Calculate and interpret appropriate measures in order to describe disease frequency, association and attributable risk for given scenarios.
Calculate sensitivity, specificity, positive and negative predictive values, in order to interpret these values in the context of screening.
Compare and contrast different epidemiological study designs in order to describe their strengths and weaknesses.
Identify different types of biases that may occur in epidemiological studies, in order to apply strategies to reduce such biases.
Thousands of new epidemiological studies are conducted every year and their results can have a profound impact on how we live our lives. Decisions regarding the food you eat, how much you exercise, where you live and what treatment you will follow if you get sick are made based on data from such studies. This specialization aims to equip you with the skills that will allow you to correctly interpret epidemiological research, consider its limitations, and design your own studies.
The first course of the specialisation, Measuring Disease in Epidemiology, looks into the main measures used in epidemiology and how these can inform decisions around public health policy, screening and prevention.
The second course, Study Designs in Epidemiology, provides an overview of the most common study designs, their strengths and limitations.
The third course, Validity and Bias in Epidemiology, builds on the fundamental concepts taught in the previous courses to discuss bias and confounding and how they might affect study results. It also provides the essential skills to prevent and control bias and confounding and critically think about causality.
At the end of this specialization you will have gained the essential skills to design and critique epidemiological research and you will be able to pursue more advanced courses in epidemiology. Although this specialization is part of the GMPH programme, it can be taken independently of the GMPH.
Measuring Disease in Epidemiology
Epidemiological research is ubiquitous. Even if you don’t realise it, you come across epidemiological studies and the impact of their findings every single day. You have probably heard that obesity is increasing in high income countries or that malaria is killing millions of people in low income countries. It is common knowledge that smoking causes cancer and that physical activity is protective against heart disease. These facts may seem obvious today, but it took decades of epidemiological research to produce the necessary evidence. In this course, you will learn the fundamental tools of epidemiology which are essential to conduct such studies, starting with the measures used to describe the frequency of a disease or health-related condition. You will also learn how to quantify the strength of an association and discuss the distinction between association and causation. In the second half of the course, you will use this knowledge to describe different strategies for prevention, identify strengths and weaknesses of diagnostic tests and consider when a screening programme is appropriate.
Study Designs in Epidemiology
Choosing an appropriate study design is a critical decision that can largely determine whether your study will successfully answer your research question. A quick look at the contents page of a biomedical journal or even at the health news section of a news website is enough to tell you that there are many different ways to conduct epidemiological research. In this course, you will learn about the main epidemiological study designs, including cross-sectional and ecological studies, case-control and cohort studies, as well as the more complex nested case-control and case-cohort designs. The final module is dedicated to randomised controlled trials, which is often considered the optimal study design, especially in clinical research. You will also develop the skills to identify strengths and limitations of the various study designs. By the end of this course, you will be able to choose the most suitable study design considering the research question, the available time, and resources.
Validity and Bias in Epidemiology
Epidemiological studies can provide valuable insights about the frequency of a disease, its potential causes and the effectiveness of available treatments. Selecting an appropriate study design can take you a long way when trying to answer such a question. However, this is by no means enough. A study can yield biased results for many different reasons. This course offers an introduction to some of these factors and provides guidance on how to deal with bias in epidemiological research. In this course you will learn about the main types of bias and what effect they might have on your study findings. You will then focus on the concept of confounding and you will explore various methods to identify and control for confounding in different study designs. In the last module of this course we will discuss the phenomenon of effect modification, which is key to understanding and interpreting study results. We will finish the course with a broader discussion of causality in epidemiology and we will highlight how you can utilise all the tools that you have learnt to decide whether your findings indicate a true association and if this can be considered causal.
No prior epidemiological knowledge is required, but you will be expected to perform simple mathematical calculations.