Computational Framework to Assess the Risk of Global Epidemics at Mass Gatherings
Sultanah Alshammari, University of North Texas
Due to the unique nature of the global mass gatherings and the public health hazards they pose, comprehensive studies of disease spread during these events are needed. The massive influx of spectators from different regions presents serious health threats and challenges for hosting countries and the countries where participants originate. The travel patterns at the end of global events could cause a rapid spread of infectious diseases affecting a large number of people within a short period of time. Mathematical and computational models provide valuable tools that help public health authorities to estimate, study, and control disease outbreaks at challenges settings such as mass gatherings. In this study, we present a computational framework to model disease spread at the annual global event of the Hajj (Muslim pilgrimage to Makkah, Saudi Arabia), where over two million pilgrims gathered from over 189 countries. We used the travel and demographic data of five Hajj seasons (2010-2014), and spatial data of the holy sites where the rituals are performed. We simulate the interactions of pilgrims using an agent-based model where each agent represents a pilgrim and maintains related demographic attributes and health information. The proposed model includes several simulations of the stages of Hajj with hourly or daily time steps. At each stage, the agent-based model of pilgrims is integrated to simulate their interactions within space and time frames of that stage.