This Epidemiology section will comprise a common body of studies followed by Minors and/or Majors. At the end of the M2, students will have a substantial understanding of epidemiological methods as well as a substantive specialty at the master's level.
Common body of studies will establish epidemiology as one of the pillars of public health and will give the student the elementary skills to understand the basics of epidemiology, function at an entry level and go forward to further epidemiologic studies. Specifically, the student will understand that the discipline covers a full range of disease occurrence and views causation from one end to the end, i.e. from molecular factors to social and cultural determinants of disease.
In specific terms, the course objectives will be for the student to be able to discuss:

• the role of epidemiology in the broader field of public health
• the principles of disease prevention within a population
• the terminology used in epidemiology and their precise definition and understanding
• the computation and interpretation of basic population measures of health and disease occurrence
• distinguish between basic measures of association, including odds ratio, risk ratio, rate ratio, incidence density ratio, attributable risk and population attributable risk
  

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

This minor will provide a more detailed overview of design, method, substantive and analytical issues pertaining to infectious disease epidemiology. It will cover:

• the epidemiology and control of tuberculosis; from a hereditary hypothesis to an infectious one; the evolution over time; the reality of transmission and prevention; control and rate computation; drug resistance and transmission; implications for control;
• the epidemiology of cholera; John Snow and lessons learned; the recent epidemics; waterborne diseases: how do we assess the risk?
• the epidemiology of HIV and AIDS; rates of transmission assessments; individual versus population risk; social networks (assortative, dissassortative); infection versus disease; international reality versus western; the debate about the virus; epidemiology of STI; the sexual networks
• the epidemiology of influenza: what is it; epidemic and variation; the vaccine: production, guess, assessment and risk; the national policies; trends and computations of trends: pros and cons; flu, avian flu, cold: what is it? transportation and flu: social networks.
  

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

This minor will provide a more detailed overview of design, method, substantive and analytical issues pertaining to infectious disease epidemiology.  It will cover:

• Infectious causes versus chronic slow causes
• Implications for causal thinking and analysis
• Issues of time
• The epidemiology of risk factors
  

Specific issues::

• Epidemiology of cancer: breast cancer risk among women; computation of risk; population versus individual risk; cancers in the western world; cancers and diet; trends in cancer; risk factors for cancer;
• Epidemiology of CVD; trends; CVD in the world; CVD and diet; risk factors
  

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

The majors are intended to be specialties in epidemiologic fields at the master?s level.� The majors include 3 modules: the first 2 are methodological in nature, advanced in content and reasoning, and meant to delve into methodological advances in the field of epidemiology.
Major A will be conceptual and methodological::
1- Causal inference in Epidemiology
2- Practical framework: developing hypothesis
3- Designs: experimental and Cohort
4- Design: Case control, nested case-control and case-cohort studies
5- Design: Ecological, cross-sectional
6- Operationalization of hypotheses
7- When to act? When is enough enough?

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

Major B will be analytical and will bridge biostatistics and epidemiology. In other words, it will provide the epidemiological explanation and rationale as well as the tools behind certain analytical decisions.
1- Analytical approaches: Equal observation periods
2- Analytical approaches: Unequal observation periods
3- Sampling and Power
4- Measurement error in Epidemiology and its impact
5- Matched designs and analysis
6- Life table and survival analysis
7- Proportional hazards in epidemiology
8- Age cohort period effect and Poisson regression

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

Major C will be substantive and will cover an area of interest of the student. S/he will choose between the fields above (Cardiovascular disease, Cancer, Psychiatric…).  Not all fields will be offered every year.  As an example, a highly specialized course on cardiovascular disease (CVD) epidemiology will be offered the first year and will cover:
1- Global challenge and recent trends
2- The epidemiologic transition of CVD
3- Stroke and cardiovascular disease
4- Pathophysiology of CVD
5- Atherosclerosis and subclinical CVD
6- Lipids, lipoproteins, diet
7- Genetics of CVD
8- Lifecourse and social factors
9- Interpretation of diagnostic data in epidemiology: the case of ECG
10- Infections, inflammation and CVD
11- AIDS and CVD
Group works and practical real-life exercises will be integrated in the teaching at various levels.

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

This module provides an overview of methodological approaches and their applications, bearing in mind their present day and future impact on public health. Three topics, namely biostatistics, mathematical and computational modelling and information sciences, are covered, with special emphasis on applications to public health. For each topic, the course goes over historical developments, the state of the art and potential future directions. Furthermore, a conference deals with the present situation in Europe for each topic.

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

Individual-based stochastic models are one of the modelling approaches with a growing use in public health during these last years. They represent an appropriate and powerful tool for the simulation of dynamics involving individual characteristics and behaviours of populations.
This course will present in more details individual-based models and related simulations schemes introduced in the minor "Mathematical and computational modelling", as well as methodological points and interpretation of results that these kinds of models raise. The course will also address different approaches for approximations of stochastic dynamics. A particular attention will be paid to numerical optimisation methods used for parameter estimation.

Workload and ECTS

Class workload	Total workload	ECTS
30	30	3

Integrative methods, widely used over the past years, are techniques that allow taking into account simultaneously the complexity of mechanisms involved and the increasing amount of data available in most of biomedical and health related problems.

This course presents integrative approaches to the analysis of dissemination of infectious diseases. It deals with phylodynamics, intra-host models (interactions between the immune system and the infectious agent), inter hosts models (epidemics) and the integration of all these aspects through specific examples.

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

The main purpose of this course is to illustrate the interplay of the various fields (biostatistics, theoretical modelling and information sciences) in the analysis of a specific public health problem.
This synthesis is performed through a series of lectures and practicals by one of the leading authorities in the domain.

Workload and ECTS

Class workload	Total workload	ECTS
30	90	3

Data may present several levels of variability (individual, geographic ?). To analyse this type of data and extract the maximum of information, it is necessary to take into account different sources of variability in the model. Hierarchical models (generalizing mixed models) are able to take into account the hierarchical structure of data when estimating parameters. This course will present the different steps needed to model hierarchical data; a particular attention will be paid to the choice of prior distribution and the procedure maximizing parameters estimation. This course will allow students to get used to hierarchical models through appropriate examples from public health.

Charge de travail et ECTS

Heures de cours	Charge totale de travail	ECTS
30	90	3