Find your programme or course by following the steps

Step 1/4:

I am looking for a …

Programme

Choose

Course

Choose

Step 2/4:

My research background:

I have no research experience

Choose

I have research experience

Choose

Step 3/4:

I am interested in the following discipline:

Epidemiology

Choose

Clinical Epidemiology

Choose

Genetic Epidemiology

Choose

Public Health

Choose

Pharmaco Epidemiology

Choose

Health Economics

Choose

Clinical Research

Choose

No specific interest

Choose

Step 4/4:

I am interested in following a programme:

Full-time

Choose

Part-time

Choose

Step 2/4:

I am interested in the following discipline:

Advanced Statistics

Choose

Biostatistics

Choose

Clinical Epidemiology

Choose

Clinical Research

Choose

Epidemiology

Choose

Genetic Epidemiology

Choose

Health Economics

Choose

Methodology

Choose

Pharmaco Epidemiology

Choose

Public Health

Choose

Step 3/4:

I am looking for a course on this level:

Basic

Choose

Intermediate

Choose

Advanced

Choose

Step 4/4:

I want to follow a course in this time-frame:

Summer (July August September)

Choose

Autumn (October November December)

Choose

Winter (January February March)

Choose

Spring (April May June)

Choose

Your result based on your answers

Didn't find what you were looking for?

Try again!

Programme overview (based on your choices)

Erasmus Summer Programme (ESP)

For more information about the Erasmus Summer Programme (ESP), please go to:

www.erasmussummerprogramme.nl

Master

Master of Science in Health Sciences | 1 Year | FULL-TIME | 70 ECTS

For whom?

This MSc programme focuses on training students who are already educated in research methodology, but wish to take a step further in developing a successful career in health science research. This programme is also interesting if you want to enhance your chances of pursuing a PhD.

Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Biostatistics
  • Medical Psychology
  • Research Master in Clinical Research | 2 Years | FULL-TIME | 120 ECTS

    For whom?

    There is a great need for clinicians who can combine patient care and research. This Research Master programme is a unique opportunity for medical students to become clinical investigators and pursue an academic career simultaneously.


    This programme for ambitious students with a Bachelor degree in Medicine or Biomedical Sciences. If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

    Read More

    Research Master in Health Sciences | 2 Years | FULL-TIME | 120 ECTS

    For whom?

    Just graduated with a Bachelor Degree in clinical, public health or biomedical sciences and want to start making substantial contributions to future developments in medicine as a researcher? Then this Research Master is for you! With a wide range of specialisations and guidance from some of the greatest minds in these fields, you will be well on your way to a very successful research career.


    If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Health Economic Analysis
  • Doctorate

    PhD Programme | 4 Years | FULL-TIME

    For whom?

    This content of this programme will be published soon. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Postgraduate Programme | 1 Year | FULL-TIME

    For whom?

    Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Senior Advanced PhD Programme

    For whom?

    The content of this web page is currently under construction. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Pharmaco Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Executive Education

    Executive Master of Science in Health Sciences | 2(+)years | Part-time | 70 ECTS

    For whom?

    This Executive Master programme focuses on training individuals who have already  authored scientific publications, but wish to take a step further in developing a successful career in health science research. The programme is ideal for working professionals since you can fully customize it to fit your busy schedule.

    Read More
  • Epidemiology
  • Clinical Epidemiology
  • Genetic & Molecular Epidemiology
  • Public Health Epidemiology
  • Pharmaco Epidemiology
  • Biostatistics
  • Medical Psychology
  • Courses

    29 May 2018 - 15 Jun 2018
    Introduction to Medical Writing [SC02]

    About this course

    During the second semester, full time Master of Science (70 ECTS) students will attend four workshops of three hours and one workshop of six hours on how to write correct and readable scientific articles in English. Each student will be able to bring their own work which will be commented on and corrected by participants and the teacher.

    Read More

    29 Jan 2018 - 02 Feb 2018
    Pharmaco-epidemiology and Drug Safety [EWP03]

    About this course

    Pharmaco-epidemiology plays a role of increasing importance in the field of drug safety and regulatory decision making. On the one hand, the introduction of computers into clinical practice facilitates the performance of large-scale cohort studies and nested case-control studies. On the other hand, it creates some problems regarding the quality of outcome and exposure assessment. Because the commercial consequences of pharmaco-epidemiological studies may be enormous, discussions in this area may be heated.


    In this course, referring to established drug safety problems will highlight some of the complex aspects of outcome and exposure assessment in pharmaco-epidemiology.


    Teaching Methods

    Plenary teaching as well as computer exercises on the analysis of cohort- and case-control data.

    Read More

    29 Jan 2018 - 02 Feb 2018
    Environmental Epidemiology [EXC05]

    About this course

    This intensive 3,5 day module focuses on methodologies in environmental epidemiology with examples from current topics such as air pollution, exposure assessment, cluster analysis, risk assessment using occupational epidemiology, consequences of climate change on health, uses and misuses of GIS, conflicts and disasters. Most public health epidemiology courses neglect or gloss over environmental hazards, including the role of occupational epidemiology, and this module is designed to redress the balance.


    Lecturers will introduce the topics. Teaching will be comprised ofone-hour lectures and practical sessions. Students will work in small groups inthe practical sessions, which will take a variety of forms, includingadditional lectures, group work, discussions and data interpretation andcalculation. Students are expected to read around topic areas.

    Read More

    26 Mar 2018 - 30 Mar 2018
    Planning and Evaluation of Screening [HS05]

    About this course

    This course focuses on the design and the evaluation of health care programmes for the early detection of disease or screening. Screening takes place in a population without symptoms of the disease. The screening test characteristics have consequences for the favourable (improvement of prognosis by early detection, life years saved and deaths prevented) and unfavourable (overdiagnosis, unnecessary treatments) effects of screening.


    There are a number of designs for the assessment of the effectiveness of screening, such as randomized-controlled trials, observational prospective studies and case control studies. The pros and cons of each of these designs will be discussed. Evaluation methodologies, such as cost-effectiveness, cost-utility and technology assessment will be explained, including the concepts of quality adjustment of life years and of time preference. Detailed case studies include cervical, breast and prostate cancer screening, genetic screening, youth health care and screening for tuberculosis, e.g. for high risk groups. Several computer aids for the evaluation of screening are presented.

    Read More

    26 Feb 2018 - 02 Mar 2018
    Advanced Clinical Trials [EWP10]

    About this course

    The Randomized Controlled Clinical Trial (RCT) is the most reliable  method of assessing the efficacy and effectiveness of interventions. In order to provide the best possible evidence-based health care, health professionals must be able to judge the scientific merits and clinical relevance of published RCTs. In addition, they may be involved in designing and performing a RCT and are frequently asked to recruit patients for RCTs.

    Reports published in major medical journals show a surprising variability in methods including choice of study design, blinding, avoidance of bias, outcome measures, effect parameters, sample size calculations, data analysis techniques, presentation of results in tables and figures, and inferences made from the results. Hence, appraising trial reports can be challenging. In designing RCTs many difficult decisions need to be made with respect to these same issues.

    In this course these topics and issues will be addressed and developed through lectures and group practical sessions. A laptop during classroom sessions is required in order to do the practical assignments.


    Read More

    26 Feb 2018 - 02 Mar 2018
    Chronic Disease [EXC08]

    About this course

    The theme of the module is cardiovascular disease: from aetiology to public health. It is assumed that participants will have basic understanding of general epidemiologic principles before starting on this module. The emphasis will be on learning to recognise and evaluate the epidemiologic basis for policy and practice in cardiovascular disease prevention.


    In the time available, it will obviously not be possible to cover comprehensively the topics listed, but simply to provide an introduction to the main issues in CVD epidemiology.


    Proposed general areas to be covered:

    • International, national and secular trends;
    • Risk factors including diet;Epidemiologic including intervention studies;
    • Current controversies and new ideas;
    • Strategies for prevention and public health policy.

    Read More

    23 May 2018 - 25 May 2018
    Cardiovascular Epidemiology [EP20]

    About this course

    Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. The overall objective of the cardiovascular epidemiology course is to produce epidemiologists and other health scientists with the essential knowledge to carry out high quality research in cardiovascular disease.

    Read More

    23 Apr 2018 - 26 Apr 2018
    From Problem to Solution in Public Health [HS18]

    About this course

    The current challenges in public health require a strong link between science, policy and practice. This link is bi-directional. Professionals in practice can use their vast experience to guide better and more targeted research. Policy makers can identify which solutions may work or not and researchers can provide better evidence for public health programmes.


    In two Master Classes experienced researchers and policy makers will work together with participants on major public health problems. The public health problems selected are addiction & substance use, and injuries. Through intensive interaction participants will learn (1) how to make a comprehensive analysis of the problem, (2) how this analysis will guide the required evidence-base for tackling the problems, and (3) how to plan and evaluate appropriate preventive interventions.


    The Master Classes are restricted to 25 participants and will require an intense, active participation.

    Read More

    23 Apr 2018 - 26 Apr 2018
    Biostatistical Methods I: Basic Principles Part A [CC02A]

    About this course

    The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Biostatistical Methods I: Basic Principles is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software package SPSS to work through exercises.


    In CC02 part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures.


    During the lectures, time will be spent on practical examples and exercises. SPSS will be introduced. Throughout the course, examples of SPSS-programs and -output will be demonstrated in relation to the several topics that will be discussed.


    The courses Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22) are equivalent to Biostatistical Methods I: basic principles, part A (CC02A).

    Read More

    22 Jan 2018 - 26 Jan 2018
    Advanced Topics in Decision-making in Medicine [EWP02]

    About this course

    This course deals with intermediate- to advanced level topics in the field of medical decision making. Topics that will be addressed include building decision models, evaluation of diagnostic tests, utility assessment, multi-attribute utility theory, Markov cohort models, microsimulation state-transition models, calibration and validation of models, probabilistic sensitivity analysis, value of information analysis, and behavioral decision making. The course will focus on the practical application of techniques and will include published examples and a computer practicum. Students will learn to apply state-of-the-art modeling methods (students may choose to use  either Treeage or R (or both)) to evaluate the comparative effectiveness and cost-effectiveness of health interventions. While the primary emphasis is on application, essential underlying theoretical concepts will also be discussed. During the course you will have the opportunity to work on a decision problem which you select yourself. Many students use the course as a way to start writing a paper on a decision model in the field of their interest.

    Please note: this is a challenging course. 

    Read More

    20 Feb 2018 - 23 Feb 2018
    Principles of Epidemiologic Data-analysis [EWP25]

    About this course

    The course will present the basic precepts and the principles underlying the primary methods of epidemiologic data analysis. The aim of the course is for the participant to arrive at a coherent conceptualization of the core principles of epidemiologic data analysis. This is not a statistics course; although examples of analytic calculations are given and there are lab exercises assigned for homework, there is no emphasis on proficiency in the execution and calculation of results nor how to build mathematical models.The course begins with a discussion of the principles of epidemiologic data analysis, and then progresses to a discussion of precision and validity, placing a strong emphasis on a quantitative approach to analysis, using estimation, rather than a qualitative approach based on statistical significance testing. After covering the analysis of crude data, the focus shifts to the control of confounding using stratified analysis and multivariate models. Other topics that are covered include the analysis of matched data, the evaluation of interaction, the use of multivariate summary confounder scores (including propensity scores), marginal structural models, imputation of missing data, sensitivity analysis, and the estimation of trends in effect.The class presentations will be supplemented with discussion of selected published papers and computer assignments using the Episheet spreadsheet to illustrate key analytic concepts.


    Teaching Methods

    The course consists of lectures, case studies involving reading and classroom discussion, and assignments using a spreadsheet for epidemiologic data analysis, which is supplied.

    Read More

    19 Mar 2018 - 23 Mar 2018
    Using R for Statistics in Medical Research [BST02]

    About this course

    R has recently become one of the most popular languages for data analysis and statistics. This course teaches students the basics syntax and data types of this statistical programming language. The aim of this course is to equip students with the R knowledge needed to explore their own data, make data visualizations and perform basic statistical analysis.


    The course covers practical issues in statistical computing which includes reading data into R, bringing them in the correct structure and writing R functions. This course further focuses on the concepts and tools behind reporting data analyses in a reproducible manner and building simple interactive web applications. In particular, useful features will be introduced such as debugging code, version control using git, markdown reports and shiny apps.

    Read More

    19 Feb 2018 - 23 Feb 2018
    Preventing Failed Interventions in Behavorial Research [MP05]

    About this course

    This course elaborates on intervention development, implementation and evaluation in the field of medical psychology. The focus is on learning from encountered difficulties, mistakes en failures from previous research and researchers. Questions that will be discussed are:

    • How to design an intervention taken into account both common and specific therapy factors?
    • How to evaluate the effectiveness of your intervention and not the effectiveness of the therapist?
    • How to motivate other professionals and institutions to cooperate in a multicenter trial?
    • How to prevent loss to follow-up and dropout?
    • How to prevent various biases in your outcome measures?
    • What is the best available outcome instrument for the intervention studied?
    • How to determine which elements of your intervention are most effective?
    • How to implement your intervention?

    Read More

    16 Apr 2018 - 20 Apr 2018
    Advanced Decision Science Modeling [CE15]

    About this course

    This week-long, project-based course aims to provide students with an understanding of advanced methods used in decision-analytic modeling and cost-effectiveness analyses. These include topics like the latest methods for calibration and validation, quantifying uncertainty, and consideration of heterogeneity of patient benefits and equity issues. The course combines lectures and readings to give theoretical foundation and perspectives with in depth project work and presentations to give practical concrete understanding in a way that furthers students’ specific research goals.

    Course Structure: Each day will begin with a lecture by Professor Goldhaber-Fiebert on an advanced methods topic. After the lecture, lab sessions will commence with students working on their projects as Professor Goldhaber-Fiebert circulates through the room and students assist each other in a collaborative environment. Most days Professor Goldhaber-Fiebert will also give an afternoon lecture. In addition, at the end of days 2, 3, and 4, Professor Goldhaber-Fiebert will give an additional, shorter, informal lecture (i.e., "a chalk talk") on a methods topic tailored to specific issues that are arising within students’ projects. Additionally, throughout the week, Professor Goldhaber-Fiebert will have one-on-one meetings with students about their projects.

    Read More

    14 May 2018 - 18 May 2018
    Cancer Epidemiology [EP13]

    About this course

    Cancer is a major cause of morbidity and mortality in the developed world. The aim of this 5-day course is to provide an overview of the contributions of exogenous and endogenous factors to the risk of various cancers. The course starts with descriptive cancer epidemiology and an overview of current concepts of cancer development at the molecular and cell level. Subsequently, genetic and non-genetic risk factors for the most important cancers will be extensively discussed, as well as gene-environment interactions. Special attention will be given to risk factors for multiple primary cancers and recent results of chemo prevention studies. Although the emphasis of the course will be on etiologic factors, one session will specifically address time trends in cancer incidence, mortality and survival rates, followed by a discussion on whether or not we are winning the battle against cancer.

    Read More

    14 May 2018 - 18 May 2018
    Missing Values in Clinical Research [EP16]

    About this course

    Missing data frequently occur in clinical trials as well as observational studies. An important source for missing data are patients who leave the study prematurely, so-called dropouts. Alternatively, intermittent missing data might occur as well.


    When patients are evaluated only once under treatment, then the presence of dropouts makes it hard to comply with the intention-to-treat (ITT) principle. However, when repeated measurements are taken then one can make use of the observed portion of the data to retrieve information on dropouts. Generally, commonly used methods to analyse incomplete data include complete-case (CC) analysis and, in longitudinal studies, an analysis using the last observation carried forward (LOCF). However, these methods rest on strong and unverifiable assumptions about the missing mechanism. Over the last decades, a number of analysis methods have been suggested, providing a valid estimate for, e.g., the treatment effect under less restrictive assumptions.


    The assumptions regarding the dropout mechanism have been classified by Rubin and co-workers as: missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR).


    In the first part of the course we will review various repeated measurements models and indicate under which missing data mechanism they will provide valid estimates of the treatment effect. Finally, since it is impossible to verify that the dropout mechanism is MAR we argue that, to evaluate the robustness of the conclusion, a sensitivity analysis thereby varying the assumption on the dropout mechanism should become a standard procedure when analyzing the results of a clinical trial.


    The second part of the course focuses on multiple imputation (MI), specifically the fully conditional specification (FCS, MICE), which is often considered the gold standard to handle missing data. We will discuss in detail what MI(CE) does, which assumptions need to be met in order for it to perform well, and alternative imputation approaches for settings where MICE is not optimal. The theoretic considerations will be accompanied by demonstrations and short practical sessions in R, and a workflow for doing MI using the R package mice will be proposed.

    Read More

    14 Mar 2018 - 16 Mar 2018
    Quality of Life Measurement [HS11]

    About this course

    In recent years, the patient's assessment of quality of life has developed to an important outcome measure in epidemiology and health services research. Moreover, quality of life measures are increasingly used as criteria in reimbursement policy, most notably in QALY-analysis.

    The aim of the course is to provide the participants first, with a review of the instruments currently available; Second, participants are provided with the knowledge required to select measures of quality of life that are both valid and sensitive for the research objectives of the participants;

    Third, participants will acquire the knowledge and practical skills necessary to adjust standard measures of quality of life instruments for their specific disease area’s, with a special focus on reimbursement. The programme consists of presentations, exercises and demonstrations of practical issues. Participants are invited to email their specific interest at forehand, and these topic will be discussed during the course.

    Programme:

    • Background of ‘health status' and ‘quality of life’.
    • Main principles of construction of a quality of life questionnaire.
    • Available instruments.

    Application.

    • Adaptation instruments for specific research questions: increase sensitivity.
    • QALY-analysis.
    • Practical and ethical value of measuring quality of life in a reimbursement setting.

    Read More

    13 Jun 2018 - 13 Jun 2018
    Integration module [PU04]

    About this course

    Master students in Public Health will have to demonstrate their ability to integrate their knowledge and expertise into evidence-based advice for policy makers and practitioners. Based on the (draft) research paper the student will make a presentation of 10 minutes, addressing the following topics:

    • What is the problem addressed?- How does your study contribute to this problem?
    • How will your results impact population health?
    • What action should policy makers and professionals take?
    • These presentations will be followed by a discussion with faculty and fellow students. In addition, students are required to write a one page reflection on the courses in the programme.

    Read More

    12 Jun 2018 - 12 Jun 2018
    Site visit to the Municipal Health Service Rotterdam [PU03]

    About this course

    The site visit is a orientation on public health practice in the Netherlands. The visit will be to the Municipal Public Health Service of Rotterdam (GGD Rotterdam). The objective is to provide the participant with a brief insight on how the GGD is organized and which services are provided to the community. After the field visit the participant is able to describe the learning experience regarding the visit in a structured report and to compare the services provided by the GGD and the way that these services are implemented with public health services in the participant's country of origin or country of work.

    Read More

    12 Mar 2018 - 14 Mar 2018
    Women's Health [EP19]

    About this course

    The department of Epidemiology, in collaboration with the department of Internal Medicine at Erasmus University Medical Center, offers medical and health professionals a comprehensive course in Women's Health. This course brings together experts in women's health from a multitude of disciplines and provides participants with resources that will assist them in broadening and strengthening clinical care and research programs that are aimed at improving women's health and well-being. The course will focus on the critical issues that affect women's health throughout the life cycle. Our main purpose is to provide participants interested in improving women’s health and well-being with essential knowledge and principle skills from several disciplines. For NIHES Master students, this is a 3-day elective course. For people who attend this course as a short course, it is also possible to attend 1, 2 or 3 days of this course, as part a, b and c. Topics for each course day is to be announced: Women’s Health: day 1 (EP19a) Women’s Health: day 2 (EP19b) Women’s Health: day 3 (EP19c) The number of ECTS per day is 0.3 ECTS and the course fee per day is €210.00. https://www.nihes.com/womens-health/ This year we have not requested for accreditation of the various associations for medical doctors.

    Read More

    12 Mar 2018 - 16 Mar 2018
    Survival Analysis for Clinicians [EWP24]

    About this course

    Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest. A result of this seemingly innocent observation is that for a number of subjects the event is not observed, but instead it is known that it has not taken place yet. This phenomenon is called censoring and it requires special statistical methods. During the course different types of censored and truncated data will be introduced and techniques for estimating the survival function by employing both parametric and non-parametric methods will be illustrated. Also techniques for testing equality of survival functions (the log-rank test and alternatives) are discussed. Finally regression models for survival analysis, based on the hazard function (most notably the Cox proportional hazards model), will be studied in great detail. Special aspects such as time-dependent covariates and stratification will be introduced. Techniques to be used to assess the validity of the proportional hazards regression model will be discussed. The last part of the course touches on models for multivariate survival analysis, including competing risks and multi-state models and frailty models. Finally, aspects of the planning of clinical trials with lifetime data will be discussed.


    Teaching methods

    All aspects of the course will be illustrated with real data examples and will be practiced with computer practicals and/or pen-and-paper exercises.


    Survival Analysis (EWP24) is equivalent to the Survival Analysis course (ESP28) in the Erasmus Summer Programme and the part about survival analysis in  Biostatistical Methods II: classical regression models (EP03).

    Read More

    12 Mar 2018 - 16 Mar 2018
    Physical Activity [EXC10]

    About this course

    The primary aim of the physical activity module is to describe the measurement and epidemiology of physical activity. The module will cover definitions, methods to assess free-living physical activity, physical activity and physical activity recommendations for public health. Methods to assess physical activity include self-reported methods and objective measurements techniques. The amount of physical activity necessary for different health outcomes, such as CVD, obesity and diabetes will be discussed and recent activity recommendations for different age groups will be considered. Debates by students on topics covered by the module will be included.

    Read More

    12 Feb 2018 - 16 Feb 2018
    Principles in Causal Inference [EP01]

    About this course

    Epidemiologic research often entails asking and trying to answer questions toward understanding the causes and consequences of health outcomes. Answers to such causal questions require us to combine data (e.g., from observational studies) with assumptions to estimate causal effects. This course will teach students to think critically and rigorously about the implications of study design and analysis toward addressing such causal questions. Students will learn formal causal inference "languages" – including the concept of a target trial, causal diagrams, and counterfactual theory – to articulate research questions, inform an analytic approach, and identify threats to validity such as confounding.

    Read More

    09 Apr 2018 - 13 Apr 2018
    Epidemiology of Infectious Diseases [CE05]

    About this course

    Quantitative approaches play an important role in the understanding of the spread of infectious diseases and provide important tools for prevention. During the course, the basic notions that describe the mechanisms behind the spread of a disease will be introduced. Several examples of what can be learned from the use of quantitative models will be given.


    The relation between the specific characteristics of some infectious diseases and their spread will be exemplified, e.g. for tuberculosis, hepatitis, measles, influenza, AIDS. Only a basic level of mathematics is needed, and exercises will be given to practice the theoretical concepts.

    Topics covered are:

    • Important concepts and tools in modelling the spread of infectious disease.
    • Some important quantities related to the spread of infectious diseases (incidence, prevalence, cumulative incidence, incubation time, latent time, period of infectiousness); estimation of these quantities, with an example from the HIV epidemic.
    • Simulating large scale and small scale epidemics using the computer.
    • Basic reproductive number (R0) as central determinant of whether an epidemic develops.
    • Mode of transmission (e.g. airborne, sexual) in relation to the characteristics of spread.
    • Heterogeneous spread; the role of mixing between subgroups; contact patterns.
    • Molecular epidemiology as a new tool to monitor and model the spread of an infectious disease.


    Prevention programmes.

    • Vaccination strategies in relation to characteristics of the infectious disease.
    • Cost-effectiveness analyses of prevention and treatment.
    • Screening of pooled blood samples.

    Read More

    09 Apr 2018 - 13 Apr 2018
    Repeated Measurements [CE08]

    About this course

    This course covers statistical methods to be used when one or more variables are repeatedly measured in time on the same experimental unit. For instance, in a clinical trial, the outcome variable can be measured at baseline and at different times during the treatment period. In a meta-analysis, the study can be regarded as the experimental unit and the observations of patients within the same study as repeated measurements.


    In the last 10 or 15 years much progress has been made in the development of new methods of analysis. In recent years several of these new methods have been implemented in a wide variety of computer packages.


    The course starts with a short overview of simple methods for analyzing repeated measurements data, followed by a short recap of the most basic concepts of linear algebra needed for the presentation of the most advanced models.


    Then the main focus turns on more advanced methods. For approximately normally distributed repeated measurements outcomes marginal and linear mixed models are introduced. For non-normal responses, first the generalized estimating equations (GEE) approach for marginal inferences is presented, followed by extensions of random effects models to categorical outcomes. All these methods are exemplified using data from of clinical and epidemiological studies.


    Computer practicals in the statistical programming language R will be used to acquire hands on experience in applying these techniques to real data. All code used during the course will be live demonstrated using a web app, which will be made avaliable to participants.


    Participants need to bring their own laptop with certain pre-installed software (instructions will be given before start of the course). The assignment for this course needs to be handed in two weeks after the ending of the course on Friday April 27 2018.

    Read More

    07 May 2018 - 25 May 2018
    Public Health in Low and Middle Income Countries [PU06]

    About this course

    This module aims to teach methods to assess the health of populations in low and middel income countries and to quantitatively evaluate the effects of interventions on population health. Students are taught use modern techniques as health impact assessment to predict changes in population health due to particular programmes, for example control programmes for infectious diseases.

    Read More

    07 Mar 2018 - 09 Mar 2018
    Advanced Analysis of Prognosis Studies [EWP13]

    About this course

    Prognostic models are increasingly published in the medical literature each year. But are the results relevant for clinical practice? What are the critical elements of a well developed prognostic model? How can we assume that the model makes accurate predictions for our patients, and not only for the sample that was used to develop the model (generalizability, or external validity)?


    In the course we will address these and other questions from a methodological perspective, using examples from the clinical literature.The participants will be encouraged to participate in interactive discussions and in practical computer exercises.

    Read More

    07 Feb 2018 - 04 Apr 2018
    Health Services: Research and Practice [HS15]

    About this course

    The course explores the various hurdles in linking the principles of health services research with the realities of practice. Researchers will be taught how to become more sensitive to the information needs of practitioners, managers and policy makers and how to make their studies more practice-oriented while balancing methodological requirements.


    The various steps of the research cycle will be discussed (formulation of the research question, study design, data-collection, analysis and presentation of results), and for each step the focus will be on the research-practice interface. In addition to classical research plans, the activities before the study is designed and the follow-up activities to promote implementation in practice, will be highlighted. Special emphasis will be put on the independent role of the researcher in the various forms of evaluation research. The course will be a combination of lectures and exercises and on the third day participants will be asked to present their own practice-based health services research proposal.


    This module is offered in cooperation with the CaRe research school and is developed at the request of ZonMw (Netherlands Organisation for Health Research).

    Read More

    06 Mar 2018 - 09 Mar 2018
    Nutrition Epidemiology [EXC09]

    About this course

    The primary aim of the nutrition module is to describe the measurement and epidemiology of nutrition. The module will cover definitions, methods to assess nutrition, epidemiology of nutrition in relation to cancer, aspects of cardiovascular disease and malnourished populations. Methods to assess nutrition include questionnaires, biomarkers and food records.Debates by students on topics covered by the module will be included.


    Debates by students on topics covered by the module willbe included.

    Lecturers will introduce the topics. Teaching will becomprised of one-hour lectures and practical sessions. Students will work insmall groups in the practical sessions, which will take a variety of forms,including additional lectures, group work, discussions and data interpretationand calculation. Students are expected to read around topic areas.

    Read More

    05 Mar 2018 - 09 Mar 2018
    An Introduction to the Analysis of the Next-generation Sequencing Data [GE13]

    About this course

    This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.Subjects that will be covered include:

    • NGS: an introduction to methodology and techniques;
    • Basic statistics of NGS data, e.g. coverage;
    • Aligning the sequence reads;
    • Calling sequence and structural variants;
    • Dealing with various file formats (samtools, VCFtools, GATK);
    • Annotating sequence and structural variants;
    • Evaluating functional effects of the genetic variants on proteins;
    • Conversion to other formats;
    • Single variant and Collapsed genotype analyses with various tools (e.g. seqMeta, RAREMETAL and RVtest);
    • Finding variants with recessive effects and compound heterozygosity;
    • Search for rare variants in families and population based studies for complex phenotypes;
    • Search for rare variants in Mendelian disorders, and
    • Imputation of sequence variants.

    Read More

    05 Feb 2018 - 09 Feb 2018
    Psychopharmacology [MP03]

    About this course

    Medical psychology is all about the interaction between mind and body: how do physical complaints affect our psychological functioning? But also: how does our psychological functioning affect us physically? When dealing with this interaction in a clinical setting, drug treatments often play an important role. Patients receiving drug treatment for psychiatric disorders frequently suffer physical side-effects, and drugs prescribed for somatic disorders can influence our mental state.


    Therefore, medical psychologists need to know which drugs are prescribed for common psychiatric and somatic disorders, and need to have a basic understanding of how these (psychoactive) drugs work, how and why they invariably lead to side-effects, and how these side-effect affect compliance. We will look at drug treatment for psychiatric disorders such as depression and schizophrenia, but also at drugs like corticosteroids – used in the treatment of somatic conditions such as inflammatory bowel disease – which have been found to increase the risk of suicidal behavior and neuropsychiatric disorders (i.e. depression, panic and manic episodes).

    Read More

    04 Jun 2018 - 08 Jun 2018
    Bayesian Statistics [CE09]

    About this course

    There is growing acknowledgement of the value of Bayesian methods for complex models in biostatistics and epidemiology, in dealing with issues such as multiplicity, measurement error, spatial associations and hierarchical structure. This course will introduce the essentials of Bayesian ideas, emphasizing practical application using exact and simulation-based software. Examples will include the use of Bayesian methods in clinical trials, institutional comparisons, smoothing of disease rates, and frailty models.

    Read More

    Erasmus Winter Programme (EWP)

    For more information about the Erasmus Winter Programme (EWP), please go to:

    See overview of all available courses