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.


Our new study about the evolution of the Lassa virus endemic area and population at risk

On September 23 2022 by Simon Dellicour

Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Read more...

New review: accommodating sampling location uncertainty in continuous phylogeography

On July 07 2022 by Simon Dellicour

Phylogeographic inference of the dispersal history of viral lineages offers key opportunities to tackle epidemiological questions about the spread of fast-evolving pathogens across human, animal, and plant populations. In continuous space, i.e. when locations are specified by longitude and latitude, these reconstructions are however often limited by the availability or accessibility of precise sampling locations required for such spatially-explicit analyses. In our new study published in Virus Evolution, we review the different approaches that can be considered when genomic sequences are associated with a geographic area of sampling instead of precise coordinates. Read more...

We are hiring! A 2-year post-doc position to work on viral landscape phylogeography at the SpELL

On December 20 2021 by Simon Dellicour

We are hiring! A 2-year post-doc position to work on viral landscape phylogeography. Description A 2-year post-doc position is open at the Spatial Epidemiology Lab (SpELL) of the University of Brussels (ULB) to work on landscape phylogeographic approaches. The position is available immediately and should start no later than June 1, 2022. The researcher will work on a research project funded by an Incentive Grant for Scientific Research awarded by the Fonds de la Recherche Scientifique (FNRS, Belgium). 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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