Dynamics of HLB Transmission: Integrating Saturated Removal and Vector Bias in Spatial/Non-Spatial Models
Huanglongbing (HLB), a globally devastating citrus disease, demands sophisticated mathematical modeling to decipher its complex transmission dynamics and inform optimized disease management protocols. This investigation develops an innovative compartmental framework that simultaneously incorporates two critical factors in HLB epidemiology: saturated removal rates of infected citrus trees and behavioral bias in vector movement patterns. Our study delves into the dynamics of non-spatial systems by analyzing the basic reproduction numbers, equilibria, bifurcation phenomena, and the stability of these equilibria. Additionally, we explore the impact of spatial factors on system stability. Results indicate that when the basic reproduction number R0<1, the system may exhibit bistable behavior, while R0>1 leads to a unique stable equilibrium. Notably, vector bias significantly enhances the likelihood of forward bifurcation, and the delay in the removal of diseased trees increases the risk of backward bifurcation. However, reaction–diffusion processes do not alter the stability of the system’s equilibria, and the spatial system lacks complex dynamic properties. This research offers valuable insights into the mechanisms driving HLB transmission and provides a foundation for developing effective control strategies.
Authors
- Yushun Gao (ORCID: https://orcid.org/0000-0003-3992-6671)
- Shujing Gao (ORCID: https://orcid.org/0000-0002-4461-5061)
- Fumin Zhang (ORCID: https://orcid.org/0000-0003-0053-4224)
- Yang Liu (ORCID: https://orcid.org/0009-0008-1519-3788)
Institutions
- Gannan Normal University (CN)
Publication Details
- Journal
- Axioms
- Published
- 2025-06-02
- DOI
- https://doi.org/10.3390/axioms14060434
- Citations
- 1
- Primary Topic
- Plant Virus Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangxi Province