Farr's Law and Social Risk Aversion in the Study of Epidemics
Brimacombe, M.
Show abstract
The modeling of the frequency of new cases of infection in an epidemic within a given time period remains of great interest. Farrs Law and the related Brownlee-Farr condition on infection counts implies a specific functional form for the relative infection incidence rate I(t) over the course of the epidemic. This form includes the Gaussian distribution, but also other distributions such as the exponential distribution. The Brownlee-Farr condition is shown to correspond as a mathematical function to the Pratt-Arrow ARA measure of relative risk avoidance, and also the hazard rate, with differences due to slight variations in the chosen units of measurement. These types of linkages may allow for the development of new areas of application for the various underlying model types, implying a greater flexibility in the choice of statistical model.
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