Spatial epidemiology studies the effect of spatial factors on the emergence, spread and persistence of diseases and invasive species. The understanding of key spatial factors, such as environmental or anthropogenic variables, and their integration into spatial models can then be used to predict the geographical distribution of risk, which can contribute to better targetted prevention, surveillance and control measures.
More specifically, our spatial epidemiology lab is concerned with baseline works on the denominator, i.e. the number of hosts, which are key spatial variables used in most epidemiological models, and we actively work on the improvement of large-scale data sets on the distribution of human and livestock populations. A second focus of active research is the spatial epidemiology of avian influenza, a major disease of poultry with a strong zoonotic potential. The Spatial epidemiology lab. was founded in the academic year 2015-2016 and its researches were previously carried out under the Biological control and spatial ecology lab.
On October 28 2018 by Marius Gilbert
In collaboration with the Food and Agriculture Organization of the UN (FAO) and other collaborators, we are publishing this week in Nature Scientific Data the result of several years of research to improve global data on the distribution of livestock (cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks). These new data sets provide estimates of the density (individuals / km2) of these species at a spatial resolution of 5 minutes of arc (approximately 10 km at the equator) over the globe. Read more...
On September 05 2018 by Marius Gilbert
A 2-year post-doc position starting immediately is available to work on global spatial and temporal distribution models of livestock. Description The global livestock sector faces major challenges in terms of the sustainability of its development due to the considerable externalities that livestock production has on society, health and the environment. High-resolution maps of livestock are essential tools to assess the sustainability of livestock production systems. Maps allow, for example, the estimation of potential impacts of various hazards that have strong spatial dimensions such as the release of pollutants. Read more...
On February 12 2018 by Marius Gilbert
A 2-year post-doc position is opened to work on spatial epidemics and phylogeographic models applied to Bluetongue. Description Several factors can contribute to the spread of animal diseases their relative effect can be difficult to disentangle. In this project, we aim to compare spatial epidemic models and spatial phylogeographic models in their capacity to quantify the effect of different factors on patterns of spread, using past bluetongue epidemics as study system. Read more...
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.See more
The geographical distribution of livestock (cattle, sheep, goat, pig, chicken, duck, buffaloes, camels) is a key driver of the distribution of diseases and has important environmental impacts at a global scale in terms of direct pollution through manure managment, greenhouse gaz emissions and contribution to antimicrobial resistance. Our work aim to better map the distribution of livestock production at a global scale, with some special emphasis on intensive livestock production and projections.See more
For many low-income countries of the World where disease burden is greatest, spatially detailed, contemporary census data on human population are missing. As partner of the Worldpop consortiumn, we are working on improving human population distribution maps in Africa and on urban expansion model that would allow us to project how the distribution of human population may change over time.See more
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.See more