Sophie O. Vanwambeke

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

BackgroundVector-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.ResultsNegative 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.ConclusionA 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.

Multi-level analyses of spatial and temporal determinants for dengue infection

BackgroundDengue is a mosquito-borne viral infection that is now endemic in most tropical countries. In Thailand, dengue fever/dengue hemorrhagic fever is a leading cause of hospitalization and death among children. A longitudinal study among 1750 people in two rural and one urban sites in northern Thailand from 2001 to 2003 studied spatial and temporal determinants for recent dengue infection at three levels (time, individual and household).MethodsDeterminants for dengue infection were measured by questionnaire, land-cover maps and GIS. IgM antibodies against dengue were detected by ELISA. Three-level multi-level analysis was used to study the risk determinants of recent dengue infection.ResultsRates of recent dengue infection varied substantially in time from 4 to 30%, peaking in 2002. Determinants for recent dengue infection differed per site. Spatial clustering was observed, demonstrating variation in local infection patterns. Most of the variation in recent dengue infection was explained at the time-period level. Location of a person and the environment around the house (including irrigated fields and orchards) were important determinants for recent dengue infection.ConclusionWe showed the focal nature of asymptomatic dengue infections. The great variation of determinants for recent dengue infection in space and time should be taken into account when designing local dengue control programs.

Impact of land-use change on dengue and malaria in northern Thailand

Land-use change, a major constituent of global environmental change, potentially has significant consequences for human health in relation to mosquito-borne diseases. Land-use change can influence mosquito habitat, and therefore the distribution and abundance of vectors, and land use mediates human–mosquito interactions, including biting rate. Based on a conceptual model linking the landscape, people, and mosquitoes, this interdisciplinary study focused on the impacts of changes in land use on dengue and malaria vectors and dengue transmission in northern Thailand. Extensive data on mosquito presence and abundance, land-use change, and infection risk determinants were collected over 3 years. The results of the different components of the study were then integrated through a set of equations linking land use to disease via mosquito abundance. The impacts of a number of plausible scenarios for future land-use changes in the region, and of concomitant behavioral change were assessed. Results indicated that land-use changes have a detectable impact on mosquito populations and on infection. This impact varies according to the local environment but can be counteracted by adoption of preventive measures.

Integrated Mapping of Establishment Risk for Emerging Vector-Borne Infections: A Case Study of Canine Leishmaniasis in Southwest France

Background Zoonotic visceral leishmaniasis is endemic in the Mediterranean Basin, where the dog is the main reservoir host. The diseases causative agent, Leishmania infantum, is transmitted by blood-feeding female sandflies. This paper reports an integrative study of canine leishmaniasis in a region of France spanning the southwest Massif Central and the northeast Pyrenees, where the vectors are the sandflies Phlebotomus ariasi and P. perniciosus. Methods Sandflies were sampled in 2005 using sticky traps placed uniformly over an area of approximately 100 by 150 km. High- and low-resolution satellite data for the area were combined to construct a model of the sandfly data, which was then used to predict sandfly abundance throughout the area on a pixel by pixel basis (resolution of c. 1 km). Using literature- and expert-derived estimates of other variables and parameters, a spatially explicit R 0 map for leishmaniasis was constructed within a Geographical Information System. R 0 is a measure of the risk of establishment of a disease in an area, and it also correlates with the amount of control needed to stop transmission. Conclusions To our knowledge, this is the first analysis that combines a vector abundance prediction model, based on remotely-sensed variables measured at different levels of spatial resolution, with a fully mechanistic process-based temperature-dependent R 0 model. The resulting maps should be considered as proofs-of-principle rather than as ready-to-use risk maps, since validation is currently not possible. The described approach, based on integrating several modeling methods, provides a useful new set of tools for the study of the risk of outbreaks of vector-borne diseases.

The potential effects of global warming on changes in canine leishmaniasis in a focus outside the classical area of the disease in Southern France

In 1994, an ecoepidemiologic study was carried out in the mid-Ariège valley (French Pyrenees) where autochthonous cases of canine leishmaniasis had been previously reported. Serologic samples were collected from 336 dogs in two groups of villages. The seroprevalences were 11.67% in the valley villages and only 1.43% in the foothill villages. Five lymph node biopsies were taken from serologically positive dogs, and resultant isolates were identified as Leishmania infantum zymodeme MON-1. Phlebotomine sandflies were collected in five locations by CDC light traps. Both of the known French vectors, Phlebotomus ariasi and P. perniciosus, were identified. Bioclimatic and floristic studies showed that this area is an enclave of the supra-Mediterranean climatic zone, containing a typically xerothermophilic Mediterranean flora. The Pyrenees Mountains are usually considered to be outside of the endemic range of leishmaniasis in southern France, and so our demonstration of a microfocus of canine leishmaniasis in the northern foothills is noteworthy. A second serologic survey carried out in 2007 (216 dogs) showed an inversion of the seropositive rates between the two groups of villages compared with those of 1994: only 2.72% in the valley villages and 11.32% in the foothills villages. The decrease of seroprevalence in the first area (valley villages) can be related to a considerable use of deltamethrin collars during the transmission season. The increase of seroprevalence of the foothill villages could be related to climatic conditions, since there was an increase of about 1 degrees C in the mean annual temperature.

Landscape and Land Cover Factors Influence the Presence of Aedes and Anopheles Larvae

Abstract 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.

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin.

BackgroundGlobal environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data.MethodsWe explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 – 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions.ResultsSignificant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model.ConclusionsOur results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change.

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.

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

BackgroundTicks 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.MethodsA 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.ResultsAt 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.ConclusionsNymphal 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.