Mass gatherings stress local and global health care systems as they bring together individuals from all over the world that have very different health conditions. We firstly provide an overview of the concepts and results of mathematical epidemiology and public health. Secondly, we present an introduction to the mathematical modelling of measles using deterministic and stochastic approaches for both single and multiple populations. Lastly, we develop a model for mass gatherings and present an application to measles during the Hajj by studying an SIR deterministic metapopulation model with residency and its stochastic analogue. The models incorporate real world country data and time dependent movement and transmission rates, accounting for realistic volume of international travel and seasonality of measles activity. Numerical results for the deterministic system are presented. We conclude with a discussion on further work.

Mass gatherings stress local and global health care systems as they bring together individuals from all over the world that have very different health conditions. We firstly provide an overview of the concepts and results of mathematical epidemiology and public health. Secondly, we present an introduction to the mathematical modelling of measles using deterministic and stochastic approaches for both single and multiple populations. Lastly, we develop a model for mass gatherings and present an application to measles during the Hajj by studying an SIR deterministic metapopulation model with residency and its stochastic analogue. The models incorporate real world country data and time dependent movement and transmission rates, accounting for realistic volume of international travel and seasonality of measles activity. Numerical results for the deterministic system are presented. We conclude with a discussion on further work.

This dissertation presents a data-driven computational epidemic framework to simulate disease epidemics at global mass gatherings. The annual Muslim pilgrimage to Makkah, Saudi Arabia is used to demonstrate the simulation and analysis of various disease transmission scenarios throughout the different stages of the event from the arrival to the departure of international participants. The proposed agent-based epidemic model efficiently captures the demographic, spatial, and temporal heterogeneity at each stage of the global event of Hajj. Experimental results indicate the substantial impact of the demographic and mobility patterns of the heterogeneous population of pilgrims on the progression of the disease spread in the different stages of Hajj. In addition, these simulations suggest that the differences in the spatial and temporal settings in each stage can significantly affect the dynamic of the disease. Finally, the epidemic simulations conducted at the different stages in this dissertation illustrate the impact of the differences between the duration of each stage in the event and the length of the infectious and latent periods. This research contributes to a better understanding of epidemic modeling in the context of global mass gatherings to predict the risk of disease pandemics caused by associated international travel. The computational modeling and disease spread simulations in global mass gatherings provide public health authorities with powerful tools to assess the implication of these events at a different scale and to evaluate the efficacy of control strategies to reduce their potential impacts.