Avec l’entrée d’internet dans notre quotidien, avec les réseaux sociaux, dans un monde de plus en plus numérique et mobile, le recours à la communication par internet est indispensable dans les stratégies de communication, et particulièrement en communication de crise. Une enquête, auprès d’universités françaises, permet d’analyser, à partir de l’exemple de la grippe A, comment internet est devenu un outil majeur dans la communication des universités en situation de crise. La communication par internet est d’abord une aide. Elle permet de diffuser largement les messages d’information et de prévention. A ce titre, elle est une communication interne. Elle aide aussi l’établissement à assurer la continuité du service public d’enseignement, grâce aux outils numériques qu’il développe. Mais la communication par internet présente aussi des risques. Elle peut être brouillée, altérant ainsi les effets attendus, comme il a été constaté lors de la campagne de communication sur la vaccination. Elle peut aussi être victime d’attaques, parce que toute communication empruntant la voie internet est menacée, posant ainsi le problème de la sécurité des systèmes d’information. En cas de crise, les établissements seraient confrontés, d’une part à la nécessité de maîtriser les techniques de communication, d’autre part aux besoins liés à l’utilisation des outils numériques ; mais aussi aux risques pesant sur les systèmes d’information. Prévoir, dans la mesure du possible, la survenance de problèmes qui pourraient se poser en cas de crise, est nécessaire. En se préparant à l’avance à la gestion de crise, grâce notamment à la mutualisation des moyens et à une prise de conscience des risques, les universités pourraient mieux maîtriser ces difficultés. / Internet communication is now generally acknowledged as indispensable in communication strategies, and particularly in crisis communication. A survey of French universities makes it possible to analyze, through the example of the H1N1 flu pandemic, how the Internet became a major tool for the communication of universities in a crisis. At the internal level, Internet communication appears as a reliable resource, allowing the diffusion of informative and preventive messages. It also helps the institution to ensure the continuity of public educational services through digital tools. But Internet communication also involves risks. Messages can be blurred, thus altering their expected effects, as became clear during the communication campaign on immunization. Messages can also be the victim of attacks, because any communication via the Internet channel may be threatened in various ways. This poses the problem of the security of information systems. In sum, institutions in crisis must face not only the necessity to master digital techniques of communication, and to comply with the requirements inherent in the use of digital tools, but also to manage risks that are specific to digital information systems. Anticipating, so far as is possible, the occurrence of problems that might arise in a crisis is essential. By preparing to cope with crises, including through the pooling of resources and the awareness of risks, universities may better control these difficulties. The study of this crisis reveals not only the pertinent issues, but also how such preparation might be most effectively undertaken.

This thesis describes how transmission of the 2009 A/H1N1 influenza pandemic in the United States varied geographically, with emphasis on population distribution and age structure. This is made possible by the availability of medical claims records maintained in the private sector that capture the weekly incidence of influenza-like illness in 834 US cities. First, a probabilistic method is developed to infer each city's outbreak onset time. This reveals a clear wave-like pattern of transmission originating in the south-eastern US. Then, a mechanistic mathematical model is constructed to describe the between-city transmission of the epidemic. A model selection procedure reveals that transmission to a city is modulated by its population size, surrounding population density, and possibly by students mixing in schools. Geographic variation in transmissibility is explored further by nesting a latent Gaussian process within the mechanistic transmission model, revealing a possible region of elevated transmissibility in the south-eastern US. Then, using the mechanistic model and a probabilistic back-tracing procedure, the geographic introduction sites (the `transmission hubs') of the outbreak are identified. The transmission hubs of the 2009 pandemic were generally mid-sized cities, contrasting with the conventional perspective that major outbreaks should start in large population centres with high international connectivity. Transmission is traced forward from these hubs to identify `basins of infection', or regions where outbreaks can be attributed with high probability to a particular hub. The city-level influenza data is also separated into 12 age categories. Techniques adapted from signal processing reveal that school-aged children may have been key drivers of the epidemic. Finally, to provide a point of comparison, the procedures described above are applied to the 2003-04 and 2007-08 seasonal influenza outbreaks. Since the 2007-08 outbreak featured three antigenically distinct strains of influenza, it is possible to identify which antigenic strains may have been responsible for infecting each transmission hub. These strains are identified using a probabilistic model that is joined with the geographic transmission model, providing a link between population dynamics and molecular surveillance.