Within each implemented intervention policy, the impact of having a fast testkit on the total and peak attack rates is only matched when a slower diagnosis method is used and the patient stays at the hospital. In some cases, requiring the patients to stay while waiting for the test results may even be more effective in containing the virus, as exemplified by policies P3b and P4b shown in figure 4a. However, the peak waiting time associated with such an approach may prohibit its effective implementation. Of course, one can simply assume that all patients who exhibit influenza-like symptoms have contracted pandemic influenza and issue them with the antiviral drugs. The downside of this approach is then the increased drug usage, and the proportion being wasted due to consumption by those inflicted with ILIs (figure 5a). Nonetheless, it may still be a viable option if the testkits constitute another limited resource that has to be managed properly. Figure 6 shows the plot comparing the total attack rate with the aggregate cost. From the plot, we see that in the context of most intervention policies, diagnostic approach D1 is distributed closer to the desired lower-left quadrant-which corresponds to an optimal ratio of number of people infected compared with resources consumed-especially when contact tracing has been implemented. Even with the use of diagnostic testkits, a slower one that requires the patient to stay, coupled with an appropriate intervention policy, is comparable to using a fast testkit. The only consideration for such an approach would then be the peak hospital waiting room occupancy. However, given that the availabilities of antiviral drugs and testkits are usually the main limiting factors, a slow testkit with the patient waiting in the hospital may still be preferred when a fast and accurate kit is not yet ready.