PCR testing is a crucial capability for managing disease outbreaks, but it is also a limited resource and must be used carefully to ensure the information gain from testing is valuable . Testing has two broad uses, namely to track epidemic dynamics and to reduce transmission by identifying and managing cases . In this work we develop a modelling framework to examine the effects of test allocation in an epidemic, with a focus on using testing to minimise transmission . Using the COVID-19 pandemic as an example, we examine how the number of tests conducted per day relates to reduction in disease transmission, in the context of logistical constraints on the testing system . We show that if daily testing is above the routine capacity of a testing system, which can cause delays, then those delays can undermine efforts to reduce transmission through contact tracing and quarantine . This work highlights that the two goals of aiming to reduce transmission and aiming to identify all cases are different, and it is possible that focusing on one may undermine achieving the other . To develop an effective strategy, the goals must be clear and performance metrics must match the goals of the testing strategy . If metrics do not match the objectives of the strategy, then those metrics may incentivise actions that undermine achieving the objectives.