Abstract
During the 2009 H1N1 influenza pandemic, there was rising concern about the potential contribution of international travel and global mass gatherings on the dynamic of the virus. The travel patterns after global mass gatherings can cause a rapid spread of infections. Studying the impact of travel patterns, high population density, and social mixing on disease transmission in these events could help public health authorities assess the risk of global epidemics and evaluate various prevention measures. There have been many studies on computational modeling of epidemic spread in various settings, but few of them address global mass gatherings. In this paper, we develop a stochastic susceptible-exposed-infected-recovered agent-based model to predict early stage of a disease epidemic among international participants in the annual Hajj or pilgrimage to Makkah (also called Mecca). The epidemic model is used to explore several scenarios with initial reproduction number R0 range from 1.3 to 1.7, and various initial proportions of infections range from 0.5% to 1% of total arriving pilgrims. Following an epidemic with one infectious per flight, the model results predict an average of 30% infectious and 20% exposed individuals in Makkah by the end of the arrival period. The proposed model can be used to assess various intervention measures during the arrival of international participants to control potential epidemics in different global mass gatherings.
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Alshammari, S.M., Mikler, A.R. (2018). Modeling Spread of Infectious Diseases at the Arrival Stage of Hajj. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10814. Springer, Cham. https://doi.org/10.1007/978-3-319-78759-6_39
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DOI: https://doi.org/10.1007/978-3-319-78759-6_39
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