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Agent Based Modelling and West Nile Virus: A Survey

  • Hamid Reza Nasrinpour
  • Marcia R. Friesen
  • Robert D. McLeod
Review Article
  • 27 Downloads

Abstract

West Nile Virus (WNV) is a mosquito-borne disease heavily influenced by Avian species as amplifying hosts. In many other mosquito-borne diseases humans act as amplifying host. This, in general, makes the modelling effort of WNV fundamentally differs from other mosquito-borne diseases. Agent-based modelling (ABM) is a fairly recent approach for studying complex systems such as WNV transmission. Intrinsically, ABMs can capture heterogeneous properties of a system by designing the rules of behaviour at an individual-level. In the WNV epidemiology, these individuals (i.e. agents) are various species of mosquitoes, birds and mammals (including humans). In this paper, we survey the literature of some traditional mathematical models of WNV, a number of agent-based models of mosquito behaviours and mosquito-borne diseases, as well as ABM within the WNV epidemiology. While there is a relatively large number of studies of both ABMs and WNV models on their own, very few WNV–ABM exist.

Keywords

Agent-based model Individual-based model Mosquito-borne disease Multi-agent systems West Nile Virus 

Notes

Funding

Funding was supported by The Teaching Reform Project of Higher Education of Zhejiang Province (No. jg20160374), The Teaching Reform Project of Higher Education of Zhejiang Province (No. jg20160374).

References

  1. 1.
    Smithburn, K. C., Hughes, T. P., Burke, A. W., & Paul, J. H. (1940). A neurotropic virus isolated from the blood of a native of Uganda1. The American Journal of Tropical Medicine and Hygiene, 1(4), 471–492.CrossRefGoogle Scholar
  2. 2.
    Zeller, H. G., & Schuffenecker, I. (2004). West Nile virus: An overview of its spread in Europe and the Mediterranean basin in contrast to its spread in the Americas. European Journal of Clinical Microbiology and Infectious Diseases, 23, 147–156.  https://doi.org/10.1007/s10096-003-1085-1.CrossRefGoogle Scholar
  3. 3.
    Nash, D., Mostashari, F., Fine, A., Miller, J., O’Leary, D., Murray, K., et al. (2001). The outbreak of West Nile virus infection in the New York City area in 1999. New England Journal of Medicine, 344, 1807–1814.CrossRefGoogle Scholar
  4. 4.
    Health Canada. West Nile virus. October 10, 2012. Retrieved April 15, 2015, from http://healthycanadians.gc.ca/diseases-conditions-maladies-affections/disease-maladie/wnv-vno-eng.php.
  5. 5.
    Government of Manitoba. West Nile virus fact sheet. Retrieved April 15, 2015, from http://www.gov.mb.ca/health/publichealth/factsheets/target.pdf.
  6. 6.
    Chen, C.-C., Epp, T., Jenkins, E., Waldner, C., Curry, P. S., & Soos, C. (2012). Predicting weekly variation of Culex tarsalis (Diptera: Culicidae) West Nile virus infection in a newly endemic region, the Canadian prairies. Journal of Medical Entomology, 49, 1144–1153.  https://doi.org/10.1603/ME11221.CrossRefGoogle Scholar
  7. 7.
    American Mosquito Control Association. Mosquito life cycle. Retrieved April 15, 2015, from http://www.mosquito.org/life-cycle, http://www.webcitation.org/6iJntDZde.
  8. 8.
    Bowman, C., Gumel, A. B., van den Driessche, P., Wu, J., & Zhu, H. (2005). A mathematical model for assessing control strategies against West Nile virus. Bulletin of Mathematical Biology, 67, 1107–1133.  https://doi.org/10.1016/j.bulm.2005.01.002.MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Rappole, J. H., Compton, B. W., Leimgruber, P., Robertson, J., King, D. I. (2006). Renner SCC-/home/cmbarker/documents/references/Rappole_2006_VBZD_Modeling_movement_of_WNV_in_the_western_hemisphere. pd. Modeling movement of West Nile virus in the western hemisphere. Vector-Borne Zoonotic Disease 6, 128–139.  https://doi.org/10.1673/031.007.0501.
  10. 10.
    Nasrinpour, H. R., Reimer, A. A., Friesen, M. R., & McLeod, R. D. (2017). Data preparation for West Nile virus agent-based modelling: Protocol for processing bird population estimates and incorporating ArcMap in AnyLogic. JMIR Research Protocols, 6, e138.  https://doi.org/10.2196/resprot.6213.CrossRefGoogle Scholar
  11. 11.
    Nasrinpour, H. R., Friesen, M. R., McLeod, R.D. (2016). An agent-based model of message propagation in the facebook electronic social network. http://arxiv.org/abs/1611.07454.
  12. 12.
    Chevalier, V., Tran, A., & Durand, B. (2013). Predictive modeling of west nile virus transmission risk in the mediterranean basin: How far from landing? International Journal of Environmental Research and Public Health, 11, 67–90.  https://doi.org/10.3390/ijerph110100067.CrossRefGoogle Scholar
  13. 13.
    Rodríguez-Prieto, V., Martínez-López, B., Martínez, M., Muñoz, M. J., & Sánchez-Vizcaíno, J. M. (2012). Identification of suitable areas for West Nile virus outbreaks in equid populations for application in surveillance plans: The example of the Castile and Leon region of Spain. Epidemiology and Infection, 140, 1617–1631.  https://doi.org/10.1017/S0950268811002366.CrossRefGoogle Scholar
  14. 14.
    Balenghien, T., Fouque, F., Sabatier, P., & Bicout, D. J. (2011). Theoretical formulation for mosquito host-feeding patterns: Application to a West Nile virus focus of southern France. Journal of Medical Entomology, 48, 1076–1090.CrossRefGoogle Scholar
  15. 15.
    Thomas, D. M., & Urena, B. (2001). A model describing the evolution of West Nile-like encephalitis in New York City. Mathematical and Computer Modelling, 34, 771–781.  https://doi.org/10.1016/S0895-7177(01)00098-X.MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Wonham, M. J., De-Camino-Beck, T., & Lewis, M. A. (2004). An epidemiological model for West Nile virus: Invasion analysis and control applications. Proceedings of the Royal Society of London B: Biological Sciences., 271, 501–507.  https://doi.org/10.1098/rspb.2003.2608.CrossRefGoogle Scholar
  17. 17.
    Cruz-Pacheco, G., Esteva, L., Montaño-Hirose, J. A., & Vargas, C. (2005). Modelling the dynamics of West Nile Virus. Bulletin of Mathematical Biology, 67, 1157–1172.  https://doi.org/10.1016/j.bulm.2004.11.008.MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Simpson, J. E., Hurtado, P. J., Medlock, J., Molaei, G., Andreadis, T. G., Galvani, A. P., et al. (2012). Vector host-feeding preferences drive transmission of multi-host pathogens: West Nile virus as a model system. Proceedings of the Royal Society of London B: Biological Sciences, 279, 925–933.  https://doi.org/10.1098/rspb.2011.1282.CrossRefGoogle Scholar
  19. 19.
    Friesen, M. R., & McLeod, R. D. (2014). A survey of agent-based modeling of hospital environments. IEEE Access, 2, 227–233.  https://doi.org/10.1109/ACCESS.2014.2313957.CrossRefGoogle Scholar
  20. 20.
    Laskowski, M., Demianyk, B. C. P., Witt, J., Mukhi, S. N., Friesen, M. R., & McLeod, R. D. (2011). Agent-based modeling of the spread of influenza-like illness in an emergency department: A simulation study. IEEE Transactions on Information Technology in Biomedicine, 15, 877–889.  https://doi.org/10.1109/TITB.2011.2163414.CrossRefGoogle Scholar
  21. 21.
    Neighbour, R., Oppenheimer, L., Mukhi, S. N., Friesen, M. R., & McLeod, R. D. (2010). Agent based modeling of “crowdinforming” as a means of load balancing at emergency departments. Online Journal of Public Health Informatics.  https://doi.org/10.5210/ojphi.v2i3.3225.Google Scholar
  22. 22.
    Silverman, B. G., Hanrahan, N., Bharathy, G., Gordon, K., & Johnson, D. (2015). A systems approach to healthcare: Agent-based modeling, community mental health, and population well-being. Artificial Intelligence in Medicine, 63, 61–71.  https://doi.org/10.1016/j.artmed.2014.08.006.CrossRefGoogle Scholar
  23. 23.
    Cummins, B., Cortez, R., Foppa, I. M., Walbeck, J., & Hyman, J. M. (2012). A spatial model of mosquito host-seeking behavior. PLoS Computational Biology, 8(5), e1002500.  https://doi.org/10.1371/journal.pcbi.1002500.MathSciNetCrossRefGoogle Scholar
  24. 24.
    de Almeida, S. J., Martins Ferreira, R. P., Eiras, Á. E., Obermayr, R. P., & Geier, M. (2010). Multi-agent modeling and simulation of an Aedes aegypti mosquito population. Environmental Modelling & Software, 25, 1490–1507.  https://doi.org/10.1016/j.envsoft.2010.04.021.CrossRefGoogle Scholar
  25. 25.
    Chao, D. L., Halstead, S. B., Halloran, M. E., & Longini, I. M. (2012). Controlling dengue with vaccines in Thailand. PLoS Neglected Tropical Diseases., 6, e1876.  https://doi.org/10.1371/journal.pntd.0001876.CrossRefGoogle Scholar
  26. 26.
    Eckhoff, P. A. (2011). A malaria transmission-directed model of mosquito life cycle and ecology. Malaria Journal, 10, 303.  https://doi.org/10.1186/1475-2875-10-303.MathSciNetCrossRefGoogle Scholar
  27. 27.
    Arifin, S., Zhou, Y., Davis, G. J., Gentile, J. E., Madey, G. R., & Collins, F. H. (2014). An agent-based model of the population dynamics of Anopheles gambiae. Malaria Journal, 13, 424.  https://doi.org/10.1186/1475-2875-13-424.CrossRefGoogle Scholar
  28. 28.
    Gunaratne, C., Akbas, M. I., Garibay, I., Ozmen, O. (2016). Evaluation of Zika vector control strategies using agent-based modeling. arXiv:1604.06121.
  29. 29.
    Mniszewski, S. M., Manore, C. A., Bryan, C., Del Valle, S. Y., Roberts, D. (2014). Towards a hybrid agent-based model for mosquito borne disease. Summer Computer Simulation Conference (SCSC 2014) (p. 10). Monterey, California, USA: NIH Public Access http://www.ncbi.nlm.nih.gov/pubmed/26618203.
  30. 30.
    Manore, C. A., Hickmann, K. S., Hyman, J. M., Foppa, I. M., Davis, J. K., Wesson, D. M., et al. (2015). A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease. Journal of Biological Dynamics, 9, 52–72.  https://doi.org/10.1080/17513758.2015.1005698.MathSciNetCrossRefGoogle Scholar
  31. 31.
    Adams, B., & Kapan, D. D. (2009). Man bites mosquito: Understanding the contribution of human movement to vector-borne disease dynamics. PLoS ONE, 4, e6763.  https://doi.org/10.1371/journal.pone.0006763.CrossRefGoogle Scholar
  32. 32.
    Perkins, T. A., Scott, T. W., Le Menach, A., & Smith, D. L. (2013). Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission. PLoS Computational Biology, 9, e1003327.  https://doi.org/10.1371/journal.pcbi.1003327.CrossRefGoogle Scholar
  33. 33.
    Padmanabha, H., Durham, D., Correa, F., Diuk-Wasser, M., & Galvani, A. (2012). The interactive roles of aedes aegypti super-production and human density in dengue transmission. PLoS Neglected Tropical Diseases, 6, E1799.  https://doi.org/10.1371/Journal.Pntd.0001799.CrossRefGoogle Scholar
  34. 34.
    Li, Z., Hayse, J., Hlohowskyj, I., Smith, K., Smith, R. (2005). Agent-based model for simulation of West Nile virus transmission. The agent 2005 conference on generative social processes, models, and mechanisms (pp. 459–472). http://mysite.science.uottawa.ca/rsmith43/AgentbasedmodelWNV.pdf, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.493.9366.
  35. 35.
    Bouden, M., Moulin, B., & Gosselin, P. (2008). The geosimulation of West Nile virus propagation: A multi-agent and climate sensitive tool for risk management in public health. International Journal of Health Geographics, 7, 35.  https://doi.org/10.1186/1476-072X-7-35.CrossRefGoogle Scholar
  36. 36.
    Régnière, J., St-Amant, R., Béchard, A. (2014). BioSIM 10—User’s manual. Natl Resour Canada, Can For Serv, Info Rep LAU-X-155. https://cfs.nrcan.gc.ca/publications?id=34818 ISBN:978-1-100-23464-9.
  37. 37.
    Madder, D. J., Surgeoner, G. A., & Helson, B. V. (1983). Number of generations, egg production, and developmental time of Culex pipiens and Culex restauns (Diptera: Culicidae) in southern Ontario. Journal of Medical Entomology, 20, 275–287.CrossRefGoogle Scholar
  38. 38.
    Sauer, J. R., Hines, J. E., Fallon, K. L., Pardieck, D. J., Ziolkowski, J., Link, W. A. (2014). The North American breeding bird survey, results and analysis 1966–2013. Version 01302015 USGS Patuxent Wildlife Research Center, Laurel, MD. http://www.mbr-pwrc.usgs.gov/bbs/ Retrieved April 24, 2015, from http://www.webcitation.org/6lCuLOI3C.
  39. 39.
    Reeves, W. T. (1983). Particle systems—a technique for modeling a class of fuzzy objects. ACM Transactions on Graphics (TOG), 17, 359–375.  https://doi.org/10.1145/964967.801167.Google Scholar

Copyright information

© Taiwanese Society of Biomedical Engineering 2018

Authors and Affiliations

  1. 1.Electrical and Computer Engineering DepartmentUniversity of ManitobaWinnipegCanada
  2. 2.Centre for Engineering Professional Practice & Engineering EducationUniversity of ManitobaWinnipegCanada

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