Veckodisposition

  • General

    Epidemic modelling, simulation and statistical analysis (7.5 ECTS)

    We are happy to announce a new BGC-Network course during autumn 2015. The BGC network is a Nordic Biostatistics Graduate Course network between the four capital universities of the Nordic countries: Copenhagen, Helsinki, Oslo and Stockholm. For more general information about the network and its courses, click here.

    The current course is an intensive course given during two separate intensive weeks in November 2015 – see below for details.

    Dates

    The two full time weeks are: 02-06 November 2015 and 23-27 November 2015. Furthermore, the course

    consists of preperational work before the course weeks and project work during, between and after the two full

    weeks (workload corresponding to a 7.5 ECTS course).

    Location

    All teaching will take place at the Department of Mathematics at Stockholm University, Stockholm, Sweden. See http://www.math.su.se/om-oss/hitta-till-oss for information on how to find the location.

    All teaching will take place in House 5 at the campus 'Kräftriket' (Roslagsvägen 101) – a detailed map can be found here. The exact room varies each day and can be found as part of the TimeEdit schedule and the Syllabus linked below.

    Teachers

    • Tom Britton, Department of Mathematics, Stockholm University

    • Lisa Brouwers, Public Health Agency of Sweden (Folkhälsomyndigheten)

    • Tobias Fasth, Public Health Agency of Sweden (Folkhälsomyndigheten)

    • Michael Höhle, Department of Mathematics, Stockholm University

    • Sharon Kühlmann-Berenzon, Public Health Agency of Sweden (Folkhälsomyndigheten)

    Course Aim

    After finishing the course the students are expected to:

    • Have a broad understanding of a statistical approach to epidemic modeling

    • Understand how deterministic and stochastic epidemic models differ

    • Be comfortable in using the Vensim software or R for producing system dynamic simulations, especially SIR-models

    • Use the R software environment to analyze outbreak and surveillance data


    More information about the course contents can be found in the item 'Syllabus' below.

  • Week 1: 02-06 November 2015

    Prior reading to do before week 1:

    • Britton, T. (2010). Stochastic epidemic models: a survey. Math. Biosci, 225, 24-35.

    • SD modeling compendium – chapters 1, 2 and 4.

    Vensim information

    • Information about how to download and install the software Vensim PLE is available in a step-by-step instruction: (see pdf file below)
    • Tutorials on how to create system dynamic models in Vensim are available here: (see pdf files below)

    Hand-In Exercise

    • The hand-in exercise of week 1 consists of two separate parts with deadlines 04 Nov and 11 Nov 2015, respectively. Please see the PDF file below for details.
  • Week 2: 23-27 November 2015

    Prior reading to do before week 2:

    • S. Meyer, L. Held, M. Höhle (2014), Spatio-Temporal Analysis of Epidemic Phenomena Using the R Package surveillance, http://arxiv.org/abs/1411.0416.

    • M. Salmon, D. Schumacher, M. Höhle (2015), Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance. To appear in Journal of Statistical Software, http://arxiv.org/abs/1411.1292.

    Hand-In Exercise

    • The hand-in exercise of week 2 consists of two separate parts with deadline 09 Dec Nov 2015. Please see the PDF file below for details.

  • Project work

    Students will work together in groups of 3-4 persons. The project consists of three deliverables:

    1. Create a project group, choose a project, and write a plan (see example below) that describes what needs to be done for carrying out the project. This will be done during the first week of the course. Deadline: Thursday, November 5 at 23:59 GMT+1.
    2. During the time between the first and second weeks of the course, carry out the project and write the report on the work done. The reports should be turned in electronically in pdf format and be written in a pedagogical style. Details on the format of the report are found on the course webpage as the item Report structure.pdf. Make clear if the assumptions or the data are taken from literature, in which case it must be referenced, or if it is your own guesses. Deadline for the report: Wednesday, November 25 at 23:59 GMT+1.
    3. Present the results during the seminar session on Friday, November 27, i.e. in the second week of the course. The oral presentations should be approximately 20 min long.  Another group will oppose the presentation during 5-10 min.

    The links below contain more information on the six project proposals.