2nd module

Prof. Andrea Pugliese
A.A. 1998/99

Topics and aims of the course

 The second part of Biomathematics is a monographic course, where
mathematical models of a particular biological system are studied in
detail; thus students will be introduced to current research.
 In the Academic Year 1998/99, the application of epidemic models to
existing data on measles (in Italy, in Trentino, and others) will be
considered. The method used in the course will be problem based learning
(PBL). According to that approach, the students (organized in one or
several groups) will be asked to perform some tasks. Through the discussion
and solution (the teacher will provide help and reference to the
literature, when appropriate) of the problems, the students should acquire
a good competence in the analysis of models and data more and more complex.
As a goal of the method and of the course, this competence should be
transferable to other contexts.


 Because of the didactic method, the following program is only tentative;
it is possible that other kinds of models or problems arise from the
discussion; or that some of the following topics will be ignored:
* application of simple SIR models to simulated data
* deterministic models and stochastic phenomena
* application of simple SIR models to real data. Possible complications:
seasonality in contacts, age of infected individuals, data on several
spatial scales, latency period, temporary immunity
* review of existing literature on SIR models with some of the previous
complications; and on application of SIR models to data
* vaccination against measles and other infectious diseases: general
* vaccination against measles: search for optimal strategies


Written tasks, including reference to texts, will be given to students.


Students taking part to the course will have to perform (in groups) the
tasks given, and prepare written reports of the activities. The final
evaluation will be based on this work, and on a short oral exam concerning
the main topics dealt with during the course.