How Does a Stochastic Graph Model Help to Control an Infectious Disease Outbreak?

• Activity Number: 126
• Type: Contributed
• Date/Time: Monday, August 1, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Health Policy Statistics
• Author(s): Yasaman Hosseinkashi*+ and Shojaeddin Chenouri and Christopher Small
• Companies: University of Waterloo and University of Waterloo and University of Waterloo
• Keywords: Stochastic graph process ; contact network ; measles outbreak ; stochastic epidemic models ; basic reproductive number

Abstract

A stochastic graph model is a bridge between standard SIR or SEIR epidemic models and graph theory. This combination provides a framework for analyzing the propagation of an infectious disease over a susceptible population with known or estimated contact network. The model permits the estimation of a sequence of outdegrees and indegrees which quantify the role of individuals in the infection spread. In this work we use the out- and indegree sequence to detect the super spreaders and the resistant individuals in the data from 1861 measles outbreak in Hagelloch, Germany. The result is applied to the adoption of optimum movement bands or quarantine. The disease outbreak is simulated in the same population, under different control strategies. In addition to the detection of influential individuals, the fitted model also permits estimating a dynamic version of the basic reproductive number over the outbreak period. A time series plot of this index is applied in comparing the simulation results.