considering the impacts of extreme weather events and climate shifts is essential for the development of robust vector control strategies. Furthermore, our distinct findings serve as a prime illustration of utilizing statistical modeling to gain mechanistic insights into ecological patterns and processes.

VectAbundance: a spatio-temporal database of Aedes mosquitoes observations

Modelling approaches play a crucial role in supporting local public health agencies by estimating and forecasting vector abundance and seasonality. However, the reliability of these models is contingent on the availability of standardized, high-quality data. Addressing this need, our study focuses on collecting and harmonizing egg count observations of the mosquito Aedes albopictus, obtained through ovitraps in monitoring and surveillance efforts across Albania, France, Italy, and Switzerland from 2010 to 2022. We processed the raw observations to obtain a continuous time series of ovitraps observations allowing for an extensive geographical and temporal coverage of Ae. albopictus population dynamics. The resulting post-processed observations are stored in the open-access database VectAbundance.This initiative addresses the critical need for accessible, high-quality data, enhancing the reliability of modelling efforts and bolstering public health preparedness.

Dynamics of a Mosquito Egg-Larvae Model with Seasonality

We propose a two stages mosquito egg-larvae model with seasonality as a simplification of a four stages one. For the simplified model we characterize the dynamics in terms of the vectorial reproduction number, [Formula: see text], obtaining extinction if [Formula: see text] and convergence to a unique positive periodic orbit if [Formula: see text]. We illustrate each case with an example, by providing general conditions on the periodic coefficients for its occurrence. These examples are further developed using numerical simulations where the periodic parameters satisfy the conditions obtained. In the [Formula: see text] case, real climatic data is used for inferring the parameter behaviour. For the four stage system, using alternative oviposition rate functions, we present a result which generalizes others given for models with delays and even with diffusion to the case in which competition between the larvae is introduced. The analytical study of our initial four stages system when [Formula: see text] remains open, since we were not able to prove that in this case the system is dissipative.

The current landscape of software tools for the climate-sensitive infectious disease modelling community

Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.

Machine Learning Modeling of Aedes albopictus Habitat Suitability in the 21st Century

The Asian tiger mosquito, Aedes albopictus, is an important vector of arboviruses that cause diseases such as dengue, chikungunya, and zika. The vector is highly invasive and adapted to survive in temperate northern territories outside its native tropical and sub-tropical range. Climate and socio-economic change are expected to facilitate its range expansion and exacerbate the global vector-borne disease burden. To project shifts in the global habitat suitability of the vector, we developed an ensemble machine learning model, incorporating a combination of a Random Forest and XGBoost binary classifiers, trained with a global collection of vector surveillance data and an extensive set of climate and environmental constraints. We demonstrate the reliable performance and wide applicability of the ensemble model in comparison to the known global presence of the vector, and project that suitable habitats will expand globally, most significantly in the northern hemisphere, putting at least an additional billion people at risk of vector-borne diseases by the middle of the 21st century. We project several highly populated areas of the world will be suitable for Ae. albopictus populations, such as the northern parts of the USA, Europe, and India by the end of the century, which highlights the need for coordinated preventive surveillance efforts of potential entry points by local authorities and stakeholders.

Features in and around residential gardens affecting the presence and abundance of questing Ixodes ricinus ticks

People may be exposed to questing Ixodes ricinus ticks in urban settings, e.g. residential gardens. Little is known about the garden characteristics that support a tick population. To determine which features in and around residential gardens support or limit the occurrence and abundance of questing I. ricinus ticks, we sampled them in residential gardens in the Braunschweig region that differed in various intrinsic and extrinsic parameters. We recorded the number of questing nymphal and adult ticks on transects, and by using mixed-effects generalized linear regression models, we related their occurrence and abundance to garden characteristics, meteorological covariates, and landscape features in the vicinity. We detected questing I. ricinus ticks in about 90% of the 103 surveyed gardens. Our occurrence model (marginal R2 = 0.31) predicted the highest probability of questing ticks on transects with hedges or groundcover in gardens, which are located in neighborhoods with large proportions of forest. The abundance of questing ticks was similarly influenced. We conclude that I. ricinus ticks are frequent in residential gardens in Northern Germany and likely associated with intrinsic garden characteristics on a small scale, such as hedges, as well as extrinsic factors on a local scale, such as the proportion of nearby woodland.

The relative importance of key meteorological factors affecting numbers of mosquito vectors of dengue fever

Although single factors such as rainfall are known to affect the population dynamics of Aedes albopictus, the main vector of dengue fever in Eurasia, the synergistic effects of different meteorological factors are not fully understood. To address this topic, we used meteorological data and mosquito-vector association data including Breteau and ovitrap indices in key areas of dengue outbreaks in Guangdong Province, China, to formulate a five-stage mathematical model for Aedes albopictus population dynamics by integrating multiple meteorological factors. Unknown parameters were estimated using a genetic algorithm, and the results were analyzed by k-Shape clustering, random forest and grey correlation analysis. In addition, the population density of mosquitoes in 2022 was predicted and used for evaluating the effectiveness of the model. We found that there is spatiotemporal heterogeneity in the effects of temperature and rainfall and their distribution characteristics on the diapause period, the numbers of peaks in mosquito densities in summer and the annual total numbers of adult mosquitoes. Moreover, we identified the key meteorological indicators of the mosquito quantity at each stage and that rainfall (seasonal rainfall and annual total rainfall) was more important than the temperature distribution (seasonal average temperature and temperature index) and the uniformity of rainfall annual distribution (coefficient of variation) for most of the areas studied. The peak rainfall during the summer is the best indicator of mosquito population development. The results provide important theoretical support for the future design of mosquito vector control strategies and early warnings of mosquito-borne diseases.

Linking mathematical models and trap data to infer the proliferation, abundance, and control of Aedes aegypti

Aedes aegypti is one of the most dominant mosquito species in the urban areas of Miami-Dade County, Florida, and is responsible for the local arbovirus transmissions. Since August 2016, mosquito traps have been placed throughout the county to improve surveillance and guide mosquito control and arbovirus outbreak response. In this paper, we develop a deterministic mosquito population model, estimate model parameters by using local entomological and temperature data, and use the model to calibrate the mosquito trap data from 2017 to 2019. We further use the model to compare the Ae. aegypti population and evaluate the impact of rainfall intensity in different urban built environments. Our results show that rainfall affects the breeding sites and the abundance of Ae. aegypti more significantly in tourist areas than in residential places. In addition, we apply the model to quantitatively assess the effectiveness of vector control strategies in Miami-Dade County.

dynamAedes: a unified modelling framework for invasive Aedes mosquitoes

Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers because of their capacity to transmit viruses that affect humans. Some of these species were brought outside their native range by means of trade and tourism and then colonised new regions thanks to a unique combination of eco-physiological traits. Considering mosquito physiological and behavioural traits to understand and predict their population dynamics is thus a crucial step in developing strategies to mitigate the local densities of invasive Aedes populations. Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data. Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on the species' biology which could be applied to the management of invasive Aedes populations as well as to more theoretical ecological inquiries.

Temperature sensitivity of pest reproductive numbers in age-structured PDE models, with a focus on the invasive spotted lanternfly

Invasive pest establishment is a pervasive threat to global ecosystems, agriculture, and public health. The recent establishment of the invasive spotted lanternfly in the northeastern United States has proven devastating to farms and vineyards, necessitating urgent development of population dynamical models and effective control practices. In this paper, we propose a stage-age-structured system of PDEs to model insect pest populations, in which underlying dynamics are dictated by ambient temperature through rates of development, fecundity, and mortality. The model incorporates diapause and non-diapause pathways, and is calibrated to experimental and field data on the spotted lanternfly. We develop a novel moving mesh method for capturing age-advection accurately, even for coarse discretization parameters. We define a one-year reproductive number ([Formula: see text]) from the spectrum of a one-year solution operator, and study its sensitivity to variations in the mean and amplitude of the annual temperature profile. We quantify assumptions sufficient to give rise to the low-rank structure of the solution operator characteristic of part of the parameter domain. We discuss establishment potential as it results from the pairing of a favorable [Formula: see text] value and transient population survival, and address implications for pest control strategies.

A dynamically structured matrix population model for insect life histories observed under variable environmental conditions

Various environmental drivers influence life processes of insect vectors that transmit human disease. Life histories observed under experimental conditions can reveal such complex links; however, designing informative experiments for insects is challenging. Furthermore, inferences obtained under controlled conditions often extrapolate poorly to field conditions. Here, we introduce a pseudo-stage-structured population dynamics model to describe insect development as a renewal process with variable rates. The model permits representing realistic life stage durations under constant and variable environmental conditions. Using the model, we demonstrate how random environmental variations result in fluctuating development rates and affect stage duration. We apply the model to infer environmental dependencies from the life history observations of two common disease vectors, the southern (Culex quinquefasciatus) and northern (Culex pipiens) house mosquito. We identify photoperiod, in addition to temperature, as pivotal in regulating larva stage duration, and find that carefully timed life history observations under semi-field conditions accurately predict insect development throughout the year. The approach we describe augments existing methods of life table design and analysis, and contributes to the development of large-scale climate- and environment-driven population dynamics models for important disease vectors.

Snow-Covered Tires Generate Microhabitats That Enhance Overwintering Survival of Aedes albopictus (Diptera: Culicidae) in the Midwest, USA

The Asian tiger mosquito, Aedes albopictus (Skuse), is a public health threat because it can potentially transmit multiple pathogenic arboviruses, exhibits aggressive diurnal biting, and is highly invasive. As Ae. albopictus moved northward into the United States, the limits of expansion were predicted as locations with a mean January temperature warmer than -2.5°C. We postulated that the range of Ae. albopictus could exceed these temperature limits if eggs in diapause overwinter in tires that provide an insulating effect from extreme temperatures. Fifteen tires with Ae. albopictus and Aedes triseriatus (Say) eggs, a native cold hardy species, were placed outside at five locations along a latitudinal gradient in Wisconsin and Illinois during the winter of 2018-2019; notably, in January 2019, a regional arctic air event brought the lowest temperatures recorded in over 20 yr. External and internal tire temperatures were recorded at 3 hr intervals, and egg survival was recorded after six months. Aedes albopictus eggs survived only from tires at northernmost locations. The mean internal January temperature of tires that supported survival was -1.8°C, while externally the mean temperature was -5.3°C, indicating that tires provided an average of +3.5°C of insulation. Tires that supported egg survival also had over 100 mm of snow cover during January. In the absence of snow cover, tires across the study area provided an average +0.79°C [95% CI 0.34-1.11] insulation. This work provides strong argument for the inclusion of microhabitats in models of dispersal and establishment of Ae. albopictus and other vector species.

Seasonality and timing of peak abundance of <em>Aedes albopictus</em> in Europe: Implications to public and animal health

Aedes albopictus is a known vector of dengue and chikungunya. Understanding the population dynamics characteristics of vector species is of pivotal importance to optimise surveillance and control activities, to estimate risk for pathogen-transmission, and thus to enhance support of public health decisions. In this paper we used a seasonal activity model to simulate the start (spring hatching) and end (autumn diapause) of the vector season. In parallel, the peak abundance of the species was assessed using both VectorNet field survey data complemented with field studies obtained from literature across the Mediterranean Basin. Our results suggest that spring hatching of eggs in the current distribution area can start at the beginning of March in southern Europe and in April in western Europe. In northern Europe, where the species is not (yet) present, spring hatching would occur from late April to late May. Aedes albopictus can remain active up to 41 weeks in southern Europe whilst the climatic conditions in northern Europe are limiting its potential activity to a maximum of 23 weeks. The peak of egg density is found during summer months from end of July until end of September. During these two months the climatic conditions for species development are optimal, which implies a higher risk for arbovirus transmission by Ae. albopictus and occurrence of epidemics.

Assessing the suitability for Aedes albopictus and dengue transmission risk in China with a delay differential equation model

Dengue is considered non-endemic to mainland China. However, travellers frequently import the virus from overseas and local mosquito species can then spread the disease in the population. As a consequence, mainland China still experiences large dengue outbreaks. Temperature plays a key role in these outbreaks: it affects the development and survival of the vector and the replication rate of the virus. To better understand its implication in the transmission risk of dengue, we developed a delay differential equation model that explicitly simulates temperature-dependent development periods and tested it with collected field data for the Asian tiger mosquito, Aedes albopictus. The model predicts mosquito occurrence locations with a high accuracy (Cohen's κ of 0.78) and realistically replicates mosquito population dynamics. Analysing the infection dynamics during the 2014 dengue outbreak that occurred in Guangzhou showed that the outbreak could have lasted for another four weeks if mosquito control interventions had not been undertaken. Finally, we analyse the dengue transmission risk in mainland China. We find that southern China, including Guangzhou, can have more than seven months of dengue transmission per year while even Beijing, in the temperate north, can have dengue transmission during hot summer months. The results demonstrate the importance of using detailed vector and infection ecology, especially when vector-borne disease transmission risk is modelled over a broad range of climatic zones.

Sterile Insect Technique (SIT) against Aedes Species Mosquitoes: A Roadmap and Good Practice Framework for Designing, Implementing and Evaluating Pilot Field Trials

Aedes albopictus and Aedes aegypti are invasive mosquito species that impose a substantial risk to human health. To control the abundance and spread of these arboviral pathogen vectors, the sterile insect technique (SIT) is emerging as a powerful complement to most commonly-used approaches, in part, because this technique is ecologically benign, specific, and non-persistent in the environment if releases are stopped. Because SIT and other similar vector control strategies are becoming of increasing interest to many countries, we offer here a pragmatic and accessible 'roadmap' for the pre-pilot and pilot phases to guide any interested party. This will support stakeholders, non-specialist scientists, implementers, and decision-makers. Applying these concepts will ensure, given adequate resources, a sound basis for local field trialing and for developing experience with the technique in readiness for potential operational deployment. This synthesis is based on the available literature, in addition to the experience and current knowledge of the expert contributing authors in this field. We describe a typical path to successful pilot testing, with the four concurrent development streams of Laboratory, Field, Stakeholder Relations, and the Business and Compliance Case. We provide a graphic framework with criteria that must be met in order to proceed.

Influence of Temperature on the Life-Cycle Dynamics of Aedes albopictus Population Established at Temperate Latitudes: A Laboratory Experiment

Simple Summary

Mosquitoes represent a potential major public health concern, as they are capable of transmitting several pathogens when biting humans. It is well known that temperature is a crucial factor affecting mosquito biology: for instance, warmer conditions can increase survival and fecundity. Here, we quantify the influence of different temperatures on the bionomics of Aedes albopictus, which is a mosquito species native to Southeast Asia that has been able to spread worldwide during the last forty years. We used specimens collected from northern Italy to assess if temperate individuals are characterized, possibly thanks to an adaptation process, by a different thermal response with respect to subtropical individuals. We found that immature stages are well adapted to colder temperatures, which nonetheless seem to prevent any blood-feeding activity. Adult longevity and fecundity were substantially greater at mild conditions. This thermal adaptation might increase the length of the breeding season and could allow the colonization of areas at higher altitude, resulting in an overall increased risk for potential transmission of Ae. albopictus-borne pathogens.

Abstract

The mosquito species Aedes albopictus has successfully colonized many areas at temperate latitudes, representing a major public health concern. As mosquito bionomics is critically affected by temperature, we experimentally investigated the influence of different constant rearing temperatures (10, 15, 25, and 30 °C) on the survival rates, fecundity, and developmental times of different life stages of Ae. albopictus using a laboratory colony established from specimens collected in northern Italy. We compared our results with previously published data obtained with subtropical populations. We found that temperate Ae. albopictus immature stages are better adapted to colder temperatures: temperate larvae were able to develop even at 10 °C and at 15 °C, larval survivorship was comparable to the one observed at warmer conditions. Nonetheless, at these lower temperatures, we did not observe any blood-feeding activity. Adult longevity and fecundity were substantially greater at 25 °C with respect to the other tested temperatures. Our findings highlight the ability of Ae. albopictus to quickly adapt to colder environments and provide new important insights on the bionomics of this species at temperate latitudes.

Land cover affects microclimate and temperature suitability for arbovirus transmission in an urban landscape

The emergence of mosquito-transmitted viruses poses a global threat to human health. Combining mechanistic epidemiological models based on temperature-trait relationships with climatological data is a powerful technique for environmental risk assessment. However, a limitation of this approach is that the local microclimates experienced by mosquitoes can differ substantially from macroclimate measurements, particularly in heterogeneous urban environments. To address this scaling mismatch, we modeled spatial variation in microclimate temperatures and the thermal potential for dengue transmission by Aedes albopictus across an urban-to-rural gradient in Athens-Clarke County GA. Microclimate data were collected across gradients of tree cover and impervious surface cover. We developed statistical models to predict daily minimum and maximum microclimate temperatures using coarse-resolution gridded macroclimate data (4000 m) and high-resolution land cover data (30 m). The resulting high-resolution microclimate maps were integrated with temperature-dependent mosquito abundance and vectorial capacity models to generate monthly predictions for the summer and early fall of 2018. The highest vectorial capacities were predicted for patches of trees in urban areas with high cover of impervious surfaces. Vectorial capacity was most sensitive to tree cover during the summer and became more sensitive to impervious surfaces in the early fall. Predictions from the same models using temperature data from a local meteorological station consistently over-predicted vectorial capacity compared to the microclimate-based estimates. This work demonstrates that it is feasible to model variation in mosquito microenvironments across an urban-to-rural gradient using satellite Earth observations. Epidemiological models applied to the microclimate maps revealed localized patterns of temperature suitability for disease transmission that would not be detectable using macroclimate data. Incorporating microclimate data into disease transmission models has the potential to yield more spatially precise and ecologically interpretable metrics of mosquito-borne disease transmission risk in urban landscapes.

Predicting the effects of temperature on mosquito abundance and arbovirus transmission cycles is essential for mapping hot spots of disease risk and projecting responses to climate change. In urban landscapes, the built environment and natural features create distinctive environments. Buildings and roads generate warmer conditions through the urban heat island effect, while vegetation can have a cooling effect because of shading and evaporative heat loss. We used land cover data to map microclimate temperature in Athens-Clarke County, GA and applied a temperature-dependent vectorial capacity model to predict the effects of microclimate on dengue transmission by Aedes albopictus. The highest vectorial capacity was predicted in patches of trees located in the urbanized portion of the study area. These locations had relatively warm nighttime and cool daytime temperature, which kept temperatures close to the optimum for disease transmission. This work demonstrates the feasibility of predicting variation in mosquito microenvironments in urban landscapes using satellite Earth observations. Incorporating microclimate data into disease transmission models has the potential to yield more spatially precise and ecologically interpretable metrics of mosquito-borne disease transmission risk.

Toward implementation of combined incompatible and sterile insect techniques for mosquito control: Optimized chilling conditions for handling Aedes albopictus male adults prior to release

Combined incompatible and sterile insect technique (IIT-SIT) has been considered to be an effective and safe approach to control mosquito populations. Immobilization of male adults by chilling is a crucial process required for the packing, transportation and release of the mosquitoes during the implementation of IIT-SIT for mosquito control. In this study, effects of chilling on the Aedes albopictus males with triple Wolbachia infections (HC line), a powerful weapon to fight against the wild type Ae. albopictus population via IIT-SIT, were evaluated under both laboratory and field conditions. Irradiated HC (IHC) males were exposed to 1, 5 and 10°C for 1, 2, 3, 6 and 24 h. The survival rate of the post-chilled IHC males was then monitored. Longevity of post-chilled IHC males was compared to non-chilled males under laboratory and semi-field conditions. Mating competitiveness of IHC/HC males after exposure to 5 or 10°C for 0, 3 and 24 h was then evaluated. Effects of compaction and transportation under chilled conditions on the survival rate of IHC males were also monitored. The optimal chilling conditions for handling IHC males were temperatures between 5 and 10°C for a duration of less than 3 h with no negative impacts on survival rate, longevity and mating competitiveness when compared to non-chilled males. However, the overall quality of post-chilled IHC/HC males decreased when exposed to low temperatures for 24 h. Reduced survival was observed when IHC males were stored at 5°C under a compaction height of 8 cm. Transportation with chilling temperatures fluctuating from 8 to 12°C has no negative impact on the survival of IHC males. This study identified the optimal chilling temperature and duration for the handling and transportation of Ae. albopictus IHC male adults without any detrimental effect on their survival, longevity and mating competitiveness. Further studies are required to develop drone release systems specific for chilled mosquitoes to improve release efficiency, as well as to compare the population suppression efficiency between release of post-chilled and non-chilled males in the field.

The UK's suitability for Aedes albopictus in current and future climates

The Asian tiger mosquito Aedes albopictus is able to transmit various pathogens to humans and animals and it has already caused minor outbreaks of dengue and chikungunya in southern Europe. Alarmingly, it is spreading northwards and its eggs have been found in the UK in 2016 and 2017. Climate-driven models can help to analyse whether this originally subtropical species could become established in northern Europe. But so far, these models have not considered the impact of the diurnal temperature range (DTR) experienced by mosquitoes in the field. Here, we describe a dynamical model for the life cycle of Ae. albopictus, taking into account the DTR, rainfall, photoperiod and human population density. We develop a new metric for habitat suitability and drive our model with different climate data sets to analyse the UK's suitability for this species. For now, most of the UK seems to be rather unsuitable, except for some densely populated and high importation risk areas in southeast England. But this picture changes in the next 50 years: future scenarios suggest that Ae. albopictus could become established over almost all of England and Wales, indicating the need for continued mosquito surveillance.

Accelerating invasion potential of disease vector Aedes aegypti under climate change

Vector-borne diseases remain a major contributor to the global burden of disease, while climate change is expected to exacerbate their risk. Characterising vector development rate and its spatio-temporal variation under climate change is central to assessing the changing basis of human disease risk. We develop a mechanistic phenology model and apply it to Aedes aegypti, an invasive mosquito vector for arboviruses (e.g. dengue, zika and yellow fever). The model predicts the number of life-cycle completions (LCC) for a given location per unit time based on empirically derived biophysical responses to environmental conditions. Results suggest that the world became ~1.5% more suitable per decade for the development of Ae. aegypti during 1950–2000, while this trend is predicted to accelerate to 3.2–4.4% per decade by 2050. Invasion fronts in North America and China are projected to accelerate from ~2 to 6 km/yr by 2050. An increase in peak LCC combined with extended periods suitable for mosquito development is simulated to accelerate the vector’s global invasion potential.

Understanding how life cycles of vectors respond to climatic factors is important to predict potential shifts in vector-borne disease risk in the coming decades. Here the authors develop a mechanistic phenological model for the invasive mosquito Aedes aegypti and apply it to project shifts under climate change scenarios.

Development and calibration of a model for the potential establishment and impact of Aedes albopictus in Europe

The Asian tiger mosquito (Aedes albopictus) is one of the most invasive disease vectors worldwide. The species is a competent vector of dengue, chikungunya, Zika viruses and other severe parasites and pathogens threatening human health. The capacity of this mosquito to colonize and establish in new areas (including temperate regions) is enhanced by its ability of producing diapausing eggs that survive relatively cold winters. The main drivers of population dynamics for this mosquito are water and air temperature and photoperiod. In this paper, we present a mechanistic model that predicts the potential distribution, abundance and activity of Asian tiger mosquito in Europe. The model includes a comprehensive description of: i) the individual life-history strategies, including diapause, ii) the influence of weather-driven individual physiological responses on population dynamics and iii) the density-dependent regulation of larval mortality rate. The model is calibrated using field data from several locations along an altitudinal gradient in the Italian Alps, which enabled accurate prediction of cold temperature effects on population abundance, including identification of conditions that prevent overwintering of the species. Model predictions are consistent with the most updated information on species' presence and absence. Predicted population abundance shows a clear south-north decreasing gradient. A similar yet less evident pattern in the activity of the species is also predicted. The model represents a valuable tool for the development of strategies aimed at the management of Ae. albopictus and for the implementation of effective control measures against vector-borne diseases in Europe.

Complementarity of empirical and process-based approaches to modelling mosquito population dynamics with Aedes albopictus as an example-Application to the development of an operational mapping tool of vector populations

Mosquitoes are responsible for the transmission of major pathogens worldwide. Modelling their population dynamics and mapping their distribution can contribute effectively to disease surveillance and control systems. Two main approaches are classically used to understand and predict mosquito abundance in space and time, namely empirical (or statistical) and process-based models. In this work, we used both approaches to model the population dynamics in Reunion Island of the 'Tiger mosquito', Aedes albopictus, a vector of dengue and chikungunya viruses, using rainfall and temperature data. We aimed to i) evaluate and compare the two types of models, and ii) develop an operational tool that could be used by public health authorities and vector control services. Our results showed that Ae. albopictus dynamics in Reunion Island are driven by both rainfall and temperature with a non-linear relationship. The predictions of the two approaches were consistent with the observed abundances of Ae. albopictus aquatic stages. An operational tool with a user-friendly interface was developed, allowing the creation of maps of Ae. albopictus densities over the whole territory using meteorological data collected from a network of weather stations. It is now routinely used by the services in charge of vector control in Reunion Island.

Seasonality modeling of the distribution of Aedes albopictus in China based on climatic and environmental suitability

Background

Aedes albopictus is a highly invasive mosquito species and a major vector of numerous viral pathogens. Many recent dengue fever outbreaks in China have been caused solely by the vector. Mapping of the potential distribution ranges of Ae. albopictus is crucial for epidemic preparedness and the monitoring of vector populations for disease control. Climate is a key factor influencing the distribution of the species. Despite field studies indicating seasonal population variations, very little modeling work has been done to analyze how environmental conditions influence the seasonality of Ae. albopictus. The aim of the present study was to develop a model based on available observations, climatic and environmental data, and machine learning methods for the prediction of the potential seasonal ranges of Ae. albopictus in China.

Methods

We collected comprehensive up-to-date surveillance data in China, particularly records from the northern distribution margin of Ae. albopictus. All records were assigned long-term (1970–2000) climatic data averages based on the WorldClim 2.0 data set. Machine learning regression tree models were developed using a 10-fold cross-validation method to predict the potential seasonal (or monthly) distribution ranges of Ae. albopictus in China at high resolution based on environmental conditions. The models were assessed based on sensitivity, specificity, and accuracy, using area under curve (AUC). WorldClim 2.0 and climatic and environmental data were used to produce environmental conduciveness (probability) prediction surfaces. Predicted probabilities were generated based on the averages of the 10 models.

Results

During 1998–2017, Ae. albopictus was observed at 200 out of the 242 localities surveyed. In addition, at least 15 new Ae. albopictus occurrence sites lay outside the potential ranges that have been predicted using models previously. The average accuracy was 98.4% (97.1–99.5%), and the average AUC was 99.1% (95.6–99.9%). The predicted Ae. albopictus distribution in winter (December–February) was limited to a small subtropical-tropical area of China, and Ae. albopictus was predicted to occur in northern China only during the short summer season (usually June–September). The predicted distribution areas in summer could reach northeastern China bordering Russia and the eastern part of the Qinghai-Tibet Plateau in southwestern China. Ae. albopictus could remain active in expansive areas from central to southern China in October and November.

Conclusions

Climate and environmental conditions are key factors influencing the seasonal distribution of Ae. albopictus in China. The areas predicted to potentially host Ae. albopictus seasonally in the present study could reach northeastern China and the eastern slope of the Qinghai-Tibet Plateau. Our results present new evidence and suggest the expansion of systematic vector population monitoring activities and regular re-assessment of epidemic risk potential.

Forecasting Zoonotic Infectious Disease Response to Climate Change: Mosquito Vectors and a Changing Environment

Infectious diseases are changing due to the environment and altered interactions among hosts, reservoirs, vectors, and pathogens. This is particularly true for zoonotic diseases that infect humans, agricultural animals, and wildlife. Within the subset of zoonoses, vector-borne pathogens are changing more rapidly with climate change, and have a complex epidemiology, which may allow them to take advantage of a changing environment. Most mosquito-borne infectious diseases are transmitted by mosquitoes in three genera: Aedes, Anopheles, and Culex, and the expansion of these genera is well documented. There is an urgent need to study vector-borne diseases in response to climate change and to produce a generalizable approach capable of generating risk maps and forecasting outbreaks. Here, we provide a strategy for coupling climate and epidemiological models for zoonotic infectious diseases. We discuss the complexity and challenges of data and model fusion, baseline requirements for data, and animal and human population movement. Disease forecasting needs significant investment to build the infrastructure necessary to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions. These investments can contribute to building a modeling community around the globe to support public health officials so as to reduce disease burden through forecasts with quantified uncertainty.

Spatial Modeling of Mosquito Vectors for Rift Valley Fever Virus in Northern Senegal: Integrating Satellite-Derived Meteorological Estimates in Population Dynamics Models

Mosquitoes are vectors of major pathogen agents worldwide. Population dynamics models are useful tools to understand and predict mosquito abundances in space and time. To be used as forecasting tools over large areas, such models could benefit from integrating remote sensing data that describe the meteorological and environmental conditions driving mosquito population dynamics. The main objective of this study is to assess a process-based modeling framework for mosquito population dynamics using satellite-derived meteorological estimates as input variables. A generic weather-driven model of mosquito population dynamics was applied to Rift Valley fever vector species in northern Senegal, with rainfall, temperature, and humidity as inputs. The model outputs using meteorological data from ground weather station vs satellite-based estimates are compared, using longitudinal mosquito trapping data for validation at local scale in three different ecosystems. Model predictions were consistent with field entomological data on adult abundance, with a better fit between predicted and observed abundances for the Sahelian Ferlo ecosystem, and for the models using in-situ weather data as input. Based on satellite-derived rainfall and temperature data, dynamic maps of three potential Rift Valley fever vector species were then produced at regional scale on a weekly basis. When direct weather measurements are sparse, these resulting maps should be used to support policy-makers in optimizing surveillance and control interventions of Rift Valley fever in Senegal.

A climate-driven and field data-assimilated population dynamics model of sand flies

Sand flies are responsible for the transmission of leishmaniasis, a neglected tropical disease claiming more than 50,000 lives annually. Leishmaniasis is an emerging health risk in tropical and Mediterranean countries as well as temperate regions in North America and Europe. There is an increasing demand for predicting population dynamics and spreading of sand flies to support management and control, yet phenotypic diversity and complex environmental dependence hamper model development. Here, we present the principles for developing predictive species-specific population dynamics models for important disease vectors. Based on these principles, we developed a sand fly population dynamics model with a generic structure where model parameters are inferred using a surveillance dataset collected from Greece and Cyprus. The model incorporates distinct life stages and explicit dependence on a carefully selected set of environmental variables. The model successfully replicates the observations and demonstrates high predictive capacity on the validation dataset from Turkey. The surveillance datasets inform about biological processes, even in the absence of laboratory experiments. Our findings suggest that the methodology can be applied to other vector species to predict abundance, control dispersion, and help to manage the global burden of vector-borne diseases.

Water-induced strong protection against acute exposure to low subzero temperature of adult Aedes albopictus

As an important vector of dengue and Zika, Aedes albopictus has been the fastest spreading invasive mosquitoes in the world over the last 3–4 decades. Cold tolerance is important for survival and expansion of insects. Ae. albopictus adults are generally considered to be cold-intolerant that cannot survive at subzero temperature. However, we found that Ae. albopictus could survive for several hours’ exposure to -9 to -19 ^oC so long as it was exposed with water. Median lethal time (LT₅₀) of Ae. albopictus exposed to -15 and -19 ^oC with water increased by more than 100 times compared to those exposed to the same subzero temperature without water. This phenomenon also existed in adult Aedes aegypti and Culex quinquefasciatus. Ae. albopictus female adults which exposed to low subzero temperature at -9 ^oC with water had similar longevity and reproductive capacity to those of females without cold exposure. Cold exposure after a blood meal also have no detrimental impact on survival capacity of female adult Ae. albopictus compared with those cold exposed without a blood meal. Moreover, our results showed that rapid cold hardening (RCH) was induced in Ae. albopictus during exposing to low subzero temperature with water. Both the RCH and the relative high subzero temperature of water immediate after cold exposure might provide this strong protection against low subzero temperature. The molecular basis of water-induced protection for Ae. albopictus might refer to the increased glycerol during cold exposure, as well as the increased glucose and hsp70 during recovery from cold exposure. Our results suggested that the water-induced strong protection against acute decrease of air temperature for adult mosquitoes might be important for the survival and rapid expansion of Ae. albopictus.

Aedes albopictus is one of two most important vectors for dengue and zika. During the last 3–4 decades, this mosquito has spread from native Asian area to all continents except Antarctica, becoming the most invasive mosquitoes which imposed extensive public health threat to human beings throughout the world. Cold tolerance is important for distribution and survival of insects. During the expansion of Ae. albopictus, especially a spatial expansion to cooler climate areas, it needs to cope with cold temperatures. Moreover, because of such widespread distribution adult Ae. albopictus will certainly often encounter sudden drops in air temperature even below subzero that often happens in early spring and winter, and late autumn. Thus far, adult Ae. albopictus are generally considered to be cold-intolerant that can not survive at subzero temperature. In this study, we found that water can provide strong protection against low subzero temperature even below -10 ^oC. Cold exposure of adult female Ae. albopictus to low subzero temperature with water either before or after a blood meal have no detrimental impact on fitness costs of these adult mosquitoes. Considering water is common in nature, our results indicated that during the expansion of Ae. albopictus especially when adult mosquitoes encounter a sudden drop in air temperature water could be a good shelter for cope with such cold temperature below subzero.

sPop: Age-structured discrete-time population dynamics model in C, Python, and R

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

Modeling a single season of Aedes albopictus populations based on host-seeking data in response to temperature and precipitation in eastern Tennessee

In the southern Appalachia of the U.S., Aedes mosquitoes maintain and transmit La Crosse virus (LACV) which causes La Crosse encephalitis, a neuroinvasive disease of children. In response to mosquito outbreaks, communities organize prevention, detection, and response measures that are dependent on local characteristics of the mosquito population and the community. Knowing Ae. albopictus is an accessory vector of LACV and a nuisance biter, our objective was to build a system of ordinary differential equations to model dynamics in a single season using our data and readily available environmental variables that can reflect the abundance and activity of Ae. albopictus. Consequently, we built an Ae. albopictus single-season mathematical model for eastern Tennessee to fit our 2013 mosquito collection data in order to understand the population fluctuations. We included precipitation, temperature, and rate of change of temperature in the model because Aedes mosquitoes oviposit desiccant tolerant eggs with peak activity occurring over 26° C and those data are readily available and used frequently as forecast predictors. Our ordinary differential equation model accurately fits the data and facilitates predictions and better understanding of Ae. albopictus populations in southern Appalachia.

Forecasting the spatial and seasonal dynamic of Aedes albopictus oviposition activity in Albania and Balkan countries

The increasing spread of the Asian tiger mosquito, Aedes albopictus, in Europe and US raises public health concern due to the species competence to transmit several exotic human arboviruses, among which dengue, chikungunya and Zika, and urges the development of suitable modeling approach to forecast the spatial and temporal distribution of the mosquito. Here we developed a dynamical species distribution modeling approach forecasting Ae. albopictus eggs abundance at high spatial (0.01 degree WGS84) and temporal (weekly) resolution over 10 Balkan countries, using temperature times series of Modis data products and altitude as input predictors. The model was satisfactorily calibrated and validated over Albania based observed eggs abundance data weekly monitored during three years. For a given week of the year, eggs abundance was mainly predicted by the number of eggs and the mean temperature recorded in the preceding weeks. That is, results are in agreement with the biological cycle of the mosquito, reflecting the effect temperature on eggs spawning, maturation and hatching. The model, seeded by initial egg values derived from a second model, was then used to forecast the spatial and temporal distribution of eggs abundance over the selected Balkan countries, weekly in 2011, 2012 and 2013. The present study is a baseline to develop an easy-handling forecasting model able to provide information useful for promoting active surveillance and possibly prevention of Ae. albopictus colonization in presently non-infested areas in the Balkans as well as in other temperate regions.

The Asian tiger mosquito Aedes albopictus, originating from Asia, in the last decade has spread in many regions in Europe and US. Beside the nuisance problem causing to the citizens during the day, this species has raised public health concern, due to its strict association with humans and anthropic habitats, its expanding distribution and its capacities to transmit several human arboviruses. We developed a spatio-temporal model of Ae. albopictus dynamics that helps to understand the biology and the ecology of the species in relation to environmental factors, and to inform efficient control strategies. Here we developed a dynamical species distribution modeling approach at high spatial (over the Balkans) and temporal resolution (weekly scale), enabling to link oviposition activities and climatic conditions across different time periods to forecast the potential future oviposition activities of Ae. albopictus in unknown locations or identify target areas and periods of highest activities. Extrapolating Ae. albopictus abundance over the Balkan region may help to identify habitat suitability where the species has never been reported so far. The temperature-related predictors remain the most determinant predictors among all candidate predictors e.g land cover and rainfall. The model provides useful information for promoting active surveillance on Ae. albopictus and assessing the risk of exotic arbovirus transmission in temperate regions.

Larval superiority of Culex pipiens to Aedes albopictus in a replacement series experiment: prospects for coexistence in Germany

Background

The Asian tiger mosquito Aedes albopictus is an extremely invasive, globally distributed and medically important vector of various human and veterinary pathogens. In Germany, where this species was recently introduced, its establishment may become modulated by interspecific competition from autochthonous mosquito species, especially Culex pipiens (s.l.). While competitive superiority of Ae. albopictus to Cx. pipiens (s.l.) has been described elsewhere, it has not been assessed in the epidemiological conditions of Germany. The present study aimed to determine if such superiority exists under the physicochemical and microclimatic conditions typical for container habitats in Germany.

Methods

In a replacement series experiment, the larval and pupal responses of Ae. albopictus and Cx. pipiens (s.l.) (mortality, development time, growth) to interspecific interaction (five larval ratios) at (sub-)optimal temperatures (15, 20 and 25 °C) and differing food supply (3 and 6 mg animal-based food larva^-1) were investigated using a randomized split-plot design. In addition to physicochemical measurements of the test media, natural physicochemical conditions were determined for comparative analyses in mosquito breeding sites across the Rhine-Main metropolitan region of Germany.

Results

Under the physicochemical and microclimatic conditions similar to the breeding sites of the Rhine-Main region, competitive superiority of Cx. pipiens (s.l.) to Ae. albopictus in terms of larval survival was more frequently observed than balanced coexistence. Food regime and multifactorial interactions, but not temperature alone, were controlling factors for interspecific competition. Larval food regime and the larval ratio of Ae. albopictus influenced the physicochemistry and algal growth at 15 °C, with increased Ae. albopictus mortality linked to a decreasing number of Scenedesmus, Oocystis and Anabaena algae.

Conclusions

Under the present environmental conditions, the spread of Ae. albopictus from isolated foci in Germany may generally be slowed by biotic interactions with the ubiquitous Cx. pipiens (s.l.) (and potentially other container-breeding mosquito species) and by limnic microalgae in microhabitats with high resource levels. Detailed knowledge of the context dependency in temperate mosquito ecology, and interrelations of physicochemistry and phycology may help to achieve a better understanding of the upcoming Ae. albopictus colonization processes in central and northern Europe.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2665-3) contains supplementary material, which is available to authorized users.

Modeling the Environmental Suitability for Aedes (Stegomyia) aegypti and Aedes (Stegomyia) albopictus (Diptera: Culicidae) in the Contiguous United States

The mosquitoes Aedes (Stegomyia) aegypti (L.)(Diptera:Culicidae) and Ae. (Stegomyia) albopictus (Skuse) (Diptera:Culicidae) transmit dengue, chikungunya, and Zika viruses and represent a growing public health threat in parts of the United States where they are established. To complement existing mosquito presence records based on discontinuous, non-systematic surveillance efforts, we developed county-scale environmental suitability maps for both species using maximum entropy modeling to fit climatic variables to county presence records from 1960-2016 in the contiguous United States. The predictive models for Ae. aegypti and Ae. albopictus had an overall accuracy of 0.84 and 0.85, respectively. Cumulative growing degree days (GDDs) during the winter months, an indicator of overall warmth, was the most important predictive variable for both species and was positively associated with environmental suitability. The number (percentage) of counties classified as environmentally suitable, based on models with 90 or 99% sensitivity, ranged from 1,443 (46%) to 2,209 (71%) for Ae. aegypti and from 1,726 (55%) to 2,329 (75%) for Ae. albopictus. Increasing model sensitivity results in more counties classified as suitable, at least for summer survival, from which there are no mosquito records. We anticipate that Ae. aegypti and Ae. albopictus will be found more commonly in counties classified as suitable based on the lower 90% sensitivity threshold compared with the higher 99% threshold. Counties predicted suitable with 90% sensitivity should therefore be a top priority for expanded mosquito surveillance efforts while still keeping in mind that Ae. aegypti and Ae. albopictus may be introduced, via accidental transport of eggs or immatures, and potentially proliferate during the warmest part of the year anywhere within the geographic areas delineated by the 99% sensitivity model.

Cold tolerance of the Asian tiger mosquito Aedes albopictus and its response to epigenetic alterations

Phenotypic plasticity is considered as one of the key traits responsible for the establishment of populations of the invasive mosquito Aedes albopictus, an important vector of viral and parasitic pathogens. The successful spread of this species to higher altitudes and latitudes may be explained by its ability to rapidly induce a heritable low-temperature phenotype (cold hardiness in eggs). As a result of the low genetic diversity of founder populations, an epigenetic short-term mechanism has been suggested as the driver of this diversification. We investigated if random epigenetic alterations promoted the cold hardiness of Ae. albopictus eggs from a transgenerational study of two epigenetic agents (genistein and vinclozolin). To this end, we evaluated changes in lethal time for 50% of pharate larvae (Lt₅₀) from eggs exposed to -2°C in two subsequent generations that used a new dose-response test design. We detected a significant diversification of the cold hardiness of eggs (up to 64.5%) that was associated with the epigenetic change in the two subsequent offspring generations. An effect size of epigenetically modulated cold hardiness of this magnitude is likely to have an impact on the spatial distribution of this species. Our results provide a framework for further research on epigenetic temperature adaptation of invasive species to better explain and predict their rapid range expansions.

A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology

Chikungunya is a viral disease transmitted to humans primarily via the bites of infected Aedes mosquitoes. The virus caused a major epidemic in the Indian Ocean in 2004, affecting millions of inhabitants, while cases have also been observed in Europe since 2007. We developed a stochastic spatiotemporal model of Aedes albopictus-borne chikungunya transmission based on our recently developed environmentally-driven vector population dynamics model. We designed an integrated modelling framework incorporating large-scale gridded climate datasets to investigate disease outbreaks on Reunion Island and in Italy. We performed Bayesian parameter inference on the surveillance data, and investigated the validity and applicability of the underlying biological assumptions. The model successfully represents the outbreak and measures of containment in Italy, suggesting wider applicability in Europe. In its current configuration, the model implies two different viral strains, thus two different outbreaks, for the two-stage Reunion Island epidemic. Characterisation of the posterior distributions indicates a possible relationship between the second larger outbreak on Reunion Island and the Italian outbreak. The model suggests that vector control measures, with different modes of operation, are most effective when applied in combination: adult vector intervention has a high impact but is short-lived, larval intervention has a low impact but is long-lasting, and quarantining infected territories, if applied strictly, is effective in preventing large epidemics. We present a novel approach in analysing chikungunya outbreaks globally using a single environmentally-driven mathematical model. Our study represents a significant step towards developing a globally applicable Ae. albopictus-borne chikungunya transmission model, and introduces a guideline for extending such models to other vector-borne diseases.

Mechanistic models for predicting insect responses to climate change

Mechanistic models of the impacts of climate change on insects can be seen as very specific hypotheses about the connections between microclimate, ecophysiology and vital rates. These models must adequately capture stage-specific responses, carry-over effects between successive stages, and the evolutionary potential of the functional traits involved in complex insect life-cycles. Here we highlight key considerations for current approaches to mechanistic modelling of insect responses to climate change. We illustrate these considerations within a general mechanistic framework incorporating the thermodynamic linkages between microclimate and heat, water and nutrient exchange throughout the life-cycle under different climate scenarios. We emphasise how such a holistic perspective will provide increasingly robust insights into how insects adapt and respond to changing climates.

Zika virus, vectors, reservoirs, amplifying hosts, and their potential to spread worldwide: what we know and what we should investigate urgently

OBJECTIVES

The widespread epidemic of Zika virus infection in South and Central America and the Caribbean in 2015, along with the increased incidence of microcephaly in fetuses born to mothers infected with Zika virus and the potential for worldwide spread, indicate the need to review the current literature regarding vectors, reservoirs, and amplification hosts.

VECTORS

The virus has been isolated in Africa in mosquitoes of the genera Aedes, Anopheles, and Mansonia, and in Southeast Asia and the Pacific area in mosquitoes of the genus Aedes. Aedes albopictus has invaded several countries in Central Africa and all Mediterranean countries, and continues to spread throughout Central and Northern Europe. The wide distribution of the virus in animal hosts and vectors favors the emergence of recombinants.

ANIMAL HOSTS

The virus has been isolated in monkeys, and antibodies have been detected in domestic sheep, goats, horses, cows, ducks, rodents, bats, orangutans, and carabaos.

CONCLUSIONS

It is a public health imperative to define the domestic and wild animal reservoirs, amplification hosts, and vector capacity of the genera Aedes, Anopheles, and Mansonia. These variables will define the geographic distribution of Zika virus along with the indicated timing and scale of the environmental public health interventions worldwide.