Summer Programme Courses


WEEK 1, AUGUST 07 – 11, 2017

    From 8:45 till 11:45
    Principles of Research in Medicine and Epidemiology [ESP01]

    About this course

    Faculty: Prof. Arfan Ikram, MD PhD

    This course will provide an orientation to medical research from a quantitative and epidemiological viewpoint. The course will give an introduction to the design of clinical and public health research, and it will discuss measures of disease frequency and association, and the validity of research in medicine. It will give an overview of elements of data-analysis.

    Teaching methods:
    Interactive lectures, exercises, practicals

    Read More

    From 13:00 till 18:00
    Introduction to Data-analysis [ESP03]

    About this course

    Faculty: Prof. Adelin Albert, PhD

    This course is a general introduction to the basics of statistics used in biomedical and public health applications. We start with a general definition of statistics and give some examples. We then review the notions of population, sample, variables (qualitative and quantitative) and data (missing, outlying, and censored). Next, the course will focus on modern ways to describe data such as tables, graphs, distributions and summary statistics (mean, standard deviation, median, quartiles), as required in the international scientific literature. The analysis of survival data will also be envisaged, in particular the renowned Kaplan-Meier survival curve. Finally, the association between variables will be discussed (correlation, relative risk, odds ratio and regression) as well as the agreement between observers (Cohen kappa coefficient).

    The course will then turn on the relation between the population and the random sample and on how effects observed in the sample can be generalized to the total population. Some elementary probability elements will be needed here. This will lead to the important concepts of standard error and confidence intervals (for means, proportions, odds ratios). The general theory of hypothesis testing will be briefly outlined from an intuitive perspective and the fundamental concepts of statistical significance, power calculation and p-value will be introduced. Then, we shall review the most frequently used testing procedures: correlation test, unpaired and paired t-tests for comparing two means values, analysis of variance for comparing several means (with multiple tests correction), chi-squared test (and Fisher exact test) for comparing two proportions and more generally for contingency tables, McNemar test for paired proportions, and two-way analysis of variance for repeated data. The logistic model and Cox model will be briefly alluded to because of their importance in the international medical literature. The basic principles underlying non parametric tests will be outlined and the most used distribution-free tests mentioned (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).

    All topics covered in the course will be illustrated using real data from the medical and biomedical literature and applied during practical sessions.

    Written exam on the Friday in the week after ESP (only for NIHES MSc students and for ‘keuzevak students’). Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.9 ECTS when you take the exam, instead of 1.4 ECTS.

    This course is equivalent to Biostatistics for Clinicians (EWP22) and Biostatistical Methods I: basic principles, part A (CC02A).

    Read More

    From 13:00 till 16:00
    Clinical Trials [ESP14]

    About this course

    Faculty: Prof. Marcel Zwahlen, PhD and Sven Trelle, MD, MSc

    This basic and intermediate level course covers design, conduct and analysis issues of clinical trials.
    We will discuss the clinical, scientific, and regulatory aspects of clinical trials, which investigate the efficacy and safety of candidate treatments or of diagnostic procedures. We will cover issues regarding the design such as the identification of the target population, choice and definition of the intervention and the comparators, choice and definition of study outcomes and assumptions needed to determine the size of the trial. Regarding the conduct and implementation of clinical trials we will cover the need for trial registration, choice of randomization strategies and procedures, the role of blinding, issues on prevention and handling of missing data, monitoring of the study, and the standards for the reporting of the trial results. Throughout the course emphasis is placed on pre-specification of these elements in a well-defined study protocol and on documentation of implementation and conduct of the study.

    Teaching methods:
    Lectures and group works on critical appraisal of trial protocols and published trial results.

    Read More

    From 8:45 till 11:45
    Topics in Meta-analysis [ESP15]

    About this course

    Faculty: Prof. Matthias Egger, MD PhD & Prof. Olaf Dekkers, MD PhD

    Programme
    Introductory lecture: Why do we need systematic reviews and meta-analyses?
    Lecture / pen and paper practical: Measures of association
    Lecture: Basic statistical methods

    Computer practical Basic meta-analysis in Stata
    Lecture / demonstration: Identifying relevant studies
    Practical: Identifying relevant studies in PubMed

    Lecture Assessing quality and risk of bias
    Lecture The scope of meta-analysis: Meta-analysis of observational studies
    Case study / group work: How good is this meta-analysis?
    Case study / group presentations How good is this meta-analysis?
    Lecture Explaining heterogeneity and detecting bias
    Lecture / case study Individual participant data (IPD) meta-analysis

    Lecture Meta-analysis of dose-response relationships in epidemiology
    Computer practical Advanced meta-analysis in Stata I & II

    Read More

    From 13:00 till 16:00
    Pharmaco-epidemiology [ESP21]

    About this course

    Faculty: Prof. Bruno Stricker, PhD

    Pharmaco-epidemiology pertains to the study of the use and of the effects of drugs. It links clinical pharmacology and epidemiology. This course provides, at an intermediate level, the theoretical basis for studying the intended effects as well as the adverse effects of drugs used in humans. The course will mainly focus on drug research after marketing, including post marketing surveillance and drug risk assessment.

    This course is intended for those who already followed introductory courses in study design, data-analysis and principles of research in medicine.

    Teaching methods
    Plenary interactive teaching with real-life examples and exercises

    Read More

    From 8:45 till 11:45
    Conceptual Foundation of Epidemiologic Study Design [ESP38]

    About this course

    Faculty: Prof. Kenneth Rothman, DrPH

    This course elaborates the fundamental principles of epidemiologic study design. It begins with an introduction to the basic principles of epidemiologic inference, including concepts of causation, causal inference and the measurement of disease occurrence and causal effects. With this foundation, attention shifts to the principles of study design and discussion of the major types of epidemiologic study, primarily cohort and case-control studies. The utility and consequences of matching in subject selection is also addressed. The course concludes with a presentation of the underlying principles of epidemiologic data analysis.

    Read More

    From 13:00 till 16:00
    Introduction to Global Public Health [ESP41]

    About this course

    Faculty: Rajiv Chowdhury, MD PhD

    The key aim of this course is to learn about the principal issues surrounding global health and the main outcome of the course will be a better understanding of how epidemiology and public health can more effectively protect the health of disadvantaged populations in the changing global context.

    Some of the specific health issues to be discussed include: the global rise of the non-communicable diseases (NCD) such as cardiovascular disease and diabetes; threats to health from pre-existing and emerging communicable diseases; maternal and child health issues, and the impact of global environmental change. Additionally, other related issues such as concepts and realities of health systems around the world, impact of globalization on health, and how to measure global health will be discussed. For each health problem, where appropriate, there will be a discussion of: burden of disease, major determinants, intervention policies and programmes, and evaluation of the effectiveness of the interventions. A key focus of the course would be small group interactions.

    Read More

    From 13:00 till 18:00
    Principles of Genetic Epidemiology [ESP43]

    About this course

    Faculty: Prof. Cornelia van Duijn, Ir. PhD

    This course aims to give a basic introduction to various methods used in classical genetic epidemiology. In combination with the course Searching Genes for Complex Disorders, the course offers an excellent introduction to genetic epidemiologic research for epidemiologists, clinicians and molecular biologists with no background in genetic epidemiology. Participants are introduced to the basic principles of population genetics, segregation, linkage and association analyses. The relevant background of human genetics and statistics is presented. The goal of the course is that participants are able to interpret the findings in modern genetic research.

    Read More

    From 8:45 till 16:00
    Logistic Regression [ESP66]

    About this course

    Faculty: Prof. Stanley Lemeshow, PhD

    This course provides theoretical and practical training for biostatisticians, epidemiologists and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression. The increasingly popular logistic regression model has become the standard method for regression analysis of binary, multinomial and ordinal response data in the health sciences.

    Read More

WEEK 2, AUGUST 14 – 18, 2017

    From 8:45 till 16:00
    Regression Analysis [ESP09]

    About this course

    Faculty: Prof. Brian Marx, PhD

    This intermediate level course aims at providing theoretical and practical training for epidemiologists, clinicians and other professionals of related health disciplines in statistical modeling with particular emphasis on straight line linear and multiple regression. Included topics are: review of straight line regression and correlation, ANOVA for straight line regression, appropriateness of straight line model, polynomial regression, multiple regression analysis, partial F-test, dummy/indicator variables, statistical interaction, comparing straight line regressions, analysis of covariance, estimation and interpretation, goodness-of-fit, model selection, collinearity and outlier diagnostics. Additionally, extensions to some generalized linear models, such as logistic (binomial) regression and Poisson regression, will be introduced and interpreted through examples-- thus helping to bridge the material presented in ESP66 (Logistic Regression).

    Written exam on the Friday in the week after ESP (only for NIHES MSc students and for ‘keuzevak students’). Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.9 ECTS when you take the exam, instead of 1.4 ECTS.

    This course is equivalent to Regression Analysis for Clinicians (EWP23).

    Read More

    From 8:45 till 11:45
    Methods of Public Health Research [ESP11]

    About this course

    Faculty: Prof. Lex Burdorf, Ir. PhD

    This course provides an introduction to essential study designs and analytic methods available to public health researchers to describe the influence of important determinants on public health and to evaluate effects of primary preventive intervention on public health. This course focuses on population health rather than individual health and explains why different designs and methods are required, such as ecological studies and multilevel analysis. The course targets three key issues: (1) summary measures of population health, such as life expectancy, (2) measures of association and relative importance of specific causes for population health, such as population attributable fraction, and (3) evaluation of population interventions through community trials and study designs based on natural experiments instead of RCT. Designs and methods will be illustrated in lectures and exercises and application will demonstrate their usefulness in current hot topics, such as health inequalities; causes and consequences of ageing; avoidable diseases such as cancer; and evaluation of complex societal interventions.

    The course will be relevant to those who have a basic knowledge of epidemiology, and who wish to start a career in public health research.

    Teaching methods:
    This course will use lectures, exercises, and group discussion as teaching tools.

    Read More

    From 13:00 till 16:00
    Cohort Studies [ESP39]

    About this course

    Faculty: Prof. Javier Nieto, MD PhD MPH

    This course will provide an introduction to the cohort and other longitudenal designs for students with an intermediate level background in epidemiology.
    It will focus on design and interpretation, emphasizing the principles and complexities of data collection over time and potential biases that may affect cohort data. Topics to be covered include cohort definition, follow-up and definition of outcomes, fixed and time-dependent exposures, quality control, mixed study designs (nested case-cohort studies), and quality assurance and control. The course will also cover the use of the cohort design in clinical/translational research.

    The course will also cover the basic analytic methods appropriate to various types of cohort data, including the application of both non-parametric methods and regression models. The course will be based on lectures as well as in small group and plenary discussions of exercises. Competencies to be gained in the course include the ability to interpret findings from cohort studies and to apply principles for the design of cohort studies.

    Read More

    From 8:45 till 11:45
    Case-control Studies [ESP40]

    About this course

    Faculty: Prof. Moyses Szklo, MD PhD

    The course will provide an introduction to the design and analysis of case-control studies. Topics to be covered include case-based case-control, nested case-control and case-cohort designs, selection of cases and controls, the parameter measured by the odds ratio as a function of control selection, matched and unmatched strategies, confounding and common biases, and evaluation of additive and multiplicative interaction in case-control studies. These topics will be discussed in the context of the case-control design as a special way to analyze cohort data. In addition, a discussion of adjustment approaches appropriate to case-control data will be covered, including stratified and regression methods. The course will be based on classroom lectures and small group discussions of exercises.

    Read More

    From 13:00 till 16:00
    Methods of Health Services Research [ESP42]

    About this course

    Faculty: Prof. Niek Klazinga, MD PhD

    Health Services Research addresses issues such as access and quality of health care delivery, financing and use of health care services, workforce planning, implementation of change and the overall functioning and performance of health care systems.
    This introductory course provides insight in the various research questions, research designs, data-collection methods and analysis methods used in health services research. It puts emphasis on the links between research, policy and practice. The course is organized around lectures and group exercises.

    Read More

    From 08:45 till 11:45
    History of Epidemiologic Ideas [ESP53]

    About this course

    Faculty: Prof. Alfredo Morabia, MD PhD

    This is a methodology course, which focuses on the historical evolution of methods (e.g., study designs) and concepts (e.g., confounding, bias, interaction and causal inference) that constitute today’s epidemiology. For each topic, we review and discuss the historical contexts and some landmark studies that led to specific innovations in terms of performance of group comparisons, population thinking and framing of hypotheses. We finally discuss the historical conditions for the emergence of epidemiology as a scientific discipline, the phases it went through and its potential, future developments.

    Read More

    From 8:45 till 16:00
    Genomics in Molecular Medicine [ESP57]

    About this course

    Faculty: Prof. André Uitterlinden, PhD, Joyce van Meurs, PhD, Fernando Rivadeneira Ramirez, PhD

    Molecular genetics plays an increasingly important role in medical research. The course addresses various molecular principles relevant for genetic epidemiological research. Different approaches to localize disease genes will be discussed. Cloning of disease genes will be discussed from the bench point of view and with the use of modern bioinformatical methods.The course is particularly interesting for clinicians and epidemiologists who wish to be introduced in methods for identifying (complex) disease genes and its practical applications and basic knowledge of molecular biology.

    Read More

    From 16:00 till 17:00
    Masterclass: Advances in Genomics Research [ESP63]

    About this course

    Moderator Prof. André Uitterlinden, PhD

    In this masterclass, timely topics in genomics research will be addressed. Four renowned researchers will address the latest developments in epigenetics, forensic genomics, personalized medicine, whole genome sequencing, and new genetic variants.

    Read more about the topics and speakers on the Master Classes page, find this page in the drop-down menu of Programme.

    The Master Classes are open without registration or fee for participants of the Erasmus Summer Programme, the NIHES programmes, employees of the Erasmus MC University Medical Center and public at large. For NIHES Master students doing specalisation Genetic Epidemiology this course is compulsory.

    Read More

    From 8:45 till 16:00
    Introduction to Bayesian Methods in Clinical Research [ESP68]

    About this course

    Faculty: Prof. Emmanuel Lesaffre, PhD

    This course provides an introduction to Bayesian methods with an emphasis on the intuitive ideas and applications. The course treats the basic concepts of the Bayesian approach, such as the prior and posterior distribution and their summary measures (mean, median, credible interval, etc), the posterior predictive distribution. In addition, Bayesian methods for model selection and model evaluation will be treated. The Bayesian approach will also be compared, both conceptually as well as practically, with the classical frequentist approach. Markov Chain Monte Carlo techniques are introduced and exemplified in a variety of applications.

    The Bayesian approach will be illustrated in clinical trials, epidemiological studies, meta-analyses, diagnostic testing, agreement studies, etc. WinBUGS and OpenBUGS will be used as software. But also the use of their interfaces with R, i.e. R2WinBUGS and R2OpenBUGS will be illustrated.

    Course format:
    In the first three days of the course the Bayesian concepts will be explained. Theory and exercises will then be mixed depending on the topic. The final two days will be devoted to particular application areas and have largely a practical flavor. In addition the application of the Bayesian methodology in the medical literature will be highlighted.

    Teaching methods:
    Interactive lectures, exercises, practicals

    Read More

    From 13:00 till 16:00
    Fundamentals of Medical Decision Making [ESP70]

    About this course

    Faculty: Prof. John Wong, MD

    Introduction to Methods for Decision-making in Health Care: Integrating evidence and values
    This course will provide an introduction to health care decision making. Given the uncertainty, trade-offs and values that are involved, how should patients, policymakers and physicians navigate through a complex and tangled web of diagnostic and therapeutic choices, patient preferences, and resource constraints to make optimal decisions? Medical interventions may have benefits but also adverse effects, e.g., surgery may lead to undesirable complications, and diagnostic technologies may produce false or inconclusive results.

    In many clinical and health policy decisions it is necessary to counterbalance benefits and harms and to trade off competing objectives such as maximizing life expectancy vs. optimizing quality of life vs. minimizing the resources required. In this course we will discuss a proactive approach to such decisions and discuss the basic concepts underlying decision modeling and cost-effectiveness analysis in order to integrate evidence and values for optimal care choices.

    Teaching methods: Interactive lectures, exercises and practicums.

    Read More

    From 8:45 till 11:45
    Joint Models for Longitudinal and Survival Data [ESP72]

    About this course

    Faculty: Dimitris Rizopoulos, PhD

    Longitudinal and time-to-event outcomes are the main types of outcomes encountered in medical studies. Primary examples of the former are biomarkers or other patient parameters that are measured during follow-up, whereas for the latter examples include the time to relapse of the disease, time to re-operation or time to death. This course introduces a new type of statistical models that can be used to investigate the association structure between longitudinal and survival outcomes.

    In terms of software, we will use R and illustrate how these models can be fitted using package JM and JMbayes.
    Participants will be expected to bring their own laptop computers to the session, and to have recent versions of R
    (http://www.r-project.org/) and of R packages JM
    (http://cran.r-project.org/package=JM) and JMbayes
    (http://cran.r-project.org/package=JMbayes) already installed on these computers. All necessary computer code will be provided beforehand.

    Read More

    From 08:45 till 16:00
    Causal Inference [ESP48]

    About this course

    Faculty: Prof. Miguel Hernán, MD & Sonja Swanson, ScD

    The goal of many epidemiologic studies is to quantify the causal effect of a treatment (or exposure) on an outcome. In contrast, commonly used statistical methods provide measures of association that may lack a causal interpretation even when the investigator adjusts for all potential confounders in the analysis of a properly designed study.

    To eliminate the discordance between the causal goals and the associational methods in epidemiology, it is necessary to a) formally define causal concepts such as causal effect and confounding, b) identify the conditions required to estimate causal effects, and c) use analytical methods that, under those conditions, provide estimates that can be endowed with a causal interpretation. These so-called g-methods can be used under less restrictive conditions than traditional statistical methods. For example, g-methods allow one to estimate the causal effect of a time-varying treatment in the presence of time-varying confounders that are affected by the treatment.

    This course combines counterfactual theory and graph theory to present an integrated framework for causal inference from observational data, with a special emphasis on complex longitudinal data. The course presents the latest methodologic developments for the design and analysis of longitudinal studies. Specifically, the course will introduce the three g-methods (inverse probability weighting of marginal structural models; parametric g-formula; and g-estimation of structural nested models) in the setting of time-fixed treatments, and demonstrate inverse probability weighting for addressing causal questions regarding static and dynamic treatment strategies.

    Read More

WEEK 3, AUGUST 21 – 25, 2017

    From 13:00 till 16:00
    Health Economics [ESP25]

    About this course

    Faculty: Ken Redekop, PhD

    Economic thinking is becoming increasingly important in health care.
    This course begins with a two day introduction of main concepts of health economics. The remaining three days are used to provide students with more in depth knowledge. The student will learn to analyze the cost-effectiveness of health care interventions (e.g., medicine, diagnostic test, health care programme).
    Both methodology and practical examples will be covered. Exercises are used to illustrate the various steps in economic thinking.

    Read More

    From 8:45 till 11:45
    Primary and Secondary Prevention Research [ESP45]

    About this course

    Faculty: Prof. Oscar Franco, MD PhD and Prof. Harry de Koning, MD PhD

    This course will introduce and illustrate methods and practices of research in the planning, development and evaluation of interventions to prevent ill health. Primary and secondary prevention may work together, depending on the determinants of disease and technology available. Life style factors, like for example cigarette smoking, dietary habits and physical activity, are important determinants of health and disease. Therefore, promoting healthy life styles is important in public health interventions.

    Screening for diseases that are related to these determinants can possibly improve prognosis, gain life-years and quality of life. However, early detection also means a longer period of life during which a person is aware of having the disease, and false-positive test results will induce unnecessary diagnostic interventions. Crucial in prevention research is the population perspective, with consequences for designing a study, evaluating an intervention, communicating to the people and setting priorities. Special emphasis will be given to cancer research, cardiovascular interventions, but also to preventing language delays in children or promoting alcohol consumption. The course will consist of lectures, exercises and presentations of illustrative examples of primary and secondary prevention research.

    Teaching format: Lectures, exercises, discussions.

    Read More

    From 13:00 till 16:00
    Social Epidemiology [ESP61]

    About this course

    Faculty: Prof. Frank van Lenthe, PhD & Prof. Johan Mackenbach, MD PhD

    This course aims to introduce and illustrate modern research methods in social epidemiology, i.e. the study of the social determinants and social outcomes of health. The three main areas to be covered are: the measurement of health inequalities, the explanation of health inequalities, and the evaluation of interventions and policies to reduce health inequalities. Application of the research methods will be illustrated with historical landmark studies as well as recent examples from the international literature.

    The programme consists of lectures, hands-on exercises, and group discussions. The focus will be on socioeconomic inequalities in health, but the role of other social factors (such as ethnicity and marital status) will also be discussed.

    Read More

    From 13:00 till 16:00
    Markers and Prediction Research [ESP62]

    About this course

    Faculty: Prof. John Ioannidis, MD DSc, Prof. Ewout Steyerberg, PhD & Maryam Kavousi, MD PhD

    Prognostic research is of growing importance, as globally more people are living with disease and clinicians and policy makers seek ways of targeting existing treatments and improving health outcomes. There is a rapid expansion in the number of new prognostic markers. Often, bold claims are made about their potential to assist in personalising approaches to medical care and treatment. Prognostic models may be useful to summarize the effects of multiple predictors but while commonly developed, such models are often not well validated or used in clinical practice.

    This course aims to provide the basic knowledge and principles to evaluate the quality of prognostic research and its translation to inform decision making of clinicians and policymakers. Drawing on recent examples and current controversies in cardiovascular disease, cancer, trauma and other conditions, the course examines molecular biomarkers and genetic variants through to the quality of healthcare as predictors of outcome. Topics include design, conduct and analysis of prognostic research; outcomes research; prognostic factors and prognostic markers; prognostic models for risk prediction; and stratified and personalised medicine.

    There will be lectures, interactive debates and critical appraisal of papers, but no computer labs (the course does not cover advanced statistical methods, see Further reading).

    Read More

    From 8:45 till 11:45
    The Practice of Epidemiologic Analysis [ESP65]

    About this course

    Faculty: Kamran Ikram, MD PhD

    This is a course in which the theoretical background and practical application of basic epidemiologic analytic tools is discussed. Special attention will be paid on issues such as normalization, standardization, and categorization, combining multiple variables, combining multiple sources etc.
    The goal is to provide students with the understanding and tools to perform epidemiologic data analysis.

    The course is particularly intended for students who have completed their data collection and move towards data analysis. No prior knowledge is required although understanding of basic epidemiology is helpful.

    Read More

    From 8:45 till 11:45
    Causal Mediation Analysis [ESP69]

    About this course

    Faculty: Linda Valeri, PhD

    The course will cover some of the recent developments in causal mediation analysis and provide practical tools to implement these techniques. Mediation analysis concerns assessing the mechanisms and pathways by which causal effects operate. The course will cover the relationship between traditional methods for mediation in epidemiology and the social sciences and new methods in causal inference. For dichotomous, continuous, and time-to-event outcomes, discussion will be given as to when the standard approaches to mediation analysis are valid. Using ideas from causal inference and natural direct and indirect effects, alternative mediation analysis techniques will be described when the standard approaches will not work. The no-confounding assumptions needed for these techniques will be described.

    SAS, SPSS and Stata macros to implement these techniques will be covered and distributed to course participants. The use and implementation of sensitivity analysis techniques to assess the how sensitive conclusions are to violations of assumptions will be covered. Discussion will be given to how such mediation analysis approaches can be extended to settings in which data come from a case-control study design. The methods will be illustrated by various applications.

    The course will employ a combination of lecture, discussion, and software demonstration. Powerpoint slides will be used to present material in lecture form. Extensive printed notes will be available for students. A wide variety of examples from epidemiology and the social sciences will be used to illustrate the techniques and approaches. Ample time will be given for discussion and questions. A variety of software packages will be discussed. Students will have worked exercises that they can complete on their own.

    Read More

    From 8:45 till 11:45
    Genome-wide association studies [ESP74]

    About this course

    Faculty: Prof. Cornelia van Duijn, Ir. PhD & Fernando Rivadeneira, MD PhD

    Genome-wide association studies (GWAS) constitute a powerful approach to investigate the genetic basis of multifactorial disorders. In the last decade, GWAS have yielded spectacular successes in the discovery of genes involved in complex traits and disorders (e.g. body height, BMI, cardiovascular disease, cancer and neurological disorders). This was made possible by the advent of high-throughput genotyping technology and the knowledge on genome structure and organization derived from the HapMap and 1000 Genomes Projects. Applying the GWAS approach has facilitated researchers to incorporate these analyses into large genetic, clinical and epidemiological studies.

    This course aims to introduce epidemiologists, molecular biologists and clinicians into the basic principles of GWAS, addressing aspects of study design, data collection and analysis, extending to the interpretation and follow-up of results. The course consists of lectures providing a conceptual framework on crucial aspects of quality control, imputation of missing genotypes, statistical tools, methods to detect and correct for stratification, meta-analysis and genomic annotation of GWAS signals; accompanied by instructive hands-on computer exercises on the principles of analysis of quantitative traits and disease outcomes using software packages that are available in the public domain.

    The course format will allow interactive break-out discussion sessions on theoretical and practical aspects of running GWAS, together with expert-advice procurement on diverse components of collaborative research within networks and consortia.

    Read More

    From 13:00 till 16:00
    Human Epigenomics [ESP75]

    About this course

    Faculty: Jordana Bell, PhD

    This course is formerly known as Epigenetics.

    This course aims to give an introduction to epigenetics and epigenomic studies of human disease. The course offers an overview of epigenetic mechanisms and their importance during development and over the life course. Different sources of epigenomic variation will be discussed, as well as approaches to characterize epigenomic variability with the use of modern molecular and bioinformatics methods. The course will then focus on epigenomic studies of human disease, to enable participants to interpret the findings in modern epigenetic research and put these into a functional perspective.

    A laptop is required for computer exercises during the course.

    Read More

    From 13:00 till 16:00
    Value Based Healthcare, from theory to implementation [ESP76]

    About this course

    Faculty: Prof. Jan Hazelzet, MD PhD, Dr. Tom Kelley, MD MBA & Dr. Rishi Hazarika, MBBS BSc

    Overall aim: To provide participants an overview of all aspects of value-based-health care (VBH) as theorised by Prof Michael Porter, Harvard Business School. Where value is defined as the outcomes achieved for patients relative to costs. Using the case based method of teaching and incorporating practical examples of how leading health care organisations have followed VBH principles and implemented and utilised outcome measurement to aid clinical practice and patient led decision making. The programme consists of 15 lectures and will deal with all the aspects of value based healthcare.




    Read More

    From 16:00 till 17:00
    Erasmus Summer Lectures [ESP64]

    About this course

    In these lectures, timely topics in study design of epidemiologic and clinical studies will be addressed. Four renowned researchers will address advanced study design issues in a seminar format.

    Moderator Prof. Arfan Ikram, MD PhD

    Read more about the topics and speakers on the Erasmus Summer Lectures page, find this page in the drop-down menu of Programme.

    The lectures are open without registration or fee for participants of the Erasmus Summer Programme, the NIHES programmes, employees of the Erasmus MC University Medical Center and public at large.

    Read More