Spatial Epidemiology Lab

Université Libre de Bruxelles

Spatial epidemiology studies the effect of spatial factors on the emergence, spread, persistence and evolution of diseases and invasive species. The understanding of key spatial factors, such as environmental or anthropogenic variables, and their integration into spatial models is used to predict the geographical distribution of risk, which can contribute to better targetted prevention, surveillance and control measures. We also work toward the improvement of methods in spatial modelling and landscape phylogeography, and of large-scale data sets on farm animals.

News

New study on the contribution of climate change to the spatial expansion of West Nile virus in Europe

On February 13 2024 by Diana Erazo & Simon Dellicour

Our new study on the contribution of climate change to the spatial expansion of West Nile virus in Europe has been published in Nature Communications. West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land use and human population changes. Read more...

New study on the dispersal and human-fish host switching history of Streptococcus agalactiae ST283

On October 04 2023 by Dan Schar and Simon Dellicour

Fish consumption-associated outbreaks of Streptococcus agalactiae (group B Streptococcus; GBS) sequence type (ST) 283 in Asia have drawn attention to GBS ST283 as an emerging foodborne pathogen capable of generating disease in the general population. To inform public health interventions, researchers gathered 328 whole genome sequences collected from humans and fish between 1998 and 2021 across eleven countries spanning four continents, applying Bayesian modeling to reconstruct the evolutionary history of ST283, host transitions and geographic dispersal. Read more...

New publication in Nature: projected decline in European bumblebee populations in the 21st century

On September 11 2023 by Simon Dellicour

Our new study on the projected decline in European bumblebee populations has been published in Nature. Habitat degradation and climate change are globally acting as pivotal drivers of wildlife collapse, with mounting evidence that this erosion of biodiversity will accelerate in the following decades. In this study, we quantified the past, present, and future ecological suitability of Europe for bumblebees, a threatened group of pollinators ranked among the highest contributors to crop production value in the northern hemisphere. Read more...


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Research topics

Landscape phylogeography

Spatially-explicit phylogeographic analyses can be used to introduce phylogenetic trees in a geographic context. Over the last years, we started exploiting such spatially-annotated trees to investigate the impact on environmental factors on the dispersal history and dynamic of viral lineages (dispersal velocity, dispersal direction and dispersal frequency). Furthermore, we also aim to use phylogeographic reconstruction to assess hypothetical intervention strategies in the context of viral epidemics.

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Livestock diseases and mapping

Our research mainly deal with the spatial epidemiology of avian influenza (AI) at different spatial scales, with particular emphasis on on the role of agro-ecological factors on the emergence, spread and persistence of AI viruses. Over the years, we have also been involved in research on other important livestock diseases such as bluetongue, bovine tuberculosis, foot and mouth disease, porcine reproductive and respiratory syndrome, and Nipah virus infections. In addition, we also have research projects to better map the distribution of livestock production at a global scale.

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Modelling geographical invasions

Invading organisms spreading though a heterogeneous landscape are difficult to study using conventional statistical models. We aim to develop new methodology to study those type of data, to review existing methods, and to compare all methods in their capacity to detect the influence of landscape heterogeneity on the pattern of spread.

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