Module 2: In-depth courses

In this Module 2 course, you will learn how to organize your projects, visualize your data, collaborate with your colleagues, and write reproducible reports using the programming language R and other tools.

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In this Module 2 course, you will learn basic statistical methods that are widely used in biostatistical research.

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Epidemiology - a core discipline of the public health sciences – provides a toolbox for studying the frequency and patterns of health/disease conditions and their determinants. In this Module 2 course, we introduce concepts and measures used to quantify the frequency of health outcomes and their associations with exposures of interest in a given population. We discuss the main types of epidemiological study designs and their potential sources of bias. We also introduce fundamental concepts of causality and discuss whether causal effects can be assessed in a given epidemiological study.

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In this Module 2 course, you will learn the basic concepts of diagnostic test evaluation with examples from human and animal health. Furthermore, we will focus on the interpretation of diagnostic test results and the reporting of diagnostic test accuracy studies.

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This Module 2 course is directed towards everyone conducting qualitative health research. In this living lab, we will not talk about how to do QHR but rather we will do it and train ourselves in the practices of analysis, interpretation and reflexivity – skills essential for high quality research but too often neglected in project work, doctoral studies, or studies alongside daily tasks.

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In this Module 2 Book Club we will meet for 8 sessions focused on selected chapters of the Book “Nutritional Epidemiology” by Walter Willett.

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The Module 2 course will introduce participants to basic principles of patient and public involvement in health research, discuss important aspects of participatory research and provide insights into selecting suitable approaches for different study designs and topics.

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Health systems are differently organized in the rich and the less rich countries. The health system organizes the “market” of health care providers and how the payment of health care is divided among the government, insurance companies, and private out-of-pocket payments. In this Module 2 course you will encounter the variety of these organizational aspects and dive into the fine details of the Swiss system of with a “managed competition” at the levels of health care providers and health insurance companies. Important contributors to variation in delivered and “financially covered” care will be discussed, as well as the foundations of decision making from the perspective of economic theory.

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This Module 2 course is directed towards everyone conducting qualitative health research. In this living lab, we will not talk about how to do QHR but rather we will do it and train ourselves in the practices of analysis, interpretation and reflexivity – skills essential for high quality research but too often neglected in project work, doctoral studies, or studies alongside daily tasks.

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This course provides an introduction to regression modeling in public health sciences. Participants will learn the basic theoretical concepts and how to apply regression modelling in the context of their research.

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This Module 2 course is directed towards everyone who conducts and writes up qualitative health research.

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This course provides an primer to cost-effectiveness analyses (CEA) of single health care interventions (pharmaceuticals, procedures, etc.), and introduces other types of analyses such as cost-benefit and cost-utility (CUA). Participants get to know methods, types of analyses, and aspects to be considered in performing a CUA. Approaches to present and appraise results including CUA in Health Technology Assessment (HTA) will be given.

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Have you ever wondered about the complexities of health care, either as patient, relative, or professional? In this Module 2 course you will dive into four specific, important areas of health care. You’ll discover how health policy, law and financing shape health care systems, their organization and outcomes. Applied to specific examples, you learn which specific methods are used to study health care.

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This 3-day Module 2 course introduces students to important concepts in cancer epidemiology such as cancer registration, statistics, etiology, risk factors, and prognosis. The course will focus on the cancer burden in Switzerland but also discuss cancer epidemiology internationally. Furthermore, the public health approaches to cancer control will be covered (primary prevention, screening, equity in access to established treatments). Lung, colon, and cervical cancer will serve as “case studies” for this course.

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One Health is an approach that aims to find integrated and sustainable solutions on complex problems affecting the health of people, animals and ecosystems, and generating an added value for each sector. In this course, the concepts of One Health will be learned, including theory and exercises applied to concrete examples (e.g. zoonoses, antimicrobial resistance, non-communicable diseases).

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This Module 2 course is directed towards everyone interested in qualitative health research. In each session, we will discuss landmark methodological papers as well as empirical studies to understand the essentials of qualitative health research.

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This Module 2 course provides an introduction to the relevance of law to public health. Law and politics form the framework for public health measures, because state measures always need a legal basis. How does law emerge and what is the role of politics and policy? What are the international and national legal authorities and what is the significance of law for policy and practice?

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Prognosis is the probability that a specific event will occur in the future. Prognostic Research is fundamental to clinical decision making, healthcare policy, and discovering new approaches to patient management. In this course we describe the basic concepts used to develop, validate, and implement a prognostic model in clinical practice and discuss how a web-based calculator might be constructed to give a useful decision-making tool. In addition, we consider the reporting and impact of prognostic models and how the quality of prognostic research might be improved in order that prognostic information may be translated into clinically useful decision tools.

As part of their PhD, many students will have to do one or several systematic reviews, and some students will also want to combine results from several studies in meta-analysis. This intensive 3-day course will cover the principles and practical steps of systematic reviews, including the design and conduct of comprehensive literature searches, data extraction and presentation, assessment of bias in the included studies, synthesis of data and examination of publication bias and other biases. The statistical methods for combining results in meta-analysis will also be covered and the course will include practical exercises in R.