Question

Regarding John Snow and the cholera outbreak use case control design to answer the following.

What are the historical concepts and practices of case control design that provide the foundation for the practice of epidemiology and epidemiological research related sciences?

What are the advantages and disadvantages of case control design as it relates to cholera?

What common statistical measures are utilized in case control design? What are the sampling issues with this design?

Regarding epidemiological research how is cholera controlled with case control design?

Answer 1

Advantages:

• They are efficient for rare diseases or diseases with a long latency period between exposure and disease manifestation.
• They are less costly and less time-consuming; they are advantageous when exposure data is expensive or hard to obtain.
• They are advantageous when studying dynamic populations in which follow-up is difficult.

Disadvantages:

• They are subject to selection bias.
• They are inefficient for rare exposures.
• Information on exposure of Cholera is subject to observation bias.
• They generally do not allow calculation of incidence of cholera (absolute risk).

A cohort study is one in which subjects, initially disease free, are followed up over a period of time. Some will be exposed to some risk factor, for example cigarette smoking. The outcome may be death and we may be interested in relating the risk factor to a particular cause of death. Clearly, these have to be large, long term studies and tend to be costly to carry out. If records have been kept routinely in the past then a historical cohort study may be carried out. The cohort is all cases of appendicitis admitted over a given period and a sample of the records could be inspected retrospectively. A typical example would be to look at birth weight records and relate birth weight to disease in later life.

These studies differ in essence from retrospective studies, which start with diseased subjects and then examine possible exposure. Such case control studies are commonly undertaken as a preliminary investigation, because they are relatively quick and inexpensive. It is retrospective because we argued from the blood pressure to the occupation and did not start out with subjects assigned to occupation. There are many confounding factors in case control studies. For example, does occupational stress cause high blood pressure, people prone to high blood pressure choose stressful occupations. A particular problem is recall bias, in that the cases, with the disease, are more motivated to recall apparently trivial episodes in the past than controls, who are disease free.

Good sampling methods must exist in the environment of all of these steps. These steps are (1) a statement of the survey objectives, (2) the definition of the population to be sampled, (3) the data to be collected, (4) the degree of precision required, (5) the methods of measurement, (6) the frame or the partitioning of the population into sampling units, (7) the sample selection methods, (8) the pretest, (9) the fieldwork organization, (10) the summary and analysis of the data, and (11) a review of the entire process to see what can be learned for future surveys. Mathematically, the major concerns for sample design have focused on the sample selection procedures and the associated estimation procedures that yield precise estimates. Optimization of sample designs involves obtaining the best possible precision for a fixed cost or minimizing survey costs subject to one or more constraints on the precision of estimates. Optimized designs sometimes are called efficient designs.

Case-control studies are commonly used to evaluate effectiveness of licensed vaccines after deployment in public health programs. Such studies can provide policy-relevant data on vaccine performance under ‘real world’ conditions, contributing to the evidence base to support and sustain introduction of new vaccines. However, case-control studies do not measure the impact of vaccine introduction on disease at a population level, and are subject to bias and confounding, which may lead to inaccurate results that can misinform policy decisions.