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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 calculated as = / = /, where is the incidence in the exposed group, is the incidence in the unexposed group, and is the relative risk. [2] It is used when an exposure increases the risk, as opposed to reducing it, in which case its symmetrical notion is preventable fraction among the unexposed .
For example, in 1953 Levin's paper estimated that lung cancer has a relative risk of 3.6–13.4 in smokers compared to non-smokers, and that the proportion of the population exposed to smoking was 0.5–0.96, resulting in the high AF p value of 0.56–0.92. [6]
In statistics a population proportion, generally denoted by or the Greek letter, [1] is a parameter that describes a percentage value associated with a population.A census can be conducted to determine the actual value of a population parameter, but often a census is not practical due to its costs and time consumption.
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 ...
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.