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A Guide to HIV/AIDS Epidemiological and Surveillance Terms

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Frequently Used Terms in HIV/AIDS Monitoring and Epidemiological Research in Canada

C

CASE
(See also AIDS CASE)

A case is a person who has a particular disease. A variety of criteria may be used to identify cases. Cases can include people who are included in surveillance databases and reports. Often, this term is used generally to refer to individuals seeking the advice of a health care provider.

For example, a person with a diagnosis of HIV infection may be referred to as an HIV case, or there were 2,119 HIV cases reported in Canada in the year 2000. More generally, "Dr. Smith reviewed the files of the 100 cases seen this month at his clinic."

COHORT

A cohort is a group of people followed over a specified period of time. The term may be used generally, such as a group of students following the same program in school, but is more often applied to a group of people who are the subject of a research study.

In research, each member of a cohort has specific characteristics. These known characteristics can include

  • being free of the disease under investigation at the time the study begins;
  • either having or not having specific risk behaviour patterns (risk factors); or
  • having or not having prior experience of the treatment under investigation.

In the context of HIV studies, for example, subjects who have tested negative for HIV are followed for a prolonged period to see how the later development of new HIV infections is related to HIV-related risk factors.

The term cohort is frequently used in HIV/AIDS research to refer to the participants in a cohort study.

For example, the participants in Montreal's OMEGA Study are frequently referred to as the "Omega cohort". The OMEGA cohort is explained under the term COHORT STUDY below.

COHORT STUDY

The purpose of a cohort study is to investigate the development of new occurrences of a disease or to investigate how responses to treatment are related to specific factors. These factors can be recorded at the beginning of the study and/or during the course of the study.

A cohort study starts with a group of people who will be participants in the study. This group of people is called a cohort.

The cohort is followed for a specified time period, which can be weeks, months, years or decades. Follow-up data are collected at regularly defined periods either through the use of questionnaires, personal interviews, laboratory testing, medical examinations, or a combination of these methods.

A cohort study is sometimes referred to as a prospective study or a longitudinal study.

For example, recruitment for the OMEGA cohort study began in the Montreal region in October 1996. Each participant was tested for HIV and completed a questionnaire at study entry. Participants also completed the same questionnaire every 6 months afterwards. Men who tested negative for HIV and who gave their consent for participation in the study became study participants. During the first four years of the study, 15 men in the cohort became infected with HIV. Statistical analysis of the participants' questionnaire data showed that having a new HIV infection was related to a number of factors. These included low income, drug use, and having six or more casual sexual partners. (Remis et al., 2001)

CO-INFECTION

Having two infections at the same time. For example, a person infected with both HIV and hepatitis C (HCV), or HIV and tuberculosis (TB), has a co-infection. With co-infection the progression of either disease can potentially be accelerated as a result of infection with the other disease.

CONFIDENCE INTERVAL (CI)
(See also STATISTICAL SIGNIFICANCE, P VALUE)

Statistical analysis of research study data will not produce a result that is 100% accurate. The result reported for a study is the most likely result. A confidence interval is an estimate of the spread between the lowest likely result (lower confidence limit) and the highest likely result (upper confidence limit) of a study. The true result of the study probably lies somewhere within this confidence interval. The smaller the spread of the confidence interval, the more precise the result is likely to be.

Most research studies display results using 95% confidence intervals. A 95% confidence interval means that there is a 95% chance that the true study result lies between these two confidence limits. In opinion surveys, a 95% confidence interval is sometimes expressed by the phrase, "the result is accurate 19 times out of 20", which is equal to 95%. That is, the true study result lies within the interval with a 95% probability.

Confidence intervals are determined by the use of mathematical formulas with a set of data.

The term confidence interval is abbreviated as CI.

In a hypothetical example, it may be reported that "The estimated number of people living with HIV (prevalence) among a group of injecting drug users (IDUs) was 18.6% with a 95% CI of 12.9-24.0." This means that the study investigators are 95% sure that the true prevalence lies somewhere between the two confidence limits of 12.9% and 24.0%.

If there were 1,000 injecting drug users in the group under study, it would be reported that approximately 186 (18.6%) of them were living with HIV. It is most accurate to say that the study investigators are 95% sure that between 129 (12.9%) and 240 (24.0%) of the injecting drug users in the study were living with HIV.

CUMULATIVE INCIDENCE
(See Appendix)


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Date Modified: 2006-09-27

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