A new insight into isolating the high-degree nodes in network to control infectious diseases

Abstract

It has been a challenge to formulate network-based control measures on infectious diseases, especially on emerging diseases, due to the complexity of the network topology. Generally, isolating high-degree nodes is one of the intuitive intervention measures. The final size and the epidemic duration are two vital evaluation indices of infectious diseases severity, but the last one has not been explicitly calculated so far in network-based models. Therefore, in this paper, we studied the effects of two measures of isolating high-degree nodes at different time—complete isolation and incomplete isolation, on these two indices. We applied the reducing-dimension method to convert the mean-field model in networks into an equivalent and simpler low-dimension model, and then calculated the exact expression of the final size and the epidemic duration. We 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 such a strategy lengthens the epidemic duration, and otherwise shortens that period. 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 insight into controlling infectious diseases in network.