Study of an Epidemiological Model for Plant Virus Diseases with Periodic Coefficients
Source abstract
Abstract
In the present article, we research the existence of the positive periodic solutions for a mathematical model that describes the propagation dynamics of a pathogen living within a vector population over a plant population. We propose a generalized compartment model of the susceptible–infected–susceptible (SIS) type. This model is derived primarily based on four assumptions: (i) the plant population is subdivided into healthy plants, which are susceptible to virus infection, and infected plants; (ii) the vector population is categorized into non-infectious and infectious vectors; (iii) the dynamics of pathogen propagation follow the standard susceptible–infected–susceptible pattern; and (iv) the rates of pathogen propagation are time-dependent functions. The main contribution of this paper is the introduction of a sufficient condition for the existence of positive periodic solutions in the model. The proof of our main results relies on a priori estimates of system solutions and the application of coincidence degree theory. Additionally, we present some numerical examples that demonstrate the periodic behavior of the system.
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Research context
OpenAlex topics: Mathematical and Theoretical Epidemiology and Ecology Models · Evolution and Genetic Dynamics · Plant Virus Research Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento de Ciencias Básicas—Centro de Ciencias Exactas CCE-UBB, Facultad de Ciencias, Universidad del Bío-Bío, Campus Fernando May, Chillán 3780000, Chile
Departamento de Matemática, Facultad de Ciencias Naturales, Matemáticas y del Medio Ambiente, Universidad Tecnológica Metropolitana, Ñuñoa, Santiago de Chile 7750000, Chile
Department of Information Systems, University of Bio-Bio, Concepcion 4051381, Chile
Funding
Universidad del Bío-Bío (Chile) · Universidad Tecnológica Metropolitana · ANID (Chile)
References (45)
Show source-provided references
1. Plant virus epidemiology: Applications and prospects for mathematical modeling and analysis to improve understanding and disease control10.1094/PDIS-04-17-0612-FE ↗
2. The origins and epidemiology of some important plant virus diseases
3. Progress curves of plant virus disease
4. An epidemiological model of the com stunt system in Central America10.1016/0304-3800(90)90018-C ↗
5. A model for analysing plant-virus transmission characteristics and epidemic development10.1093/imammb/15.1.1 ↗
6. Jeger, M.J. (2020). The Epidemiology of Plant Virus Disease: Towards a New Synthesis. Plants, 9.10.3390/plants9121768 ↗
7. Plant virus epidemiology
8. Transmission dynamics and sensitivity analysis of pine wilt disease with asymptomatic carriers via fractal-fractional differential operator of Mittag-Leffler kernel10.1016/j.apnum.2022.12.004 ↗
9. Unraveling pine wilt disease: Comparative study of stochastic and deterministic model using spectral method10.1016/j.eswa.2023.122407 ↗
10. Ahmad, Z., El-Kafrawy, S.A., Alandijany, T.A., Giannino, F., Mirza, A.A., El-Daly, M.M., Faizo, A.A., Bajrai, L.H., Kamal, M.A., and Azhar, E.I. (2022). A global report on the dynamics of COVID-19 with quarantine and hospitalization: A fractional order model with non-local kernel. Comput. Biol. Chem., 98.10.1016/j.compbiolchem.2022.107645 ↗
11. A report on COVID-19 epidemic in Pakistan using SEIR fractional model10.1038/s41598-020-79405-9 ↗
12. Advanced methods of plant disease detection. A review10.1007/s13593-014-0246-1 ↗
13. Saleem, M.H., Potgieter, J., and Arif, K.M. (2019). Plant Disease Detection and Classification by Deep Learning. Plants, 8.10.3390/plants8110468 ↗
14. Plant diseases recognition on images using convolutional neural networks: A systematic review10.1016/j.compag.2021.106125 ↗
15. A review of advanced techniques for detecting plant diseases10.1016/j.compag.2010.02.007 ↗
16. Nakakawa, J.N., Mugisha, J.Y.T., Shaw, M.W., and Karamura, E. (2020). Banana Xanthomonas Wilt Dynamics with Mixed Cultivars in a Periodic Environment. Int. J. Biomath., 13.10.1142/S1793524520500059 ↗
17. Modelling cholera in periodic environments10.1080/17513758.2014.896482 ↗
18. A Plant Virus Disease Model with Periodic Environment and Pulse Roguing10.1111/sapm.12109 ↗
19. Analysis of a High-Dimensional Mathematical Model for Plant Virus Transmission with Continuous and Impulsive Roguing Control
20. Cardona, C., Rodriguez, I.V., Bueno, J.M., and Tapia, X. (2005). Biología de la Mosca Blanca Trialeurodes vaporariorum en Habichuela y Frijol, Department for International Development (DFID), Centro Internacional de Agricultura Tropical (CIAT). Publicacion CIAT No. 345.
21. Anderson, P., and Morales, F. (2005). Whitefly and Whiteflyborne Viruses in the Tropics: Building a Knowledge Base for Global Action, Centro Internacional de Agricultura Tropical (CIAT).
22. Effects of Heat Shock on Survival and Reproduction of Two Whitefly Species, Trialeurodes vaporariorum and Bemisia tabaci Biotype B10.1673/031.008.2401 ↗
23. An epidemiological model incorporating vector population dynamics applied to African cassava mosaic virus disease10.2307/2404924 ↗
24. Population biology of infectious diseases I10.1038/280361a0 ↗
25. Anderson, R.M., and May, R.M. (1991). Infectious Diseases of Humans, Oxford University Press.10.1093/oso/9780198545996.001.0001 ↗
26. Brauer, F., and Castillo-Chavez, C. (2012). Mathematical Models in Population Biology and Epidemiology, Springer. [2nd ed.].10.1007/978-1-4614-1686-9 ↗
27. Diekmann, O., and Heesterbeek, J.A.P. (2000). Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation, John Wiley & Sons.
28. An analytical model of plant virus disease dynamics with roguing and replanting10.2307/2404439 ↗
29. Global stability of an SEI model for plant diseases10.1515/ms-2015-0137 ↗
30. Disease outbreaks in plant-vector-virus models with vector aggregation and dispersal10.3934/dcdsb.2016042 ↗
31. Epidemiology of insect-transmitted plant viruses: Modelling disease dynamics and control interventions10.1111/j.0307-6962.2004.00394.x ↗
32. Considering behaviour to ensure the success of a disease control strategy10.1098/rsos.170721 ↗
33. Global dynamic analysis of a vector-borne plant disease model10.1186/1687-1847-2014-59 ↗
34. A general model of plant-virus disease infection incorporating vector aggregation10.1046/j.1365-3059.2000.00469.x ↗
35. Optimal control of a vectored plant disease model for a crop with continuous replanting10.1080/17513758.2019.1622808 ↗
36. Gaines, R., and Mawhin, J. (1977). Coincidence Degree and Nonlinear Differential Equations, Springer.10.1007/BFb0089537 ↗
37. Sufficient conditions for the existence of positive periodic solutions of a generalized nonresident computer virus model10.2989/16073606.2019.1686438 ↗
38. Cassava mosaic geminiviruses: Actual knowledge and perspectives10.1111/j.1364-3703.2009.00559.x ↗
39. Developing broad-spectrum resistance in cassava against viruses causing the cassava mosaic and the cassava brown streak diseases10.3389/fpls.2023.1042701 ↗
40. Effect of planting and harvesting time on cassava (Manihot esculenta Crantz) Var. Gambyong10.1088/1755-1315/458/1/012036 ↗
41. Modelling the dynamics of Cassava Mosaic Disease with non-cassava host plants10.1016/j.imu.2022.101086 ↗
42. Modeling the dynamics and transmission of cassava mosaic disease in Tanzania
43. Numerical identification of parameters for a strongly degenerate convection-diffusion problem modelling centrifugation of flocculated suspensions10.1016/j.apnum.2004.08.002 ↗
44. Numerical solution of an inverse problem for a scalar conservation law modelling sedimentation
45. On the existence and uniqueness of an inverse problem in epidemiology10.1080/00036811.2019.1608964 ↗