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.
We are hiring! A PhD student position is open at the SpELL to work on the avian flu VIVACE project
On October 31 2024 by Simon Dellicour
The present PhD student position and associated research project is part of the 13 PhD projects of the VIVACE Doctoral Network, funded by the Marie Sklodowska-Curie action of the Horizon Europe programme. Context on the VIVACE doctoral network While outbreaks of highly pathogenic avian influenza viruses (HPAIV) in Europe used to be rare and geographically contained, the situation has dramatically changed in the last few years with thousands of outbreaks reported in domestic poultry and wild birds. Read more...
New study on integrating indicator-based and event-based surveillance data to improve risk mapping
On October 30 2024 by Kyla Serres
Our new study on integrating indicator-based and event-based surveillance data to improve risk mapping has just been published in Eurosurveillance. West Nile virus (WNV) has an enzootic cycle between birds and mosquitoes, humans being incidental dead-end hosts. Circulation of WNV is an increasing public health threat in Europe. While detection of WNV is notifiable in humans and animals in the European Union, surveillance based on human case numbers presents some limitations, including reporting delays. Read more...
New study on modelling farm distribution now published in PLoS Computational Biology
On October 18 2024 by Marie-Cécile Dupas
Our new study on modelling farm distribution has been published in PLoS Computational Biology. We have developed a model to predict the location and size of poultry farms in countries or regions with limited data. This is important because knowing the distribution of farms helps in understanding how diseases spread, especially in areas with rapidly growing farm populations. Our model uses advanced statistical methods and is calibrated with environmental and human activity data to simulate farm locations and sizes, which we tested on farms in Bangladesh, Gujarat (India), and Thailand. Read more...
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.
See moreOur 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.
See moreInvading 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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