Adaptive data-driven age and patch mixing in contact networks with recurrent mobility

ABSTRACT

Graphical Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form contacts if they meet in patch C. We build upon their approach to address three potential gaps that remain, outlined in the bullets below. We describe the steps required to implement our approach in detail, and present step-wise results of an example application to generate contact matrices for SARS-CoV-2 transmission modelling in Ontario, Canada. We also provide methods for deriving the mobility matrix based on GPS mobility data (appendix).