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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 ]
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 epidemiology, preventable fraction for the population (PFp), is the proportion of incidents in the population that could be prevented by exposing the whole population.. It is calculated as = /, where is the incidence in the exposed group, is the incidence in the populati
Many theoretical studies of the population dynamics, structure and evolution of infectious diseases of plants and animals, including humans, are concerned with this problem. [27] Research topics include: antigenic shift; epidemiological networks; evolution and spread of resistance; immuno-epidemiology; intra-host dynamics; Pandemic; pathogen ...
The formula for calculating the NEPP is = where N = population size,; P d = prevalence of the disease,; P e = proportion eligible for treatment,; r u = risk of the event of interest in the untreated group or baseline risk over appropriate time period (this can be multiplied by life expectancy to produce life-years),
In epidemiology, the standardized mortality ratio or SMR, is a quantity, expressed as either a ratio or percentage quantifying the increase or decrease in mortality of a study cohort with respect to the general population.
Firstly, a proportional measure of the extent of infection is chosen as the disease extent metric. For example, the metric might be the proportion of leaf area affected by mildew or the proportion of plants in a population showing dieback lesions. Measures of disease extent are then taken over time, and a mathematical model is fitted. The model ...
To derive the formula for the one-sample proportion in the Z-interval, a sampling distribution of sample proportions needs to be taken into consideration. The mean of the sampling distribution of sample proportions is usually denoted as μ p ^ = P {\displaystyle \mu _{\hat {p}}=P} and its standard deviation is denoted as: [ 2 ]