Relative Prevalence-based Dispersal in an Epidemic Patch Model
Document Type
Article
Publication Date
4-2023
Publication Title
Journal of Mathematical Biology
Abstract
In this paper, we propose a two-patch SIRS model with a nonlinear incidence rate: beta(i) (1 + v(i) I-i)I-i S-i and nonconstant dispersal rates, where the dispersal rates of susceptible and recovered individuals depend on the relative disease prevalence in two patches. In an isolated environment, the model admits Bogdanov-Takens bifurcation of codimension 3 (cusp case) and Hopf bifurcation of codimension up to 2 as the parameters vary, and exhibits rich dynamics such as multiple coexistent steady states and periodic orbits, homoclinic orbits and multitype bistability. The long-term dynamics can be classified in terms of the infection rates beta(i) (due to single contact) and vi (due to double exposures). In a connected environment, we establish a threshold R-0 = 1 between disease extinction and uniform persistence under certain conditions. We numerically explore the effect of population dispersal on disease spread when v(i) = 0 and patch 1 has a lower infection rate, our results indicate: (i) R-0 can be nonmonotonic in dispersal rates and R-0 <= max{R-01, R-02} (R-0i is the basic reproduction number of patch i) may fail; (ii) the constant dispersal of susceptible individuals (or infective individuals) between two patches (or from patch 2 to patch 1) will increase (or reduce) the overall disease prevalence; (iii) the relative prevalence-based dispersal may reduce the overall disease prevalence. When v(i )> 0 and the disease outbreaks periodically in each isolated patch, we find that: (a) small unidirectional and constant dispersal can lead to complex periodic patterns like relaxation oscillations or mixed-mode oscillations, whereas large ones can make the disease go extinct in one patch and persist in the form of a positive steady state or a periodic solution in the other patch; (b) relative prevalence-based and unidirectional dispersal can make periodic outbreak earlier.
Repository Citation
Lu, Min; Gao, Daozhou; Huang, Jicai; and Wang, Hao, "Relative Prevalence-based Dispersal in an Epidemic Patch Model" (2023). Mathematics and Statistics Faculty Publications. 349.
https://engagedscholarship.csuohio.edu/scimath_facpub/349
DOI
10.1007/s00285-023-01887-8
Volume
86
Issue
4
Comments
Research was partially supported by NSFC (Nos. 11871235, 12231008 and 12071300) and NSERC (RGPIN-2020-03911 and RGPAS-2020-00090).