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 the emergence and dissemination of the SARS-CoV-2 variant XBB.1.5 in New York

On June 02 2024 by Fabiana Gámbaro

Our new study on the emergence and dissemination of the SARS-CoV-2 variant XBB.1.5 in New York has been published in Virus Evolution. The recombinant SARS-CoV-2 Omicron XBB.1.5 variant was first detected in New York City (NYC) and rapidly became the predominant variant in the area by early 2023. The increased occurrence of circulating variants within the SARS-CoV-2 XBB-sublineage prompted the modification of COVID-19 mRNA vaccines by Moderna and Pfizer-BioNTech. This update, implemented in mid-September 2023, involved the incorporation of a monovalent XBB. Read more...

We are hiring! A 2-year post-doc position to work on spatial models to target under-immunised communities

On May 14 2024 by Simon Dellicour

Description A 2-year post-doc position is open at the Spatial Epidemiology Lab of the University of Brussels (ULB) to work on spatial models helping to target under-immunised communities during vaccination activities in the Democratic Republic of the Congo. The position should start between October 1, 2024, and January 1, 2025. The researcher will work on a project funded by Innoviris, the public organisation that funds and supports research and innovation in the Brussels-Capital Region (Belgium). Read more...

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...

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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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