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 <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 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.

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.

Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.

Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.

Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. We present a new version of the Gridded Livestock of the World (GLW 3) database, reflecting the most recently compiled and harmonized subnational livestock distribution data for 2010. GLW 3 provides global population densities of cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in each land pixel at a spatial resolution of 0.083333 decimal degrees (approximately 10 km at the equator). They are accompanied by detailed metadata on the year, spatial resolution and source of the input census data. Two versions of each species distribution are produced. In the first version, livestock numbers are disaggregated within census polygons according to weights established by statistical models using high resolution spatial covariates (dasymetric weighting). In the second version, animal numbers are distributed homogeneously with equal densities within their census polygons (areal weighting) to provide spatial data layers free of any assumptions linking them to other spatial variables.

Seroprevalence of Borrelia burgdorferi in Belgian forestry workers and associated risk factors

Background

As forest is the preferred environment for ticks, forestry workers are exposed to tick bites and tick-borne diseases. We assessed the seroprevalence of anti-Borrelia burgdorferi (Bb) antibodies and investigated, using an integrated landscape approach, the individual and environmental factors associated with the seroprevalence of Bb in Belgian forestry workers, a high-risk group in Belgium.

Methods

A group of 310 Belgian forest workers was examined to assess the seroprevalence of anti-Borrelia IgG antibodies. Using principal component analysis and binary logistic regression, the joint effects of individual characteristics and environmental characteristics were examined.

Results

Sixty-seven of the 310 workers were seropositive for Lyme disease (LD), leading to a seroprevalence of 21.6%. The seroprevalence was higher among forest workers visiting forests more frequently (P = 0.003) or who reported over 100 tick bites (P-value < 0.001). The intensity of tick bites and the use of protection measures against tick bites have a positive impact on LD seroprevalence while the quantity of shadow from trees at ground level had a negative one.

Conclusions

This study showed that forest workers are a population at risk for LD and, by extension, at risk for various tick-borne diseases. In addition to the role of the environment, our results also showed the importance of considering exposure when predicting the risk of infection by Bb.

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

During 1999–2012, 77% of the cases of tick-borne encephalitis (TBE) were recorded in two out of 16 Polish provinces. However, historical data, mostly from national serosurveys, suggest that the disease could be undetected in many areas. The aim of this study was to identify which routinely-measured meteorological, environmental, and socio-economic factors are associated to TBE human risk across Poland, with a particular focus on areas reporting few cases, but where serosurveys suggest higher incidence. We fitted a zero-inflated Poisson model using data on TBE incidence recorded in 108 NUTS-5 administrative units in high-risk areas over the period 1999–2012. Subsequently we applied the best fitting model to all Polish municipalities. Keeping the remaining variables constant, the predicted rate increased with the increase of air temperature over the previous 10–20 days, precipitation over the previous 20–30 days, in forestation, forest edge density, forest road density, and unemployment. The predicted rate decreased with increasing distance from forests. The map of predicted rates was consistent with the established risk areas. It predicted, however, high rates in provinces considered TBE-free. We recommend raising awareness among physicians working in the predicted high-risk areas and considering routine use of household animal surveys for risk mapping.

Time trend of clinical cases of Lyme disease in two hospitals in Belgium, 2000-2013

BACKGROUND

As several studies indicated an increase in Lyme disease (LD), notably in neighbouring countries, concerns have arisen regarding the evolution of Lyme disease in Belgium. In order to confirm or infirm the increase of LD in Belgium, we focused on hospital admissions of patients diagnosed with LD between 2000 and 2013 based on hospital admission databases from two hospitals in Belgium.

METHODS

Hospital databases are a stable recording system. We did a retrospective analysis of the medical files of patients hospitalized with Lyme disease in two Belgian hospitals between 2000 and 2013.

RESULTS

The annual number of cases of LD for the two studied Belgian hospitals remained stable between 2000 and 2013, ranging from 1 for the Cliniques universitaires Saint-Luc to 15 for the the Clinique Saint-Pierre. No increasing trend were noted in the estimated annual incidence rate but the average estimated annual incidence rate was higher for the hospital Saint-Pierre (8.1 ± 3.7 per 100,000 inhabitants) than Saint-Luc (2.2 ± 1.5 per 100,000 inhabitants). The number of hospital cases of LD peaked between June and November.

CONCLUSIONS

Based on hospital admissions with LD, no increasing trend was observed for the period 2000-2013 in the two studied Belgian hospitals. This is in line with other studies carried out in Belgium.

The current status of resistance to alpha-cypermethrin, ivermectin, and amitraz of the cattle tick (Rhipicephalus microplus) in Ecuador

Rhipicephalus microplus is widely distributed in tropical and subtropical areas of the world where livestock is a principal activity with great veterinary and economic importance. In Ecuador, this hematophagous ectoparasite has been observed between 0 and 2600 masl. One of the main tick control measures is the use of acaricides, which have been indiscriminately used worldwide and in Ecuador. In this country, no studies on acaricide resistance in Rhipicephalus microplus have been published. The current study aims to characterise the level of resistance of R. microplus against three main acaricides commonly used in Ecuador i.e. amitraz, alpha-cypermethrin and ivermectin to determine the level and pattern of dose-responses for R. microplus in 12 field populations (farms). The level of acaricide resistance was evaluated using three different bioassays: adult immersion test (AIT), larval package test (LPT) and larval immersion test (LIT), as recommended by the FAO. The predictive dose-responses were analysed by binomial logistics regression of the larval survival rate (resistance). In general, we found resistance of 67% for amitraz; 50% for alpha-cypermethrin and from 25 to 42% for ivermectin in the twelve field populations analysed. Resistance levels were studied in larval and adult bioassays, respectively, which were slightly modified for this study. For larval bioassays based on corrected mortality i.e. high (above 51%), medium (21–50%) and low (11–20%) resistance, percentages less than 10% were considered as susceptible. For the adult test, two resistance levels were used i.e. high (more than 76%) and medium (51 to 75%) resistance. Percentages lower than 50% were considered as susceptible. In this context, for larval bioassays, amitraz showed 21%, 38% and 8% for high, medium and low resistance, respectively. Alpha-cypermethrin presented 8%, 4 and 38% for high, medium and low resistance, respectively. Ivermectin presented 8%, 25% and 8% for high, medium and low resistance, respectively. For adult tests with amitraz 50% and 17% of the field populations showed average and high resistance, with evidences of average resistance to alpha-cypermethrin in 50% of the samples and average resistance against ivermectin in 25% of the farms. No statistical difference amongst the three bioassays was found and acaricide resistance was confirmed by logistic regression analysis; hence resistance (dose-responses) in each field populations differed, depending on the choice of the acaricide, frequent usage, frequency of treatment and farm management. The effective estimated dose needed to eliminate 99% of ticks is higher than dose recommended by the manufacturer. In conclusion, amitraz showed the highest resistance followed by ivermectin and alpha-cypermethrin and reveals differences on resistance in each individual field population. This information is important in order to establish the monitoring of resistance on each farm individually, contributing to the rational use of acaricides included in an integrated control program for R. microplus.

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.

Seroprevalence of Borrelia burgdorferi, Anaplasma phagocytophilum, and Francisella tularensis Infections in Belgium: Results of Three Population-Based Samples

To estimate the seroprevalence of Borrelia burgdorferi (Bb), Anaplasma phagocytophilum (Ap), and Francisella tularensis (Ft) in Belgium, we tested sera from three population-based samples in which exposure to pathogen is assumed to vary: 148 samples from workers professionally exposed, 209 samples from rural blood donors, and 193 samples from urban blood donors. Sera were tested using ELISA or the immunofluorescence assay test. The seroprevalence of Bb was 5.4% in workers professionally exposed, 2.9% in rural blood donors, and 2.6% in urban blood donors, which is similar to other studies. The fraction of negative results decreases significantly from urban blood donors and rural blood donors to workers. Regarding the seroprevalence of Ap, the cutoff titer of 1:64 recommended by the manufacturer may be set too low and produces artificially high seroprevalence rates. Using a cutoff titer of 1:128, the seroprevalence of Ap was estimated at 8.1% for workers professionally exposed, 6.2% for rural blood donors, and 5.7% for urban blood donors. Tularemia sera confirmed the presence of the pathogen in Belgium at 2.0% for workers and 0.5% for rural and urban blood donors. Our study is one of the few providing an estimation of the seroprevalences of Bb, Ap, and Ft in three different populations in Belgium, filling the gap in seroprevalence data among those groups. Our findings provide evidence that the entire Belgian population is exposed to Bb, Ap, and Ft infections, but a higher exposure is noticed for professionals at risk. Education on the risk factors for tick bites and preventive measures for both professionals exposed and the general population is needed.

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

Forest, in particular deciduous forest, is a key element in determining areas with a high probability of tick presence. The way forest is generally monitored may be ill suited to some landscapes where Ixodes ricinus is found, as forest is usually characterised using crisp land cover classes. However, tree vegetation can be found outside of forests and continuous gradations of tree density can be found in a variety of landscapes. In this paper we investigate the probability of tick presence in southern Norway using landscape description based both on land cover classes and continuous data describing the tree cover fraction. Both perspectives on the landscape are significant in the logistic model, indicating that the usual approach based solely on land cover classes may not be comprehensive enough in capturing tick habitat, and characterising the landscape with variables focused on single specific elements may be insufficient.

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.

High Resolution Spatial Analysis of Habitat Preference of Aedes Albopictus (Diptera: Culicidae) in an Urban Environment

Over the past decades, the Asian tiger mosquito (Aedes albopictus (Skuse, 1895)) has emerged in many countries, and it has colonized new environments, including urban areas. The species is a nuisance and a potential vector of several human pathogens, and a better understanding of the habitat preferences of the species is needed for help in successful prevention and control. So far, the habitat preference in urban environments has not been studied in Southern European cities. In this paper, spatial statistical models were used to evaluate the relationship between egg abundances and land cover types on the campus of Sapienza University in Rome, which is taken as an example of a European urban habitat. Predictor variables included land cover types, classified in detail on a high resolution image, as well as solar radiation and month of capture. The models account for repeated measures in the same trap and are adjusted for meteorological circumstances. Vegetation and solar radiation were found to be positively related to the number of eggs. More specifically, trees were positively related to the number of eggs and the relationship with grass was negative. These findings are consistent with the species' known preference for shaded areas. The unexpected positive relationship with solar radiation is amply discussed in the paper. This study represents a first step toward a better understanding of the spatial distribution of Ae. albopictus in urban environments.

Landscape and regional environmental analysis of the spatial distribution of hantavirus human cases in europe

Background: In Europe, the most prevalent hantavirus, Puumala virus, is transmitted by bank voles and causes nephropathia epidemica in human. The European spatial distribution of nephropathia epidemica is investigated here for the first time with a rich set of environmental variables.

Methods: The influence of variables at the landscape and regional level is studied through multilevel logistic regression, and further information on their effects across the different European ecoregions is obtained by comparing an overall niche model (boosted regression trees) with regressions by ecoregion.

Results: The presence of nephropathia epidemica is likely in populated regions with well-connected forests, more intense vegetation activity, low soil water content, mild summers, and cold winters. In these regions, landscapes with a higher proportion of built-up areas in forest ecotones and lower minimum temperature in winter are expected to be more at risk. Climate and forest connectivity have a stronger effect at the regional level. If variables are staying at their current values, the models predict that nephropathia epidemica may know intensification but should not spread (although southern Sweden, the Norwegian coast, and the Netherlands should be kept under watch).

Conclusion: Models indicate that large-scale modeling can lead to a very high predictive power. At large scale, the effect of one variable on disease may follow three response scenarios: the effect may be the same across the entire study area, the effect can change according to the variable value, and the effect can change depending on local specificities. Each of these scenarios impacts large-scale modeling differently.

Species distribution modelling for Rhipicephalus microplus (Acari: Ixodidae) in Benin, West Africa: comparing datasets and modelling algorithms

Rhipicephalus microplus is one of the most widely distributed and economically important ticks, transmitting Babesia bigemina, B. bovis and Anaplasma marginale. It was recently introduced to West Africa on live animals originating from Brazil. Knowing the precise environmental suitability for the tick would allow veterinary health officials to draft vector control strategies for different regions of the country. To test the performance of modelling algorithms and different sets of environmental explanatory variables, species distribution models for this tick species in Benin were developed using generalized linear models, linear discriminant analysis and random forests. The training data for these models were a dataset containing reported absence or presence in 104 farms, randomly selected across Benin. These farms were sampled at the end of the rainy season, which corresponds with an annual peak in tick abundance. Two environmental datasets for the country of Benin were compared: one based on interpolated climate data (WorldClim) and one based on remotely sensed images (MODIS). The pixel size for both environmental datasets was 1 km. Highly suitable areas occurred mainly along the warmer and humid coast extending northwards to central Benin. The northern hot and drier areas were found to be unsuitable. The models developed and tested on data from the entire country were generally found to perform well, having an AUC value greater than 0.92. Although statistically significant, only small differences in accuracy measures were found between the modelling algorithms, or between the environmental datasets. The resulting risk maps differed nonetheless. Models based on interpolated climate suggested gradual variations in habitat suitability, while those based on remotely sensed data indicated a sharper contrast between suitable and unsuitable areas, and a patchy distribution of the suitable areas. Remotely sensed data yielded more spatial detail in the predictions. When computing accuracy measures on a subset of data along the invasion front, the modelling technique Random Forest outperformed the other modelling approaches, and results with MODIS-derived variables were better than those using WorldClim data. The high environmental suitability for R. microplus in the southern half of Benin raises concern at the regional level for animal health, including its potential to substantially alter transmission risk of Babesia bovis. The northern part of Benin appeared overall of low environmental suitability. Continuous surveillance in the transition zone however remains relevant, in relation to important cattle movements in the region, and to the invasive character of R. microplus.

Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks

Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches.

Shaping zoonosis risk: landscape ecology vs. landscape attractiveness for people, the case of tick-borne encephalitis in Sweden

BACKGROUND

In this paper, the hazard and exposure concepts from risk assessment are applied in an innovative approach to understand zoonotic disease risk. Hazard is here related to the landscape ecology determining where the hosts, vectors and pathogens are and, exposure is defined as the attractiveness and accessibility to hazardous areas. Tick-borne encephalitis in Sweden was used as a case study.

METHODS

Three boosted regression tree models are compared: a hazard model, an exposure model and a global model which combines the two approaches.

RESULTS

The global model offers the best predictive power and the most accurate modelling. The highest probabilities were found in easy-to-reach places with high landscape diversity, holiday houses, waterbodies and, well-connected forests of oak, birch or pine, with open-area in their ecotones, a complex shape, numerous clear-cuts and, a variation in tree height.

CONCLUSION

While conditions for access and use of hazardous areas are quite specific to Scandinavia, this study offers promising perspectives to improve our understanding of the distribution of zoonotic and vector-borne diseases in diverse contexts.

Physico-chemical and biological characterization of anopheline mosquito larval habitats (Diptera: Culicidae): implications for malaria control

BACKGROUND

A fundamental understanding of the spatial distribution and ecology of mosquito larvae is essential for effective vector control intervention strategies. In this study, data-driven decision tree models, generalized linear models and ordination analysis were used to identify the most important biotic and abiotic factors that affect the occurrence and abundance of mosquito larvae in Southwest Ethiopia.

METHODS

In total, 220 samples were taken at 180 sampling locations during the years 2010 and 2012. Sampling sites were characterized based on physical, chemical and biological attributes. The predictive performance of decision tree models was evaluated based on correctly classified instances (CCI), Cohen's kappa statistic (κ) and the determination coefficient (R2). A conditional analysis was performed on the regression tree models to test the relation between key environmental and biological parameters and the abundance of mosquito larvae.

RESULTS

The decision tree model developed for anopheline larvae showed a good model performance (CCI = 84 ± 2%, and κ = 0.66 ± 0.04), indicating that the genus has clear habitat requirements. Anopheline mosquito larvae showed a widespread distribution and especially occurred in small human-made aquatic habitats. Water temperature, canopy cover, emergent vegetation cover, and presence of predators and competitors were found to be the main variables determining the abundance and distribution of anopheline larvae. In contrast, anopheline mosquito larvae were found to be less prominently present in permanent larval habitats. This could be attributed to the high abundance and diversity of natural predators and competitors suppressing the mosquito population densities.

CONCLUSIONS

The findings of this study suggest that targeting smaller human-made aquatic habitats could result in effective larval control of anopheline mosquitoes in the study area. Controlling the occurrence of mosquito larvae via drainage of permanent wetlands may not be a good management strategy as it negatively affects the occurrence and abundance of mosquito predators and competitors and promotes an increase in anopheline population densities.

An update on distribution models for Rhipicephalus microplus in West Africa

The cattle tick, Rhipicephalus microplus, which reached the West African region approximately 8 years ago, has established viable populations in Côte d'Ivoire and Benin and spread rapidly from the assumed points of introduction. However, existing maps of its distribution range do not agree on the areas at risk, most probably due to suboptimal modelling approaches. Therefore, we undertook a re-investigation of the potential distribution range based on a high-quality dataset from West Africa that includes information on 104 farms located all over Benin. Focussing on climate suitability and applying advanced modelling, a subset of representative and uncorrelated climate variables was selected and fed into Maxent software to obtain an estimate of climate suitability for West Africa. The resulting map was validated using an independent dataset of 13 farms along the apparent distribution edge. The entire southern part of West Africa (covering southern Nigeria, Benin, Togo and Ghana) features high climate suitability for R. microplus. All of Côte d'Ivoire is inside the distribution range of this tick and the southern rim of Burkina Faso is expected to be suitable for the establishment of R. microplus populations. The validation of the distribution, dated one year after the initial field visit, confirmed the predicted distribution range, although a small number of individuals of R. microplus were found north of the predicted limit. These low numbers might indicate that the climate is not suitable for the establishment of a viable tick population. An alternative explanation is the recent introduction by nomadic cattle herds passing through this location. In this region of the world, it is quite common for cattle owners to lead their livestock over distances of more than 500 km in search of food and water.

Geographic distribution of the invasive cattle tick Rhipicephalus microplus, a country-wide survey in Benin

The cattle tick Rhipicephalus microplus is currently invading the West African region, and little information is available on the spread of this exotic tick in this region. We set out a country-wide field survey to determine its current distribution in Benin. Ticks were collected on cattle from 106 farms selected by random sampling covering all regions of the country. Rhipicephalus annulatus was found on 70 % of all farms, R. decoloratus on 42 %, R. geigyi on 58 %, and R. microplus on 49 %. There is a clear geographic separation between the indigenous Rhipicephalus species and R. microplus. Rhipicephalus annulatus occurs mainly in the northern departments, but it was also observed in lower numbers in locations in the south. The presence of R. decoloratus is limited to the northern region, and in most locations, this tick makes up a small proportion of the collected ticks. The tick R. geigyi tends to be dominant, but occurs only in the four northern departments. The observations concerning R. microplus are entirely different, this species occurs in the southern and central region. The results of this survey confirm the invasive character and displacement properties of R. microplus, since in less than a decade it has colonized more than half of the country and has displaced indigenous ticks of the same genus in many of the sampled locations.

Geographic distribution of the invasive cattle tick Rhipicephalus microplus, a country-wide survey in Benin

The cattle tick Rhipicephalus microplus is currently invading the West African region, and little information is available on the spread of this exotic tick in this region. We set out a country-wide field survey to determine its current distribution in Benin. Ticks were collected on cattle from 106 farms selected by random sampling covering all regions of the country. Rhipicephalus annulatus was found on 70 % of all farms, R. decoloratus on 42 %, R. geigyi on 58 %, and R. microplus on 49 %. There is a clear geographic separation between the indigenous Rhipicephalus species and R. microplus. Rhipicephalus annulatus occurs mainly in the northern departments, but it was also observed in lower numbers in locations in the south. The presence of R. decoloratus is limited to the northern region, and in most locations, this tick makes up a small proportion of the collected ticks. The tick R. geigyi tends to be dominant, but occurs only in the four northern departments. The observations concerning R. microplus are entirely different, this species occurs in the southern and central region. The results of this survey confirm the invasive character and displacement properties of R. microplus, since in less than a decade it has colonized more than half of the country and has displaced indigenous ticks of the same genus in many of the sampled locations.

Modelling zoonotic diseases in humans: comparison of methods for hantavirus in Sweden

Because their distribution usually depends on the presence of more than one species, modelling zoonotic diseases in humans differs from modelling individual species distribution even though the data are similar in nature. Three approaches can be used to model spatial distributions recorded by points: based on presence/absence, presence/available or presence data. Here, we compared one or two of several existing methods for each of these approaches. Human cases of hantavirus infection reported by place of infection between 1991 and 1998 in Sweden were used as a case study. Puumala virus (PUUV), the most common hantavirus in Europe, circulates among bank voles (Myodes glareolus). In northern Sweden, it causes nephropathia epidemica (NE) in humans, a mild form of hemorrhagic fever with renal syndrome.Logistic binomial regression and boosted regression trees were used to model presence and absence data. Presence and available sites (where the disease may occur) were modelled using cross-validated logistic regression. Finally, the ecological niche model MaxEnt, based on presence-only data, was used.In our study, logistic regression had the best predictive power, followed by boosted regression trees, MaxEnt and cross-validated logistic regression. It is also the most statistically reliable but requires absence data. The cross-validated method partly avoids the issue of absence data but requires fastidious calculations. MaxEnt accounts for non-linear responses but the estimators can be complex. The advantages and disadvantages of each method are reviewed.

A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium

Background

Ticks are the most important pathogen vectors in Europe. They are known to be influenced by environmental factors, but these links are usually studied at specific temporal or spatial scales. Focusing on Ixodes ricinus in Belgium, we attempt to bridge the gap between current “single-sided” studies that focus on temporal or spatial variation only. Here, spatial and temporal patterns of ticks are modelled together.

Methods

A multi-level analysis of the Ixodes ricinus patterns in Belgium was performed. Joint effects of weather, habitat quality and hunting on field sampled tick abundance were examined at two levels, namely, sampling level, which is associated with temporal dynamics, and site level, which is related to spatial dynamics. Independent variables were collected from standard weather station records, game management data and remote sensing-based land cover data.

Results

At sampling level, only a marginally significant effect of daily relative humidity and temperature on the abundance of questing nymphs was identified. Average wind speed of seven days prior to the sampling day was found important to both questing nymphs and adults. At site level, a group of landscape-level forest fragmentation indices were highlighted for both questing nymph and adult abundance, including the nearest-neighbour distance, the shape and the aggregation level of forest patches. No cross-level effects or spatial autocorrelation were found.

Conclusions

Nymphal and adult ticks responded differently to environmental variables at different spatial and temporal scales. Our results can advise spatio-temporal extents of environment data collection for continuing empirical investigations and potential parameters for biological tick models.

Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach

The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial effects or artificial representations for outlining possible empirical investigations.

Spatially disaggregated disease transmission risk: land cover, land use and risk of dengue transmission on the island of Oahu

Vector-borne diseases persist in transmission systems that usually comprise heterogeneously distributed vectors and hosts leading to a highly heterogeneous case distribution. In this study, we build on principles of classical mathematical epidemiology to investigate spatial heterogeneity of disease risk for vector-borne diseases. Land cover delineates habitat suitability for vectors, and land use determines the spatial distribution of humans. We focus on the risk of exposure for dengue transmission on the Hawaiian island of Oahu, where the vector Aedes albopictus is well established and areas of dense human population exist. In Hawai'i, dengue virus is generally absent, but occasionally flares up when introduced. It is therefore relevant to investigate risk, but difficult to do based on disease incidence data. Based on publicly available data (land cover, land use, census data, surveillance mosquito trapping), we map the spatial distribution of vectors and human hosts and finally overlay them to produce a vector-to-host ratio map. The resulting high-resolution maps indicate a high spatial variability in vector-to-host ratio suggesting that risk of exposure is spatially heterogeneous and varies according to land cover and land use.

Pathogenic landscapes: interactions between land, people, disease vectors, and their animal hosts

BACKGROUND

Landscape attributes influence spatial variations in disease risk or incidence. We present a review of the key findings from eight case studies that we conducted in Europe and West Africa on the impact of land changes on emerging or re-emerging vector-borne diseases and/or zoonoses. The case studies concern West Nile virus transmission in Senegal, tick-borne encephalitis incidence in Latvia, sandfly abundance in the French Pyrenees, Rift Valley Fever in the Ferlo (Senegal), West Nile Fever and the risk of malaria re-emergence in the Camargue, and rodent-borne Puumala hantavirus and Lyme borreliosis in Belgium.

RESULTS

We identified general principles governing landscape epidemiology in these diverse disease systems and geographic regions. We formulated ten propositions that are related to landscape attributes, spatial patterns and habitat connectivity, pathways of pathogen transmission between vectors and hosts, scale issues, land use and ownership, and human behaviour associated with transmission cycles.

CONCLUSIONS

A static view of the "pathogenecity" of landscapes overlays maps of the spatial distribution of vectors and their habitats, animal hosts carrying specific pathogens and their habitat, and susceptible human hosts and their land use. A more dynamic view emphasizing the spatial and temporal interactions between these agents at multiple scales is more appropriate. We also highlight the complementarity of the modelling approaches used in our case studies. Integrated analyses at the landscape scale allows a better understanding of interactions between changes in ecosystems and climate, land use and human behaviour, and the ecology of vectors and animal hosts of infectious agents.

Landscape predictors of tick-borne encephalitis in Latvia: land cover, land use, and land ownership

Although the presence of tick-borne encephalitis (TBE) virus circulating in tick populations depends on large-scale patterns of climate, and the local density of infected ticks depends on the abundance of mammalian hosts, the risk of human infection depends on the access and use by human populations of tick-infested habitats, particularly forests, at the landscape level. We investigated the incidence of reported TBE cases in rural parishes (i.e., municipalities) in Latvia. The following major characteristics of parishes were considered: whether their environment is suitable for tick and tick-host populations (depending on land cover); whether the local human population is likely to enter the forest on a regular base (depending on land use); and whether the spatial distributions of these two aspects are likely to intersect, through access rules (as a function of land ownership). The results indicated that all three aspects are important in explaining and predicting the spatial distribution of TBE cases in the rural areas of Latvia. The concept of landscape is here given new depth by consideration of its physical structure, its use by human populations, and its accessibility as modulated by ownership.

Distribution and density of tsetse flies (Glossinidae: Diptera) at the game/people/livestock interface of the Nkhotakota Game Reserve human sleeping sickness focus in Malawi

In large parts sub-Saharan Africa, tsetse flies, the vectors of African human or animal trypanosomiasis, are, or will in the foreseeable future, be confined to protected areas such as game or national parks. Challenge of people and livestock is likely to occur at the game/livestock/people interface of such infested areas. Since tsetse control in protected areas is difficult, management of trypanosomiasis in people and/or livestock requires a good understanding of tsetse population dynamics along such interfaces. The Nkhotakota Game Reserve, an important focus of human trypanosomiasis in Malawi, is a tsetse-infested protected area surrounded by a virtually tsetse-free zone. The abundance of tsetse (Glossina morsitans morsitans) along the interface, within and outside the game reserve, was monitored over 15 months using epsilon traps. A land cover map described the vegetation surrounding the traps. Few flies were captured outside the reserve. Inside, the abundance of tsetse at the interface was low but increased away from the boundary. This uneven distribution of tsetse inside the reserve is attributed to the uneven distribution of wildlife, the main host of tsetse, being concentrated deeper inside the reserve. Challenge of people and livestock at the interface is thus expected to be low, and cases of trypanosomiasis are likely due to people and/or livestock entering the reserve. Effective control of trypanosomiasis in people and livestock could be achieved by increasing the awareness among people of dangers associated with entering the reserve.

Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium

BACKGROUND

Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis.

RESULTS

Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis.

CONCLUSION

A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.

Landscape and land cover factors influence the presence of Aedes and Anopheles larvae

The objective of this study was to test for associations between land cover data and the presence of mosquito larvae of the genera Aedes Meigen and Anopheles Meigen in northern Thailand at the landscape scale. These associations were compared with associations between larval habitat variables and the presence of mosquito larvae at a finer spatial scale. Collection data for the larvae of one Aedes species and three species-groups of Anopheles, all of which are involved in pathogen transmission, were used. A variety of northern Thai landscapes were included, such as upland villages, lowland villages and peri-urban areas. Logistic regression was used to evaluate associations. Generally, land cover and landscape variables explained the presence of larvae as well as did larval habitat variables. Results were best for species/species-groups with specific habitat requirements. Land cover variables act as proxies for the types of habitat available and their attributes. Good knowledge of the habitat requirements of the immature stages of mosquitoes is necessary for interpreting the effects of land cover.