It has been a challenge to formulate network-based control measures on infectious diseases, especially on emerging diseases due to the complex network topology. Isolating high-degree nodes is the generally intuitive intervention measure. The final size and the epidemic duration are two vital evaluation indices of infectious diseases severity, but the epidemic duration has not been explicitly calculated so far in network-based models. Therefore, in this talk, we studied the effects of two measures of isolating high-degree nodes at different time—complete isolation and incomplete isolation, on two indices. We applied the reducing-dimension technique to convert the mean-field model in network into an equivalent and simpler low-dimension model, and then calculated the exact expression of the final size and the epidemic duration. We also calculated two indices explicitly in two isolation measures. It was found that, in complete isolation the final size always reduces but there exists an isolation time threshold of the epidemic duration in some cases, before that the complete isolation lengthens the epidemic duration, and otherwise shortens the epidemic duration. In contrast, in incomplete isolation the epidemic duration always increases but there exists an isolation time threshold of the final size, before which, the incomplete isolation reduces the final size, and otherwise increases the final size. This result provides a new insights into controlling infectious diseases in network.