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Modeling Spread of Infectious Diseases at the Arrival Stage of Hajj

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10814))

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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Notes

  1. 1.

    www.uqu.edu.sa/en/hajj.

References

  1. Abubakar, I., Gautret, P., Brunette, G.W., Blumberg, L., Johnson, D., Poumerol, G., Memish, Z.A., Barbeschi, M., Khan, A.S.: Global perspectives for prevention of infectious diseases associated with mass gatherings. Lancet. Infect. Dis. 12(1), 66–74 (2012)

    Article  Google Scholar 

  2. Ajelli, M., Gonçalves, B., Balcan, D., Colizza, V., Hu, H., Ramasco, J.J., Merler, S., Vespignani, A.: Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models. BMC Infect. Dis. 10(1), 190 (2010)

    Article  Google Scholar 

  3. Al-Tawfiq, J.A., Gautret, P., Benkouiten, S., Memish, Z.A.: Mass gatherings and the spread of respiratory infections. Lessons from the Hajj. Ann. Am. Thorac. Soc. 13(6), 759–765 (2016)

    Article  Google Scholar 

  4. Balcan, D., Gonçalves, B., Hu, H., Ramasco, J.J., Colizza, V., Vespignani, A.: Modeling the spatial spread of infectious diseases: the global epidemic and mobility computational model. J. Comput. Sci. 1(3), 132–145 (2010)

    Article  Google Scholar 

  5. Boëlle, P.Y., Ansart, S., Cori, A., Valleron, A.J.: Transmission parameters of the A/H1N1 (2009) influenza virus pandemic: a review. Influenza Other Respir. Viruses 5(5), 306–316 (2011)

    Article  Google Scholar 

  6. Carley, K.M., Fridsma, D.B., Casman, E., Yahja, A., Altman, N., Chen, L.C., Kaminsky, B., Nave, D.: BioWar: scalable agent-based model of bioattacks. IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 36(2), 252–265 (2006)

    Article  Google Scholar 

  7. Chao, D.L., Halloran, M.E., Obenchain, V.J., Longini Jr., I.M.: FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS Comput. Biol. 6(1), e1000656 (2010)

    Article  MathSciNet  Google Scholar 

  8. Chowell, G., Nishiura, H., Viboud, C.: Modeling rapidly disseminating infectious disease during mass gatherings. BMC Med. 10(1), 159 (2012)

    Article  Google Scholar 

  9. Coburn, B.J., Wagner, B.G., Blower, S.: Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1). BMC Med. 7(1), 30 (2009)

    Article  Google Scholar 

  10. Dridi, M.H.: Tracking individual targets in high density crowd scenes analysis of a video recording in Hajj 2009. Curr. Urban Stud. 3, 35–53 (2015)

    Article  Google Scholar 

  11. Fiore, A.E., Fry, A., Shay, D., Gubareva, L., Bresee, J.S., Uyeki, T.M., Centers for Disease Control and Prevention (CDC), et al.: Antiviral agents for the treatment and chemoprophylaxis of influenza: recommendations of the advisory committee on immunization practices (ACIP). MMWR Recomm. Rep. 60(1), 1–24 (2011)

    Google Scholar 

  12. Fraser, C., Donnelly, C.A., Cauchemez, S., Hanage, W.P., Van Kerkhove, M.D., Hollingsworth, T.D., Griffin, J., Baggaley, R.F., Jenkins, H.E., Lyons, E.J., et al.: Pandemic potential of a strain of influenza A (H1N1): early findings. Science 324(5934), 1557–1561 (2009)

    Article  Google Scholar 

  13. Hu, H., Nigmatulina, K., Eckhoff, P.: The scaling of contact rates with population density for the infectious disease models. Math. Biosci. 244(2), 125–134 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  14. Khan, K., Arino, J., Hu, W., Raposo, P., Sears, J., Calderon, F., Heidebrecht, C., Macdonald, M., Liauw, J., Chan, A., et al.: Spread of a novel influenza A (H1N1) virus via global airline transportation. N. Engl. J. Med. 361(2), 212–214 (2009)

    Article  Google Scholar 

  15. Memish, Z.A., Zumla, A., Alhakeem, R.F., Assiri, A., Turkestani, A., Al Harby, K.D., Alyemni, M., Dhafar, K., Gautret, P., Barbeschi, M., et al.: Hajj: infectious disease surveillance and control. Lancet 383(9934), 2073–2082 (2014)

    Article  Google Scholar 

  16. Morse, S.S.: Factors in the emergence of infectious diseases. In: Price-Smith, A.T. (ed.) Plagues and Politics. GIS, pp. 8–26. Palgrave Macmillan UK, London (2001). https://doi.org/10.1057/9780230524248_2

    Chapter  Google Scholar 

  17. Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G.S., Wallinga, J., et al.: Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med. 5(3), e74 (2008)

    Article  Google Scholar 

  18. Patlolla, P., Gunupudi, V., Mikler, A.R., Jacob, R.T.: Agent-based simulation tools in computational epidemiology. In: Böhme, T., Larios Rosillo, V.M., Unger, H., Unger, H. (eds.) IICS 2004. LNCS, vol. 3473, pp. 212–223. Springer, Heidelberg (2006). https://doi.org/10.1007/11553762_21

    Chapter  Google Scholar 

  19. Perez, L., Dragicevic, S.: An agent-based approach for modeling dynamics of contagious disease spread. Int. J. Health Geogr. 8(1), 50 (2009)

    Article  Google Scholar 

  20. Shi, P., Keskinocak, P., Swann, J.L., Lee, B.Y.: The impact of mass gatherings and holiday traveling on the course of an influenza pandemic: a computational model. BMC Public Health 10(1), 778 (2010)

    Article  Google Scholar 

  21. Steffen, R., Bouchama, A., Johansson, A., Dvorak, J., Isla, N., Smallwood, C., Memish, Z.A.: Non-communicable health risks during mass gatherings. Lancet. Infect. Dis. 12(2), 142–149 (2012)

    Article  Google Scholar 

  22. Stehlé, J., Voirin, N., Barrat, A., Cattuto, C., Colizza, V., Isella, L., Régis, C., Pinton, J.F., Khanafer, N., Van den Broeck, W., et al.: Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees. BMC Med. 9(1), 87 (2011)

    Article  Google Scholar 

  23. Tabatabaei, S.M., Metanat, M., et al.: Mass gatherings and infectious diseases epidemiology and surveillance. Int. J. Infect. 2(2) (2015)

    Google Scholar 

  24. Tanaka, G., Urabe, C., Aihara, K.: Random and targeted interventions for epidemic control in metapopulation models. Sci. Rep. 4, 5522 (2014)

    Article  Google Scholar 

  25. Tian, D., Liu, C., Sheng, Z., Chen, M., Wang, Y.: Analytical model of spread of epidemics in open finite regions. IEEE Access 5, 9673–9681 (2017)

    Article  Google Scholar 

  26. Tuite, A.R., Greer, A.L., Whelan, M., Winter, A.L., Lee, B., Yan, P., Wu, J., Moghadas, S., Buckeridge, D., Pourbohloul, B., et al.: Estimated epidemiologic parameters and morbidity associated with pandemic H1N1 influenza. Can. Med. Assoc. J. 182(2), 131–136 (2010)

    Article  Google Scholar 

  27. Yang, Y., Sugimoto, J.D., Halloran, M.E., Basta, N.E., Chao, D.L., Matrajt, L., Potter, G., Kenah, E., Longini, I.M.: The transmissibility and control of pandemic influenza A (H1N1) virus. Science 326(5953), 729–733 (2009)

    Article  Google Scholar 

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Correspondence to Sultanah M. Alshammari .

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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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