Ateneo - UPO

The integrated course provides the fundamental concepts of statistics and epidemiological methodology applied to public health and biomedical research. The topics covered include: descriptive and inferential statistics, confidence intervals, hypothesis testing, correlation, and linear regression; general principles of hygiene and public health; epidemiological methods and study designs, measurement of disease frequency and association, sources of bias, and causal inference; systematic reviews and meta-analyses; evidence-based medicine (EBM); drug development, pharmacoepidemiology, and pharmacovigilance; relationship between climate change and health; structure of a scientific article, scientific publishing system, and ethics of research.

For Statistical Methods for experimental studies module:
Whitlock MC, Schluter D. Analysis of Biological Data. Zanichelli, 2010.
For Epidemiology module:
Barbuti, Fara, Giammanco. Igiene, medicina preventiva, Sanità Pubblica. Edises Editore, 2022.
Rothman. Epidemiology: An Introduction. Oxford Press (Italian edition: Rothman. Epidemiologia. Idelson - Gnocchi).

The integrated course aims to provide students with the methodological, statistical, and epidemiological tools necessary for the design, analysis, and critical interpretation of biological and medico-health studies. At the end of the course, students will be able to statistically describe experimental data, identify and perform appropriate statistical tests based on the biological hypothesis, understand data sources and epidemiological study designs, evaluate sources of bias and causality in medicine, and critically interpret evidence from systematic reviews, meta-analyses, and scientific literature.

Basic knowledge of mathematics for statistics module. No additional specific prerequisites are required.

Interactive lectures alongside practical exercises dedicated to the concrete application of acquired theoretical concepts in statistics and epidemiology

Teaching materials used in class and exercises will be made available on the DIR platform.
Students with disabilities, DSA, BES, once they have contacted the University Staff, can contact the teacher in charge of the course in relation to the declination of the exam methods, regarding the teaching aspects.

The examination is held in written form and evaluates the competencies acquired in both modules:
Statistical Methods Module: Written exam consisting of 4/5 numerical and conceptual exercises divided into multiple sub-questions, along with simple theoretical questions. Each sub-question is assigned a weight between 0.5 and 3.5 depending on difficulty, for a total sum of 31 points. The score of each sub-question (from 0 to 1) multiplied by its weight determines the final grade for the module, passed with a minimum total of 18/30. Calculators, distribution tables, and a formula sheet provided on the DIR platform are allowed during the exam.
Epidemiology Module: Written exam with multiple-choice questions, open questions, and numerical exercises designed to evaluate the ability to calculate fundamental epidemiological measures and interpret meta-analysis results.
The final grade is determined taking into account the achievement of the expected learning outcomes of all modules of the integrated course. The student will pass overall if they achieve a passing grade in both modules. The grade 30 cum laude is awarded when the exam is passed with 30 in both modules.

Module: Statistical Methods for Experimental Studies
Descriptive statistics: Types of variables, frequency tables, measures of location and dispersion.
Probability and distributions: Basics of probability and normal distribution.
Uncertainty and estimates: Confidence intervals.
Hypothesis testing: General principles of hypothesis testing; Hypothesis testing for a mean and for proportions; Chi-square test; Student's t-test for independent and paired samples; ANOVA test for comparing more than two means.
Relationships between variables: Overview of correlation and simple linear regression.
Module: Epidemiology
General principles of Hygiene: Definition of Hygiene and Public Health; concept of health and its evolution.
Epidemiological methods for public health: Sources and data collection methods, data processing and presentation; Health status indicators: incidence, mortality, prevalence, survival; Measures of frequency and association.
Epidemiological study designs: Clinical trials, cohort studies, case-control studies, cross-sectional and descriptive studies.
Quality and causality evaluation in studies: Sources of uncertainty: role of chance, bias, and confounding; Effect modification; Causal inference in epidemiology.
Evidence synthesis and evaluation of healthcare interventions: Systematic reviews and meta-analyses; Evaluation of healthcare interventions efficacy and Evidence-Based Medicine (EBM).
Pharmacoepidemiology and Pharmacovigilance: Drug approval process, adverse drug reactions, and introduction to pharmacoepidemiology.
Special topics and ethics: Relationship between climate change and health; Structure of an epidemiological article, scientific editorial system, and ethical aspects of epidemiological research

At the end of the course the student must have acquired the knowledge and full understanding of the topics deriving from the achievement of the educational objectives of each of the two teachings of the integrated course.
EPIDEMIOLOGY Knowledge and understanding: To know the most important sources of epidemiological data. To understand the elements in the design and conduct of the most important types of epidemiological studies. To know the most important sources of bias in epidemiological studies. To understand the criteria for characterizing the causality of associations in Medicine. To know the key features of a systematic review of the scientific literature to know the most important determinants of health in Italy and worldwide. To know the key features of the process of drug discovery and development. to understand the key features of Evidence-Based Medicine. To know the key features of National Health Systems. Applying knowledge and understanding: To be able to calculate measures of frequency and association; to able to interpret the results of a meta-analysis
STATISTICAL METHODS FOR EXPERIMENTAL STUDIES Knowledge: At the end of the course the students will know the main descriptive and inferential statistical analysis techniques Skills: Students will be able to describe the results deriving from a biological experiment and carry out the correct statistical test based on the biological hypothesis that guided the experiment carried out. They will also be able to understand the results reported in a scientific article regarding regression. Transversal skills: Students will be able to understand the statistical analysis and the results reported in a scientific article in order to verify what is already known in the literature about a specific biological question of interest and compare the results obtained with those available in the scientific literature.