Dynamical patterns of epidemic outbreaks in complex heterogeneous networks

We present a thorough inspection of the dynamical behavior of epidemic phenomena in populations with complex and heterogeneous connectivity patterns. We show that the growth of the epidemic prevalence is virtually instantaneous in all networks characterized by diverging degree fluctuations, independently of the structure of the connectivity correlation functions characterizing the population network. By means of analytical and numerical results, we show that the outbreak time evolution follows a precise hierarchical dynamics. Once reached the most highly connected hubs, the infection pervades the network in a progressive cascade across smaller degree classes. Finally, we show the influence of the initial conditions and the relevance of statistical results in single case studies concerning heterogeneous networks. The emerging theoretical framework appears of general interest in view of the recently observed abundance of natural networks with complex topological features and might provide useful insights for the development of adaptive strategies aimed at epidemic containment.Comment: 13 pages, 11 figure

Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions

We present a study of the worldwide spread of a pandemic influenza and its possible containment at a global level taking into account all available information on air travel. We studied a metapopulation stochastic epidemic model on a global scale that considers airline travel flow data among urban areas. We provided a temporal and spatial evolution of the pandemic with a sensitivity analysis of different levels of infectiousness of the virus and initial outbreak conditions (both geographical and seasonal). For each spreading scenario we provided the timeline and the geographical impact of the pandemic in 3,100 urban areas, located in 220 different countries. We compared the baseline cases with different containment strategies, including travel restrictions and the therapeutic use of antiviral (AV) drugs. We show that the inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks. The large-scale therapeutic usage of AV drugs in all hit countries would be able to mitigate a pandemic effect with a reproductive rate as high as 1.9 during the first year; with AV supply use sufficient to treat approximately 2% to 6% of the population, in conjunction with efficient case detection and timely drug distribution. For highly contagious viruses (i.e., a reproductive rate as high as 2.3), even the unrealistic use of supplies corresponding to the treatment of approximately 20% of the population leaves 30%-50% of the population infected. In the case of limited AV supplies and pandemics with a reproductive rate as high as 1.9, we demonstrate that the more cooperative the strategy, the more effective are the containment results in all regions of the world, including those countries that made part of their resources available for global use.Comment: 16 page

The role of geography and traffic in the structure of complex networks

We report a study of the correlations among topological, weighted and spatial properties of large infrastructure networks. We review the empirical results obtained for the air transportation infrastructure that motivates a network modeling approach which integrates the various attributes of this network. In particular we describe a class of models which include a weight-topology coupling and the introduction of geographical attributes during the network evolution. The inclusion of spatial features is able to capture the appearance of non-trivial correlations between the traffic flows, the connectivity pattern and the actual distances of vertices. The anomalous fluctuations in the betweenness-degree correlation function observed in empirical studies are also recovered in the model. The presented results suggest that the interplay between topology, weights and geographical constraints is a key ingredient in order to understand the structure and evolution of many real-world networks

La loi LRU a-t-elle modifié les distributions de pouvoir au sein des universités françaises ?

La loi LRU (loi relative aux libertés et responsabilités des universités) change la structure du pouvoir au sein des universités françaises. Seuls les membres du conseil d'administration (CA) prennent part à l'election du president, alors qu'auparavant, les membres du conseil scientifique (CS) et du conseil des etudes et de la vie universitaire (CEVU) prenaient part au vote. Notre question est alors de savoir si ce changement radical, le nombre de votants est desormais compris entre 20 et 30, alors qu'il etait compris entre 70 et 140, presente souvent comme une reforme majeure du systeme universitaire, a engendre une repartition differente du pouvoir parmi les groupes representatifs tels que les enseignants, les etudiants, les personnels IATOS et les membres exterieurs.Indice de Banzhaf, pouvoir, universites francaises, loi LRU

Loi relative aux libertés et responsabilités des universités (loi LRU), élection du président et conseil d’administration : une analyse en termes de pouvoir

L’objet de cet article est de mesurer le pouvoir des membres des conseils d’administration des universités françaises tel qu’il est défini par la loi relative aux libertés et responsabilités des universités (loi LRU). A l’aide d’outils issus de la théorie des jeux coopératifs, et en particulier l’indice de pouvoir de Banzhaf, nous montrons que le nombre de représentants d’un groupe, par exemple les professeurs des universités ou les étudiants, et le pouvoir, sont des notions dont les relations sont parfois surprenantes. Nous présentons des exemples où le réel pouvoir de décision n’appartient pas forcément aux groupes auxquels nous pensions intuitivement.conseil d’administration, indice de Banzhaf, pouvoir, universités françaises.

Nonlinear dynamics of spatio-temporal waves in multimode fibres

Nonlinear multimode fibers provide an intriguing test-bed for exploring complex spatio-temporal beam dynamics. We overview recent experimental observations of Kerr beam self-cleaning, parametric sideband series and supercontinuum generation in passive and active multimode optical fibers

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Transition numérique et pratiques de recherche et d’enseignement supérieur en agronomie, environnement, alimentation et sciences vétérinaires à l’horizon 2040.

Pour citer ce document:Barzman M. (Coord.), Gerphagnon M. (Coord.), Mora O. (Coord.),Aubin-Houzelstein G., Bénard A., Martin C., Baron G.L, Bouchet F., Dibie-Barthélémy J., Gibrat J.F., Hodson S., Lhoste E., Moulier-Boutang Y., Perrot S., Phung F., Pichot C., Siné M., Venin T. 2019. Transition numérique et pratiques de recherche et d’enseignement supérieur en agronomie, environnement, alimentation et sciences vétérinaires à l’horizon 2040.INRA, France, 161pagesTransition numérique et pratiques de recherche et d’enseignement supérieur en agronomie, environnement, alimentation et sciences vétérinaires à l’horizon 2040