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A mathematical model for the transmission of louse-borne relapsing fever

Published online by Cambridge University Press:  24 August 2017

AHUOD ALSHERI
Affiliation:
Department of Mathematics, University of Surrey, Guildford, Surrey GU2 7XH, UK emails: a.alsheri@surrey.ac.uk, s.gourley@surrey.ac.uk
STEPHEN A. GOURLEY
Affiliation:
Department of Mathematics, University of Surrey, Guildford, Surrey GU2 7XH, UK emails: a.alsheri@surrey.ac.uk, s.gourley@surrey.ac.uk

Abstract

We present a detailed derivation and analysis of a model consisting of seven coupled delay differential equations for louse-borne relapsing fever (LBRF), a disease transmitted from human to human by the body louse Pediculus humanus humanus. Delays model the latency stages of LBRF in humans and lice, which vary in duration from individual to individual, and are therefore modelled using distributed delays with relatively general kernels. A particular feature of the transmission of LBRF to a human is that it involves the death of the louse, usually by crushing which has the effect of releasing the infected body fluids of the dead louse onto the hosts skin. Careful attention is paid to this aspect. We obtain results on existence, positivity, boundedness, linear and nonlinear stability, and persistence. We also derive a basic reproduction number R0 for the model and discuss its dependence on the model parameters. Our analysis of the model suggests that effective louse control without crushing should be the best strategy for LBRF eradication. We conclude that simple measures and precautions should, in general, be sufficient to facilitate disease eradication.

Type
Papers
Copyright
Copyright © Cambridge University Press 2017 

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References

[1] Badiaga, S. & Brouqui, P. (2012) Human louse-transmitted infectious diseases. Clin. Microbiol. Infect. 18, 332337.Google Scholar
[2] Ciervo, A., Mancini, F., Di Bernardo, F., Giammanco, A., Vitale, G., Dones, P., Fasciana, T., Quartaro, P., Mazzola, G. & Rezza, G. (2016) Louse-borne relapsing fever in young migrants, Sicily, Italy, July–September 2015. Emerg. Infect. Dis. 22, 152153.Google Scholar
[3] Cutler, S. J., Abdissa, A. & Trape, J. F. (2009) New concepts for the old challenge of African relapsing fever borreliosis. Clin. Microbiol. Infect. 15, 400406.Google Scholar
[4] Gourley, S. A., Thieme, H. R. & van den Driessche, P. (2011) Stability and persistence in a model for bluetongue dynamics. SIAM J. Appl. Math. 71, 12801306.Google Scholar
[5] Gubbins, S., Carpenter, S., Baylis, M., Wood, J. L. N. & Mellor, P. S. (2008) Assessing the risk of bluetongue to UK livestock: Uncertainty and sensitivity analyses of a temperature-dependent model for the basic reproduction number. J. R. Soc. Interface 5, 363371.Google Scholar
[6] Hale, J. K. & Verduyn Lunel, S. M. (1993) Introduction to Functional-Differential Equations, Applied Mathematical Sciences, Vol. 99, Springer-Verlag, New York.Google Scholar
[7] Hartemink, N. A., Purse, B. V., Meiswinkel, R., Brown, H. E., de Koeijer, A., Elbers, A. R., Boender, G.-J., Rogers, D. J. & Heesterbeek, J. A. P. (2009) Mapping the basic reproduction number (R 0) for vector-borne diseases: A case study on bluetongue virus. Epidemics 1, 153161.Google Scholar
[8] Hoch, M., Wieser, A., Löscher, T., Margos, G., Pürner, F., Zühl, J., Seilmaier, M., Balzer, L., Guggemos, W., Rack-Hoch, A., Von Both, U., Hauptvogel, K., SchöNberger, K., Hautmann, W., Sing, A. & Fingerle, V. (2015) Louse-borne relapsing fever (Borrelia recurrentis) diagnosed in 15 refugees from northeast Africa: Epidemiology and preventive control measures, Bavaria, Germany, July to October 2015. Euro Surveill 20 (42):pii=30046, doi: 10.2807/1560-7917.ES.2015.20.42.30046.Google Scholar
[9] Horton, B. J. & Carew, A. L. (2015) A comparison of deterministic and stochastic models for predicting the impacts of different sheep body lice (Bovicola ovis) management practices. Anim. Prod. Sci. 55, 122132.Google Scholar
[10] Kuang, Y. (1993) Delay Differential Equations with Applications in Population Dynamics, Mathematics in Science and Engineering, Vol. 191, Academic Press, Inc., Boston, MA.Google Scholar
[11] Laguna, M. F. & Risau-Gusman, S. (2011) Of lice and math: Using models to understand and control populations of head lice. PLoS One 6 (7), e21848.Google Scholar
[12] Meri, T., Cutler, S. J., Blom, A. M., Meri, S. & Jokiranta, T. S. (2006) Relapsing fever spirochetes Borrelia recurrentis and B. duttonii acquire complement regulators C4b-binding protein and factor H. Infect. Immunity 74, 41574163.Google Scholar
[13] Palmer, C. (2016) The Dynamics of Vector-borne Relapsing Diseases, PhD dissertation. University of Montana.Google Scholar
[14] Raoult, D. & Roux, V. (1999) The body louse as a vector of reemerging human diseases. Clin. Infect. Dis. 29, 888911.Google Scholar
[15] Smith, H. L. (1995) Monotone Dynamical Systems. An Introduction to the Theory of Competitive and Cooperative Systems, Mathematical Surveys and Monographs, Vol. 41, American Mathematical Society, Providence, RI.Google Scholar
[16] Southern, P. M., Jr. & Sanford, J. P. (1969) Relapsing fever: A clinical and microbiological review. Medicine 48, 129150.Google Scholar