In the control of tropical disease, data are typically collected using pool screening design. When eradication programs have been in place for a period of time, researchers are interested in testing whether the disease prevalence is below a certain target level using one-sided likelihood ratio test (LRT). We will investigate the finite and largesample properties of this test statistic. Based on simulations, if the number of pools is not large enough, the LRT has inflated type I error rate. Consequently, researchers will make the critical mistake of stopping the treatment when the target level has not been reached.