Epidemic Modeling Research
Bruno Gonçalves has made foundational contributions to computational epidemiology, combining large-scale mobility data, complex networks, and statistical physics to model and forecast the spread of infectious diseases. His work spans influenza forecasting, COVID-19 dynamics, and the development of global epidemic simulators used by public health agencies worldwide.
GLEaM — Global Epidemic and Mobility Model
The GLEaM (Global Epidemic and Mobility Model) is a computational framework that integrates real-world human mobility data — including airline travel, commuting patterns, and short-range movements — with compartmental epidemic models to simulate the worldwide spread of infectious diseases.
Bruno contributed to GLEaM's development and has used it extensively to study pandemic preparedness, real-time forecasting, and the impact of intervention strategies. The model has been applied to H1N1 influenza, seasonal flu, COVID-19, and other pathogens.
Key Publications
- The power law in human mobility is a mixture artifact: evidence from a pandemic natural experiment
Ferres, Gonçalves. arXiv preprint (2026)
- Human mobility and the worldwide impact of intentional localized highly pathogenic virus release
Gonçalves, Balcan, Vespignani. Scientific Reports (2013)
- Real time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm
Tizzoni, Bajardi, Poletto, Ramasco, Balcan, Gonçalves, Perra, Colizza, Vespignani. BMC Medicine (2012)
- The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale
Van den Broeck, Gioannini, Gonçalves, Quaggiotto, Colizza, Vespignani. BMC Infectious Diseases (2011)
- Towards a characterization of behavior-disease models
Perra, Balcan, Gonçalves, Vespignani. PLOS ONE (2011)
- Multiscale mobility networks and the spatial spreading of infectious diseases
Balcan, Colizza, Gonçalves, Hu, Ramasco, Vespignani. PNAS (2009)
Media Coverage
Bruno's epidemic modeling research has been covered by outlets including Wired, Scientific American, USA Today, Physics World and The Conversation, from the 2009 H1N1 pandemic to the 2014 Ebola outbreak.
Newsletter
Bruno writes regularly about epidemic modeling, AI, and data science on his Substack newsletter. Subscribe for in-depth posts on computational epidemiology, network science, and machine learning.