Epidemiology is about studying the occurrence of health events and their determinants in populations and there are different ways to classify the types of epidemiological studies. One way is to differentiate between observational studies and experimental studies. In experimental studies, the researchers control almost every aspect of the study, including who is exposed and who is not exposed. When studying infectious diseases in human populations, it is unacceptable to deliberately decide on exposure of humans, so most often observational studies are used to study the exposure that has happened accidentally in real life (which is sometimes referred to as 'the experiment of nature'). Among the observational studies we can distinguish descriptive studies and analytical studies.
Descriptive studies aim to quantify and qualify public health problems (what goes on where, when, among whom) while analytical studies aim to explain the mechanisms in which public health problems emerge, propagate and sustain themselves in populations (asking 'how' and 'why'). Both classes of studies require a careful design, in order to ensure that the results accurately and realistically reflect the situation in the population. The challenge in any of those study designs is to minimize bias (which leads to a misrepresentation of the real situation) and to define the objects of measurement (disease, health even or determinants such as behaviour) in a precise enough manner.
Studies can also be classified into descriptive, exploratory, inferential, predictive, causal and mechanistic studies. Descriptive studies aim to describe a dataset. Explorative analysis aims to find relationships between several variables. Infertial analysis refers to using a small sample of data to infer something on a bigger population. Predictive analysis uses data on some objects to predict values for another object. Causal studies aim to identify causes preferably via randomized controlled trials. Mechanistic analysis aims to understand the exact changes in variables that lead to changes in other variables.
Descriptive epidemiological studies are an important source of evidence for setting priorities in public health. Authorities that have the ability to effectively and efficiently describe the health status of the population, will also be able to set priorities for example according to the magnitude, impact or burden of disease. This may also include economic consequences of disease.
Similarly it will be relevant to public health authorities to know how determinants of health are developing in 'their' population; do people still decide to vaccinate? Is the use of recreational drugs increasing? Does our needle exchange programme for drug users still cover the needs? By measuring and monitoring determinants, authorities can be informed about risks of health events within the population even before they occur.
As it is not enough to know what is going on, but also to understand how and why, analytical studies are a powerful tool for generating evidence for policies for disease prevention and control. As most authorities aim to interfere with the daily life of citizens as little as possible and only when it is really necessary, interventions designed to prevent and control diseases are ideally very specific and highly effective. This usually requires a solid knowledge of the relationship between health events and their determinants. Analytical studies aim to contribute to that body of knowledge.