Red deer reveal spatial risks of Crimean-Congo haemorrhagic fever virus infection

Crimean-Congo haemorrhagic fever virus (CCHFV) continues to cause new human cases in Iberia while its spatial distribution and ecological determinants remain unknown. The virus remains active in a silent tick-animal cycle to which animals con-tribute maintaining the tick populations and the virus itself. Wild ungulates, in particular red deer, are essential hosts for Hyalomma ticks in Iberia, which are the principal competent vector of CCHFV. Red deer could be an excellent model to understand the ecological determinants of CCHFV as well as to predict infection risks for humans because it is large, gregarious, abundant and the principal host for Hyalomma lusitanicum . We designed a cross-sectional study, analysed the presence of CCHFV antibodies in 1444 deer from 82 populations, and statistically modelled exposure risk with host and environmental predictors. that the model predicts human infection risk accurately. A recent human case of CCHF occurred in northwestern Spain, a region that the model predicted as low risk, point-ing out that it needs improvement to capture all determinants of the CCHFV infection risk. In this study, we have been able to identify the main ecological determinants of CCHFV, and we have also managed to create an accurate model to assess the risk of CCHFV infection.


INTRODUCTION
The causes underlying the spatial spread of vector-borne pathogens (VBP) have been investigated in some highly relevant model VBP of human, agriculture or conservation impact, for example Borrelia burgdorferi s.l., tick-borne encephalitis virus, West Nile virus or bluetongue virus (Jacquot et al., 2017;Jaenson et al., 2012;Kilpatrick, 2011;Mannelli et al., 2012). These examples show that VBP spread on their (flying) vectors and hosts in search of new suitable ecosystems. Sometimes, VBP find favourable conditions to colonize new areas by adapting to local autochthonous vertebrates and invertebrates (Kilpatrick, 2011). VBP can also spread on their competent vectors and hosts to the neighbourhood (Leighton et al., 2012). If pathogens are plastic enough to adapt to new (host and vector) environments, their chances to colonize and spread to new vast unexplored rich niches are high. Ticks cannot fly, but some manage to take a free and comfortable flight that transports them to distant places. Ticks exploit migratory birds that fly across large distances in a short period between reproduction and wintering headquarters (Estrada-Peña et al., 2021). Resident hosts also spread ticks at shorter distances (Buczek et al., 2020;Ruiz-Fons & Gilbert, 2010). The colonization of new ecosystems by VBP may be silent if pathogens spread without attracting the attention of health/conservation authorities or researchers.

Crimean-Congo haemorrhagic fever virus (CCHFV), a tick-borne
Orthonairovirus of African origin and currently endemic to the African, Asian and (southeastern) European continents, may have been flying in infected ticks on migratory birds for thousands of years across the western Mediterranean Basin (Palomar et al., 2013). The virus might also have passively exploited the movements of their vectors in internationally traded livestock (Muhanguzi et al., 2020) as well as in anthropogenic wildlife translocations (Tsao et al., 2021) to reach southwestern Europe. It is not known how long CCHFV has been circulating in southwestern Europe. There was no evidence of the virus in Iberia until 1985 when CCHFV antibodies appeared in two humans during a serological survey for tick-borne pathogens in Portugal (Filipe et al., 1985).
In 2010, the virus was detected in Hyalomma lusitanicum ticks collected on red deer (Cervus elaphus) in west-central Spain (Estrada-Peña et al., 2012), and later human clinical cases emerged in 2016, 2018, 2020 and 2021 in western Spain. Recently, the first known human clinical case of CCHF in Spain has been traced back to 2013 (Negredo et al., 2021).
Ten human cases have been reported to date in the country, three of whom resulted in death (30% fatality rate): one case in 2013, one case in 2016, two cases in 2018, three cases in 2020 and two cases in 2021.
No human clinical case has been reported in Portugal to date. The primary cases reported had clinical symptoms of haemorrhagic fever, but these may represent only a small proportion of the real infection cases that occur in Spain and Portugal annually. This perception relies on the high proportion of infections that may go unnoticed due to mild, nonspecific clinical signs (Bente et al., 2013). Additionally, a proportion of non-fatal cases of haemorrhagic fever may go undiagnosed, for example one of the primary cases reported in 2018 was diagnosed during a retrospective survey on fever cases of unknown origin in west-central Spain, and the 2013 case was also a patient with high fever of undiagnosed aetiology.
The virus has been detected in several areas of Iberia, mostly in H. lusitanicum ticks collected (mainly) on red deer (Cajimat et al., 2017;Negredo et al., 2019). A study undertaken by the Spanish Ministry for Agriculture (MSCBS, 2019) revealed higher antibody prevalence in wildlife when compared to livestock in specific areas of Spain, suggesting that the virus was widespread in a sylvatic cycle on the mainland. Recently, CCHFV-positive ticks were found in new areas in southcentral and southern Spain. This observation provides more evidence of an enzootic but not homogeneous circulation of the virus in Iberia (Moraga-Fernández et al., 2020).
Primordial tick vectors of CCHFV are species in the genus Hyalomma (Spengler & Bente, 2017). Two Hyalomma ticks are well established in Iberia, H. lusitanicum and H. marginatum. The former predominates in abundance over H. marginatum in southwestern Iberia, where nine of the ten human cases occurred. This region of Iberia has abundant populations of red deer and other wild ungulates (Acevedo et al., 2007(Acevedo et al., , 2008) that maintain high burdens of H. lusitanicum ticks (Ruiz-Fons et al., 2006Valcárcel et al., 2016). The red deer is, notably more than other wild ungulates, the primary host of H. lusitanicum (and other) ticks in this region, and it is also widely distributed in Iberia (Bencatel et al., 2019;Palomo et al., 2007; Figure 1). Domestic ruminants are also abundant in this region, and they are managed frequently under extensive production systems in large extensions of land. Domestic ruminants interact with coexisting wildlife, so H. lusitanicum and F I G U R E 1 Spatial location of the surveyed red deer populations (red dots) and local sample size in relation to red deer (blue shaded squares) distribution in the Iberian Peninsula (Bencatel et al., 2019;Palomo et al., 2007) H. marginatum ticks are frequent in extensively raised domestic ruminants even though acaricides are spread over animals or administered in feed at different times of the year within the main tick activity period (spring to autumn). CCHFV infection causes no disease in ungulates and other mammals. However, infected animals may either replicate and transmit the virus to uninfected ticks, allow co-feeding transmission among infected and uninfected ticks, ease venereal transmission between adult ticks at mating or favour virus maintenance in the tick population by feeding ticks (Estrada-Peña et al., 2013a;Ruiz-Fons et al., 2012). The virus may be maintained in the tick population by transovarial transmission. Direct exposure to ungulate carcass fluids may also be a relevant transmission pathway at the animal-human interface (Shahhosseini et al., 2018). However, in the EU, there is no evidence of transmission from domestic or wild ungulates to abattoir or game meat professionals during carcass dressing (ECDC, 2020).
No vaccine is available to protect humans against CCHFV, so prevention is the only measure for avoiding new infections. Preventing tick bites include a series of recommendations to people in contact with domestic or wild animals or with the environment where they live, such as wearing appropriate clothes, carrying out a thorough inspection of the skin to remove ticks after any field activity, or using repellents against ticks. However, informing about high-risk areas would significantly increase awareness where it is more needed and result in better prevention strategies. In Iberia, the spatial distribution of CCHFV is currently unknown, even though the virus has a huge potential to spread as it is occurring with West Nile virus in this region (ECDC, 2020). Attempts to map the distribution of CCHFV in the human population have been unfruitful because humans do not frequently become exposed to tick bites (Monsalve Arteaga et al., 2020). Farmers often treat extensively produced livestock with acaricides that reduce exposure to CCHFV. In contrast, wild ungulates host high amounts of (Hyalomma) ticks, are infrequently treated against them and are widely distributed in Iberia (Bencatel et al., 2019;Palomo et al., 2007). Red deer meet most of the requisites that would make them good indicators of the risk of CCHFV infection in Iberia: (i) they are abundant; (ii) they are gregarious; (iii) they are widely distributed and (iv) they host high numbers of Hyalomma spp. (and other) ticks. We thus hypothesized that the intimate relationship of red deer and Hyalomma ticks in Iberia might aid in mapping the risk of CCHFV exposure to inform public health authorities and the public as a preventative measure and thus reduce human CCHF cases. Understanding the fundamentals of the ecological background of the enzootic cycle of CCHFV would additionally result in insights for the future control of this emerging zoonosis in Iberia.

Survey design
The study focused on the Iberian Peninsula, a 596,740 km 2 land heterogeneous in climatic, orographic, ecosystemic, and socioeconomic terms. We designed a cross-sectional survey based upon the hypothesis that red deer are exposed to bites from CCHFV infected ticks at a higher rate than other Iberian ungulates (Ruiz-Fons et al., 2013) and being abundant and widely distributed in the region as well, they would provide a realistic map of the risk of infection by CCHFV for humans. That would render red deer as exceptional indicators for the spatial distribution of CCHFV. Therefore, this would be very useful for informing the health authorities about the areas where the risk of exposure to CCHFV is higher so that preventative measures may be taken. To achieve this, we chose to estimate the rate of exposure of red deer to CCHFV by detecting the presence of specific antibodies in blood serum. The study design needed to be based on a representative sample of red deer populations in Iberia, so we checked the distribution range of the red deer (Bencatel et al., 2019;Palomo et al., 2007). The unit of study was the epidemiological population. For this study, we defined an epidemiological population as the group of red deer individuals inhabiting a specific territory under the management of a single authority (local/regional administration, hunters' association or landowner). With this classification, the effect of the set of specific management measures to which deer were exposed locally could be homogenized, which depends exclusively on the goals of the local manager. These may vary from those of neighbouring populations subject to the decisions of another manager. We chose this classification system because many of the study populations are artificially restricted to a particular territory (range around 300 to 12,000 has) by large game fences (Acevedo et al., 2007(Acevedo et al., , 2008. We calculated the minimum number of samples required to estimate antibody prevalence in the study units at the previously known circulation rates in western Europe (Spengler et al., 2016a) with a 95% confidence level and an accepted 10% error using the proportion calculator of Epitools (Sergeant, 2018).
When designing the cross-sectional survey, few serological surveys had been conducted on CCHFV in domestic ungulates in western Europe (Spengler et al., 2016a). Reported antibody prevalence did not exceed 2%, so we estimated the required sample size for a 2% expected proportion. We selected serum samples of red deer collected between 2008 and 2016. When gathering samples, we also collected data on the surveyed location and individuals. We recorded the geographical coordinates of the surveyed sites with portable GPS devices. All the samples were collected from hunter-harvested red deer shot during commercial/social hunting events, or after official population control events carried out by environment agents in protected areas. We performed the sampling according to Spanish and EU regulations. We did not require any ethical approval from authorities because we did not shoot animals deliberately for the survey.

Serological analyses
The presence of specific CCHFV antibodies in serum samples was estimated using a species-independent in-house competitive ELISA (cELISA) developed at the Friedrich-Loeffler Institute in Germany (Schuster et al., 2016 (previously classified as antibody-positive using adapted commercial serological screening tests for CCHFV) and sera of experimentally infected rhesus macaques as positive controls. Animal and huma sera from a non-enzootic country (Germany) were employed as negative controls. The cut-off point for maximizing the diagnostic sensitivity and specificity of the cELISA was determined by the receiving operator characteristics (ROC) analysis. PI values above 49 were considered positive, and those below 37 were considered negative. Those between 37 and 49 were considered inconclusive. The estimated diagnostic sensitivity for the competitive ELISA was 95%, and its diagnostic specificity reached 99% (Schuster et al., 2016) at the established cutoff point.
The sera with homogeneous results in the duplicate analysis (both positive or both negative) were classified as positive or negative, respectively. Sera with contrasting results or with two inconclusive results were retested to classify them as negative or positive. The prevalence of antibodies was estimated as the ratio between the number of positive and analysed sera in percentage terms. We controlled uncertainty in prevalence values by associating the exact Clopper-Pearson exact 95% confidence interval (CI) to each prevalence value.

Spatial cluster analysis
We initially explored the spatial dependence of antibody prevalence in the study populations to identify the highest risk areas for red deer in Iberia. This was carried out by implementing a spatial cluster analysis with SaTScanTM v9.6 software (Kulldorf, 2018) to identify both high and low relative risk areas (RR), RR > 1 and RR < 1, respectively. The Bernoulli model was employed for the cluster analysis (Coleman et al., 2009;Kulldorff, 1999) without including temporal parameters due to the cross-sectional nature of the survey. We set a circular spatial window for the clusters with a maximum population size at risk of 50% with no overlapping between neighbouring clusters. Analyses were run with 9999 replications. The p value was estimated with the Gumbel approximation to infer the significance of cluster RR. Clusters were considered significant at p < .05. The clusters were hierarchically numbered and organized according to the p value.

Risk factor analysis
To understand the factors determining variations in the probability of exposure to CCHFV, we undertook statistical modelling with a series of explanatory variables selected from the host individual and host population factors (Table 1). We gathered environmental variables as well because these may modulate exposure to CCHFV by influencing host and tick population dynamics (Ruiz-Fons et al., 2012. This approach was aimed at providing an overview of the factors determining exposure at the population level (as defined in this study) that could help design future strategies for reducing CCHFV transmission at the host-tick interface. Two purely spatial, nine climatic, two topographical, seven habitat, six host population and two individual host variables were initially selected based on their potential to modulate exposure to CCHFV tick vectors (see Appendix 1) and on availability at the study scale (see Acevedo et al., 2010). A large portion of the host population predictors and all environmental predictors were estimated at UTM 10 × 10 km spatial scale to cover the whole range of study populations (300-12,000 has).
Environmental and host population predictors were only available in Spain. Therefore, any of the four surveyed Portuguese populations close to the Spanish border ( Figure 1) were linked with data from the closest Spanish UTM 10 × 10 km square and that in central Portugal was discarded for statistical analyses. We thoroughly checked data to rule out any potential interference in statistical modelling (Zuur et al., 2010). This initial step enabled potential outlier values in the predictors to be evaluated and controlled, that, when identified, were ruled out by logarithmic transformation. Logarithmic transformation was applied to all the continuous climatic predictors selected for modelling to homogenize the range of scales in the measures. A Pearson correlation plot was built with continuous predictors using the 'corrplot' package of R in RStudio (Wei & Simko, 2017). Any collinearity (r ≥ |0.7|) was removed when selecting the predictors for modelling. We checked for any potential dependence in the predictors and that sample size was balanced among classes in categorical variables. We finally checked for poten-tial meaningful interactions between predictors. We selected two that could modulate host-tick interaction patterns: (i) deer sex and ageclass interaction because previous findings show the combined effect of sex and age driving the amount of H. lusitanicum ticks on red deer (Ruiz-Fons et al., 2013) and (ii) slope and soil permeability interaction because steep slope terrains may counteract the water retention potential of low permeable soils by runoff effects whereas highly permeable soils on flat terrains may lose water through drainage, which affects tick survival and abundance, and hence CCHFV transmission to deer.
Thereafter, the individual risk of exposure to CCHFV ('ecchfv'; positive/negative; N = 1247) was modelled with the selected covariates in a logistic regression modelling approach [ecchfv ∼ mg + sex + age  using the 'modEvA' R package (Barbosa et al., 2013; see also Real et al., 2003).

Risk mapping
To map the risk of exposure to CCHFV using red deer as an indicator of the transmission risk from infected ticks, a new model for mainland  (Efron & Tibshirani, 1994) and by split-sample validation with the 'caret' R package (Kuhn, 2008). The logit equation from the output of the average model enabled the predicted probability of exposure to be estimated for every UTM 10 × 10 km square on the Spanish mainland.
Those probabilities were represented at the UTM 10 × 10 km square level and mapped using ArcMap 10.5 (ESRI, Redlands, CA, USA) software.

RESULTS
The minimum largest required sample size per population was eight individuals for a 10% precision estimate in a large population (>400 individuals). The study was based on the retrospective analysis of red deer serum samples collected within the framework of other research projects. Therefore, we adapted our survey to the serum banks

F I G U R E 3
Spatial range of CCHFV high (red shadowed) and low (blue shadowed) relative risk (RR) prevalence clusters in relation to surveyed red deer populations. Populations included in any of the low or high RR identified clusters are shown distinctly to red deer populations not included in any cluster (white dots). The numbers on the right upper side of each cluster correspond to cluster numbers as shown in Table 2 and population factors explained the 17.7% variation in risk. However, the highest explained variation in proportion was achieved by the sum effects of (host) population and environmental predictors (64.7%; Supplementary Figure S2).

Risk modelling within the main spatial range of H. lusitanicum in
Iberia resulted in six models displaying AICc differences below the two established units (Supplementary Table S1). We built the model with 1025 samples from 63 deer populations in southwestern Iberia.
Calibration of the average model was poor according to the Hosmer-Lemeshow test (p < .05), albeit good discriminatory power was maintained (AUC = 0.717). In this core area, (host) individual traits were less significant predictors of virus exposure risk (Table 4). We included age and sex for model averaging, but their effect was not statistically significant. The (host) individual factor could indeed explain only 2.2% of the variation in exposure risk (Supplementary Figure S2). Host population and environmental variables were good predictors on this spatial scale.
The host population factor explained 8.5% of variation in the model.
The environment factor accounted for 52.5% of it. Jointly, these two factors could explain 66.3% of variation in the model. The index of environmental favourability for the red deer lost power with the regional model (probably because it was on a national basis and calculated with presence/absence -not abundance -data). However, livestock density (a more reliable estimate of local densities calculated with census data collected at the local veterinary unit level) still displayed a signif-icant positive relationship to exposure risk. Deer farms in this region had a higher risk of exposure when compared to deer farming on the scale of mainland Spain. On this regional scale, the NDVI had the effect of boosting virus exposure to deer. In contrast, on the premise of an expected higher vegetation production with increasing annual rainfall, annual precipitation on this regional scale had a slight albeit significant negative effect on exposure risk. In contrast, seasonality in precipitation displayed positive influences. Finally, we observed a negative joint effect of the slope/soil permeability interaction on infection risk.
The model built to predict exposure risk in mainland Spain corroborated the observed effects of (host) population and environmental factors with the peninsular scale model (Table 5) with a split-sample procedure using 50% of the data as a training set and the remaining 50% as a test dataset. Estimated accuracy was 74%. Therefore, the model could not classify 26% of the samples correctly.

TA B L E 2
Descriptive parameters for significant predictors of the risk of exposure to CCHFV (identified by the selected overall risk model) of the high and low relative risk (RR) spatial clusters identified as statistically distinct Note: The values displayed for any predictor include the average value of the set of populations included in the cluster and the range (except for single population clusters). The RR and the number of populations included in each cluster are shown. Cluster numbers correspond to those in Figure 3. Predictors and abbreviations are fully described in Table 1. NA: not estimated.

DISCUSSION
A set of preliminary results suggested that CCHFV could be enzootic  -Fons et al., 2006). We therefore expected to find an additional positive effect of wild boar density. The lack of influence of wild boar density on the Spanish mainland and southwestern scales and the unexpected negative effect in the model built to project exposure risk may indicate that the environmental favourability index employed was an inaccurate proxy of wild boar density. Thus, we cannot draw any conclusion concerning the effect of wild boar abundance on the ecology of CCHFV from this study. The ongoing research for gaining an insight into the influence of local host-tick interaction patterns on CCHFV dynamics in questing ticks will help to understand CCHFV ecology on small spatial scales, improve our understanding of the role of the wild boar and enhance risk predictions.
No gender effects were observed in exposure risk even though stags host ten times more ticks than hinds (Ruiz-Fons et al., 2013)  after CCHFV infection may support the lack of a gender effect. The age effect could also be supported by increasing tick burdens with deer age (Ruiz-Fons et al., 2013), but that would mean a higher risk for adults than for yearlings, not the contrary. We studied whether finding significantly higher exposure rates in yearlings could be caused by regional imbalances in sampling. The proportion of yearlings in a red deer were collected on a red deer farm where animals had very high tick burdens (González-Barrio et al., 2015b), and 26 had CCHFV antibodies (86.7%). In the remaining survey locations, 24.5% of 49 yearlings were seropositive. That is also above the average antibody prevalence of juveniles (17%) and sub-adults (18.8%). All yearlings were over 6month-old in order to rule out any potential interference from maternal antibodies (González-Barrio et al., 2015a). These results indicate that, even though there was spatial bias in our study, yearlings may be significant to understanding the dynamics of pathogens in serosurveys performed over samples collected from wildlife disease surveillance programs as antibodies in yearling indicate recent infection.
Game management has been found repeatedly as a significant risk factor for several wild ungulate pathogens .
We therefore expected to find higher exposure to risk in deer with medium-high management when compared to unmanaged deer. Game management promotes a higher density of ungulates and aggregation of individuals (Acevedo et al., 2008), and host density is a significant local driver of tick burdens (Ruiz-Fons et al., 2012). We expected climate to be an influential factor because it is significant in terms of the presence and abundance of particular tick species in a territory.
The seasonal inter-annual variation of climatic parameters may similarly or better shape arthropod demographics than average values (Ewing et al., 2016). H. lusitanicum ticks decrease questing activity in these seasons (Valcárcel et al., 2016). NDVI and temperature seasonality had a protective effect against exposure to CCHFV on a national scale, whereas these were insignificant in southwestern Iberia. Continentality implies thermal contrasts (Stonevicius et al., 2018)   Active Archive Center (http://LPDAAC.usgs.gov). We estimated the average altitude at the UTM 10 × 10 km square. The slope was calculated, based on altitude, using the Idrisi SLOPE command (Eastman, 2004) and averaged with the spatial unit of the study.
We selected habitat variables (vegetation productivity, land cover and soil traits) as potential predictors of CCHFV exposure risk because of their effects on the vectors and the hosts (e.g. Acevedo et al., 2010). We included two predictors related to the Normalized Difference Vegetation Index (NDVI) -average annual NDVI and NDVI seasonality. We considered NDVI registers as proxies for the contribution of the moisture of the soil (Nicholson & Farrar, 1994) to vegetation productivity. Thus, we included these as indices of the hydric stress that ticks suffer in soil. We derived NDVI values from a monthly dataset obtained from the NASA Goddard DAAC website (http//daac.gsfc.nasa.gov/data/avhrr/) at a resolution scale of 1000 m in 18 years (1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000). We estimated NDVI seasonality as the coef- Hosts are principal determinants of tick population dynamics. Host population traits may also be relevant predictors of the risk of exposure to CCHFV. Wild and domestic ungulates host high burdens of ticks (Castellà et al., 2001;Ruiz-Fons et al., 2013), contributing significantly to tick abundance (Ruiz-Fons & Gilbert, 2010;Ruiz-Fons et al., 2012). Mammals, including ungulates, additionally replicate CCHFV for a short time after infection and transmit it to feeding ticks (Spengler et al., 2016b). Mammals allow CCHFV co-feeding transmission between ticks, its horizontal tick-to-tick venereal transmission and its vertical transmission which enable adult females to produce abundant infected offspring. Our aim was not to unravel the many traits of the community of hosts (for the ticks and the virus) that modulate the risk of exposure but rather to find significant associations that help us gain an insight into this unknown system. For this purpose, we selected variables indicating the relative abundance of the major potential hosts for CCHFV ticks in Iberia, that is, domestic ruminants, red deer, roe deer (Capreolus capreolus) and Eurasian wild boar (Sus scrofa). Livestock census data were obtained from the Spanish Ministry for Ecological Transition (https://www.miteco.gob.es/es/) on a regional veterinary unit level for 2008. Data from the veterinary units were downscaled to UTM 10 × 10 km squares. Data on wild ungulate abundance on a large scale are scarce in Iberia. Therefore, we chose to estimate species abundance using the values for environmental favourability for red deer, roe deer and Eurasian wild boar calculated in a previously published study to model Culicoides imicola abundance in Spain (Acevedo et al., 2010). Iberian red deer populations are managed for different purposes and management schemes, which may influence exposure to ticks and thus to CCHFV. Public territories under protection and social hunting grounds promote natural management of wild ungulates with minimum intervention; these may include occasional deliveries of animal feed to attract deer to a specific area before hunting or specific habitat management practices, among other minor interventions. On lands devoted to hunting (hunting estates, game reserves), management practices are highly variable; these may range from occasional feeding before hunting to high-wire fencing with (occasional) artificial year-round feeding. Deer farming in Iberia is an extensive activity. Ani- Specifically, farmed deer are frequently treated with acaricides. The intensity of managing any deer population in the study was classified as low, medium or high.
Several host traits may modulate the exposure individuals have to ticks that ultimately determine CCHFV transmission. In the red deer-H. lusitanicum system, we previously found sound differences related to deer sex and age (Ruiz-Fons et al., 2013), so these two host individual variables were considered as potentially significant predictors of the risk of exposure to CCHFV.