Course Unit Page

Academic Year 2021/2022

Learning outcomes

The learning objectives are: - To understand how the "health problem" is multidisciplinary, multidimensional and involves a variety of different agents that interact with each other in a complex way - To develop complex thinking skills regarding HL issues and reading simple computational simulations of health sector - Develop knowledge and skills for a correct risk assessment and informed decisions in the health sector - Develop knowledge in the preventive field, with a particular focus on the prevention of infectious diseases through vaccinations - Develop knowledge about current and possible applications in the health sector of Artificial Intelligence and big data

Course contents

Introduction to the course (2 hours) - Teacher Maria Pia Fantini Topics covered "Health and statistical literacy": what we need to know and know how to do to be responsible citizens and to protect our health and that of those who live next to us.

Choosing intuitively is not always the best choice: with particular reference to health protection, numbers can deceive us. The uncertainties of the real world and research: how can we live with them?

Module 1: "The science of forecasting and its impact in medicine" (12 hours) - Lecturers Eleonora Barelli and Riccardo Rovatti Topics covered The power of predictions: a success story in human history Complexity science and network theory to create the mathematical basis for an understanding of social phenomena Data, algorithms and predictions The construction of forecasting models and the spread of infectious diseases Big data, forecasting and artificial intelligence Artificial intelligence in medicine: state of knowledge, recent developments, opportunities and risks. Group work for the exploration of applications in the medical and health fields.

Module 2: "The importance of understanding risk, vaccines and tests: analysis of case studies in medicine" (10 hours) - Lecturers Davide Gori and Jacopo Lenzi Topics covered: Risk Assessment: How talking about absolute frequencies can be more understandable and useful for health-related decisions than referring to probabilities. How do health professionals and the media communicate? The case study of the birth control pill. "How to use numbers to understand the importance of so-called group immunity" to avoid the spread of infectious diseases. The measles case study Tests for clinical diagnosis, screening and health surveillance: the problem of false positives and false negatives. The SARS-CoV-2 / COVID-19 test case study Vaccine Hesitancy as a phenomenon linked to Health / Statistical Illiteracy. Presentation and discussion of mandatory and recommended vaccinations for the age group of young adults. Collective discussion and advice also on an individual basis, if desired, of the vaccination status of the students participating in the course. Professionals from the AUSL of Bologna and the AUSL of Romagna will also be involved in this lesson.



1. Acceleration and Alienation : Towards a Critical Theory of Late-Modern Temporality von Hartmut Rosa - Suhrkamp Insel Bücher Buchdetail [Internet]. [cited 2019 Oct 29]. Available from: https://www.suhrkamp.de/buecher/acceleration_and_alienation_-hartmut_rosa_58596.html?d_view=english

2. WHO | Glossary of terms used [Internet]. WHO. [cited 2019 Oct 29]. Available from: https://www.who.int/hia/about/glos/en/

3. Sørensen K, Van Den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: A systematic review and integration of definitions and models. Vol. 12, BMC Public Health. 2012.

4. Alessandro Vespignani, L'algoritmo e l'oracolo Come la scienza predice il futuro e ci aiuta a cambiarlo, Edizioni Le Scienze, 2020

5. Union PO of the E. Key competences for lifelong learning. [Internet]. 2019 [cited 2019 Oct 29]. Available from: https://op.europa.eu:443/en/publication-detail/-/publication/297a33c8-a1f3-11e9-9d01-01aa75ed71a1/language-en [https://op.europa.eu/en/publication-detail/-/publication/297a33c8-a1f3-11e9-9d01-01aa75ed71a1/language-en]

4. Gigerenzer G. Calculated risks: how to know when numbers deceive you [Internet]. New York: Simon & Schuster Audio; 2015 [cited 2019 Oct 29]. Available from: https://www.overdrive.com/search?q=B2B09D47-73A1-4B4E-9489-0655B719BF6D

5. Huff D, 3M Company. How to Lie with Statistics [Internet]. Place of publication not identified: W.W. Norton & Company; 2010 [cited 2019 Oct 29]. Available from: http://ebook.3m.com/library/neworleanspubliclibrary-document_id-hugdxz9

6. Ramesh AN, Kambhampati C, Monson JRT, Drew PJ. Artificial intelligence in medicine. Ann R Coll Surg Engl. 2004 Sep;86(5):334–8.

7. Preising B, Hsia TC, Mittelstadt B. A literature review: robots in medicine. IEEE Eng Med Biol Mag. 1991 Jun;10(2):13–22.

8. Hengstler M, Enkel E, Duelli S. Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices. Technol Forecast Soc Change. 2016 Apr 1;105:105–20.

9. WHO | Track 2: Health literacy and health behaviour. WHO. 2010;

10. WHO | Health literacy and the SDGs. WHO. 2016;

Teaching methods

24 hours in total (by virtue of the COVID-19 emergency, differently from what was previously declared, they will be carried out in their entirety in blended mode and with the part of the exercises in the presence) The 24 hours will be divided into 2 modules of 12 and 10 hours each with a general introduction lasting 2 hours.

Assessment methods

Candidates will be subjected to a final test with a result of thirty / thirty.

Teaching tools

Power point presentations, practical online workshops and a face-to-face exercise

Office hours

See the website of Maria Pia Fantini