Study design
Epidemiological studies can be described as belonging to one of two categories: descriptive or analytical. Descriptive studies involve detailed investigations of individuals in order to improve knowledge of disease. Descriptive studies often have no prior hypotheses and are opportunistic studies of disease whereas analytical studies are used to test hypotheses by selection and comparison of groups. However, data obtained from analytical studies can be used in a descriptive manner and vice versa.
Descriptive studies
Descriptive studies include case-series, case-reports and surveys. Although unable to test hypotheses, as they do not involve the comparison of groups, they improve knowledge and understanding of disease and are useful for generating hypotheses. The overarching aims of descriptive studies are covered in another page.
Case reports
These are descriptions of disease in individual animals (or in a very small number of cases). Although the small number of animals included in these types of studies limit the ability to relate the results to larger populations, they provide useful information for further studies - in particular, in the case of rare or emerging diseases.
Case series
These include greater numbers of individuals than case reports (and can in fact include greater numbers of individuals than surveys in some cases), and therefore provide more information regarding the animal, place, time pattern of disease. However, these studies are often not planned out in advance, and the data collected may have been collected for other reasons than the study in question. This means that the individuals included may not be representative of external populations, and that data on factors of interest may be missing.
Surveys
These are carefully planned studies with clear, specific aims and a defined source population (for example, aiming to estimate the prevalence of disease X in country Y at time Z), which differentiates them from case series studies. Surveys will have a clear sampling strategy and a method of data collection (such as a questionnaire or serological test) used specifically for the study in question. If data regarding both outcomes (such as disease status) and exposures of interest are collected, then the study would be more accurately described as a cross sectional analytic study (see below).
Analytic studies
Analytical studies aim to identify different 'subpopulations' of animals (defined by the presence or absence of exposures of interest) amongst which disease experience differs, in an attempt to identify risk factors or protective factors for disease. The ultimate aim is to draw conclusions regarding possible causative associations between exposures and disease (although, as mentioned earlier, causation is impossible to prove). Depending on the study design, this may be achieved by comparing 'disease outcome' between groups of animals with or without the exposure of interest, or by comparing 'exposure' between groups of animals with or without disease. Analytical studies can be viewed as observational or experimental in nature. In the case of observational studies, the investigator does has no control over the exposure status of the animals, whereas in experimental studies, the investigator allocates exposures to a selection of the animals. This has important repercussions for the interpretation of the results, as in the case of observational studies, the groups of animals defined by the exposure of interest may differ from each other in other ways than just the exposure of interest.
Observational studies
As mentioned above, observational studies are based on the investigator observing the real-life situation and drawing inferences from this. Therefore, there is potential for biases and confounding, which must be considered when interpreting the results. Observational studies can be classified as one of three types, according to the method of selection of participants (although some studies may use aspects of different study designs). The study design will affect which measures of disease are possible.
Cross sectional studies
Cross sectional studies involve the selection of a sample of the population, regardless of their exposure or outcome status. As the sample is collected at one point in time, the prevalence of disease can be estimated, and this must be considered when identifying associations. As the prevalence of disease at any one point in time is dependent upon both the incidence of disease and the duration of disease, this can cause problems when trying to identify causal associations - primarily because the prerequisite for causation stating that the exposure must precede the outcome may not be able to be definitively proved (as the exposure may have been different at the time the animal actually developed the disease). Another problem for cross sectional studies is that of selection bias, which may result from a refusal of some individuals to participate.
Cross sectional approaches can also be used to follow up a population over time, by repeatedly sampling from the population - known as a repeated cross sectional design. Although this may appear to be similar to a cohort study (see below), they differ in that in a repeated cross sectional study, the same individual animals are not necessarily sampled each time, and so are not followed up over time.
Cohort studies
Cohort studies, as mentioned above, involve following animals over time in order to record whether or not they experience the outcome of interest. The selection of animals may be based upon exposure status (in which case, the study design is a cohort study, sensu stricto), or a selection of disease-negative animals may be made, with the exposure status determined after selection (which is strictly known as a longitudinal study). Cohort studies allow the measurement of the incidence of disease, as all animals are negative at the start of the study and are then followed up over time, which solves some of the problems described above when investigating prevalence in analytic studies. As for cross sectional studies, failure of some individuals to enrol may result in selection bias, as can individuals dropping out of the study as time progresses ('losses to follow-up'). One other problem with cohort studies is that they can be costly and can take a long period of time to complete.
Case-control studies
Case-control studies are based upon the identification of two populations of individuals - one ('cases') comprising those who have experienced the outcome of interest (e.g. disease) and one ('controls') comprising those who have not experienced the outcome of interest (but who are otherwise comparable to the cases). As the outcome itself is involved in the selection of participants, no measures of disease frequency can be made from a case-control study, which are only used for the identification of exposures associated with disease (through the estimation of 'odds ratios'). Although case-control studies can be very useful in the investigation of rare diseases, there can be considerable difficulties in ensuring that the control group are comparable to the case group. If these groups are not comparable, there can be considerable selection bias, which an invalidate the results of the study.
Experimental studies
In experimental studies (also known as intervention studies), the investigator allocates the exposure of interest to a selection of the participants prior to following them up. The allocation of the exposure should be randomised, and there should be a clear control group which does not receive the exposure (known as a Randomised Controlled Trial). Ideally, 'blinding' of participants and investigators to the treatment allocation should also be performed whenever possible in order to reduce any differences between the groups. As biases and confounding are reduced through the randomised allocation of exposure, these studies provide the best quality of evidence of any single study type. However, in a similar fashion to cohort studies, they can be very costly, both in terms of money and time. Additionally, in the case of suspected harmful exposures, randomised controlled trials may not be an ethical option, and so they are commonly used when investigating interventions which are suspected to be beneficial.