Chalmers Conferences, 9th European Conference on Mathematical and Theoretical Biology

Which nodes should be prioritised for intervention to effectively control epidemic outbreaks in networks?
Christoforos Hadjichrysanthou

Last modified: 2014-03-31


In cases where there are limited resources for the eradication of an epidemic, or where we seek to minimise possible adverse impacts of interventions such as vaccination, it is essential to optimise the efficacy of control measures. We introduce a new approach, Epidemic Control Analysis (ECA), to design effective targeted intervention strategies to mitigate and control the propagation of infections across complex heterogeneous networks. We exemplify this methodology in the context of a newly developed individual-level deterministic Susceptible-Infectious-Susceptible (SIS) epidemiological model. This provides a flexible way to systematically determine the impact of interventions on endemic infections in the population. Individuals are ranked based on their influence on the level of infectivity. The highest-ranked individuals are prioritised for targeted intervention. Many previous intervention strategies have determined prioritisation based mainly on the position of individuals in the network, described by various local and global network centrality measures, and their chance of being infectious. Comparisons of the predictions of the proposed strategy with those of widely used targeted intervention programmes on various model and real-world networks reveal its efficiency and accuracy. It is demonstrated that targeting central individuals or individuals that have high infection probability is not always the best strategy. The importance of individuals is not determined by network structure alone, but can be highly dependent on the infection dynamics. This interplay between network structure and infection dynamics is effectively captured by ECA.


Individual-based epidemic models; Heterogeneous contact networks; Targeted intervention strategies