A Predictive Model Has Identified Tick-Borne Encephalitis High-Risk Areas in Regions Where No Cases Were Reported Previously, Poland, 1999-2012

A fatal case of tick-borne encephalitis in an immunocompromised patient: case report from Northeastern Poland and review of literature

Tick-borne encephalitis (TBE) is an infectious illness of the central nervous system caused by the TBE virus, which is commonly transmitted through a tick-bite. TBE is endemic in Europe and mid-Asia. In this study, we report a case of a 36-year-old woman, living in Northeastern Poland, with a history of double corneal transplantation and post-transplant immunosuppressive therapy who was admitted to hospital because of progressive weakness, acute headache, nausea, vertigo, vomiting, and fever. The patient was diagnosed with TBE. However, the diagnosis was challenging as the initial serological tests for antibodies against the TBE virus were negative. We want to raise the awareness among the clinicians that the course of TBE is often unpredictable and that it tends to be more severe in immunocompromised individuals.. Delayed production of antibodies against TBE virus, which might inhibit the diagnosis of the disease, is observed in some immunocompromised patients.

Ecological and environmental factors affecting the risk of tick-borne encephalitis in Europe, 2017 to 2021

BackgroundTick-borne encephalitis (TBE) is a disease which can lead to severe neurological symptoms, caused by the TBE virus (TBEV). The natural transmission cycle occurs in foci and involves ticks as vectors and several key hosts that act as reservoirs and amplifiers of the infection spread. Recently, the incidence of TBE in Europe has been rising in both endemic and new regions.AimIn this study we want to provide comprehensive understanding of the main ecological and environmental factors that affect TBE spread across Europe.MethodsWe searched available literature on covariates linked with the circulation of TBEV in Europe. We then assessed the best predictors for TBE incidence in 11 European countries by means of statistical regression, using data on human infections provided by the European Surveillance System (TESSy), averaged between 2017 and 2021.ResultsWe retrieved data from 62 full-text articles and identified 31 different covariates associated with TBE occurrence. Finally, we selected eight variables from the best model, including factors linked to vegetation cover, climate, and the presence of tick hosts.DiscussionThe existing literature is heterogeneous, both in study design and covariate types. Here, we summarised and statistically validated the covariates affecting the variability of TBEV across Europe. The analysis of the factors enhancing disease emergence is a fundamental step towards the identification of potential hotspots of viral circulation. Hence, our results can support modelling efforts to estimate the risk of TBEV infections and help decision-makers implement surveillance and prevention campaigns.

Tick-borne encephalitis epidemiology and surveillance in Poland, and comparison with selected European countries before and during the COVID-19 pandemic, 2008 to 2020

BackgroundTick-borne encephalitis (TBE) is the most common viral central nervous system (CNS) infection in Poland. Previous research suggests that its incidence was underestimated in the pre-pandemic period. The COVID-19 pandemic caused a considerable burden on surveillance systems, which could further impact reporting.AimWe aimed to assess the completeness of reporting of TBE in the years 2008 to 2020 and explore the potential impact of the COVID-19 pandemic on reporting to the epidemiological surveillance system, compared with hospitalisations for TBEV and other viral neuro-infections.MethodsWe compared the Polish epidemiology of TBE and other viral infections of the CNS from national surveillance reports with data on hospitalisations from 2008 to 2020 and data from selected European countries.ResultsBetween 2008 and 2020, 3,016 TBE cases were reported to surveillance compared with 3,620 hospitalisations. There was an increasing trend in hospitalisations, while surveillance data demonstrated the opposite, with the largest discrepancy observed in the first pandemic year (354 hospitalisations vs 159 cases reported to surveillance). Serological testing for TBE was used more in the known endemic region of north-eastern Poland and less in non-endemic areas. Other European countries reported higher TBE case numbers and an increase during the COVID-19 pandemic, whereas Poland observed an opposite trend.ConclusionThe sensitivity of TBE surveillance in Poland requires improvement. There are considerable regional differences. Regions that test for TBE intensively report most cases. Policymakers should be made aware of the value of quality epidemiological data for planning prophylactic measures in risk areas.

Decoding the Geography of Natural TBEV Microfoci in Germany: A Geostatistical Approach Based on Land-Use Patterns and Climatological Conditions

Background: Tickborne-encephalitis (TBE) is a potentially life-threating neurological disease that is mainly transmitted by ticks. The goal of the present study is to analyze the potential uniform environmental patterns of the identified TBEV microfoci in Germany. The results are used to calculate probabilities for the present distribution of TBEV microfoci in Germany based on a geostatistical model. Methods: We aim to consider the specification of environmental characteristics of locations of TBEV microfoci detected in Germany using open access epidemiological, geographical and climatological data sources. We use a two-step geostatistical approach, where in a first step, the characteristics of a broad set of environmental variables between the 56 TBEV microfoci and a control or comparator set of 3575 sampling points covering Germany are compared using Fisher's Exact Test. In the second step, we select the most important variables, which are then used in a MaxEnt distribution model to calculate a high resolution (400 × 400 m) probability map for the presence of TBEV covering the entire area of Germany. Results: The findings from the MaxEnt prediction model indicate that multi annual actual evapotranspiration (27.0%) and multi annual hot days (22.5%) have the highest contribution to our model. These two variables are followed by four additional variables with a lower, but still important, explanatory influence: Land cover classes (19.6%), multi annual minimum air temperature (14.9%), multi annual sunshine duration (9.0%), and distance to coniferous and mixed forest border (7.0%). Conclusions: Our findings are based on defined TBEV microfoci with known histories of infection and the repeated confirmation of the virus in the last years, resulting in an in-depth high-resolution model/map of TBEV microfoci in Germany. Multi annual actual evapotranspiration (27%) and multi annual hot days (22.5%) have the most explanatory power in our model. The results may be used to tailor specific regional preventive measures and investigations.

Geo-Spatial Characteristics of 567 Places of Tick-Borne Encephalitis Infection in Southern Germany, 2018-2020

Tick-borne encephalitis (TBE) is a growing public health problem with increasing incidence and expanding risk areas. Improved prevention requires better understanding of the spatial distribution and ecological determinants of TBE transmission. However, a TBE risk map at sub-district level is still missing for Germany. We investigated the distribution and geo-spatial characteristics of 567 self-reported places of probable TBE infection (POI) from 359 cases notified in 2018-2020 in the study area of Bavaria and Baden-Wuerttemberg, compared to 41 confirmed TBE foci and 1701 random comparator places. We built an ecological niche model to interpolate TBE risk to the entire study area. POI were distributed heterogeneously at sub-district level, as predicted probabilities varied markedly across regions (range 0-93%). POI were spatially associated with abiotic, biotic, and anthropogenic geo-spatial characteristics, including summer precipitation, population density, and annual frost days. The model performed with 69% sensitivity and 63% specificity at an optimised probability threshold (0.28) and an area under the curve of 0.73. We observed high predictive probabilities in small-scale areas, consistent with the known circulation of the TBE virus in spatially restricted microfoci. Supported by further field work, our findings may help identify new TBE foci. Our fine-grained risk map could supplement targeted prevention in risk areas.

Spatial patterns of pathogen prevalence in questing Ixodes ricinus nymphs in southern Scandinavia, 2016

Tick-borne pathogens cause diseases in animals and humans, and tick-borne disease incidence is increasing in many parts of the world. There is a need to assess the distribution of tick-borne pathogens and identify potential risk areas. We collected 29,440 tick nymphs from 50 sites in Scandinavia from August to September, 2016. We tested ticks in a real-time PCR chip, screening for 19 vector-associated pathogens. We analysed spatial patterns, mapped the prevalence of each pathogen and used machine learning algorithms and environmental variables to develop predictive prevalence models. All 50 sites had a pool prevalence of at least 33% for one or more pathogens, the most prevalent being Borrelia afzelii, B. garinii, Rickettsia helvetica, Anaplasma phagocytophilum, and Neoehrlichia mikurensis. There were large differences in pathogen prevalence between sites, but we identified only limited geographical clustering. The prevalence models performed poorly, with only models for R. helvetica and N. mikurensis having moderate predictive power (normalized RMSE from 0.74-0.75, R2 from 0.43-0.48). The poor performance of the majority of our prevalence models suggest that the used environmental and climatic variables alone do not explain pathogen prevalence patterns in Scandinavia, although previously the same variables successfully predicted spatial patterns of ticks in the same area.

Etiology, Clinical Presentation and Incidence of Infectious Meningitis and Encephalitis in Polish Children

Little is known about the causes and the frequency of meningitis and encephalitis in Poland. We did a retrospective single-center cohort study of children under 18 years old hospitalized with infectious meningitis or encephalitis. Incidence rates were calculated using collected data from patients from the North-East Poland only. A total of 374 children hospitalized between 1 January 2015 and 31 December 2019 were included in the study. A total of 332 (89%) children had meningitis, and 42 (11%) had encephalitis. The etiology of the infection was established in 331 (89%) cases. Enteroviruses accounted for 224 (60%) of all patients. A total of 68 (18%) cases were tick-borne infections. Bacterial pathogens were detected in 26 (7%) children. The median length of hospital stay for children with enteroviral meningitis was 7 days (IQR 7–9), increasing to 11 days (8–13) in those treated with antibiotics. The incidence of meningitis was estimated to be 32.22 (95% CI, 25.33–40.98) per 100,000 and that of encephalitis to be 4.08 (95% CI, 2.07–8.02) per 100,000. By the broad use of molecular diagnostic methods, we managed to identify etiology of the infection in the majority of children. Our data suggest that thorough diagnostics of central nervous system infections are needed to rationalize treatment.

Modelling tick bite risk by combining random forests and count data regression models

The socio-economic and demographic changes that occurred over the past 50 years have dramatically expanded urban areas around the globe, thus bringing urban settlers in closer contact with nature. Ticks have trespassed the limits of forests and grasslands to start inhabiting green spaces within metropolitan areas. Hence, the transmission of pathogens causing tick-borne diseases is an important threat to public health. Using volunteered tick bite reports collected by two Dutch initiatives, here we present a method to model tick bite risk using human exposure and tick hazard predictors. Our method represents a step forward in risk modelling, since we combine a well-known ensemble learning method, Random Forest, with four count data models of the (zero-inflated) Poisson family. This combination allows us to better model the disproportions inherent in the volunteered tick bite reports. Unlike canonical machine learning models, our method can capture the overdispersion or zero-inflation inherent in data, thus yielding tick bite risk predictions that resemble the original signal captured by volunteers. Mapping model predictions enables a visual inspection of the spatial patterns of tick bite risk in the Netherlands. The Veluwe national park and the Utrechtse Heuvelrug forest, which are large forest-urban interfaces with several cities, are areas with high tick bite risk. This is expected, since these are popular places for recreation and tick activity is high in forests. However, our model can also predict high risk in less-intensively visited recreational areas, such as the patchy forests in the northeast of the country, the natural areas along the coastline, or some of the Frisian Islands. Our model could help public health specialists to design mitigation strategies for tick-borne diseases, and to target risky areas with awareness and prevention campaigns.

Occurrence of canine and feline extra-intestinal nematodes in key endemic regions of Italy

Extra-intestinal nematodes of companion animals are of growing concern in veterinary medicine for their pathogenic potential and the current expansion throughout Europe. The present study has evaluated the occurrence of major canine and feline extra-intestinal nematodes in regions of Italy having epidemiological relevance. Associations of various recorded parameters related to the examined animals have been statistically evaluated, along with a comparative analysis with the most recent epidemiological data. Overall, 1055 dogs and 1000 cats were tested. Among extra-intestinal nematodes Angiostrongylus vasorum was the most common in dogs followed by Capillaria aerophila and Dirofilaria spp.; Aelurostrongylus abstrusus was the most recorded parasite in cats, followed by C. aerophila and Troglostrongylus brevior. The statistical analysis revealed that outdoor access is associated with A. vasorum, A. abstrusus and T. brevior infections, that were also more prevalent in animals with cardio-respiratory signs. Moreover, cats aged less than 12 months had more chances to be infected by lungworms. The data herein presented confirm the occurrence and the possible risk of expansion of different extra-intestinal parasitoses of dogs and cats in Italy, underlining the importance of a constant epidemiologic vigilance and of appropriate control methods.

Model of Risk of Exposure to Lyme Borreliosis and Tick-Borne Encephalitis Virus-Infected Ticks in the Border Area of the Czech Republic (South Bohemia) and Germany (Lower Bavaria and Upper Palatinate)

In Europe, Lyme borreliosis (LB) and tick-borne encephalitis (TBE) are the two vector-borne diseases with the largest impact on human health. Based on data on the density of host-seeking Ixodes ricinus ticks and pathogen prevalence and using a variety of environmental data, we have created an acarological risk model for a region where both diseases are endemic (Czech Republic-South Bohemia and Germany-Lower Bavaria, Upper Palatinate). The data on tick density were acquired by flagging 50 sampling sites three times in a single season. Prevalence of the causative agents of LB and TBE was determined. Data on environmental variables (e.g., altitude, vegetation cover, NDVI, land surface temperature) were obtained from various sources and processed using geographical information systems. Generalized linear models were used to estimate tick density, probability of tick infection, and density of infected ticks for the whole area. A significantly higher incidence of human TBE cases was recorded in South Bohemia compared to Bavarian regions, which correlated with a lower tick density in Bavaria. However, the differences in pathogen prevalence rates were not significant. The model outputs were made available to the public in the form of risk maps, indicating the distribution of tick-borne disease risk in space.

Large-scale health disparities associated with Lyme disease and human monocytic ehrlichiosis in the United States, 2007-2013

Promoting health equity is a fundamental public health objective, yet health disparities remain largely overlooked in studies of vectorborne diseases, especially those transmitted by ticks. We sought to identify health disparities associated with Lyme disease and human monocytic ehrlichiosis, two of the most pervasive tickborne diseases within the United States. We used general linear mixed models to measure associations between county-level disease incidence and six variables representing racial/ethnic and socioeconomic characteristics of counties (percent white non-Hispanic; percent with a bachelors degree or higher; percent living below the poverty line; percent unemployed; percent of housing units vacant; per capita number of property crimes). Two ecological variables important to tick demography (percent forest cover; density of white-tailed deer) were included in secondary analyses to contextualize findings. Analyses included data from 2,695 counties in 37 states and the District of Columbia during 2007-2013. Each of the six variables was significantly associated with the incidence of one or both diseases, but the direction and magnitude of associations varied by disease. Results suggested that the incidence of Lyme disease was highest in counties with relatively higher proportions of white and more educated persons and lower poverty and crime rates; the incidence of human monocytic ehrlichiosis was highest in counties with relatively higher proportions of white and less educated persons, higher unemployment rates and lower crime rates. The percentage of housing units vacant was a strong positive predictor for both diseases with a magnitude of association comparable to those between incidence and the ecological variables. Our findings indicate that racial/ethnic and socioeconomic disparities in disease incidence appear to be epidemiologically important features of Lyme disease and human monocytic ehrlichiosis in the United States. Steps to mitigate encroachment of wild flora and fauna into areas with vacant housing might be warranted to reduce disease risk.