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.


New study on evidence of cross‑channel dispersal into England of the forest pest Ips typographus

On March 19 2024 by Jean-Claude Grégoire

In 2018, for the first time in the British history, reproducing populations of the spruce bark beetle Ips typographus, the most damaging pest in Europe, were found in Kent, in southern England. Our study, carried out with Forest Research in Britain, relied on networks of pheromone traps deployed from an outbreak hotspot in the French and Belgian Ardenne to the English coast. We show that, contrary to the hypothesis that the pest entered Britain with infested wood, the insects managed to fly over the English Channel. Read more...

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...

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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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