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Preparedness and vulnerability of African countries against importations of COVID-19: a modelling study
Detecting rich-club ordering in complex networks
The presented analysis enables the measurement of the rich-club ordering and its relation with the function and dynamics of networks in examples drawn from the biological, social and technological domains.
Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks
- C. Cattuto, W. V. D. Broeck, A. Barrat, V. Colizza, J. Pinton, Alessandro Vespignani
- Computer SciencePloS one
- 15 July 2010
A scalable experimental framework for gathering real-time data resolving face-to-face social interactions with tunable spatial and temporal granularities is presented and shows an interesting super-linear behavior, which indicates the possibility of defining super-connectors both in the number and intensity of connections.
Multiscale mobility networks and the spatial spreading of infectious diseases
- D. Balcan, V. Colizza, B. Gonçalves, H. Hu, J. Ramasco, Alessandro Vespignani
- EconomicsProceedings of the National Academy of Sciences
- 20 July 2009
The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework.
Seasonal transmission potential and activity peaks of the new influenza A(H1N1): a Monte Carlo likelihood analysis based on human mobility
The analysis shows the potential for an early epidemic peak occurring in October/November in the Northern hemisphere, likely before large-scale vaccination campaigns could be carried out, and suggests that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak in order to restore the effectiveness of the vaccination programs.
Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions
- V. Colizza, A. Barrat, M. Barthelemy, A. Valleron, Alessandro Vespignani
- MedicinePLoS medicine
- 1 January 2007
The inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks and it is demonstrated 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.
Reaction–diffusion processes and metapopulation models in heterogeneous networks
This work lays out a theoretical and computational microscopic framework for the study of a wide range of realistic metapopulation and agent-based models that include the complex features of real-world networks.
The role of the airline transportation network in the prediction and predictability of global epidemics
- V. Colizza, A. Barrat, M. Barthelemy, Alessandro Vespignani
- Computer ScienceProceedings of the National Academy of Sciences…
- 3 February 2006
A stochastic computational framework for the forecast of global epidemics that considers the complete worldwide air travel infrastructure complemented with census population data and defines a set of quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern.
Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies
- Laura Di Domenico, G. Pullano, C. E. Sabbatini, P. Böelle, V. Colizza
- MedicineBMC Medicine
- 17 April 2020
A stochastic age-structured transmission model integrates data on age profile and social contacts in Île-de-France to assess the epidemic in the region, evaluate the impact of lockdown, and propose possible exit strategies and estimate their effectiveness.
The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale
- W. V. D. Broeck, C. Gioannini, B. Gonçalves, M. Quaggiotto, V. Colizza, Alessandro Vespignani
- Computer ScienceBMC infectious diseases
- 2 February 2011
The user-friendly graphical interface of the GLEaMviz tool, along with its high level of detail and the realism of its embedded modeling approach, opens up the platform to simulate realistic epidemic scenarios.