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 atypically pathogenic H3N1 avian influenza epidemic that occurred in 2019 in Belgium

On January 23 2023 by Simon Dellicour

The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of an H3N1 low pathogenic avian influenza epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially-explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Read more...

Delighted to welcome new researchers in our interdisciplinary team at the Spatial Epidemiology Lab

On October 14 2022 by Simon Dellicour

The Spatial Epidemiology Lab is delighted to welcome three new researchers in its interdisciplinary team: Fabiana Gámbaro whose post-doctoral project will be dedicated to application and methodological developments of phylodynamic approaches, Guillaume Ghisbain whose post-doctoral project will focus on investigating the dynamics and drivers of insect invasions at the European scale, as well as Jonathan Thibaut who just started a PhD project at the Laboratory of Clinical Microbiology of the KU Leuven and co-supervised at the SpELL. Read more...

Introducing the Fan-trap, an inexpensive, light and scalable insect trap

On October 13 2022 by Jean-Claude Grégoire

Monitoring is an important component of pest management, to prevent or mitigate outbreaks of native pests, and to check for quarantine organisms. Surveys often rely on trapping, especially when the target species respond to semiochemicals. Many traps are available for this purpose, but they are bulky in most cases, which raises transportation and deployment issues, and they are expensive, which limits the size and accuracy of any network. To overpass these difficulties, en-tomologists have used recycled material, such as modified plastic bottles, producing cheap and reliable traps but at the cost of recurrent handywork, not necessarily possible for all end-users (e. 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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