The rates and measures that we explored in Chapter 2 provide a variety of ways to describe the health of a population and thus also enable us to compare patterns of health and disease between populations and over time. This allows us to answer the core questions relating to disease burden that are the essential first step in setting health planning and service priorities. As we discussed in Chapter 1, this descriptive epidemiology, concerned as it is with ‘person, place and time’, attempts to answer the questions ‘Who?’, ‘What?’, ‘Where?’ and ‘When?’. This can include anything from a description of disease in a single person (a case report) or a special survey conducted to measure the prevalence of a particular health issue in a specific population, to reports from national surveys and data collection systems showing how rates of disease or other health-related factors vary in different geographical areas or over time (time trends).
Although descriptive data may be collected specifically to answer a defined question, they often come from governments, health care providers and statistical agencies that routinely collect vast amounts of information. Summary data – often the various forms of rate which you met in Chapter 2 – can be accessed from published reports and, increasingly, from online databanks. In some cases it is also possible to obtain information from which the rates are calculated at the individual level. These descriptive data are essential to identify health problems and for health planning and, although they cannot usually answer the question ‘Why?’, they may provide the first ideas about causality and thus generate hypotheses that can then be tested in more formal ‘analytic’ studies that we will discuss in Chapter 4. As you will come to see in later chapters, descriptive studies also play a critical and often under-appreciated role in monitoring the effects of large-scale interventions.
In this chapter we will look in more detail at some of the most common types of descriptive data and where they come from. However, before embarking on a data hunt, we first need to decide exactly what it is we want to know, and this can pose a challenge; to make good use of the most relevant descriptive data, it is critical to formulate our question as precisely as possible.