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Incidence is usually more useful than prevalence in understanding the disease etiology: for example, if the incidence rate of a disease in a population increases, then there is a risk factor that promotes the incidence. For example, consider a disease that takes a long time to cure and was widespread in 2002 but dissipated in 2003.
In science, prevalence describes a proportion (typically expressed as a percentage). For example, the prevalence of obesity among American adults in 2001 was estimated by the U. S. Centers for Disease Control (CDC) at approximately 20.9%. [5] Prevalence is a term that means being widespread and it is distinct from incidence.
In epidemiology, a rate ratio, sometimes called an incidence density ratio or incidence rate ratio, is a relative difference measure used to compare the incidence rates of events occurring at any given point in time. It is defined as:
An example would be all the people in a city during a specific time period. The constant K is assigned a value of 100 to represent a percentage. An example would be to find the percentage of people in a city who are infected with HIV: 6,000 cases in March divided by the population of a city (one million) multiplied by the constant ( K ) would ...
Note that the PPV is not intrinsic to the test—it depends also on the prevalence. [2] Due to the large effect of prevalence upon predictive values, a standardized approach has been proposed, where the PPV is normalized to a prevalence of 50%. [11] PPV is directly proportional [dubious – discuss] to the prevalence of the disease or condition ...
From a mathematical point of view, by taking values between 0 and 1 or 0% and 100%, CFRs are actually a measure of risk (case fatality risk) – that is, they are a proportion of incidence, although they do not reflect a disease's incidence. They are neither rates, incidence rates, nor ratios (none of which are limited to the range 0–1). They ...
Epidemiological (and other observational) studies typically highlight associations between exposures and outcomes, rather than causation. While some consider this a limitation of observational research, epidemiological models of causation (e.g. Bradford Hill criteria) [7] contend that an entire body of evidence is needed before determining if an association is truly causal. [8]
In epidemiology, data or facts about a population are called denominator data.Denominator data are independent of any specific disease or condition. This name is given because in mathematical models of disease, disease-specific data such as the incidence of disease in a population, the susceptibility of the population to a specific condition, the disease resistance, etc. disease-specific ...