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Aggregation and environmental transmission in chronic wasting disease

  • Received: 01 March 2013 Accepted: 29 June 2018 Published: 01 December 2014
  • MSC : Primary: 92D30.

  • Disease transmission depends on the interplay between theinfectious agent and the behavior of the host. Some diseases, suchas Chronic Wasting Disease, can be transmitted directly betweenhosts as well as indirectly via the environment. The socialbehavior of hosts affects both of these pathways, and a successfulintervention requires knowledge of the relative influence of thedifferent etiological and behavioral aspects of the disease. Wedevelop a strategic differential equation model for ChronicWasting Disease and include direct and indirect transmission aswell as host aggregation into our model. We calculate the basicreproduction number and perform a sensitivity analysis based onLatin hypercube sampling from published parameter values. We findconditions for the existence of an endemic equilibrium, and showthat, under a certain mild assumption on parameters, the modeldoes not exhibit a backward bifurcation or bistability. Hence, thebasic reproduction number constitutes the disease eliminationthreshold. We find that the prevalence of the disease decreaseswith host aggregation and increases with the lifespan of theinfectious agent in the environment.

    Citation: Olga Vasilyeva, Tamer Oraby, Frithjof Lutscher. Aggregation and environmental transmission in chronic wasting disease[J]. Mathematical Biosciences and Engineering, 2015, 12(1): 209-231. doi: 10.3934/mbe.2015.12.209

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  • Disease transmission depends on the interplay between theinfectious agent and the behavior of the host. Some diseases, suchas Chronic Wasting Disease, can be transmitted directly betweenhosts as well as indirectly via the environment. The socialbehavior of hosts affects both of these pathways, and a successfulintervention requires knowledge of the relative influence of thedifferent etiological and behavioral aspects of the disease. Wedevelop a strategic differential equation model for ChronicWasting Disease and include direct and indirect transmission aswell as host aggregation into our model. We calculate the basicreproduction number and perform a sensitivity analysis based onLatin hypercube sampling from published parameter values. We findconditions for the existence of an endemic equilibrium, and showthat, under a certain mild assumption on parameters, the modeldoes not exhibit a backward bifurcation or bistability. Hence, thebasic reproduction number constitutes the disease eliminationthreshold. We find that the prevalence of the disease decreaseswith host aggregation and increases with the lifespan of theinfectious agent in the environment.


    [1] Nature Reviews Molecular Cell Biology, 8 (2007), 552-561.
    [2] PLoS One, 6 (2011), e19896.
    [3] Epidemiology and Infection, 129 (2002), 147-153.
    [4] J. Math. Biol., 66 (2013), 535-546.
    [5] Mathematical Biosciences and Engineering, 1 (2004), 361-404.
    [6] Science, 318 (2007), 930-936.
    [7] Ann. N.Y. Acad. Sci., 1134 (2008), 146-172.
    [8] Ecological Applications, 17 (2007), 140-153.
    [9] John Wiley & Sons, 2000.
    [10] Population Biology of Infectious Diseases, ed. R.M. Anderson and R.M. May, Dahlem Konferenzen, Springer-Verlag, 25 (1982), 87-102.
    [11] Wildlife Monographs, 104 (1989), 3-68.
    [12] PLoS ONE, 6 (2011), e23664.
    [13] The Journal of Wildlife Management, 65 (2001), 205-215.
    [14] Ecological Modelling, 222 (2011), 2722-2732.
    [15] Trends in Ecology & Evolution, 20 (2005), 511-519.
    [16] PLoS ONE, 4 (2009), e5916.
    [17] Journal of Animal Ecology, 47 (1978), 833-844.
    [18] Ecological Applications, 16 (2006), 2208-2214.
    [19] Emerg. Infect. Dis., 10 (2004), 1003-1006.
    [20] Princeton University Press, 2006.
    [21] Wildlife Society Bulletin, 31 (2003), 610-616.
    [22] Princeton Series in Theoretical and Computational Biology, Princeton University Press, 2003.
    [23] Journal of Applied Ecology, 46 (2009), 457-466.
    [24] Revue Scientifique et technique de l'Office International des Epizzoties, 21 (2002), 305-316.
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