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Dynamics of a Nonlocal Dispersal Foot-and-Mouth Disease Model in a Spatially Heterogeneous Environment

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Abstract

Foot-and-mouth disease is one of the major contagious zoonotic diseases in the world. It is caused by various species of the genus Aphthovirus of the family Picornavirus, and it always brings a large number of infections and heavy financial losses. The disease has become a major public health concern. In this paper, we propose a nonlocal foot-and-mouth disease model in a spatially heterogeneous environment, which couples virus-to-animals and animals-to-animals transmission pathways, and investigate the dynamics of the disperal. The basic reproduction number \({{\cal R}_0}\) is defined as the spectral radius of the next generation operator \({\cal R}\left( x \right)\) by a renewal equation. The relationship between \({{\cal R}_0}\) and a principal eigenvalue of an operator \({{\cal L}_0}\) is built. Moreover, the proposed system exhibits threshold dynamics in terms of \({{\cal R}_0}\), in the sense that \({{\cal R}_0}\) determines whether or not foot-and-mouth disease invades the hosts. Through numerical simulations, we have found that increasing animals’ movements is an effective control measure for preventing prevalence of the disease.

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References

  1. Carpenter T E, O’Brien J M, Hagerman A D, McCarl B A. Epidemic and economic impacts of delayed detection of foot-and-mouth disease: a case study of a simulated outbreak in California. J Vet Diagn Invest, 2011, 23: 26–33

    Article  Google Scholar 

  2. Matthews K. A Review of Australias Preparedness for the Threat of Foot-and-Mouth Disease[M/OL]. Canberra, ACT: Australian Government Department of Agriculture, Fisheries and Forestry 2011[2020-03-20]. http://www.agriculture.gov.au/animal-plant-health/pests-diseases-weeds/animal/fmd/review-foot-and-mouth-disease

  3. Rushton J, Knight-Jones T J D, Donaldson A I, deLeeuw P W, Ferrari G, Domenech J. The Impact of Foot and Mouth Disease-Supporting Document N1. Paper prepared for the FAO/OIE Global Conference on Foot and Mouth Disease Control. Thailand: Bangkok, 2012

  4. Brito B P, Rodriguez L L, Hammond J M, Pinto J, Perez A M. Review of the global distribution of foot-andmouth disease virus from 2007 to 2014[J/OL]. Transbound Emerg Dis, 2017, 64: 316–332. https://doi.org/10.1111/tbed.12373

    Article  Google Scholar 

  5. Jamal S M, Belsham G J. Foot-and-mouth disease: past, present and future[J/OL]. Vet Res, 2013, 44: 116. https://doi.org/10.1186/1297-9716-44-116

    Article  Google Scholar 

  6. Meyer R F, Knudsen R C. Foot-and-mouth disease: are view of the virus and the symptoms. J Environ Health, 2001, 64: 21–23

    Google Scholar 

  7. Zhang T L, Zhao X Q. Mathematical modelling for schistosomiasis with seasonal influence: a case study in China. SIAM J Appl Dynam Sys, 2020, 19(2): 1438–1417

    Article  Google Scholar 

  8. Luo X F, Jin Z. A new insight into isolating the high-degree nodes in network to control infectious diseases. Commun Nonlinear Sci Numer Simul, 2020, 91: 105363

    Article  MathSciNet  Google Scholar 

  9. Duan X C, Li X Z, Martcheva M. Qualitative analysis on a diffusive age-structured heroin transmission model. Nonlinear Anal: RWA, 2020, 54: 103105

    Article  MathSciNet  Google Scholar 

  10. Li X Z, Yang J Y, Martcheva M. Age structured epidemic modelling. Switzerland AG: Springer, 2002

    MATH  Google Scholar 

  11. Sellers R F, Gloster J. The Northumberland epidemic of foot-and-mouth disease. 1966. J Hyg (Lond), 1980, 85(1): 129–140

    Article  Google Scholar 

  12. Mikkelsen T, Alexandersen S, Astrup P, et al. Investigation of airborne foot and mouth disease virus transmission during low-wind conditions in the early phase of the UK 2001 epidemic. Atmos Chem Phys, 2003, 3: 2101–2110

    Article  Google Scholar 

  13. Kao R R. The role of mathematical modelling in the control of the 2001 FMD epidemic in the UK. Trends Microbiol, 2002, 10(6): 279–286

    Article  Google Scholar 

  14. Ferguson N M, Donnelly C A, Anderson R M. The foot-and-mouth epidemic in Great Britain: pattern of spread and impact of interventions. Science, 2001, 292: 1155–1160

    Article  Google Scholar 

  15. Ferguson N M, Donnelly C A, Anderson R M. Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain. Nature, 2001, 413: 542–548

    Article  Google Scholar 

  16. Bradhurst R A, Roche S E, East I J, et al. A hybrid modelling approach to simulating foot-andmouth disease outbreaks in Australian livestock. Front Environ Sci, 2015, 3: 17

    Article  Google Scholar 

  17. Keeling M J, et al. Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape. Science, 2001, 294: 813–817

    Article  Google Scholar 

  18. Keeling M J, Woolhouse M E J, May R M, et al. Modelling vaccination strategies against foot and mouth disease. Nature, 2003, 421: 136–142

    Article  Google Scholar 

  19. Orsel K, Bouma A. The effect of foot-and-mouth disease (FMD) vaccination on virus transmission and the significance for the field. Can vet J, 2009, 50: 1059–1063

    Google Scholar 

  20. Orsel K, Dekker A, Bouma A, et al. Vaccination against foot and mouth disease reduces virus transmission in groups of calves. Vaccine, 2005, 23(41): 4887–4894

    Article  Google Scholar 

  21. Tildesley M J, Bessell P R, Keeling M J, Woolhouse M E J. The role of pre-emptive culling in the control of foot-and-mouth disease. Proc Roy Soc Lond, B, Biol Sci, 2009, 276(1671): 3239–3248

    Article  Google Scholar 

  22. Bates P W, Zhao G. Existence, uniqueness and stability of the stationary solution to a nonlocal evolution equation arising in population dispersal. J Math Anal Appl, 2007, 332(1): 428–440

    Article  MathSciNet  Google Scholar 

  23. Han B S, Yang Y H. On a predator-prey reaction diffusion model with nonlocal effects. Commun Nonlinear Sci Numer Simulat, 2017, 46: 49–61

    Article  MathSciNet  Google Scholar 

  24. Zhao G, Ruan S. Spatial and temporal dynamics of a nonlocal viral infection model. SIAM J Appl Math, 2018, 78(4): 1954–1980

    Article  MathSciNet  Google Scholar 

  25. Kuniya T, Wang J. Global dynamics of an SIR epidemic modelwith nonlocal diffusion. Nonlinear Anal: RWA, 2018, 43: 262–282

    Article  Google Scholar 

  26. Bates P W. On some nonlocal evolution equations arising in materials science//Brunner H, Xhao X-Q, Zhou X. Nonlinear Dynamics and Evolution Equations. Fields Institute Communications, 2006, 48: 13–52

    Google Scholar 

  27. Tian H, Ju L, Du Q. A conservative nonlocal convection diffusion model and asymptotically compatible finite difference discretization. Comput Meth Appl Mech Engin, 2017, 320: 46–67

    Article  MathSciNet  Google Scholar 

  28. Zhang J, Jin Z, Yuan Y. Assessing the spread of foot and mouth disease in mainland China by dynamical switching model. J Theor Biol, 2019, 460: 209–219

    Article  MathSciNet  Google Scholar 

  29. Pazy A. Semigroups of Linear Operators and Application to Partial Differential Equations. New York: Springer-Verlag, 1983

    Book  Google Scholar 

  30. Webb G F. Theory of Nonlinear Age-Dependent Population Dynamics. New York: Marcel Dekker Inc, 1985

    MATH  Google Scholar 

  31. Wang X Y, Chen Y M, Yang J Y. Spatial and temporal dynamics of a virus infection model with two nonlocal effects[J/OL]. Complexity, 2019, Art ID5842942. https://doi.org/10.1155/2019/5842942

  32. Hale J K. Asymptotic Behavior of Dissipative Systems. Mathematical Surveys and Monographs. Providence: American Mathematical Society, 1998

    Google Scholar 

  33. Yang J, Xu F. The computational approach for the basic reproduction number of epidemic models on complex networks. IEEE Access, 2019, 7: 26474–26479

    Article  Google Scholar 

  34. Yang J Y, Jin Z, Xu F. Threshold dynamics of an age-space structured SIR model on heterogeneous environment. Appl Math Letters, 2019, 96: 68–74

    MathSciNet  MATH  Google Scholar 

  35. Wang W, Zhao X. Basic reproduction numbers for reaction-diffusion epidemic models. SIAM J Appl Dyn Sys, 2011, 11(4): 1652–1673

    Article  MathSciNet  Google Scholar 

  36. Diekmann O, Heesterbeek J A P, Metz J A J. On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. J Math Biol, 1990, 28: 365–382

    Article  MathSciNet  Google Scholar 

  37. LaSalle J P. Some extensions of Liapunov’s second method. Ire Transactions on Circuit Theory, 1960, 7(4): 520–527

    Article  MathSciNet  Google Scholar 

  38. Amann H. Fixed point equations and nonlinear eigenvalue problems in ordered Banach spaces. SIAM Rev, 1976, 18: 620–709

    Article  MathSciNet  Google Scholar 

  39. Smith H L, Zhao X Q. Robust persistence for semidynamical systems. Nonlinear Anal: TMA, 2001, 47(9): 6169–6179

    Article  MathSciNet  Google Scholar 

  40. Smith H L, Thieme H R. Dynamical systems and population persistence. Providence: American Mathematical Society, 2011

    MATH  Google Scholar 

  41. Walker J A. Dynamical Systems and Evolution Equations: Theory and Applications. New York: Plenum Press, 1980

    Book  Google Scholar 

  42. Chatelin F. The spectral approximation of linear operators with applications to the computation of eigenelements of differential and itegral operators. SIAM Rev, 1981, 23: 495–522

    Article  MathSciNet  Google Scholar 

  43. Muroya Y, Enatsu Y, Kuniya T. Global stability for a class of multi-group SIR epidemic models with patches through migration and cross path infection. Acta Mathematica Scientia, 2013, 33B(2): 341–361

    Article  Google Scholar 

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Correspondence to Junyuan Yang.

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This work was partially supported by the National Natural Science Foundation of China (12001339, 61573016, 11871316), Shanxi Scholarship Council of China (2015-094), the Natural Science Foundation of Shanxi (201801D121006), and the Shanxi Province Science Foundation for Youths (201901D211413).

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Wang, X., Yang, J. Dynamics of a Nonlocal Dispersal Foot-and-Mouth Disease Model in a Spatially Heterogeneous Environment. Acta Math Sci 41, 552–572 (2021). https://doi.org/10.1007/s10473-021-0217-y

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  • DOI: https://doi.org/10.1007/s10473-021-0217-y

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