High-resolution prediction models for Rhipicephalus microplus and Amblyomma cajennense s.l. ticks affecting cattle and their spatial distribution in continental Ecuador using bioclimatic factors.

In Ecuador, the main tick species affecting cattle are Rhipicephalus microplus and Amblyomma cajennense sensu lato. Understanding their spatial distribution is crucial. To assess their distribution, data from 2895 farms visited between 2012 and 2017 were utilized. Ticks were collected during animal inspections, with each farm's location georeferenced. Bioclimatic variables and vapor pressure deficit data were obtained from Climatologies at High resolution for the Earth´s Land Surface Areas (CHELSA) dataset. They were overlaid to develop predictive maps for each species using Random Forest (RF) models. The cross-validation results for RF prediction models showed high accuracy for both R. microplus and A. cajennense s.l. presence with values of accuracy = 0.97 and 0.98, sensitivity = 0.96 and 0.99, and specificity = 0.96 and 0.93, respectively. A carefully selected subset of bioclimatic variables was used to describe the presence of each tick species. Higher levels of precipitation had positive effect on the presence of R. microplus but a negative effect on A. cajennense s.l. In contrast, isothermality (BIO3) was more important for the presence of A. cajennense s.l. compared to R. microplus. As a result, R. microplus had a broader distribution across the country, while A. cajennense s.l. was mainly found in coastal areas with evident seasonality. The coexistence of both species in some regions could be attributed to transitional zones, whereas high altitudes limited tick presence. This information can aid in developing appropriate tick management plans, particularly considering A. cajennense s.l.'s broad host range species and R. microplus's specificity for cattle. Moreover, the predictive models can identify areas at risk of associated challenging hemoparasite, requiring special attention and mitigation measures.

Integrating learning into animal range dynamics under rapid human-induced environmental change.

Human-induced rapid environmental change (HIREC) is creating environments deviating considerably from natural habitats in which species evolved. Concurrently, climate warming is pushing species' climatic envelopes to geographic regions that offer novel ecological conditions. The persistence of species is likely affected by the interplay between the degree of ecological novelty and phenotypic plasticity, which in turn may shape an organism's range-shifting ability. Current modelling approaches that forecast animal ranges are characterized by a static representation of the relationship between habitat use and fitness, which may bias predictions under conditions imposed by HIREC. We argue that accounting for dynamic species-resource relationships can increase the ecological realism of range shift predictions. Our rationale builds on the concepts of ecological fitting, the process whereby individuals form successful novel biotic associations based on the suite of traits they carry at the time of encountering the novel condition, and behavioural plasticity, in particular learning. These concepts have revolutionized our view on fitness in novel ecological settings, and the way these processes may influence species ranges under HIREC. We have integrated them into a model of range expansion as a conceptual proof of principle highlighting the potentially substantial role of learning ability in range shifts under HIREC.

Widespread acaricide resistance and multi-resistance in Rhipicephalus microplus in Ecuador and associated environmental and management risk factors.

Rhipicephalus microplus is a cattle tick widely distributed in tropical and subtropical areas. Various acaricides are used and applied to control the ticks, but resistance is common. The objectives of this study were to evaluate the spatial distribution of resistance to the most commonly applied acaricides (amitraz, ivermectin, and alpha-cypermethrin) in ticks and assess potential risk factors associated with tick resistance in a strip between ±0.5° latitude of the continental part of Ecuador. Larval package tests were used to evaluate the level of acaricide resistance in 96 cattle farms. The association between 11 farm management and 8 ecological variables and acaricide resistance and multi-resistance was evaluated. Dose-response models were used to study the level of resistance. 72 % (69/96), 70 % (67/96), and 64 % (61/96) of farms had ticks resistant to amitraz, ivermectin, and alpha-cypermethrin, respectively. Multi-resistance was also widespread. Larger herds and dairy farms had a significantly higher probability of resistance for three commonly used acaricides. Environmental factors related to rainfall were also associated with acaricidal resistance presence. Ivermectin resistance was associated with use of the acaricide (OR = 8.9909; 7.7519-10.2300), mean temperature (OR = 1.3205;1.0742-1.6799)), and inversely associated with paddock rotation (OR = 0.1753; 0.0294-0.7836), and precipitation of the wettest month (BIO13) (OR = 0.9903; 0.9839-0.9957); amitraz with use of the acaricide (OR = 4.3934; 3.3679-5.4188), precipitation seasonality (BIO15) (OR=0.9742; 0.9542-0.9925), and precipitation (OR = 0.9995; 0.9994-0.9999); and alpha-cypermethrin with precipitation (OR=0.9995; 0.9990-0.9999) and use of the acaricide (OR = 14.4597; 13.4343-15.4852). In conclusion, acaricide resistance was widespread in our study area. Better-integrated tick management and environmentally friendly control strategies are required to reduce the use of acaricides while limiting tick-associated damage in herds.

The Effect of Habitat on Insect Movements: Experimental Evidence from Wild-Caught Butterflies.

There is broad evidence that the main driver of the ongoing biodiversity crisis is land-use change, which reduces and fragments habitats. The consequence of habitat fragmentation on behavioural responses of fitness-related traits in insects have been so far understudied. In herbivorous insects, oviposition-related behaviours determine access to larval food, and the fate of the next generation. We present a pilot study to assess differences in behaviours related to movement and oviposition in Limenitis camilla butterflies from Wallonia (Belgium), one of the most fragmented regions in Europe. We first quantified variation in functional habitat connectivity across Wallonia and found that fragmented habitats had more abundant, but less evenly distributed host plants of L. camilla. Secondly, we quantified the behaviours of field-caught L. camilla females originating from habitats with contrasted landscape connectivity in an outdoor experimental setting. We found differences in behaviours related to flight investment: butterflies from fragmented woodlands spent more time in departing flight, which we associated with dispersal, than butterflies from homogenous woodlands. Although results from this study should be interpreted with caution given the limited sample size, they provide valuable insights for the advancement of behavioural research that aims to assess the effects of global changes on insects.

Non-response bias in the analysis of the association between mental health and the urban environment: a cross-sectional study in Brussels, Belgium.

BACKGROUND: This paper aims at analysing the impact of partial non-response in the association between urban environment and mental health in Brussels. The potential threats of the partial non-response are biases in survey estimates and statistics. The effect of non-response on statistical associations is often overlooked and evidence in the research literature is lacking. METHODS: Data from the Belgian Health Interview Survey 2008 and 2013 were used. The association between non-response and potential determinants was explored through logistic regressions. RESULTS: Participants with low income, low educational levels, lower or higher age or in households with children were less likely to respond. When adjusting for socio-economic variables, non-response was higher in areas which are less vegetated, more polluted or more urbanised. Because the determinants of non-response and depressive disorders were similar, it is reasonable to assume that there will be more people with mental health problems among the non-respondents. And because more non-responses were found in low vegetation areas, the protective association between green spaces and mental health may be underestimated. CONCLUSION: Our capacity to measure the association between the urban environment and health is affected by non-response in surveys. The non-random spatial and socio-economic distribution of this bias affects the research findings.

An economic evaluation of cattle tick acaricide-resistances and the financial losses in subtropical dairy farms of Ecuador: A farm system approach.

Estimates of economic losses in cattle due to tick infestations in subtropical areas are limited, such as in Ecuador. Ticks affect animal production and health, but those direct effects are difficult to estimate since financial exercises carried out in farms consider both costs of the inputs and revenues. This study aims to quantify the costs of inputs involved in milk production and to know the role of acaricide treatment in the production costs on dairy farms in subtropical zones using a farming system approach. Regression and classification trees were used to study the relationship between tick control, acaricide resistance and the presence of high level of tick infestation in the farm system. Even though there was no significant direct association between high levels of tick infestation and the presence of acaricide resistance in ticks, a more complex structure for resistances operates in the manifestation of high tick infestation involving levels of farm technology and no acaricide resistance. Farms with higher levels of technology allocate a lower percentage of sanitary expenses to control ticks (13.41%) in comparison to semi-technified (23.97%) and non-technified farms (32.49%). Likewise, more technified and bigger herds have a lower annual expenditure on acaricide treatment (1.30% of the production budget equivalent to 8.46 USD per animal) compared to non-technified farms where it can represent more than 2.74% of the production budget and where the absence of cypermethrin resistance increases the treatment cost to 19.50 USS per animal annually. These results can motivate the development of information campaigns and control programmes targeted to the reality of small and medium farms that are the most affected in terms of the money they invest in controlling ticks.

Potential risk sites and their relationship with dengue cases, Campinas municipality, Southeast Brazil.

BACKGROUND: Among the main activities of dengue and vector control recommended by the Ministry of Health of Brazil is the inspection and monitoring of properties identified as Strategic Points (SPs) and Special Buildings (SBs). SPs are properties associated to hazard, where there is a concentration of suitable egg-laying containers for Aedes aegypti mosquitoes, while SBs have greater importance for human exposure to the dengue virus. OBJECTIVES: To investigate the effect of characteristics of the urban landscape on dengue incidence. Specifically, we tested if SPs and SBs affect dengue case distribution in Campinas, and if they do, if they affect the risk differently. We considered the period from 2013 to 2016. METHODS: We tested whether dengue cases were more numerous than expected in the vicinity of SPs and SBs, putative sources of risk, using the Negative Binomial models. We also tested the existence of a gradient in incidence with increasing distance to SPs and SBs by using Stone's test. RESULTS: The Rate Ratios (RR) values were always higher closer to the SPs and SBs, and these values tended to decrease as distance from these sources increased. In general, RR values greater than one, which indicates a higher risk, were associated to the closest buffers from the SPs/SBs properties, until nearly 550 meters for the SPs and 650 meters for the SBs. Stone's test results indicated that for all years considered, there was a correlation between the distance from the SPs/SBs and dengue cases occurrences, except for SBs from 2016. For SPs the relationship is stronger than for SBs. DISCUSSION: Results are coherent with other studies which found that these properties contribute to an increased risk of dengue transmission. We emphasize the importance of public agents' survey work and the importance to keep and improve the inspections in SPs/SBs recorded in Campinas.

dynamAedes: a unified modelling framework for invasive Aedes mosquitoes.

Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers because of their capacity to transmit viruses that affect humans. Some of these species were brought outside their native range by means of trade and tourism and then colonised new regions thanks to a unique combination of eco-physiological traits. Considering mosquito physiological and behavioural traits to understand and predict their population dynamics is thus a crucial step in developing strategies to mitigate the local densities of invasive Aedes populations. Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data. Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on the species' biology which could be applied to the management of invasive Aedes populations as well as to more theoretical ecological inquiries.

Habitat suitability map of Ixodes ricinus 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 Associated Decision and Management Factors on Cattle Tick Level of Infestation in Two Tropical Areas of Ecuador.

Decision-making on tick control practices is linked to the level of knowledge about livestock farming and to the social context in which individuals practice them. Tick infestation is one of the main problems in tropical livestock production. The objective of this study was to characterize tick-control related practices in two tropical livestock areas and their potential association with the level of tick infestation. A total of 139 farms were included in this survey. To determine this association, a multivariate logistic regression model was used. A stepwise model selection procedure was used and model validation was tested. Cattle husbandry as a main activity, the use of external paddocks, the use of amitraz, and the lack of mechanization on the farm were related with high tick infestation. On the other hand, owner involvement in the preparation of acaricide solution was identified as a protective factor against high tick infestation. At animal level, age (old), body condition status (thin), and lactation were also associated with high tick infestations, while Bos primigenius indicus cattle and their crosses reduced the probability of high tick infestations. The factors studied, such as herd size, education level of the owners, and veterinary guidance, varied from farm to farm. Nonetheless, these differences did not generate changes in the level of tick infestation. According to the area under the receiver operating characteristic curve (AUC-ROC), the model at farm level predicts a high level of infestation, with an accuracy of 72.00% and high sensitivity. In addition, at animal level, crossbreeding with indicus cattle and breeding selection for host resistance will be useful against high tick infestation. Likewise, the implementation of programs of capacitation and research on tick control for farmers, cowboys, and vets in these areas is necessary.

Modelling habitat suitability of the invasive tick Rhipicephalus microplus in West Africa.

Ticks have medical and economic importance due to their ability to transmit pathogens to humans and animals. In tropical and sub-tropical countries, tick-borne diseases (TBD) are among the most important diseases affecting livestock and humans. The fast spread of ticks and TBD requires a quick development and application of efficient prevention and/or control programs. Therefore, prior investigations on TBD and related vectors epidemiology, for instance, through accurate epidemiological models, are mandatory. This study aims to develop models to forecast suitable habitat for Rhipicephalus microplus distribution in West Africa. Tick occurrences were assembled from 10 different studies carried out in six West African countries in the past decade. Six statistical models (maximum entropy in a single model and generalised linear model, generalised additive model, random forest, boosted regression tree and support vector machine model in an ensemble model) were applied and compared to predict the habitat suitability of R. microplus distribution in West Africa. Each model was evaluated with the area under the receiver operating characteristic curve (AUC), the true skill statistic (TSS) and the Boyce index (BI). The selected models had good performance according to their AUC (above .8), TSS (above .7) and BI (above .8). Temperature played a key role in MaxEnt model, whereas normalised difference vegetation index (NDVI) was the most important variable in the ensemble model. The model predictions showed coastal countries of West Africa as more suitable for R. microplus. However, some Sahelian areas seems also favourable. We stress the importance of vector surveillance and control in countries that have not yet detected R. microplus but are in the areas predicted to host suitable habitat. Indeed, awareness-raising and training of different stakeholders must be reinforced for better prevention and control of this tick in these different countries according to their status.

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.

Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence-Belgium as a study case.

BACKGROUND: The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection. METHODS: To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio-temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence. RESULTS: Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence. CONCLUSION: Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.

Poultry farm distribution models developed along a gradient of intensification.

Efficient planning of measures limiting epidemic spread requires information on farm locations and sizes (number of animals per farm). However, such data are rarely available. The intensification process which is operating in most low- and middle-income countries (LMICs), comes together with a spatial clustering of farms, a characteristic epidemiological models are sensitive to. We developed farm distribution models predicting both the location and the number of animals per farm, while accounting for the spatial clustering of farms in data-poor countries, using poultry production as an example. We selected four countries, Nigeria, Thailand, Argentina and Belgium, along a gradient of intensification expressed by the per capita Gross Domestic Product (GDP). First, we investigated the distribution of chicken farms along the spectrum of intensification. Second, we built farm distribution models (FDM) based on censuses of commercial farms of each of the four countries, using point pattern and random forest models. As an external validation, we predicted farm locations and sizes in Bangladesh. The number of chicken per farm increased gradually in line with the gradient of GDP per capita in the following order: Nigeria, Thailand, Argentina and Belgium. Interestingly, we did not find such a gradient for farm clustering. Our modelling procedure could only partly reproduce the observed datasets in each of the four sample countries in internal validation. However, in the external validation, the clustering of farms could not be reproduced and the spatial predictors poorly explained the number and location of farms and farm sizes in Bangladesh. Further improvements of the methodology should explore other covariates of the intensity of farms and farm sizes, as well as improvements of the methodology. Structural transformation, economic development and environmental conditions are essential characteristics to consider for an extrapolation of our FDM procedure, as generalisation appeared challenging. We believe the FDM procedure could ultimately be used as a predictive tool in data-poor countries.

SARS-CoV-2 emergence and diffusion: a new disease manifesting human-environment interactions and a global geography of health.

SARS-CoV-2, and the disease it causes, COVID-19, is sweeping through the world, disrupting human activities everywhere. The consequences of this on-going event on societies are yet to be fully understood. The emergence of SARS-CoV-2 illustrates how human-environment interaction should be framing research on pathogen spillover. Furthermore, the geography of human contacts at various scales in our globalized and urbanized world affects its diffusion. Both elements plead for a robust backbone of geography of health, including land use, to understanding disease emergence and diffusion.

Spatial tick bite exposure and associated risk factors in Scandinavia.

Tick-borne diseases are emerging and re-emerging threats causing public health concerns in Europe and North America. Prevention and control requires understanding of human exposure and behaviour. The aim was to measure exposure to tick bites across Scandinavia, its spatial distribution and the associated risk factors. Methods We sent a web-based survey to a randomly chosen population and analysed answers by Principal Component Analysis and Chi-Square. Individual responses were aggregated at the municipality level to assess the spatial distribution of bites. Results Nearly 60% of adults reported bites at low levels (1-5 bites); however, the majority were not in their resident municipality. We found two spatial profiles: In their home municipalities, people were most often bitten in less, but not the least, urbanized areas. When visiting other municipalities, people were most frequently bitten in peri-urban areas. Running/walking in the forest, gardening, and paddling/rowing were activities most strongly associated with bites. Conclusion Tick bites affect the entire Scandinavian population, with a higher risk in Sweden compared to Denmark and Norway. The frequency of observation of ticks in the environment or on pets might be used as a proxy for the actual risk of exposure to tick bites. Our results indicates that urban-dwelling outdoor enthusiasts and inhabitants of rural areas must be equally targeted for prevention campaigns.

Downscaling livestock census data using multivariate predictive models: Sensitivity to modifiable areal unit problem.

The analysis of census data aggregated by administrative units introduces a statistical bias known as the modifiable areal unit problem (MAUP). Previous researches have mostly assessed the effect of MAUP on upscaling models. The present study contributes to clarify the effects of MAUP on the downscaling methodologies, highlighting how a priori choices of scales and shapes could influence the results. We aggregated chicken and duck fine-resolution census in Thailand, using three administrative census levels in regular and irregular shapes. We then disaggregated the data within the Gridded Livestock of the World analytical framework, sampling predictors in two different ways. A sensitivity analysis on Pearson's r correlation statistics and RMSE was carried out to understand how size and shapes of the response variables affect the goodness-of-fit and downscaling performances. We showed that scale, rather than shapes and sampling methods, affected downscaling precision, suggesting that training the model using the finest administrative level available is preferable. Moreover, datasets showing non-homogeneous distribution but instead spatial clustering seemed less affected by MAUP, yielding higher Pearson's r values and lower RMSE compared to a more spatially homogenous dataset. Implementing aggregation sensitivity analysis in spatial studies could help to interpret complex results and disseminate robust products.

Lyme Disease Risks in Europe under Multiple Uncertain Drivers of Change.

BACKGROUND: Debates over whether climate change could lead to the amplification of Lyme disease (LD) risk in the future have received much attention. Although recent large-scale disease mapping studies project an overall increase in Lyme disease risk as the climate warms, such conclusions are based on climate-driven models in which other drivers of change, such as land-use/cover and host population distribution, are less considered. OBJECTIVES: The main objectives were to project the likely future ecological risk patterns of LD in Europe under different assumptions about future socioeconomic and climate conditions and to explore similarity and uncertainty in the projected risks. METHODS: An integrative, spatially explicit modeling study of the ecological risk patterns of LD in Europe was conducted by applying recent advances in process-based modeling of tick-borne diseases, species distribution mapping, and scenarios of land-use/cover change. We drove the model with stakeholder-driven, integrated scenarios of plausible future socioeconomic and climate change [the Shared Socioeconomic Pathway (SSPs) combined with the Representative Concentration Pathways (RCPs)]. RESULTS: The model projections suggest that future temperature increases may not always amplify LD risk: Low emissions scenarios (RCP2.6) combined with a sustainability socioeconomic scenario (SSP1) resulted in reduced LD risk. The greatest increase in risk was projected under intermediate (RCP4.5) rather than high-end (RCP8.5) climate change scenarios. Climate and land-use change were projected to have different roles in shaping the future regional dynamics of risk, with climate warming being likely to cause risk expansion in northern Europe and conversion of forest to agriculture being likely to limit risk in southern Europe. CONCLUSIONS: Projected regional differences in LD risk resulted from mixed effects of temperature, land use, and host distributions, suggesting region-specific and cross-sectoral foci for LD risk management policy. The integrated model provides an improved explanatory tool for the system mechanisms of LD pathogen transmission and how pathogen transmission could respond to combined socioeconomic and climate changes. https://doi.org/10.1289/EHP4615.

Spatial dynamics of a zoonotic orthohantavirus disease through heterogenous data on rodents, rodent infections, and human disease.

Zoonotic diseases are challenging to study from the ecological point of view as, broadly speaking, datasets tend to be either detailed on a small spatial extent, or coarse on a large spatial extent. Also, there are many ways to assess zoonotic disease transmission systems, from pathogens to hosts to humans. We explore the complementarity of datasets considering the pathogen in its host, the host and human cases in the context of Puumala orthohantavirus infection in Germany. We selected relevant environmental predictors using a conceptual framework based on resource-based habitats. This framework assesses the functions, and associated environmental resources of the pathogen and associated host. A resource-based habitat framework supports variable selection and result interpretation. Multiplying 'keyholes' to view a zoonotic disease transmission system is valuable, but requires a strong conceptual framework to select and interpret environmental explanatory variables. This study highlights the usefulness of a structured, ecology-based approach to study drivers of zoonotic diseases at the level of virus, host, and human - not only for PUUV but also for other zoonotic pathogens. Our results show that human disease cases are best explained by a combination of variables related to zoonotic pathogen circulation and human exposure.