Health, Biology, Epidemiology
Spreading models
Forecasting disease contagion across socio-technical spaces
We research computational modeling approaches to epidemic and pandemic events able to provide rationales and quantitative analysis in support of the decision and policymaking processes, the preparation of contingency plans, and the analysis of biological threats and systemic risk. Cognizant of the epidemic-information-behavior feedback loop, we also aim at developing new classes of computational modeling frameworks for contagion processes that account for the social adaptive behavior induced by information spreading and the interdependent and multiscale properties of real world networks.