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Attributable fraction for the population combines both the relative risk of an incident with respect to the factor, as well as the prevalence of the factor in the population. Values of AF p close to 1 indicate that both the relative risk is high, and that the risk factor is prevalent.
The adverse outcome (black) risk difference between the group exposed to the treatment (left) and the group unexposed to the treatment (right) is −0.25 (RD = −0.25, ARR = 0.25).
In epidemiology, attributable fraction among the exposed (AF e) is the proportion of incidents in the exposed group that are attributable to the risk factor. The term attributable risk percent among the exposed is used if the fraction is expressed as a percentage. [ 1 ]
It is calculated as = /, where is the incidence in the exposed group, is the incidence in the population. [ 1 ] [ 2 ] It is used when an exposure reduces the risk, as opposed to increasing it, in which case its symmetrical notion is attributable fraction for the population .
The "68–95–99.7 rule" is often used to quickly get a rough probability estimate of something, given its standard deviation, if the population is assumed to be normal. It is also used as a simple test for outliers if the population is assumed normal, and as a normality test if the population is potentially not normal.
In epidemiology, preventable fraction among the unexposed (PFu), is the proportion of incidents in the unexposed group that could be prevented by exposure.It is calculated as = / =, where is the incidence in the exposed group, is the incidence in the unexposed group, and is the relative risk.
A CFR, in contrast, is the number of deaths among the number of diagnosed cases only, regardless of time or total population. [ 3 ] 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 ...
As an example, Canada's net population growth was 2.7 percent in the year 2022, dividing 72 by 2.7 gives an approximate doubling time of about 27 years. Thus if that growth rate were to remain constant, Canada's population would double from its 2023 figure of about 39 million to about 78 million by 2050.