La surveillance épidémiologique est le recueil systématique et continu d’informations sur l’état de santé des populations, leur analyse, leur interprétation et leur diffusion à tous les décideurs ayant besoin d’être informés. Un de ses objectifs est la détection des événements inhabituels, i.e. des épidémies, nécessitant la mise en place rapide de contre-mesures. Les objectifs de ce travail de thèse sont : (i) d’évaluer les principales méthodes statistiques de détection publiées et communément employées dans différents systèmes de surveillance épidémiologique, (ii) de proposer une nouvelle approche reposant sur la combinaison optimale de méthodes de détection statistique des épidémies et (iii) de développer une nouvelle méthode statistique d’analyse étiologique d’une épidémie à partir des données de surveillance épidémiologique collectées en routine par le système.Pour atteindre ces objectifs, nous évaluons les principales méthodes statistiques de la littérature, à partir d’un jeu publié de données simulées. Puis nous proposons une approche originale pour la détection des épidémies sur le principe de la combinaison de méthodes sélectionnées lors de l’étape précédente. Les performances de cette approche sont comparées aux précédentes selon la méthodologie utiliséeà la première étape. Enfin, nous proposons une méthode d’analyse étiologique d’une épidémie à partir des données de surveillance en employant des modèles statistiques adaptés aux séries chronologiques. / Public health surveillance is the ongoing, systematic collection, analysis, interpretation, and dissemination of data for use in public health action to reduce morbidity and mortality of health-related events and to improve health. One of its objectives is the detection of unusualevents, i.e. outbreaks, requiring the rapid implementation of countermeasures.The objectives of this work are: (i) to evaluate the main published statistical methods for outbreak detection commonly implemented in different public health surveillance systems, (ii) to propose a new approach based on the optimal combination of statistical methods foroutbreak detection and benchmark it to other methods; and (iii) develop a new statistical method for the etiological analysis of an outbreak from public health surveillance data routinely collected by the system. To achieve these objectives, as a first step, we evaluate the main statistical methods, from a published set of simulated public health surveillance data. Statistical methods have been evaluated for an operational purpose: for all simulated time series, we used the tuning parameters recommended by their authors for each algorithm when available. We propose sensitivity and specificity metrics suitable for these tools. Then we propose an original approach for outbreak detection based on combination of methods selected in the previous step. The performance of this approach is compared to the previous ones according to the methodology implemented in the first step.Finally, we propose a method for the etiological analysis of an outbreak from surveillance data by using statistical models suitable for time series analysis

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This diploma thesis concerns topic of control within interactivity in the new media. It deals with concept of interactivity from the perspective of the new media and semiotics. Later on it presents insight on different mechanisms and levels of control, which are present within the interactivity. The thesis is focused only on those mechanisms that are aimed at a user. These concern for example dataveillance, data-based discrimination, disciplination, tailoring, monitoring or persuasive games. This line is extended and connected with the contributions of Roland Barthes, Michel Foucault and Vilém Flusser, who dealt with topics such as power, discipline and apparatuses. The aim of this thesis is to find out, what is the position of a user in relation to the mechanisms of control and what are her/his possibilities of action against these mechanisms (if any). Keywords: interactivity, new media, control, surveillance, semiotics, user, data, apparatus

Falls can lead to unintentional injuries and possibly death, making falls an important public health problem in terms of related health care cost, incurred disabilities, and years of life lost. Approximately 1 in every 3 Americans ages 65 years and older is at risk of falling at least once every year. Children, young adults, and middle-aged adults are also vulnerable to falls. The purpose of this study was to examine the epidemiology of falls and fall-related injuries using surveillance data from nationally representative samples of hospital emergency departments in United States. The study was guided by a social-ecological model on the premise that multiple levels of risk factors affect health. Using a cross-sectional study and archival data from NEISS-AIP between 2009 and 2011, the result of multiple logistic regression indicated that age, gender, race and body part affected were significantly associated with hospitalization due to falls (p < .001) and incident locale independently predicted hospitalization due to falls in which hospitalization due to falls was considered a proxy measure of fall severity. The odds in each of the groups for fall injuries were (a) older adults versus children, 1.07 (95% CI: 1.05-1.08); (b) males versus females, 1.23 (95% CI: 1.21-1.26); (c) Blacks versus Whites, 2.12 (95% CI: 2.11-2.13); (d) body part extremities versus head area, 0.98 (95% CI: 0.97-0.99); and (e) outside home versus inside home, 1.14 (95% CI: 1.13-1.15). The results of this study may be important in forming and implementing age-specific prevention strategies and specialized safety training programs for all age groups, thereby reducing deaths, disabilities, and considerable health care cost associated with hospitalization due to fall-related injuries.

The Innovative Medicines Initiative Accelerated Development of VAccine beNefit-risk Collaboration in Europe (IMI ADVANCE) project aims to develop a framework for best practice methods on integrated rapid benefit/risk monitoring of vaccines in the European Union (EU). Burden of disease is one of the measures considered when estimating vaccine benefits. This study explores the use of notifiable infectious disease surveillance data for this purpose by estimating burden of invasive meningococcal disease in the EU/European Economic Area (EEA). We use the Burden of Communicable Diseases in Europe toolkit for computing disability-adjusted life years from incidence-based data retrieved from the European Surveillance System (TESSy) held at the European Centre for Disease Prevention and Control. Invasive meningococcal is a common cause of meningitis and septicaemia, with high case-fatality (~10%) and sequelae. We found that the median annual burden of invasive meningococcal disease in the EU/EEA, 2011-2015, was 3.87 DALYs per 100 000 total population (95% UI: 3.79-3.95). Children below one year of age and children below five years of age were at greatest risk of invasive meningococcal disease serogroup B with 89.15 DALYs per 100 000 stratum specific population (95% UI: 83.11-95.02) and 22.57 DALYs per 100 000 stratum specific population (95% UI: 21.03-24.12), respectively. We found that the distribution of burden of invasive meningococcal disease serogroup B differs widely between countries in the EU/EEA and consequently confirm that national assessment of the new infant meningococcal B vaccine is highly relevant.

Despite technological advances in public health informatics, the evaluation of infectious disease surveillance systems data remains incomplete. In this study, a thorough evaluation was performed of the West Virginia Electronic Disease Surveillance System (WVEDSS, 2007-2010) and the West Virginia Electronic Disease Surveillance System NationalEDSS -Based System (WVEDSS-NBS; March 2012 - March 2014) for Category II infectious diseases in West Virginia. The purpose was to identify key areas in the surveillance system process from disease diagnosis to disease prevention that need improvement. Grounded in the diffusion of innovation theory, a quasi-experimental, interrupted, time-series design was used to evaluate the 2 data sets. Research questions examined differences in mean reporting time, the 24-hour standard, and comparison of complete fields (DOB, gender etc.) of the data sets using independent samples t tests. The study found (a) that the mean reporting times were shorter for WVEDSS compared to WVEDSS-NBS (p < .05) for all vaccine-preventable infectious diseases (VPID) in Category II except for mumps; (b) that the 24-hour standard was not met for WVEDSS compared to WVEDSS-NBS (p < .05) for all VPID in Category II except for mumps, and (c) that most fields were complete for WVEDSS compared to WVEDSS-NBS (p < .05) for all VPID in Category II except for meningococcal disease. Healthcare professionals in the state can use the results of this research to improve the system attributes of timeliness and completeness. Implications for positive social change included improved access to public health data to better understand health disparities, which, in turn could reduce morbidity and mortality within the population.