Viruses | Free Full-Text | Epidemiological Analyses of the First Incursion of the Epizootic Hemorrhagic Disease Virus Serotype 8 in Tunisia, 2021–2022

Epizootic hemorrhagic disease virus (EHDV), which belongs to the genus Orbivirus and the Sedoreoviridae family, is a non-enveloped, double-stranded segmented RNA virus genome approximately 19–20 kb in length [1]. Since 1965, EHDV has attracted researchers’ attention through an outbreak in New Jersey, USA, which caused the death of more than 500 deer [2]. Since then, the virus has also been detected in Canada and Mexico, as well as in other parts of the world: South America, Africa, the Middle East, Japan, Southeast Asia, and Australia [3]. To date, seven serotypes of EHDV have been reported, named 1–2 and 4–8, which were identified based on phylogenetic studies, sequencing data, and cross-neutralization assays [4]. Genetic analyses demonstrated that the previously identified serotype 3 (Nigerian strain IbAr 22619) was serotype 1 [5].

The first EHDV serotype 6 outbreak in Tunisia was described in 2006 and was closely related to other EHDV-6 strains circulating in the Mediterranean basin during this period in Turkey, Morocco, Algeria, and Jordan [6]. The EHDV-7 strain was involved in outbreaks in Israel in 2006 [7]. A common “African/Arabian Peninsula and Indian Ocean Asia” origin of EHDV-6 and 7 is revealed by analysis of their genomic segments [7]. Serological investigations revealed the circulation of EHDV-6 in Tunisia in 2012–2013 without reported clinical signs [8]. In 2015, few cattle cases of EHDV-6 were reported to the World Organization for Animal Health (WOAH) by Tunisian authorities [9]. During September 2016–February 2017, EHDV-1 was recorded in ruminants in the Middle East [10]. Phylogenetic analyses indicated a close relationship with the EHDV serotype 1 strain in Nigeria [7].

From September to November 2021, many clinical cases with BTV-like clinical signs were reported in Tunisian dairy and beef farms. At the beginning of the outbreak, Bluetongue virus serotype 4 (BTV-4) was suspected since it was detected in cattle in Tunisia in 2020 [11]. It was laterassociated with EHDV serotype 8. The virus was responsible for many clinical cases in cattle and a few deer deaths [12,13]. In 2022, a second EHDV epidemic was described in Tunisia between July and November. On 25 October 2022, EHDV first appeared on the European continent in Sicily and south-eastern Sardinia-Italy, causing BTV-like clinical symptoms in cattle [14]. On 18 November 2022, EHDV serotype 8 was identified as the etiological agent of a series of outbreaks that were discovered in southern Spain [14]. Furthermore, in July 2023, EHDV was reported for the first time in Portugal [8]. More recently, EHDV outbreaks were confirmed on 18 September 2023 in south-western France, close to the Spanish border (source: https://wahis.woah.org/; last accessed on 13 December 2023).

Available data in the literature suggest that the species of Culicoides involved in EHDV transmission are likely similar to those that transmit BTV [15,16]. Recent studies showed that EHDV-8 seems to use the same transmission patterns as BTV [17]. This in turn means that EHDV-8 has the potential to spread in Europe. Like other vector-borne diseases (VBDs), EHDV infections are typically seasonal and occur when vector insect populations are most abundant, usually from mid-summer to late autumn [18,19,20]. Eco-climatic factors are known to influence the distribution of competent insect vectors. Many researchers have evaluated the correlation between meteorological factors and the distribution of Bluetongue disease [11,21]. However, there are still gaps in our understanding of infection with EHDV, which impedes its control, particularly regarding the eco-climatic factors associated with virus circulation. In the present study, we investigated the effect of environmental and climatic drivers on this disease epidemic to provide accurate information for designing more effective surveillance and control systems.

Causing several clinical cases, EHDV can be a serious problem for herd cattle in the near future. Little is known about EHDV risk factor drivers, which can have implications for designing control strategies. As with other vector-borne diseases (VBDs), the distribution of EHD largely depends on the environmental factors that determine the abundance of the arthropod vector [32]. Ecological niche modeling (ENM) can be used to predict the abundance and the spread of VBDs [33] which in turn could be useful for planners in creating mosquito/VBD surveillance programs. A commonly used method to buildspecies distribution models (SDMs)in the ecological niche theory framework includes regression-based methods, such asgeneralized linear models (GLMs).This algorithm has widely proven to produce robust models for predicting species distribution [34,35,36,37,38] as well as for infectious diseases [39,40]. In this study, we elaborated distribution models (through GLMs) in order to: (1) establish the potential area of distribution of the potential vector in Tunisia, (2) to define the potential area of EHDV distribution cases. C. imicola, the main vector for Bluetongue in Tunisia, is a competent vector for EHDV in different parts of the world [16].Taking into account its high abundance, there is a high probability that C. imicola is the vector for EHDV in Tunisia. The favorability map of this vector was generated and subsequently, used as a covariate for infection with EHDV risk mapping. For the first step, we used C. imicola occurrence points collected between 2017 and 2020 (64 presence points). Predictors, biotic and abiotic rasters, were chosen on the basis of countrywide availability and associations already proven with the vector and the disease (topography, climate, water availability, livestock, anthropic, and vegetation). Using GLMs, we created a map that predicted the distribution of C. imicola throughout the contiguous region of Tunisia. The most important variables identified by the C. imicola model were related to temperature (positive night land surface temperature (NLST)) and irrigated area. Additionally, it was favored by rural areas (those with low population density) and those with densities of sheep livestock. The NLST has been identified as one of the most important drivers of C. imicola distribution in Europe [41,42]. The distribution and abundance of C. imicola are likely directly constrained by its relatively poor tolerance to relatively low temperatures [43]. Instead, crop irrigation practices in arid zones are assumed to support the presence of C. imicola [44,45]. The favorability predictive map partially agrees with the map developed by Ben Hassine et al. in 2021 using the ENFA and Maxent models coupled with WorldClim data [45]. The presence of sheep as a risk factor for C. imicola distribution was mentioned above [45]. In the second step, the favorability of encountering C. imicola (C. imicola_F) was used as an additional variable for the EHDV circulation prediction map. We did not force the model to use the potential distribution of C. imicola (C. imicola_F variable) on the GLM model but allowed the model to analyze and include it along with the other variables if it was statistically related to the 2021 outbreaks. Most remarkably, the inclusion of the vector variable (C. imicola_F) was the most influential variable on the distribution of infection with EHDV cases in Tunisia. Furthermore, these areas exhibited high variability in both day-night temperature (lst_dn_diff; 12–16 °C) and vegetation (NVDI_diff; 0.12–0.14). The ensemble model highlighted a large portion of central and north-western Tunisia (excluding regions with dense vegetation). Zones located inland demonstrated heightened variability, which was more favorable for infection with EHDV cases. These areas also include some of the most highly irrigated areas in Tunisia. Several coastal regions (Sahel and low steppes) and some regions in the Cap Bon peninsula in the far north-eastern region of Tunisia have been identified as suitable for EHDV circulation. In southern Tunisia, different areas located principally in oases have been identified as potentially suitable for EHDV circulation. Both the C. imicola and the EHDV risk models showed high sensitivity and acceptable specificity. Our ensemble models performed well, indicating a clear ability to distinguish between suitable and unsuitable habitat. Indeed, we assessed the ability of the 2021 infection with EHDV risk model to predict cases occurred in 2022.

These results suggest that C. imicola could be a potential vector of EHDV in Tunisia. Indeed, many cases of BTV–EHDV co-infections were confirmed in Tunisia in 2021 (23/161; 14.2%), suggesting that these two viruses can share the same epidemiological ecosystem. The co-circulation of BTV and EHDV has been reported in several countries and regions [46,47,48]. A significant association between cattle with BTV infections and the seroprevalence of EHDV was observed on cattle farms in China [19]. BTV seropositivity could therefore serve as a surrogate marker for the spread of EHDV. However, co-infection with different serotypes of EHDV and BTV increases the risk of potential genomic reassortment and is likely to pose a significant threat to cattle [19]. In fact, EHDV was isolated only from C. kingi and C. oxystoma pools in the oases of Tozeur, where C. imicola was not identified [13]. Dead deer were confirmed to be EHDV positive in the forest of Ghardimaou in the north-western Tunisia in 2021 and 2022 [13], a region not identified as suitable for EHDV circulation in this study, suggesting the possibility of intervention by other competent vectors. A recent survey in Italy showed that C. obsoletus/scoticus parous females have been found positive to EHDV-8 serotype. In Tunisia, the distribution of the species of C. obsoletus complex is limited to some sites in the northern part of country characterized by an ecosystem similar to that found in the southern part of Europe [9]. Other studies have demonstrated that there are considerable differences in the distributions and risk factors for these two viruses [49,50]. Boyer et al. (2010) found that EHDV seropositivity was associated with patches of forest, whereas BTV was not [49].

To create risk maps from a regression model, it is necessary to have spatial data layers for all covariates in the model. The use of other covariates like wind [50], drought severity [51,52,53], animal movement, and variables related to herd management or individual animal level factors may help to further improve predictions. In the case of wind, this variable can influence the distribution of C. imicola at large scales [43], and can also affect its propagation [52]. The translocation of C. imicola can lead to the spread of viruses associated with the vector to new places, as has occurred with BTV between Mediterranean islands [54]. In the case of EHDV, serotype 8 may have spread from Tunisia to Italy (Sardinia and Sicily) through C. imicola transported by wind currents that go from the African to the European continent. The EHDV risk map locates the areas of greatest risk in the north-east of the country, which in turn are crossed by strong wind currents (Figure 4). Strong winds may have carried infected C. imicola from Tunisia to the Mediterranean islands, spreading the disease and producing the first cases of EHD due to serotype 8 infection in Europe [14]. Since the first cases of this serotype in Tunisia in 2021, the virus may have persisted throughout the year. The following year, in 2022, as it was already widely distributed throughout the country, the virus could have spread to the Italian islands. In Figure 4, south winds blowing towards Sardinia (dated 23 October 2022) are shown, where infected vectors could potentially reach the coast of the island. Similarly, 10 days earlier, on October 13th, west winds blowing towards Sicily may explain the cases detected in this Italian island, which is closer to Tunisia (Ventusky 2023: https://www.ventusky.com/?p=35.1;7.1;5&l=wind-10m&t=20221013/1200, last accessed on 16 October 2023).

After spreading countrywide, endemization of EHD in the country is assumed to be quite probable [55]. Surveillance of this disease is recommended, and a clear control strategy should be defined [56]. This study defines EHDV potential distribution infection so that prioritized regions can then be indicated for disease/vector surveillance in Tunisia. Although, to date, there is no effective measure against EHDV-8 by chemical vector control, and there are no vaccines against EHDV-8 on which an efficientcontrol strategy is developed and implemented, the risk maps elaborated could be useful to implement other control measures such asanimal movement control, physical vector control, and use of an autogenous vaccine.