Peri-urbanisation, counter-urbanisation, and an extension of residential exposure to ticks: a clue to the trends in Lyme borreliosis incidence in the Czech Republic?

Seroepidemiology of Borrelia burgdorferi s.l. among German National Cohort (NAKO) Participants, Hanover

Lyme borreliosis is the leading tick-related illness in Europe, caused by Borrelia Burgdorferi s.l. Lower Saxony, Germany, including its capital, Hanover, has a higher proportion of infected ticks than central European countries, justifying a research focus on the potential human consequences. The current knowledge gap on human incident infections, particularly in Western Germany, demands serological insights, especially regarding a potentially changing climate-related tick abundance and activity. We determined the immunoglobulin G (IgG) and immunoglobulin M (IgM) serostatuses for 8009 German National Cohort (NAKO) participants from Hanover, examined in 2014-2018. We used an enzyme-linked immunosorbent assay (ELISA) as the screening and a line immunoblot as confirmation for the Borrelia Burgdorferi s.l. antibodies. We weighted the seropositivity proportions to estimate general population seropositivity and estimated the force of infection (FOI). Using logistic regression, we investigated risk factors for seropositivity. Seropositivity was 3.0% (IgG) and 2.1% (IgM). The FOI varied with age, sharply increasing in participants aged ≥40 years. We confirmed advancing age and male sex as risk factors. We reported reduced odds for seropositivity with increasing body mass index and depressive symptomatology, respectively, pointing to an impact of lifestyle-related behaviors. The local proportion of seropositive individuals is comparable to previous estimates for northern Germany, indicating a steady seroprevalence.

The Effects of Lifestyle on the Risk of Lyme Disease in the United States: Evaluation of Market Segmentation Systems in Prevention and Control Strategies

The aim of this study was to investigate lifestyles at risk of Lyme disease, and to geographically identify target populations/households at risk based on their lifestyle preferences. When coupled with geographically identified patient health information (e.g., incidence, diagnostics), lifestyle data provide a more solid base of information for directing public health objectives in minimizing the risk of Lyme disease and targeting populations with Lyme-disease-associated lifestyles. We used an ESRI Tapestry segmentation system that classifies U.S. neighborhoods into 67 unique segments based on their demographic and socioeconomic characteristics. These 67 segments are grouped within 14 larger "LifeModes" that have commonalities based on lifestyle and life stage. Our dataset contains variables denoting the dominant Tapestry segments within each U.S. county, along with annual Lyme disease incidence rates from 2000 through 2017, and the average incidence over these 18 years. K-means clustering was used to cluster counties based on yearly incidence rates for the years 2000-2017. We used analysis of variance (ANOVA) statistical testing to determine the association between Lyme disease incidence and LifeModes. We further determined that the LifeModes Affluent Estates, Upscale Avenues, GenXurban, and Cozy Country Living were associated with higher Lyme disease risk based on the results of analysis of means (ANOM) and Tukey's post hoc test, indicating that one of these LifeModes is the LifeMode with the greatest Lyme disease incidence rate. We further conducted trait analysis of the high-risk LifeModes to see which traits were related to higher Lyme disease incidence. Due to the extreme regional nature of Lyme disease incidence, we carried out our national-level analysis at the regional level. Significant differences were detected in incidence rates and LifeModes in individual regions. We mapped Lyme disease incidence with associated LifeModes in the Northeast, Southeast, Midcontinent, Rocky Mountain, and Southwest regions to reflect the location-dependent nature of the relationship between lifestyle and Lyme disease.

A Generalized Additive Model Correlating Blacklegged Ticks With White-Tailed Deer Density, Temperature, and Humidity in Maine, USA, 1990-2013

Geographical range expansions of blacklegged tick [Ixodes scapularis Say (Acari: Ixodidae)] populations over time in the United States have been attributed to a mosaic of factors including 20th century reforestation followed by suburbanization, burgeoning populations of the white-tailed deer [Odocoileus virginianus Zimmerman (Artiodactyla: Cervidae)], and, at the northern edge of I. scapularis' range, climate change. Maine, a high Lyme disease incidence state, has been experiencing warmer and shorter winter seasons, and relatively more so in its northern tier. Maine served as a case study to investigate the interacting impacts of deer and seasonal climatology on the spatial and temporal distribution of I. scapularis. A passive tick surveillance dataset indexed abundance of I. scapularis nymphs for the state, 1990-2013. With Maine's wildlife management districts as the spatial unit, we used a generalized additive model to assess linear and nonlinear relationships between I. scapularis nymph abundance and predictors. Nymph submission rate increased with increasing deer densities up to ~5 deer/km2 (13 deer/mi2), but beyond this threshold did not vary with deer density. This corroborated the idea of a saturating relationship between I. scapularis and deer density. Nymphs also were associated with warmer minimum winter temperatures, earlier degree-day accumulation, and higher relative humidity. However, nymph abundance only increased with warmer winters and degree-day accumulation where deer density exceeded ~2 deer/km2 (~6/mi2). Anticipated increases in I. scapularis in the northern tier could be partially mitigated through deer herd management.

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.

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.

Using volunteered observations to map human exposure to ticks

Lyme borreliosis (LB) is the most prevalent tick-borne disease in Europe and its incidence has steadily increased over the last two decades. In the Netherlands alone, more than 20,000 citizens are affected by LB each year. Because of this, two Dutch citizen science projects were started to monitor tick bites. Both projects have collected nearly 50,000 geo-located tick bite reports over the period 2006–2016. The number of tick bite reports per area unit is a proxy of tick bite risk. This risk can also be modelled as the result of the interaction of hazard (e.g. tick activity) and human exposure (e.g. outdoor recreational activities). Multiple studies have focused on quantifying tick hazard. However, quantifying human exposure is a harder task. In this work, we make a first step to map human exposure to ticks by combining tick bite reports with a tick hazard model. Our results show human exposure to tick bites in all forested areas of the Netherlands. This information could facilitate the cooperation between public health specialists and forest managers to create better mitigation campaigns for tick-borne diseases, and it could also support the design of improved plans for ecosystem management.

Modelling and mapping tick dynamics using volunteered observations

BACKGROUND

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014.

METHOD

Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT.

RESULTS

We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level.

CONCLUSIONS

This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

GIS and Remote Sensing Use in the Exploration of Lyme Disease Epidemiology

Given the relatively recent recognition of Lyme disease (LD) by CDC in 1990 as a nationally notifiable infectious condition, the rise of reported human cases every year argues for a better understanding of its geographic scope. The aim of this inquiry was to explore research conducted on spatiotemporal patterns of Lyme disease in order to identify strategies for implementing vector and reservoir-targeted interventions. The focus of this review is on the use of GIS-based methods to study populations of the reservoir hosts, vectors and humans in addition to the spatiotemporal interactions between these populations. New GIS-based studies are monitoring occurrence at the macro-level, and helping pinpoint areas of occurrence at the micro-level, where spread within populations of reservoir hosts, clusters of infected ticks and tick to human transmission may be better understood.

Increasing Residential Proximity of Lyme Borreliosis Cases to High-Risk Habitats: A Retrospective Study in Central Bohemia, the Czech Republic, 1987-2010

An analysis of historical data on Lyme borreliosis in Central Bohemia between 1987-2010 has revealed that the rate of peri-domestic exposure, the proximity of patients' residences to high-risk habitats, and the number of disease cases have been interdependent variables and that their common upturn can be dated back to the start of the 1990s or earlier. The data indicate that the disease rise is attributable to translocation of part of the at-risk population nearer to natural environments, rather than to mere intensification of people's peri-domestic exposure at existing residential locations, or changes in the natural environment itself.

Scouts, forests, and ticks: Impact of landscapes on human-tick contacts

Just as with forest workers or people practicing outdoor recreational activities, scouts are at high risk for tick bites and tick-borne infections. The risk of a tick bite is shaped not only by environmental and climatic factors but also by land management. The aim of this study was to assess which environmental conditions favour scout-tick contacts, and thus to better understand how these factors and their interactions influence the two components of risk: hazard (related to vector and host ecology) and exposure of humans to disease vectors. A survey was conducted in the summer of 2009 on the incidence of tick bites in scout camps taking place in southern Belgium. Joint effects of landscape composition and configuration, weather, climate, forest and wildlife management were examined using a multiple gamma regression with a log link. The landscape was characterized by buffers of varying sizes around the camps using a detailed land use map, and accounting for climate and weather variables. Landscape composition and configuration had a significant influence on scout-tick contacts: the risk was high when the camp was surrounded by a low proportion of arable land and situated in a complex and fragmented landscape. The distance to the nearest forest patch, the composition of the forest ecotone as well as weather and climatic factors were all significantly associated with scout-tick contacts. Both hazard- and exposure-related variables significantly contributed to the frequency of scout-tick contact. Our results show that environmental conditions favour scout-tick contacts. For example, we emphasize the impact of accessibility of environments suitable for ticks on the risk of contact. We also highlight the significant effect of both hazard and exposure. Our results are consistent with current knowledge, but further investigations on the effect of forest management, e.g. through its impact on forest structure, on the tick-host-pathogen system, and on humans exposure, is required.

Ixodes ricinus and Its Transmitted Pathogens in Urban and Peri-Urban Areas in Europe: New Hazards and Relevance for Public Health

Tick-borne diseases represent major public and animal health issues worldwide. Ixodes ricinus, primarily associated with deciduous and mixed forests, is the principal vector of causative agents of viral, bacterial, and protozoan zoonotic diseases in Europe. Recently, abundant tick populations have been observed in European urban green areas, which are of public health relevance due to the exposure of humans and domesticated animals to potentially infected ticks. In urban habitats, small and medium-sized mammals, birds, companion animals (dogs and cats), and larger mammals (roe deer and wild boar) play a role in maintenance of tick populations and as reservoirs of tick-borne pathogens. Presence of ticks infected with tick-borne encephalitis virus and high prevalence of ticks infected with Borrelia burgdorferi s.l., causing Lyme borreliosis, have been reported from urbanized areas in Europe. Emerging pathogens, including bacteria of the order Rickettsiales (Anaplasma phagocytophilum, "Candidatus Neoehrlichia mikurensis," Rickettsia helvetica, and R. monacensis), Borrelia miyamotoi, and protozoans (Babesia divergens, B. venatorum, and B. microti) have also been detected in urban tick populations. Understanding the ecology of ticks and their associations with hosts in a European urbanized environment is crucial to quantify parameters necessary for risk pre-assessment and identification of public health strategies for control and prevention of tick-borne diseases.

Ixodes ricinus and Its Transmitted Pathogens in Urban and Peri-Urban Areas in Europe: New Hazards and Relevance for Public Health

Tick-borne diseases represent major public and animal health issues worldwide. Ixodes ricinus, primarily associated with deciduous and mixed forests, is the principal vector of causative agents of viral, bacterial, and protozoan zoonotic diseases in Europe. Recently, abundant tick populations have been observed in European urban green areas, which are of public health relevance due to the exposure of humans and domesticated animals to potentially infected ticks. In urban habitats, small and medium-sized mammals, birds, companion animals (dogs and cats), and larger mammals (roe deer and wild boar) play a role in maintenance of tick populations and as reservoirs of tick-borne pathogens. Presence of ticks infected with tick-borne encephalitis virus and high prevalence of ticks infected with Borrelia burgdorferi s.l., causing Lyme borreliosis, have been reported from urbanized areas in Europe. Emerging pathogens, including bacteria of the order Rickettsiales (Anaplasma phagocytophilum, "Candidatus Neoehrlichia mikurensis," Rickettsia helvetica, and R. monacensis), Borrelia miyamotoi, and protozoans (Babesia divergens, B. venatorum, and B. microti) have also been detected in urban tick populations. Understanding the ecology of ticks and their associations with hosts in a European urbanized environment is crucial to quantify parameters necessary for risk pre-assessment and identification of public health strategies for control and prevention of tick-borne diseases.