Geo-statistical analysis of Culicoides spp. distribution and abundance in Sicily, Italy

Identifications, spatial distribution, and seasonal occurrence of Culicoides in selected districts of Northwest Ethiopia

Culicoides, among the tiniest and most abundant hematophagous insects globally, serve as vectors for a variety of pathogens such as viruses, bacteria, parasites, protozoa, and nematodes. This study aimed to identify Culicoides species and assess their spatial distribution and seasonal occurrence in selected districts of the Central, South, and West Gondar zones, Northwest Ethiopia. A cross-sectional study was conducted between January to July 2023. A total of 44 UV light- onderstepoort traps were deployed in the study districts near specific areas. The traps were operational from dusk (6:00 PM) until dawn (6:00 AM) and were suspended at a height of 1.5 to 2 m above the ground. Poisson regression was used to assess associations, the Shannon diversity index to measure diversity, and QGIS 3.22.6 to create maps. In this study, 8,857 Culicoides were captured across the 44 trapping sites. Of the total flies captured flies, 8,838 were identified as belonging to 12 distinct species, while the classification of the remaining 19 flies remained unclear. Notably, C. kingi (54.01%) was the most prevalent species, followed by C. imicola (44.55%). The abundance of Culicoides observed from January to late April (3505) was significantly lower compared to the wet season (5355), with a marked increase in the capture of C. kingi (2499) from May to late July. A statistically significant association (p < 0.05) was observed between the occurrence of Culicoides and factors such as district, sampling point, and season. Spatial analysis revealed that C. kingi had a broader range of suitability than other Culicoides species, with high suitability observed in East Dembia. The diversity index analysis indicated that Culicoides species diversity was higher in samples from animal pens (H = 0.73) and during the wet season (H = 0.75). Additionally, this study documented the presence of eight Culicoides species namely C. corsicus, C. kibunensis, C. reioxi, C. kiouxi, C. saharienines, C. desertorum, C. reithi, and C. festivipennis, which have not been previously documented in Ethiopia. In conclusion, the study highlighted that the occurrence of Culicoides species was higher in East Dembia, with moderate presence in Wegera and West Armacho. Further research is needed to assess the impact of various Culicoides species on animal and human health, as well as their economic implications, and to develop corresponding control strategies based on these findings.

Climate correlates of bluetongue incidence in southern Portugal

Model forecasts of the spatiotemporal occurrence dynamics of diseases are necessary and can help understand and thus manage future disease outbreaks. In our study, we used ecological niche modelling to assess the impact of climate on the vector suitability for bluetongue disease, a disease affecting livestock production with important economic consequences. Specifically, we investigated the relationship between the occurrence of bluetongue outbreaks and the environmental suitability of each of the four vector species studied. We found that the main vector for bluetongue disease, Culicoides imicola, a typically tropical and subtropical species, was a strong predictor for disease outbreak occurrence in a region of southern Portugal from 2004 to 2021. The results highlight the importance of understanding the climatic factors that might influence vector presence to help manage infectious disease impacts. When diseases impact economically relevant species, the impacts go beyond mortality and have important economic consequences.

Modeling the spatial distribution of Culicoides species (Diptera: Ceratopogonidae) as vectors of animal diseases in Ethiopia

Culicoides biting midges (Diptera: Ceratopogonidae) are the major vectors of bluetongue, Schmallenberg, and African horse sickness viruses. This study was conducted to survey Culicoides species in different parts of Ethiopia and to develop habitat suitability for the major Culicoides species in Ethiopia. Culicoides traps were set in different parts of the country from December 2018 to April 2021 using UV light Onderstepoort traps and the collected Culicoides were sorted to species level. To develop the species distribution model for the two predominant Culicoides species, namely Culicoides imicola and C. kingi, an ensemble modeling technique was used with the Biomod2 package of R software. KAPPA True skill statistics (TSS) and ROC curve were used to evaluate the accuracy of species distribution models. In the ensemble modeling, models which score TSS values greater than 0.8 were considered. Negative binomialregression models were used to evaluate the relationship between C. imicola and C. kingi catch and various environmental and climatic factors. During the study period, a total of 9148 Culicoides were collected from 66 trapping sites. Of the total 9148, 8576 of them belongs to seven species and the remaining 572 Culicoides were unidentified. The predominant species was C. imicola (52.8%), followed by C. kingi (23.6%). The abundance of these two species was highly influenced by the agro-ecological zone of the capture sites and the proximity of the capture sites to livestock farms. Climatic variables such as mean annual minimum and maximum temperature and mean annual rainfall were found to influence the catch of C. imicola at the different study sites. The ensemble model performed very well for both species with KAPPA (0.9), TSS (0.98), and ROC (0.999) for C. imicola and KAPPA (0.889), TSS (0.999), and ROC (0.999) for C. kingi. Culicoides imicola has a larger suitability range compared to C. kingi. The Great Rift Valley in Ethiopia, the southern and eastern parts of the country, and the areas along the Blue Nile and Lake Tana basins in northern Ethiopia were particularly suitable for C. imicola. High suitability for C. kingi was found in central Ethiopia and the Southern Nations, Nationalities and Peoples Region (SNNPR). The habitat suitability model developed here could help researchers better understand where the above vector-borne diseases are likely to occur and target surveillance to high-risk areas.

Detection of Dirofilaria DNA and host blood-meal identification in Culicoides paolae biting-midges

The vectorial role of blood-sucking arthropods, other than mosquitoes, has been explored for Dirofilaria immitis and Dirofilaria repens which are filarioids of increasing interest due to their zoonotic potential. Given the expansion of canine heartworm infection in southern Europe due to D. immitis and the report of the infection in Linosa Island (Sicily, Italy), we investigated and focused on the potential involvement of Culicoides spp. in Dirofilaria spp. transmission as well as the blood-meal source in Dirofilaria spp. molecularly positive biting midges. Out of 1791 specimens collected 1773 were morphologically and molecularly identified as Culicoides paolae and 18 as Culicoides obsoletus complex. Of the 1596 females, 4 (0.26%) parous C. paolae tested positive for D. immitis and D. repens (i.e. 2 Culicoides specimens for each filarial species), of which D. immitis-positive samples fed on both humans and dogs and D. repens-positive samples fed only on humans. The detection of D. immitis and D. repens DNA in Culicoides midges suggests their potential involvement in the epidemiology of the filarial nematodes, which may be of medical and veterinary importance in hyper-endemic areas. Findings of this study shed new light on the epidemiology of Dirofilaria spp. infections indicating that further investigations are needed.

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.

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.

Updating the global occurrence of Culicoides imicola, a vector for emerging viral diseases

Culicoides imicola is the main vector transmitting viruses causing animal diseases such as Bluetongue, African Horse Sickness, and Schmallenberg. It has become widely distributed, with reports from South Africa to southern Europe, and from western Africa to southern China. This study presents a global compendium of Culicoides imicola occurrence between 1943 and 2018, reflecting the most recently compiled and harmonized global dataset derived from peer-reviewed literature. The procedures used in producing the data, as well as the geo-coding methods, database management and technical validation procedures are described. The study provides an updated and comprehensive global database of C. imicola occurrence, consisting of 1 039 geo-coded records from 50 countries. The datasets can be used for risk mapping of the diseases transmitted by C. imicola as well as to develop the global habitat suitability for the vector.

The possible route of introduction of bluetongue virus serotype 3 into Sicily by windborne transportation of infected Culicoides spp

In October 2017, the first outbreak of bluetongue virus serotype 3 (BTV-3) began in Italy, specifically in western Sicily. The route of entrance remains unclear, although since 2016 the same strain had been circulating only 150 km away, on the Tunisian peninsula of Cape Bon. The present analysis assessed the feasibility that wind could have carried BTV-3-infected Culicoides spp. from Tunisia to Sicily. An advection-deposition-survival (ADS) model was used to estimate when and where Culicoides spp. were likely to be introduced prior to the first BTV-3 report in Italy. Additionally, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to support ADS outputs. The modelling suggests that during September 2017, strong wind currents and suitable climatic conditions could have allowed the transportation of Culicoides spp. from BTV-3-infected areas in Tunisia into Sicily. ADS simulations suggest that particles could have reached the province of Trapani in western Sicily on 2 and 12 September. These simulations suggest the feasibility of aerial transportation of infected Culicoides spp. from Tunisia into Sicily. They demonstrate the suitability of the ADS model for retrospective studies of long-range transportation of insects across large water bodies, which may enhance the early detection of vectorial disease introduction in a region.

Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China

Bluetongue (BT) is a non-contagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. To investigate the distribution characteristics of bluetongue virus (BTV), two large-scale censuses of BTV prevalence in Xinjiang, China were collected. Spatial autocorrelation analysis, including global spatial autocorrelation and local spatial autocorrelation, was performed. Risk areas for BTV occurrence in Xinjiang were detected using the presence-only maximum entropy model. The global spatial autocorrelation of BTV distribution in Xinjiang in 2012 showed a random pattern. In contrast, the spatial distribution of BTV from 2014 to 2015 was significantly clustered. The hotspot areas for BTV infection included Balikun County (p < 0.05), Yiwu County (p < 0.05) and Hami City (p < 0.05) in 2012. These three regions were also hotspot areas during 2014 and 2015. Sheep distribution (25.6% contribution), precipitation seasonality (22.1% contribution) and mean diurnal range (16.2% contribution) were identified as the most important predictors for BTV occurrence in Xinjiang. This study demonstrated the presence of high-risk areas for BTV infection in Xinjiang, which can serve as a tool to aid in the development of preventative countermeasures of BT outbreaks.

Spatial Patterns and Risk Factors of Bluetongue Virus Infection in Inner Mongolia, China

Bluetongue (BT) is a noncontagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. Although the causative agent, BT virus (BTV) is endemic in China, a comprehensive analysis has yet to be conducted examining the spatial distribution and risk factors of the virus throughout the Inner Mongolia province. Between June 2013 and February 2015, a total of 6199 blood samples of goats and sheep were collected from 11 leagues and cities. To investigate the distribution characteristics of BTV, spatial autocorrelation analysis, including both global and local spatial autocorrelation, was conducted. To develop a model for the association between BTV infection and specific risk factors, a multiple logistic regression analysis was performed. The global spatial autocorrelation data on the distribution of BTV exhibited a random pattern. Alashan was observed to be a cold spot for BTV infection. During the study period, no hot spots were detected. An increased risk of BTV infection in Inner Mongolia was associated with the breed and age of the animal.

A Geographical Information System Based Approach for Integrated Strategies of Tick Surveillance and Control in the Peri-Urban Natural Reserve of Monte Pellegrino (Palermo, Southern Italy)

Ticks (Acari: Ixodidae) are bloodsucking arthropods involved in pathogen transmission in animals and humans. Tick activity depends on various ecological factors such as vegetation, hosts, and temperature. The aim of this study was to analyse the spatial/temporal distribution of ticks in six sites within a peri-urban area of Palermo (Natural Reserve of Monte Pellegrino) and correlate it with field data using Geographical Information System (GIS) data. A total of 3092 ticks were gathered via dragging method from June 2012 to May 2014. The species collected were: Ixodes ventalloi (46.09%), Hyalomma lusitanicum (19.99%), Rhipicephalus sanguineus (17.34%), Rhipicephalus pusillus (16.11%), Haemaphisalis sulcata (0.36%), Dermacentor marginatus (0.10%), and Rhipicephalus turanicus (0.03%). GIS analysis revealed environmental characteristics of each site, and abundance of each tick species was analysed in relation to time (monthly trend) and space (site-specific abundance). A relevant presence of I. ventalloi in site 2 and H. lusitanicum in site 5 was observed, suggesting the possible exposure of animals and humans to tick-borne pathogens. Our study shows the importance of surveillance of ticks in peri-urban areas and the useful implementation of GIS analysis in vector ecology; studies on temporal and spatial distribution of ticks correlated to GIS-based ecological analysis represent an integrated strategy for decision support in public health.