Dr. Vittoria Colizza is Director of Research at Inserm (French National Institute of Health and Medical Research) & Sorbonne University, Faculté de Médecine, Paris, France. With a PhD in Statistical and Biological Physics (SISSA, Trieste, Italy, 2004), she spent 3 years in the US at the Indiana University School of Informatics (Bloomington, IN), as post-doc and Visiting Assistant Professor, before moving to Europe and joining ISI Foundation (Turin, Italy), after being awarded a Starting Independent Career Grant in Life Sciences by the European Research Council in 2007. In 2011, Colizza joined Inserm in Paris where she leads the EPIcx lab (Epidemics in complex environments, www.epicx-lab.com) within the Pierre Louis Institute of Epidemiology and Public Health.
Her work focuses on real episodes of human and animal epidemics (e.g. 2009 H1N1 pandemic influenza, MERS-CoV epidemic, Ebola virus disease epidemic, rabies, bovine brucellosis) to gather context epidemic awareness and provide risk assessment analyses for preparedness, mitigation, and control. Her research also includes more theoretical approaches for the modeling of small- to large-scale diffusion events where contacts between hosts and their mobility are explicitly considered from data (face-to-face interactions, contact matrices, commuting, air travel, migrations, trade movements, call detail records, etc.).
Colizza received several awards, including the Young Talent Award by the Italian Ministry of Youth in 2010, the Prix Louis-Daniel Beauperthuy 2012 by the French Academy of Sciences, the Young Scientist Award for Socio-Econophysics in 2013, the Telethon Farmindustria Award in 2017, the Erdős–Rényi Prize by the Network Science Society in 2017. She also served as Young Advisor to the Vice President of the European Commission Mrs. Neelie Kroes for the Digital Agenda for Europe, and was member of the I7 Innovators’ Strategic Advisory Board on People-Centered Innovation for the Italian Government delegation for G7 in 2017.
Vulnerability of networked host populations to epidemics
Our understanding of communicable diseases prevention and control is rooted in the theory of host population transmission dynamics. The network of host-to-host contacts along which transmission can occur drives the epidemiology of communicable diseases, determining how quickly they spread and who gets infected. A large body of epidemiological, mathematical and computational studies has provided a number of insights into the understanding of the process and the identification of efficient control strategies. The explosion of time resolved contact data has however opened the stage to new challenges. What are the structural and temporal aspects, and possibly their non-trivial interplay, that are critical for disease spread ? To answer this question, I will introduce the infection propagator approach, a theoretical analytical framework for the assessment of the degree of vulnerability of a host population to disease epidemics, once we account for the time variation of its contact pattern. By reinterpreting the tensor formalism of multilayer networks, this approach allows the analytical computation of the epidemic threshold for an arbitrary time-varying network of host contacts, i.e. the critical pathogen transmissibility above which large-scale propagation occurs. I will apply this framework to a set of empirical time-varying contact networks and show how it can be used to test different intervention strategies for infection prevention and control in realistic settings.