The constraints imposed by the availability of fast and accurate diagnostic methods are factors that should not be overlooked in flu intervention policy making. However, previous works on pandemic modelling either treat ILIs as false positives that consume resources, or assume perfect diagnosis without accounting for the costs associated with the use of the different diagnostic techniques. In this work, we aim to investigate the cost and effectiveness of various intervention policies when implemented with different diagnostic methods. Specifically, we want to address the following questions-Is a fast and accurate testkit necessary in mitigating the spread of an ongoing pandemic? In addition, are there any other dominating factors that should be given due consideration in forming pandemic mitigation policies? To do so, we developed a stochastic agent-based epidemic framework and implemented it on a small city-scale model, typified by developed countries such as Singapore and the United States. The impact of testkits when used in the context of different intervention policies is then assessed by comparing the severity of the outbreak with an aggregate cost function which encompasses the various costs and resources involved.