Forest classes and tree cover gradient: tick habitat in encroached areas of southern Norway

Predicting the current and future risk of ticks on livestock farms in Britain using random forest models

The most abundant tick species in northern Europe, Ixodes ricinus, transmits a range of pathogens that cause disease in livestock. As I. ricinus distribution is influenced by climate, tick-borne disease risk is expected to change in the future. The aims of this work were to build a spatial model to predict current and future risk of ticks on livestock farms across Britain. Variables relating both to tick hazard and livestock exposure were included, to capture a niche which may be missed by broader scale models. A random forest machine learning model was used due to its ability to cope with correlated variables and interactions. Data on tick presence and absence on sheep and cattle farms was obtained from a retrospective questionnaire survey of 926 farmers. The ROC of the final model was 0.80. The model outputs matched observed patterns of tick distribution, with areas of highest tick risk in southwest and northwest England, Wales, and west Scotland. Overall, the probability of tick presence on livestock farms was predicted to increase by 5-7 % across Britain under future climate scenarios. The predicted increase is greater at higher altitudes and latitudes, further increasing the risk of tick-borne disease on farms in these areas.

Habitat suitability map of <em>Ixodes ricinus</em> tick in France using multi-criteria analysis

The tick Ixodes ricinus is widely distributed across Europe and is responsible for the transmission of several pathogens to humans and animals. In this study, we used a knowledge-based method to map variations in habitat suitability for I. ricinus ticks throughout continental France and Corsica. The multi-criteria decision analysis (MCDA) integrated four major biotic and abiotic factors known to influence tick populations: climate, land cover, altitude and the density of wild ungulates. For each factor, habitat suitability index (HSI) values were attributed to different locations based on knowledge regarding its impact on tick populations. For the MCDA, two methods of factor combination were tested, additive and multiplicative, both which were evaluated at the spatial scales of departments and local municipalities. The resulting habitat suitability maps (resolution=100x100 m) revealed that conditions are suitable for I. ricinus over most of France and Corsica. Particularly suitable habitats were located in central, north-eastern and south-western France, while less-suitable habitats were found in the Mediterranean and mountainous regions. To validate the approach, the HSI scores were compared to field data of I. ricinus nymph abundance. Regardless of scale, the correlation between abundance indicator and HSI score was stronger for the additive than for the multiplicative approach. Overall, this study demonstrates the value of MCDA for estimating habitat suitability maps for I. ricinus abundance, which could be especially useful in highlighting areas of the tick's distribution where preventive measures should be prioritised.

The influence of local environmental factors in southwestern Poland on the abundance of Ixodes ricinus and prevalence of infection with Borrelia burgdorferi s.l. and B. miyamotoi

Ticks are important ectoparasites and vectors of pathogens that cause disease in humans and animals. The natural habitat of Ixodes ricinus ticks is forests, which are convenient habitats to search for hosts, including reservoir hosts, and therefore can be an important habitat source of tick-borne pathogens. The aim of the study was to assess the usefulness of detailed forest habitat-type maps to estimate the tick-borne risk at a local scale (Lower Silesia, SW Poland). For the purposes of estimating tick abundance, we used the land cover maps available from the Forest Data Bank. For I. ricinus collection, nine sites located in three forest habitat types were chosen: broadleaf forest, mixed broadleaf and coniferous forest and coniferous forest. Ticks were collected once a month from April to June 2018 and 2019 using the standard flagging method. At each of the nine sites, ticks were collected in four plots, of 100 m² each. Tick abundance was analysed using general linear mixed models (GLMM). A total of 2196 (10.1/100 m²) ticks were collected, including 2093 Ixodes ricinus (95.3%; 9.6/100 m²), 46 Dermacentor reticulatus (2.1%; 0.2/100 m²) and 57 Haemaphysalis concinna (2.6%; 0.3/100 m²). Among the collected I. ricinus were 589 larvae (28.1%; 2.7/100 m²), 1261 nymphs (60.3%; 5.8/100 m²), 128 females (6.1%; 0.6/100 m²) and 115 males (5.5%; 0.5/100 m²). We found a highly significant effect of forest habitat type on the density of ticks for broadleaf forest (coefficient = 1.87267, p-value = 2.79e - 07). Additionally, a significant influence of air temperature and relative humidity on the abundance of ticks was observed. During spring, the peak activity of I. ricinus was recorded in May and June. For DNA amplification of Borrelia burgdorferi s.l., a nested PCR method was used. Out of 494 I. ricinus, 83 (16.8%) were positive for Borrelia spp. The RFLP method showed the occurrence of five species including four belonging to the B. burgdorferi s.l. complex: B. afzelii (30.1%), B. garinii (38.6%), B. valaisiana (2.4%) and B. lusitaniae (18.1%). Furthermore, B. miyamotoi (9.6%), a species belonging to bacteria that cause relapsing fever as well as co-infection of B. miyamotoi/B.lusitaniae (1.2%) were found. The differences in the infection level of Borrelia spp. between broadleaf forest and mixed broadleaf and coniferous forest were statistically significant.

The Isolation of Culturable Bacteria in Ixodes ricinus Ticks of a Belgian Peri-Urban Forest Uncovers Opportunistic Bacteria Potentially Important for Public Health

Most bacteria found in ticks are not pathogenic to humans but coexist as endosymbionts and may have effects on tick fitness and pathogen transmission. In this study, we cultured and isolated 78 bacteria from 954 Ixodes ricinus ticks collected in 7 sites of a Belgian peri-urban forest. Most isolated species were non-pathogenic environmental microorganisms, and were from the Firmicutes (69.23%), Actinobacteria (17.95%) and Proteobacteria (3.84%) phyla. One bacterium isolate was particularly noteworthy, Cedecea davisae, a rare opportunistic bacterium, naturally resistant to various antibiotics. It has never been isolated from ticks before and this isolated strain was resistant to ampicillin, cefoxitin and colistin. Although cultivable bacteria do not represent the complete tick microbiota, the sites presented variable bacterial compositions and diversities. This study is a first attempt to describe the culturable microbiota of ticks collected in Belgium. Further collections and analyses of ticks of different species, from various areas and using other bacterial identification methods would strengthen these results. However, they highlight the importance of ticks as potential sentinel for opportunistic bacteria of public health importance.

Environmental determinants of Anaplasma phagocytophilum infection in cattle using a kernel density function

The study of vector-borne zoonotic diseases often relies on partial data, because of the constraints associated with observing various elements of the transmission cycle: the pathogen, the vector, the host - wild or domestic. Each angle comes with its own practical challenges, leading to data reflecting poorly either on spatial or temporal dynamics, or both. In this study, we investigated the effect of landscape on the presence of bovine ehrlichiosis infection in Walloon cattle. This disease is transmitted to cattle through the bite of a tick infected by the bacterium Anaplasma phagocytophilum. The first case of bovine ehrlichiosis in the southern region of Belgium (Wallonia) was detected in 2005 and the high seroprevalence found in herds suggests that the disease is endemic. The presence of antibodies of A. phagocytophilum in one cow selected in each of 1445 herds in 2010 and 2011 was detected using indirect immunofluorescence. Samples were geolocated at the farm. However, the precise location of infection remains uncertain. To account for the data sparsity, we elaborated a spatial index for the intensity of the presence of seropositive animals, based on a non-parametric kernel density estimation. We examined this index with the landscape surrounding the pastures, using multiple regressions. Landscape factors were selected using a conceptual framework based on the ecological resources needed for the transmission cycle of A. phagocytophilum. Results suggest that our spatial index adequately reflected infection presence in cattle in Wallonia, which was highest in central regions, corresponding to more forested and fragmented landscapes. We noticed that the presence of large hosts, wild or domestic, as well as the composition and configuration of the landscape of the pasture, influenced the capacity of the pasture to support the presence of bovine ehrlichiosis in Walloon herds. This is consistent with the ecology of A. phagocytophilum and current knowledge about risk factors of tick-borne diseases in cattle at the regional scale. The nature of the kernel density index, based on uncertainties over the location of cases positive to A. phagocytophilum, reflected the infectiousness profile at the landscape and not at the pasture level. Results also highlighted that the effects of some environmental variables remain, even when considering the different agro-geographic regions of Wallonia, which present contrasted landscapes and different levels of intensity of A. phagocytophilum infection. The kernel density index is a useful tool to help veterinary practitioner to quickly target areas where A. phagocytophilum infection is likely.

Assessing the importance of Molecular and Genetic perspectives in Prophesying the KFD transmission risk provinces in the Western Ghats, Kerala, INDIA in context with spatial distribution, Extensive genetic Diversity, and phylogeography

The deadly effects of KFD have been pointed in southern India; however, the infecting regions have been getting larger in recent epochs. People who live or work in regions where KFDV infected tick vectors are present are severely prone to procuring the infection. Being aware of tick vectors and infectious agents' geospatial location is vital to direct sustenance approaches to prevent and manage such infectious diseases as KFD. The present investigation has focussed on the spatial distribution, Extensive genetic Diversity, and phylogeography to forecast the probable KFD disease risk provinces in the Western Ghats. The statistical analysis for diversity indices and community comparison has been performed by using SPSS version 24.0.0 and R software version 3.4.2. The nucleotide sequences of the respective ticks and KFDV were retrieved from NCBI. The first strand of this investigation revealed that, around the world, the Indian province was found to exhibit a maximum range of diversity for tick vectors. The next strands prophesied the KFD transmission risk areas in the Western Ghats region, India, with computational spatial analysis and phylogeography. The final strand exposed the genetic diversity of the KFD virus and the tick vectors in terms of their spatial distribution worldwide.

Identifying Environmental Risk Factors for Louping Ill Virus Seroprevalence in Sheep and the Potential to Inform Wildlife Management Policy

Identifying the risk factors for disease is crucial for developing policy and strategies for controlling exposure to pathogens. However, this is often challenging, especially in complex disease systems, such as vector-borne diseases with multiple hosts and other environmental drivers. Here we combine seroprevalence data with GIS-based environmental variables to identify the environmental risk factors associated with an endemic tick-borne pathogen—louping ill virus—in sheep in Scotland. Higher seroprevalences were associated with (i) upland/moorland habitats, in accordance with what we predicted from the habitat preferences of alternative LIV transmission hosts (such as red grouse), (ii) areas of higher deer density, which supports predictions from previous theoretical models, since deer are the key Ixodes ricinus tick reproduction host in this system, and (iii) a warmer climate, concurring with our current knowledge of how temperature affects tick activity and development rates. The implications for policy include adopting increased disease management and awareness in high risk habitats and in the presence of alternative LIV hosts (e.g., grouse) and tick hosts (especially deer). These results can also inform deer management policy, especially where there may be conflict between contrasting upland management objectives, for example, revenue from deer hunting vs. sheep farmers.

Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.

Electromagnetic radiation and behavioural response of ticks: an experimental test

Factors associated with the increased usage of electronic devices, wireless technologies and mobile phones nowadays are present in increasing amounts in our environment. All living organisms are constantly affected by electromagnetic radiation which causes serious environmental pollution. The distribution and density of ticks in natural habitats is influenced by a complex of abiotic and biotic factors. Exposure to radio-frequency electromagnetic field (RF-EMF) constitutes a potential cause altering the presence and distribution of ticks in the environment. Our main objective was to determine the affinity of Dermacentor reticulatus ticks towards RF-EMF exposure. Originally designed and constructed radiation-shielded tube (RST) test was used to test the affinity of ticks under controlled laboratory conditions. All test were performed in an electromagnetic compatibility laboratory in an anechoic chamber. Ticks were irradiated using a Double-Ridged Waveguide Horn Antenna to RF-EMF at 900 and 5000 MHz, 0 MHz was used as control. The RF-EMF exposure to 900 MHz induced a higher concentration of ticks on irradiated arm of RST as opposed to the RF-EMF at 5000 MHz, which caused an escape of ticks to the shielded arm. This study represents the first experimental evidence of RF-EMF preference in D. reticulatus. The projection of obtained results to the natural environment could help assess the risk of tick borne diseases and could be a tool of preventive medicine.

How will climate change pathways and mitigation options alter incidence of vector-borne diseases? A framework for leishmaniasis in South and Meso-America

The enormous global burden of vector-borne diseases disproportionately affects poor people in tropical, developing countries. Changes in vector-borne disease impacts are often linked to human modification of ecosystems as well as climate change. For tropical ecosystems, the health impacts of future environmental and developmental policy depend on how vector-borne disease risks trade off against other ecosystem services across heterogeneous landscapes. By linking future socio-economic and climate change pathways to dynamic land use models, this study is amongst the first to analyse and project impacts of both land use and climate change on continental-scale patterns in vector-borne diseases. Models were developed for cutaneous and visceral leishmaniasis in the Americas-ecologically complex sand fly borne infections linked to tropical forests and diverse wild and domestic mammal hosts. Both diseases were hypothesised to increase with available interface habitat between forest and agricultural or domestic habitats and with mammal biodiversity. However, landscape edge metrics were not important as predictors of leishmaniasis. Models including mammal richness were similar in accuracy and predicted disease extent to models containing only climate and land use predictors. Overall, climatic factors explained 80% and land use factors only 20% of the variance in past disease patterns. Both diseases, but especially cutaneous leishmaniasis, were associated with low seasonality in temperature and precipitation. Since such seasonality increases under future climate change, particularly under strong climate forcing, both diseases were predicted to contract in geographical extent to 2050, with cutaneous leishmaniasis contracting by between 35% and 50%. Whilst visceral leishmaniasis contracted slightly more under strong than weak management for carbon, biodiversity and ecosystem services, future cutaneous leishmaniasis extent was relatively insensitive to future alternative socio-economic pathways. Models parameterised at narrower geographical scales may be more sensitive to land use pattern and project more substantial changes in disease extent under future alternative socio-economic pathways.

Individual and environmental factors associated with the seroprevalence of Borrelia burgdorferi in Belgian farmers and veterinarians

BACKGROUND

Lyme disease (LD) is a common tick-borne disease in Europe. Diverse factors at various scales determine the spatial distribution of Borrelia burgdorferi infection risk and a better understanding of those factors in a spatially explicit framework is needed for disease management and prevention. While the ecology of ticks and the landscape favoring their abundance have been extensively studied, the environmental conditions favoring an intense contact with susceptible humans, including groups at risk, are sparse. The aim of this study is to assess which individual and environmental factors can favor B. burgdorferi infection in a Belgian group professionally at risk.

METHODS

Serological results of 127 veterinarians and farmers enrolled in this study were analyzed, taking into account their municipality of residence. Using binary logistic regression and considering interaction terms, the joint effects of landscape composition and configuration, and forest and wildlife management were examined.

RESULTS

Seven of the 127 workers were seropositive for LD, leading to a seroprevalence of 5.51%. Seropositivity was higher in older persons. The proportion of forest and semi-natural habitats and wetland had a positive impact on LD seroprevalence while arable land-grassland ecotones had a negative one. Our results confirmed the need to consider complex interactions between landscape variables in order to model risk.

CONCLUSIONS

Our data show that LD has to be considered as a risk for farmers and veterinarians. Rather than focusing either on ecological aspects of tick and pathogen distribution or on purely epidemiological aspects such as individual risk factors, our model highlights the role of human-environment interactions in LD risk assessment.