Disease Transmission on Random Graphs Using Edge‐Based Percolation and its Application to Syphilis Control in KFL&A Area

Abstract

Bond percolation methods can be used to model disease transmission on complex networks and accommodate social heterogeneity while keeping tractability. We review the seminal works on this field by Newman (2002, 2003, 2010), and Miller, Slim & Volz (2011) and present a more clear and systematic discussion about the theoretical background, assumptions, derivation and development of the percolation method. We also present a new R package based on these results that take epidemic and network parameters as input and generates estimates of the epidemic trajectory and final size. Such theoretical framework and calculation tools allow us to apply the edge-based percolation model to solving real world public health emergencies. With syphilis rates continue rising in Ontario at an alarming rate, an ongoing project is collaborating with KFL&A public health to model Syphilis transmissions within the underserved high-risk community from data. The analysis and prediction of the model could provide scientific evidence to optimize implementation strategy based on community structure, thus help public health professionals to better response to the urgent crisis.