Courses 2008

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    UiO, November 12-14 2008

    The course is intended to give a conceptual understanding of the basic techniques available for analysing and interpreting epidemiological data on infectious diseases. The course should provide the participants the background for reading and interpreting modelling papers.

    An introduction to compartmental models, exemplified by the Susceptible-Exposed-Infected-Recovered (SEIR) model; presentation of fundamental epidemiological concepts such as the basic reproductive rate of infection (R_0); endemic infections and vaccination policies; impact of population structure and human contact patterns on the transmission dynamics of infections; stochastic models; emerging infections with focus on design of intervention programmes. In the group discussion we will discuss how to calculate the basic reproductive rate, vaccine scare and impact of vaccine coverage on infectious disease development, and we will look at influenza strain drift.

    Course committee: Birgitte Freiesleben de Blasio, Ottar Bjørnstad, Odd O. Aalen, Department of Biostatistics, Institute Group of Basic Medical Sciences, University of Oslo.

  • Graphical and Causal Modelling in Genetics and Epidemiology
    UiO, June 11-13, 2008

    The fascinating idea of Mendelian randomization has in recent years emerged as a potentially important tool in epidemiology. Could the absence of designed randomization in epidemiology be substituted by nature’s own randomization? This and other timely subjects are taken up in the present course. The main statistical methods presented belong to the area of graphical models, which is a tool for describing the relationship between variables, genes and other entities in genetics and epidemiology. Such models are increasingly used due their nice representation of statistical relationships, and the insights one may get from them. They provide a natural general framework for expressing and manipulating many important concepts. Genetic mapping and pedigree uncertainty can all be handled in this context, as can issues of causal inference and identification of regulatory networks. There is a close relationship between graphs and causal thinking. Hence, causal modelling will also be a major topic in the course. In addition to its relationship to graphical models, causal modelling will also be introduced in a broader sense, including counterfactual and structural models.

    Teachers: Vanessa Didelez, Dept. of Mathematics, University of Bristol and Nuala Sheehan, Dept. of Health Sciences, University of Leicester
    For more details, see the Programme of the course.
    Organizers: Thematic research area BMMS and Statistics for Innovation (sfi)².

  • Multiple hypothesis testing - theory and applications to genomics.
    UiO, February 28-29 2008

    The University of Oslo Graduate School in Biostatistics announces a two days course on Multiple hypothesis testing - theory and applications to genomics. The lecturer at the course is associate professor Mette Langaas from The Norwegian University of Science and Technology (NTNU) in Trondheim. Students from the collaborating departments as well as others are welcome to take part in the course. A project exam will be given after the course. For those who complete the project exam, the course will give 2.5 ECTS credit points.
Innovation Areas