Statistics and Epidemiology
A.Y. 2024/2025
Learning objectives
Acquire the basic statistical and epidemiological knowledge necessary to be able to understand and address the issues related to the organization, research and teaching in the health sciences of prevention.
Expected learning outcomes
At the end of the course students will be able to:
· Apply basic statistical analysis to data obtained with social and epidemiological research of a health nature;
· Apply the basic statistics to assess the quality of the services provided within the health prevention disciplines;
· Evaluate the results of interventions in the field of research and health promotion;
· Understand the main basic statistical and epidemiological analyzes reported in the scientific literature.
· Apply basic statistical analysis to data obtained with social and epidemiological research of a health nature;
· Apply the basic statistics to assess the quality of the services provided within the health prevention disciplines;
· Evaluate the results of interventions in the field of research and health promotion;
· Understand the main basic statistical and epidemiological analyzes reported in the scientific literature.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Prerequisites for admission
No prior knowledge required
Assessment methods and Criteria
The assessment of learning outcomes consists of a written test, taking place during specific exam sessions, as per the Rules. The test includes multiple choice questions.
All the modules comprised in the teaching contribute to determining the final mark, expressed on a scale of 30 as the weighted average of the marks obtained for each module.
No intermediate or early exam sessions are planned.
Teaching materials or notes are not allowed for consultation during testing.
The results are published on the ARIEL website of the master degree.
The assessment of learning outcomes consists of a written test, taking place during specific exam sessions, as per the Rules.
All the modules comprised in the teaching contribute to determining the final mark, expressed on a scale of 30 as the weighted average of the marks obtained for each module.
For the Medical Statistics part, written examination on Moodle-SEB which takes place in the Informatics Facilities of our University. The test is based on multiple quiz questions that cover the entire course program. Each question admits 5 possible close answers, among which only one is the right one. The maximum final score of the exam is 32, divided in 6 points from hypothesis testing (with small questions providing 1 o 2 points each) and 2 points for each of the remaining questions.
No intermediate or early exam sessions are planned.
The results are published on the ARIEL website of the master degree.
All the modules comprised in the teaching contribute to determining the final mark, expressed on a scale of 30 as the weighted average of the marks obtained for each module.
No intermediate or early exam sessions are planned.
Teaching materials or notes are not allowed for consultation during testing.
The results are published on the ARIEL website of the master degree.
The assessment of learning outcomes consists of a written test, taking place during specific exam sessions, as per the Rules.
All the modules comprised in the teaching contribute to determining the final mark, expressed on a scale of 30 as the weighted average of the marks obtained for each module.
For the Medical Statistics part, written examination on Moodle-SEB which takes place in the Informatics Facilities of our University. The test is based on multiple quiz questions that cover the entire course program. Each question admits 5 possible close answers, among which only one is the right one. The maximum final score of the exam is 32, divided in 6 points from hypothesis testing (with small questions providing 1 o 2 points each) and 2 points for each of the remaining questions.
No intermediate or early exam sessions are planned.
The results are published on the ARIEL website of the master degree.
Medical statistics
Course syllabus
- Evaluation of the reliability of methods of collecting and measuring data of biomedical interest
- The concept of trustworthiness of a measure, sample, population, estimate and parameter
- Causes of systematic errors and random errors
Variability: quantitative character variability within the individual and between individuals
- Descriptive methods: Interpretation of graphic representations of a distribution; the concepts of medium value,
dispersion, and for of a distribution; Calculation of the main location and dispersion indices of a distribution;
measurement accuracy and accuracy indices; quantiles (quartiles, centili) - Reference limits; Kappa Correlation and
statistics
- Gaussian model: Interpreting population data; characteristics of the Gaussian measurement error distribution model
- Screening tests: merging and intersection of events; probability; calculation of the probability of an event, the
intersection of independent events, and conditional events; logical basis of the screening test; definitions of falsely
positive and falsely negative outcome with respect to a diagnostic marker threshold value; sensitivity and specificity
of a diagnostic test or symptom; calculation and discussion of the concept of positive and negative predictive value;
likelihood report for a success (or failure) at the diagnostic test; concept of pre-test and post-test probability and
odds; Bayes' theorem
- Sample estimate of population parameters from data expressed in various ways; sample variability; distinguishing
between sample and population concepts; distinguishing between the sample prediction concepts of a parameter
and parameter of a population
- Sampling distribution: distribution of sample estimates; standard error meaning of a sample prediction
- Confidence interval and its meaning
- Hypothesis testing: error of I and II type; power of a test; logical basis of the sample size calculation; difference
between statistical significance and clinical significance; how to build a statistical test for assumptions about the
population average (known variance); Testing of independence between variables: the chi-squared
- Differences between deterministic model and probabilistic model; characteristics of the simple linear regression
model and the meaning of simple linear regression parameters; Taking a hypothesis test on the parameters of the
simple linear regression model; how to correct (adjust) for a confusing variable the association between two data
series
- The concept of trustworthiness of a measure, sample, population, estimate and parameter
- Causes of systematic errors and random errors
Variability: quantitative character variability within the individual and between individuals
- Descriptive methods: Interpretation of graphic representations of a distribution; the concepts of medium value,
dispersion, and for of a distribution; Calculation of the main location and dispersion indices of a distribution;
measurement accuracy and accuracy indices; quantiles (quartiles, centili) - Reference limits; Kappa Correlation and
statistics
- Gaussian model: Interpreting population data; characteristics of the Gaussian measurement error distribution model
- Screening tests: merging and intersection of events; probability; calculation of the probability of an event, the
intersection of independent events, and conditional events; logical basis of the screening test; definitions of falsely
positive and falsely negative outcome with respect to a diagnostic marker threshold value; sensitivity and specificity
of a diagnostic test or symptom; calculation and discussion of the concept of positive and negative predictive value;
likelihood report for a success (or failure) at the diagnostic test; concept of pre-test and post-test probability and
odds; Bayes' theorem
- Sample estimate of population parameters from data expressed in various ways; sample variability; distinguishing
between sample and population concepts; distinguishing between the sample prediction concepts of a parameter
and parameter of a population
- Sampling distribution: distribution of sample estimates; standard error meaning of a sample prediction
- Confidence interval and its meaning
- Hypothesis testing: error of I and II type; power of a test; logical basis of the sample size calculation; difference
between statistical significance and clinical significance; how to build a statistical test for assumptions about the
population average (known variance); Testing of independence between variables: the chi-squared
- Differences between deterministic model and probabilistic model; characteristics of the simple linear regression
model and the meaning of simple linear regression parameters; Taking a hypothesis test on the parameters of the
simple linear regression model; how to correct (adjust) for a confusing variable the association between two data
series
Teaching methods
The teaching is provided through frontal classroom lessons, scheduled according to a timetable published on the ARIEL website of the master degree.
Teaching Resources
- M. Pagano e K. Gauvreau Biostatistica (2ª edizione) Editore: Idelson-Gnocchi 2003
- M. Bland Statistica medica (Idee & strumenti) http://www.deastore.com/autore/Martin Bland.html Editore: Apogeo 2009
- JF. Jekel, DL. Katz, JG. Elmore, DMG. Wild Epidemiologia Biostatistica e Medicina Preventiva (3ª edizione) Editore: Masson 2009
- M. Bland Statistica medica (Idee & strumenti) http://www.deastore.com/autore/Martin Bland.html Editore: Apogeo 2009
- JF. Jekel, DL. Katz, JG. Elmore, DMG. Wild Epidemiologia Biostatistica e Medicina Preventiva (3ª edizione) Editore: Masson 2009
Hygiene and public health
Course syllabus
1. Meaning and use of the epidemiological method: from data analysis to programming and evaluation within the health system.
2. Using health and demographic data in epidemiology
- Main sources of health and demographic data
- Indicators: meaning and use
- Guided analysis of current health data
3. Frequency measurements:
- Ratios, proportions, rates;
- Concept of prevalence, incidence, incidence density, cumulative incidence
- Rate standardization
- Guided exercises
4. Study drawings and their application
- Ecological studies (or correlation studies) and their application: the search for differences. Case study.
- Prevalence studies and their application: case study
- Cohort studies and their application
- Case control studies and their application
Experimental studies
5. Association and impact measures: relative risk, odds ratio, risk attributable as an absolute measure and as a relative measure
6. Studies for the evaluation of preventive trials
- Epidemiological impact of vaccinations
- Evaluation and meaning of screening tests
7. Global Health
- Key concepts and definition of Global Health; its evolution from tropical medicine to public health and international health
- Global burden of disease, epidemiological transition and global indicators of progress in health; recent phenomena and the future of Global Haelth
- Socio-economic determinants of health
- UN Sustainable Development Goals (SDGs)
- TB as a model for Global Haelth
- World Health Organization and other actors; international cooperation; the big challenges: migration and climate change
2. Using health and demographic data in epidemiology
- Main sources of health and demographic data
- Indicators: meaning and use
- Guided analysis of current health data
3. Frequency measurements:
- Ratios, proportions, rates;
- Concept of prevalence, incidence, incidence density, cumulative incidence
- Rate standardization
- Guided exercises
4. Study drawings and their application
- Ecological studies (or correlation studies) and their application: the search for differences. Case study.
- Prevalence studies and their application: case study
- Cohort studies and their application
- Case control studies and their application
Experimental studies
5. Association and impact measures: relative risk, odds ratio, risk attributable as an absolute measure and as a relative measure
6. Studies for the evaluation of preventive trials
- Epidemiological impact of vaccinations
- Evaluation and meaning of screening tests
7. Global Health
- Key concepts and definition of Global Health; its evolution from tropical medicine to public health and international health
- Global burden of disease, epidemiological transition and global indicators of progress in health; recent phenomena and the future of Global Haelth
- Socio-economic determinants of health
- UN Sustainable Development Goals (SDGs)
- TB as a model for Global Haelth
- World Health Organization and other actors; international cooperation; the big challenges: migration and climate change
Teaching methods
The teaching consists of frontal classroom lessons, scheduled according to a timetable published on the ARIEL website of the master degree.
Teaching Resources
- Pontello M, Auxilia F. «Igiene, Medicina Preventiva e Salute Globale» Ed. Piccin
-Lopalco PL, Tozzi AE. «Epidemiologia facile» Il pensiero scientifico editore
-Skolnik R. Global Health 101, 3rd Edition. Jones & Bartlett Learning, 2016
-Lopalco PL, Tozzi AE. «Epidemiologia facile» Il pensiero scientifico editore
-Skolnik R. Global Health 101, 3rd Edition. Jones & Bartlett Learning, 2016
Hygiene and public health
MED/42 - HYGIENE AND PUBLIC HEALTH - University credits: 1
Lessons: 8 hours
Professor:
Raviglione Mario Carlo Battista
Medical statistics
MED/01 - MEDICAL STATISTICS - University credits: 3
Practicals: 8 hours
Lessons: 20 hours
Lessons: 20 hours
Professor:
Edefonti Valeria Carla
Educational website(s)
Professor(s)
Reception:
For meetings, please write an email.
via Celoria, 22, 20133 Milano