  Fisheries management agencies around the world collect age data for the
purpose of assessing the status of natural resources in their jurisdiction.
Estimates of mortality rates represent a key information to assess the
sustainability of fish stocks exploitation. Contrary to medical research or
manufacturing where survival analysis is routinely applied to estimate failure
rates, survival analysis has seldom been applied in fisheries stock assessment
despite similar purposes between these fields of applied statistics. In this
paper, we developed hazard functions to model the dynamic of an exploited fish
population. These functions were used to estimate all parameters necessary for
stock assessment (including natural and fishing mortality rates as well as gear
selectivity) by maximum likelihood using age data from a sample of catch. This
novel application of survival analysis to fisheries stock assessment was tested
by Monte Carlo simulations to assert that it provided un-biased estimations of
relevant quantities. The method was applied to data from the Queensland
(Australia) sea mullet (Mugil cephalus) commercial fishery collected between
2007 and 2014. It provided, for the first time, an estimate of natural
mortality affecting this stock: 0.22 $\pm$ 0.08 year$^{-1}$.
