We apply a new algorithm for spatially simulating animal trapping that utilises a detection function and allows for competition between animals and traps. Estimates of the parameters of the detection function from field studies allowed us to simulate realistically the expected range of detection probabilities of brushtail possums caught in traps. Using this model we evaluated a common index of population density of brushtail possums based on the percentage of leg-hold traps catching possums. Using field estimates of the parameters of the detection function, we simulated the relationship between the trap-catch index and population density. The relationship was linear up to densities of 10 possums ha^–1. We also investigated the accuracy (bias and precision) of the trap-catch index for possums to estimate relative changes in population density (relative abundance) under conditions of varying detection probability, and compared these results with those obtained using a removal estimate of the population in the vicinity of trap lines. The ratio of trap-catch indices was a more precise estimator of relative abundance than the ratio of removal estimates but was positively biased (i.e. overestimated relative abundance). In contrast, the ratio of removal estimates was relatively unbiased but imprecise. Despite the positive bias, the trap-catch index had a higher power to determine the correct ranking between population densities than the removal estimate. Although varying detection probability can bias estimates of relative abundance using indices, we show that the potential for bias to lead to an incorrect result is small for indices of brushtail possum density based on trapping.