Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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I sem. | Oct 2, 2017 | Jan 31, 2018 |
II sem. | Mar 1, 2018 | Jun 15, 2018 |
Session | From | To |
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Sessione invernale d'esami | Feb 1, 2018 | Feb 28, 2018 |
Sessione estiva d'esame | Jun 18, 2018 | Jul 31, 2018 |
Sessione autunnale d'esame | Sep 3, 2018 | Sep 28, 2018 |
Session | From | To |
---|---|---|
Sessione Estiva Lauree Magistrali | Jul 19, 2018 | Jul 19, 2018 |
Sessione Autunnale Lauree Magistrali | Oct 18, 2018 | Oct 18, 2018 |
Sessione Invernale Lauree Magistrali | Mar 21, 2019 | Mar 21, 2019 |
Period | From | To |
---|---|---|
Christmas break | Dec 22, 2017 | Jan 7, 2018 |
Easter break | Mar 30, 2018 | Apr 3, 2018 |
Patron Saint Day | May 21, 2018 | May 21, 2018 |
Vacanze estive | Aug 6, 2018 | Aug 19, 2018 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff

Bloisi Domenico Daniele
domenico.bloisi@univr.itStudy Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.
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1° Year
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2° Year
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Epidemiological methods and clinical epidemiology (2017/2018)
Teaching code
4S004562
Academic staff
Coordinatore
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
MED/01 - MEDICAL STATISTICS
Period
I sem. dal Oct 2, 2017 al Jan 31, 2018.
Learning outcomes
The course aims to provide the theoretical and practical tools to assess the frequency of diseases in human populations and the associated risk factors, including expertise in epidemiology, biostatistics and information technology applied to the analysis of biomedical data.
At the end of the course the student must demonstrate to have acquired knowledge and skills concerning the main designs of an epidemiological study, the statistical methods for the analysis of biomedical data and the programming syntax of a statistical software (STATA).
In particular, at the end of the course the student must demonstrate to: a) know the statistical techniques used for the analysis of biomedical data; b) be able to perform data analysis using a statistical software (STATA); c) be able to interpret the results obtained. This knowledge will enable the student to choose the appropriate statistical methods in relation to the type of data and the study design.
At the end of the course the student must demonstrate to be able to clearly and concisely communicate the results of an analysis of biomedical data. The student will also be able to apply autonomously the statistical and epidemiological methods learned in the course to different biomedical problems.
Program
The course is structured in theoretical frontal lessons (32h) and in practical lessons (24h) on the use of a statistical software (STATA) for the quantitative analysis of biomedical data.
1. Introduction to epidemiology
- Definition and key features
- Traditional classification of epidemiology
- John Snow and cholera outbreaks in London
2. Measures of occurrence
- Outcomes
- Prevalence
- Cumulative incidence
- Incidence rate
3. Measures of association and public health impact
- Determinants
- Epidemiological associations
- Attributable risk (AR) and AR%
- Relative risk (RR) and Odds ratio (OR)
- Effect modification
4. Types of epidemiological studies
- Ecological studies
- Cross-sectional studies
- Cohort studies
- Case-control studies
- Experimental studies
5. Causal interpretation of an empirical association
- Statistical vs. causal associations
- Causal models in epidemiology
- Validity of a study (random error, bias, confounding)
- Types of bias
- Methods to control confounding
- Hill’s positive criteria for causality
6. Health prevention, screening and diagnostic tests
- Primary, secondary, tertiary prevention
- Validity and performance of a diagnostic test
7. Principles of inference
- Principles of sampling
- Point estimate and sampling distribution
- Confidence interval
- Hypothesis test
- Test of significance
8. Stratified analysis
- Effect modification vs. confounding
- Stratum-specific estimates
- Testing homogeneity
- Pooled estimate
- Testing the stratified null hypothesis of no association
9. Basic statistical models in epidemiological research
- Linear regression model
- Logistic regression model
10. Statistical methods for survival analysis
- Kaplan-Meier non-parametric estimator
- Cox regression model
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
Marubini E, Valsecchi MG | Analysing Survival Data from Clinical Trials and Observational Studies | John Wiley & sons | 1995 | ||
Pearce N | A short Introduction to Epidemiology (Edizione 2) | 2005 | https://vula.uct.ac.za/access/content/group/9c29ba04-b1ee-49b9-8c85-9a468b556ce2/DOH/Module%202%20(Bio_Epi)/Epidemiology/EPIDEMIOLOGY/Pearce.pdf | ||
Hennekens CH, Buring JE | Epidemiology in Medicine | Lippincott Williams & Wilkins | 1987 | ||
McCullagh P, Nelder JA | Generalized Linear Models (Edizione 2) | Chapman and Hall/CRC | 1989 | ||
Rothman KJ, Greenland S, Lash TL | Modern Epidemiology (Edizione 3) | Lippincott Williams & Wilkins | 2008 | ||
Glantz SA | Statistica per Discipline Biomediche (Edizione 6) | McGraw-Hill | 2007 | 9788838639258 |
Examination Methods
The final test is a written exam in computer lab. The test is the same for attending and non-attending students.
The aim of the test is to verify the knowledge of all the topics discussed and the ability to solve a biomedical problem by analyzing health data using the statistical software STATA.
The commands, results and interpretation of the analysis are reported in written form. In addition, students have to answer some questions to ascertain the understanding of theory.
The final evaluation is expressed in thirtieths.
Type D and Type F activities
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.
Graduation
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.Please refer to the Crisis Unit's latest updates for the mode of teaching.