Predicting the spatio-temporal distribution of Culicoides imicola in Sardinia using a discrete-time population model

Relationship Between Weather and Changes in Annual and Seasonal Abundance of Culicoides sonorensis (Diptera: Ceratopogonidae) in Alberta

Factors influencing annual and seasonal abundance of Culicoides sonorensis (Wirth and Jones) (Diptera; Ceratopogonidae) were examined at 10 sites in southern Alberta using negative binomial regression. Annual abundance varied among locations with greatest abundance in a narrow geographic band between -112.17 and -112.64°W longitude and 49.32 and 50.17°N latitude. Sites were grouped depending on whether abundance was continuous and high; discontinuous and low; or sporadic and low without much loss of information. Maximum annual abundance declined with spring precipitation, increased with spring temperature, and was unrelated to spring relative humidity, suggesting that abundance is highest during years with early drought conditions. Seasonal abundance was associated with the same factors but was further influenced by temperature and relative humidity during the sample intervals. Lagged effects were apparent, suggesting abundance increased with warmer temperatures over a six-week period, and increased when relative humidity declined closer to the sampling period. Predicted values were slightly biased and tended to overestimate observed data, but this could be adjusted using calibration curves. The model can also be used to predict presence/absence of C. sonorensis and will be useful for developing risk assessments.

Spatio-temporal modelling of Culicoides Latreille (Diptera: Ceratopogonidae) populations on Reunion Island (Indian Ocean)

BACKGROUND

Reunion Island regularly faces outbreaks of bluetongue and epizootic hemorrhagic diseases, two insect-borne orbiviral diseases of ruminants. Hematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae) are the vectors of bluetongue (BTV) and epizootic hemorrhagic disease (EHDV) viruses. In a previous study, statistical models based on environmental and meteorological data were developed for the five Culicoides species present in the island to provide a better understanding of their ecology and predict their presence and abundance. The purpose of this study was to couple these statistical models with a Geographic Information System (GIS) to produce dynamic maps of the distribution of Culicoides throughout the island.

METHODS

Based on meteorological data from ground weather stations and satellite-derived environmental data, the abundance of each of the five Culicoides species was estimated for the 2214 husbandry locations on the island for the period ranging from February 2016 to June 2018. A large-scale Culicoides sampling campaign including 100 farms was carried out in March 2018 to validate the model.

RESULTS

According to the model predictions, no husbandry location was free of Culicoides throughout the study period. The five Culicoides species were present on average in 57.0% of the husbandry locations for C. bolitinos Meiswinkel, 40.7% for C. enderleini Cornet & Brunhes, 26.5% for C. grahamii Austen, 87.1% for C. imicola Kieffer and 91.8% for C. kibatiensis Goetghebuer. The models also showed high seasonal variations in their distribution. During the validation process, predictions were acceptable for C. bolitinos, C. enderleini and C. kibatiensis, with normalized root mean square errors (NRMSE) of 15.4%, 13.6% and 16.5%, respectively. The NRMSE was 27.4% for C. grahamii. For C. imicola, the NRMSE was acceptable (11.9%) considering all husbandry locations except in two specific areas, the Cirque de Salazie-an inner mountainous part of the island-and the sea edge, where the model overestimated its abundance.

CONCLUSIONS

Our model provides, for the first time to our knowledge, an operational tool to better understand and predict the distribution of Culicoides in Reunion Island. As it predicts a wide spatial distribution of the five Culicoides species throughout the year and taking into consideration their vector competence, our results suggest that BTV and EHDV can circulate continuously on the island. As further actions, our model could be coupled with an epidemiological model of BTV and EHDV transmission to improve risk assessment of Culicoides-borne diseases on the island.

Identifying Spanish Areas at More Risk of Monthly BTV Transmission with a Basic Reproduction Number Approach

Bluetongue virus (BTV) causes a disease that is endemic in Spain and its two major biological vector species, C. imicola and the Obsoletus complex species, differ greatly in their ecology and distribution. Understanding the seasonality of BTV transmission in risk areas is key to improving surveillance and control programs, as well as to better understand the pathogen transmission networks between wildlife and livestock. Here, monthly risk transmission maps were generated using risk categories based on well-known BTV R0 equations and predicted abundances of the two most relevant vectors in Spain. Previously, Culicoides spp. predicted abundances in mainland Spain and the Balearic Islands were obtained using remote sensing data and random forest machine learning algorithm. Risk transmission maps were externally assessed with the estimated date of infection of BTV-1 and BTV-4 historical outbreaks. Our results highlight the differences in risk transmission during April-October, June-August being the period with higher R0 values. Likewise, a natural barrier has been identified between northern and central-southern areas at risk that may hamper BTV spread between them. Our results can be relevant to implement risk-based interventions for the prevention, control and surveillance of BTV and other diseases shared between livestock and wildlife host populations.

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning

BACKGROUND

Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for farmers in Europe. Vector abundance is a key factor in determining the risk of vector-borne disease spread and it is, therefore, important to predict the abundance of Culicoides species involved in the transmission of these pathogens. The objectives of this study were to model and map the monthly abundances of Culicoides in Europe.

METHODS

We obtained entomological data from 904 farms in nine European countries (Spain, France, Germany, Switzerland, Austria, Poland, Denmark, Sweden and Norway) from 2007 to 2013. Using environmental and climatic predictors from satellite imagery and the machine learning technique Random Forests, we predicted the monthly average abundance at a 1 km2 resolution. We used independent test sets for validation and to assess model performance.

RESULTS

The predictive power of the resulting models varied according to month and the Culicoides species/ensembles predicted. Model performance was lower for winter months. Performance was higher for the Obsoletus ensemble, followed by the Pulicaris ensemble, while the model for Culicoides imicola showed a poor performance. Distribution and abundance patterns corresponded well with the known distributions in Europe. The Random Forests model approach was able to distinguish differences in abundance between countries but was not able to predict vector abundance at individual farm level.

CONCLUSIONS

The models and maps presented here represent an initial attempt to capture large scale geographical and temporal variations in Culicoides abundance. The models are a first step towards producing abundance inputs for R0 modelling of Culicoides-borne infections at a continental scale.

Modelling temporal dynamics of Culicoides Latreille (Diptera: Ceratopogonidae) populations on Reunion Island (Indian Ocean), vectors of viruses of veterinary importance

BACKGROUND

Reunion Island regularly faces outbreaks of epizootic haemorrhagic disease (EHD) and bluetongue (BT), two viral diseases transmitted by haematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae) to ruminants. To date, five species of Culicoides are recorded in Reunion Island in which the first two are proven vector species: Culicoides bolitinos, C. imicola, C. enderleini, C. grahamii and C. kibatiensis. Meteorological and environmental factors can severely constrain Culicoides populations and activities and thereby affect dispersion and intensity of transmission of Culicoides-borne viruses. The aim of this study was to describe and predict the temporal dynamics of all Culicoides species present in Reunion Island.

METHODS

Between 2016 and 2018, 55 biweekly Culicoides catches using Onderstepoort Veterinary Institute traps were set up in 11 sites. A hurdle model (i.e. a presence/absence model combined with an abundance model) was developed for each species in order to determine meteorological and environmental drivers of presence and abundance of Culicoides.

RESULTS

Abundance displayed very strong heterogeneity between sites. Average Culicoides catch per site per night ranged from 4 to 45,875 individuals. Culicoides imicola was dominant at low altitude and C. kibatiensis at high altitude. A marked seasonality was observed for the three other species with annual variations. Twelve groups of variables were tested. It was found that presence and/or abundance of all five Culicoides species were driven by common parameters: rain, temperature, vegetation index, forested environment and host density. Other parameters such as wind speed and farm building opening size governed abundance level of some species. In addition, Culicoides populations were also affected by meteorological parameters and/or vegetation index with different lags of time, suggesting an impact on immature stages. Taking into account all the parameters for the final hurdle model, the error rate by Normalized Root mean Square Error ranged from 4.4 to 8.5%.

CONCLUSIONS

To our knowledge, this is the first study to model Culicoides population dynamics in Reunion Island. In the absence of vaccination and vector control strategies, determining periods of high abundance of Culicoides is a crucial first step towards identifying periods at high risk of transmission for the two economically important viruses they transmit.

Modeling the global distribution of Culicoides imicola: an Ensemble approach

Culicoides imicola is a midge species serving as vector for a number of viral diseases of livestock, including Bluetongue, and African Horse Sickness. C. imicola is also known to transmit Schmallenberg virus experimentally. Environmental and demographic factors may impose rapid changes on the global distribution of C. imicola and aid introduction into new areas. The aim of this study is to predict the global distribution of C. imicola using an ensemble modeling approach by combining climatic, livestock distribution and land cover covariates, together with a comprehensive global dataset of geo-positioned occurrence points for C. imicola. Thirty individual models were generated by ‘biomod2’, with 21 models scoring a true skill statistic (TSS) >0.8. These 21 models incorporated weighted runs from eight of ten algorithms and were used to create a final ensemble model. The ensemble model performed very well (TSS = 0.898 and ROC = 0.991) and indicated high environmental suitability for C. imicola in the tropics and subtropics. The habitat suitability for C. imicola spans from South Africa to southern Europe and from southern USA to southern China. The distribution of C. imicola is mainly constrained by climatic factors. In the ensemble model, mean annual minimum temperature had the highest overall contribution (42.9%), followed by mean annual maximum temperature (21.1%), solar radiation (13.6%), annual precipitation (11%), livestock distribution (6.2%), vapor pressure (3.4%), wind speed (0.8%), and land cover (0.1%). The present study provides the most up-to-date predictive maps of the potential distributions of C. imicola and should be of great value for decision making at global and regional scales.

Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal

Background

In Senegal, the last epidemic of African horse sickness (AHS) occurred in 2007. The western part of the country (the Niayes area) concentrates modern farms with exotic horses of high value and was highly affected during the 2007 outbreak that has started in the area. Several studies were initiated in the Niayes area in order to better characterize Culicoides diversity, ecology and the impact of environmental and climatic data on dynamics of proven and suspected vectors. The aims of this study are to better understand the spatial distribution and diversity of Culicoides in Senegal and to map their abundance throughout the country.

Methods

Culicoides data were obtained through a nationwide trapping campaign organized in 2012. Two successive collection nights were carried out in 96 sites in 12 (of 14) regions of Senegal at the end of the rainy season (between September and October) using OVI (Onderstepoort Veterinary Institute) light traps. Three different modeling approaches were compared: the first consists in a spatial interpolation by ordinary kriging of Culicoides abundance data. The two others consist in analyzing the relation between Culicoides abundance and environmental and climatic data to model abundance and investigate the environmental suitability; and were carried out by implementing generalized linear models and random forest models.

Results

A total of 1,373,929 specimens of the genus Culicoides belonging to at least 32 different species were collected in 96 sites during the survey. According to the RF (random forest) models which provided better estimates of abundances than Generalized Linear Models (GLM) models, environmental and climatic variables that influence species abundance were identified. Culicoides imicola, C. enderleini and C. miombo were mostly driven by average rainfall and minimum and maximum normalized difference vegetation index. Abundance of C. oxystoma was mostly determined by average rainfall and day temperature. Culicoides bolitinos had a particular trend; the environmental and climatic variables above had a lesser impact on its abundance. RF model prediction maps for the first four species showed high abundance in southern Senegal and in the groundnut basin area, whereas C. bolitinos was present in southern Senegal, but in much lower abundance.

Conclusions

Environmental and climatic variables of importance that influence the spatial distribution of species abundance were identified. It is now crucial to evaluate the vector competence of major species and then combine the vector densities with densities of horses to quantify the risk of transmission of AHS virus across the country.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2920-7) contains supplementary material, which is available to authorized users.

Environmental heterogeneity and variations in the velocity of bluetongue virus spread in six European epidemics

Several epidemics caused by different bluetongue virus (BTV) serotypes occurred in European ruminants since the early 2000. Studies on the spatial distribution of these vector-borne infections and the main vector species highlighted contrasted eco-climatic regions characterized by different dominant vector species. However, little work was done regarding the factors associated with the velocity of these epidemics. In this study, we aimed to quantify and compare the velocity of BTV epidemic that have affected different European countries under contrasted eco-climatic conditions and to relate these estimates to spatial factors such as temperature and host density. We used the thin plate spline regression interpolation method in combination with trend surface analysis to quantify the local velocity of different epidemics that have affected France (BTV-8 2007-2008, BTV-1 2008-2009), Italy (BTV-1 2014), Andalusia in Spain (BTV-1 2007) and the Balkans (BTV-4 2014). We found significant differences in the local velocity of BTV spread according to the country and epidemics, ranging from 7.9km/week (BTV-1 2014 Italy) to 24.4km/week (BTV-1 2008 France). We quantify and discuss the effect of temperature and local host density on this velocity.

Mechanistic model for predicting the seasonal abundance of Culicoides biting midges and the impacts of insecticide control

BACKGROUND

Understanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases. Environmental drivers such as temperature, humidity and photoperiod influence vector abundance, but it is not generally known how these drivers combine to affect seasonal population dynamics.

METHODS

In this paper, we derive and analyse a novel mechanistic stage-structured simulation model for Culicoides biting midges-the principle vectors of bluetongue and Schmallenberg viruses which cause mortality and morbidity in livestock and impact trade. We model variable life-history traits as functional forms that are dependent on environmental drivers, including air temperature, soil temperature and photoperiod. The model is fitted to Obsoletus group adult suction-trap data sampled daily at five locations throughout the UK for 2008.

RESULTS

The model predicts population dynamics that closely resemble UK field observations, including the characteristic biannual peaks of adult abundance. Using the model, we then investigate the effects of insecticide control, showing that control strategies focussing on the autumn peak of adult midge abundance have the highest impact in terms of population reduction in the autumn and averaged over the year. Conversely, control during the spring peak of adult abundance leads to adverse increases in adult abundance in the autumn peak.

CONCLUSIONS

The mechanisms of the biannual peaks of adult abundance, which are important features of midge seasonality in northern Europe and are key determinants of the risk of establishment and spread of midge-borne diseases, have been hypothesised over for many years. Our model suggests that the peaks correspond to two generations per year (bivoltine) are largely determined by pre-adult development. Furthermore, control strategies should focus on reducing the autumn peak since the immature stages are released from density-dependence regulation. We conclude that more extensive modelling of Culicoides biting midge populations in different geographical contexts will help to optimise control strategies and predictions of disease outbreaks.

Bluetongue: control, surveillance and safe movement of animals

The performance of different bluetongue control measures related to both vaccination and protection from bluetongue virus (BTV) vectors was assessed. By means of a mathematical model, it was concluded that when vaccination is applied on 95% of animals even for 3 years, bluetongue cannot be eradicated and is able to re‐emerge. Only after 5 years of vaccination, the infection may be close to the eradication levels. In the absence of vaccination, the disease can persist for several years, reaching an endemic condition with low level of prevalence of infection. Among the mechanisms for bluetongue persistence, the persistence in the wildlife, the transplacental transmission in the host, the duration of viraemia and the possible vertical transmission in vectors were assessed. The criteria of the current surveillance scheme in place in the EU for demonstration of the virus absence need revision, because it was highlighted that under the current surveillance policy bluetongue circulation might occur undetected. For the safe movement of animals, newborn ruminants from vaccinated mothers with neutralising antibodies can be considered protected against infection, although a protective titre threshold cannot be identified. The presence of colostral antibodies interferes with the vaccine immunisation in the newborn for more than 3 months after birth, whereas the minimum time after vaccination of animal to be considered immune can be up to 48 days. The knowledge about vectors ecology, mechanisms of over‐wintering and criteria for the seasonally vector‐free period was updated. Some Culicoides species are active throughout the year and an absolute vector‐free period may not exist at least in some areas in Europe. To date, there is no evidence that the use of insecticides and repellents reduce the transmission of BTV in the field, although this may reduce host/vector contact. By only using pour‐on insecticides, protection of animals is lower than the one provided by vector‐proof establishments.

This publication is linked to the following EFSA Supporting Publications article: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2017.EN-1182/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2017.EN-1171/full

Role of different Culicoides vectors (Diptera: Ceratopogonidae) in bluetongue virus transmission and overwintering in Sardinia (Italy)

Background

Bluetongue (BT) epidemics have affected the Mediterranean island of Sardinia since 2000. While Culicoides imicola represents the main bluetongue virus (BTV) vector, other European Culicoides biting midges, possibly implicated in virus transmission, have been detected here. Understanding their distribution, seasonal abundance, and infection rates is necessary to predict disease incidence and spread across coastal and inland areas, and to define their role in virus overwintering.

Methods

Biting midge abundance was determined by light traps on selected farms representing diverse climatic conditions of Sardinia. Livestock-associated Culicoides species were morphologically and molecularly identified. Infection rates in prevailing midge species captured in 2013 during a BTV-1 outbreak were determined using RT-qPCR based virus detection in insect body pools, supplemented by specific body region analyses. The seasonal infection prevalence in Culicoides samples collected in 2001 in a BTV-2 affected farm was also determined.

Results

The Newsteadi complex (C. newsteadi species A and species B) prevailed among all biting midge species (47.7 %), followed by C. imicola (27.8 %) and the Obsoletus complex (C. obsoletus and C. scoticus) (17.6 %). Whilst Culicoides imicola was more abundant along the coast, the Newsteadi complex was frequently collected at higher altitude and the Obsoletus complex was notably associated to cattle farms. Culicoides pulicaris and C. punctatus abundance was found to be marginal in all farms. BTV was detected in parous female samples of all these species, and the full dissemination of the virus within the body of C. imicola, C. obsoletus, C. scoticus, and Newsteadi complex species was confirmed by analyses of thorax and head, containing salivary glands. Higher infection rates were associated with C. scoticus, C. newsteadi species A and species B, compared to C. imicola. The virus was detected in C. newsteadi species A and C. obsoletus in winter and spring, whereas it was mainly found in summer and autumn in C. imicola.

Conclusions

In Sardinia, bluetongue virus is transmitted by multiple Culicoides vectors, including C. imicola and the Newsteadi complex being the most important. The Newsteadi complex and other midge species can play an important role in internal areas and are likely to be directly involved in virus overwintering.

Modelling the Abundances of Two Major Culicoides (Diptera: Ceratopogonidae) Species in the Niayes Area of Senegal

In Senegal, considerable mortality in the equine population and hence major economic losses were caused by the African horse sickness (AHS) epizootic in 2007. Culicoides oxystoma and Culicoides imicola, known or suspected of being vectors of bluetongue and AHS viruses are two predominant species in the vicinity of horses and are present all year-round in Niayes area, Senegal. The aim of this study was to better understand the environmental and climatic drivers of the dynamics of these two species. Culicoides collections were obtained using OVI (Onderstepoort Veterinary Institute) light traps at each of the 5 sites for three nights of consecutive collection per month over one year. Cross Correlation Map analysis was performed to determine the time-lags for which environmental variables and abundance data were the most correlated. C. oxystoma and C. imicola count data were highly variable and overdispersed. Despite modelling large Culicoides counts (over 220,000 Culicoides captured in 354 night-traps), using on-site climate measures, overdispersion persisted in Poisson, negative binomial, Poisson regression mixed-effect with random effect at the site of capture models. The only model able to take into account overdispersion was the Poisson regression mixed-effect model with nested random effects at the site and date of capture levels. According to this model, meteorological variables that contribute to explaining the dynamics of C. oxystoma and C. imicola abundances were: mean temperature and relative humidity of the capture day, mean humidity between 21 and 19 days prior a capture event, density of ruminants, percentage cover of water bodies within a 2 km radius and interaction between temperature and humidity for C. oxystoma; mean rainfall and NDVI of the capture day and percentage cover of water bodies for C. imicola. Other variables such as soil moisture, wind speed, degree days, land cover or landscape metrics could be tested to improve the models. Further work should also assess whether other trapping methods such as host-baited traps help reduce overdispersion.

Principal climatic and edaphic determinants of Culicoides biting midge abundance during the 2007-2008 bluetongue epidemic in the Netherlands, based on OVI light trap data

Palaearctic Culicoides midges (Diptera: Ceratopogonidae) represent a vital link in the northward advance of certain arboviral pathogens of livestock such as that caused by bluetongue virus. The effects of relevant ecological factors on weekly Culicoides vector abundances during the bluetongue virus serotype 8 epidemics in the Netherlands in 2007 and 2008 were quantified within a hurdle modelling framework. The relative role of meteorological parameters showed a broadly consistent association across species, with larger catches linked to temperature-related variables and lower wind speed. Moreover, vector abundance was found to be influenced by edaphic factors, likely related to species-specific breeding habitat preferences that differed markedly amongst some species. This is the first study on Culicoides vector species in the Netherlands identified during an entomological surveillance programme, in which an attempt is made to pinpoint the factors that influence midge abundance levels. In addition to providing key inputs into risk-mitigating tools for midge-borne pathogens and disease transmission models, the adoption of methods that explicitly address certain features of abundance datasets (frequent zero-count observations and over-dispersion) helped enhance the robustness of the ecological analysis.