This paper shows how biological population dynamic models in the form of coupled reaction-diffusion equations with nonlinear reaction terms can be applied to heterogeneous landscapes. The presented systems of coupled partial differential equations (PDEs) combine the dispersal of disease-vector mosquitoes and the spread of the disease in a human population. Realistic biological dispersal behavior is taken into account by applying chemotaxis terms for the attraction to the human host and the attraction of suitable breeding sites. These terms are capable of generating the complex active movement patterns of mosquitoes along the gradients of the attractants. The nonlinear initial boundary value problems are solved numerically for geometries of heterogeneous landscapes, which have been imported from geographic information system data to construct a general-purpose finite-element solver for systems of coupled PDEs. The method is applied to the dispersal of the dengue disease vector for Aedes aegypti in a small-scale rural setting consisting of small houses and different breeding sites, and to a large-scale section of the suburban zone of a metropolitan area in Vietnam. Numerical simulations illustrate how the setup of model equations and geographic information can be used for the assessment of control measures, including the spraying patterns of pesticides and biological control by inducing male sterility.
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http://dx.doi.org/10.3934/mbe.2022603 | DOI Listing |
Theor Popul Biol
December 2024
Cornell University, Department of Computational Biology, 102 Tower Rd, Ithaca, 14850, NY, USA.
Ordinary differential equation models such as the classical SIR model are widely used in epidemiology to study and predict infectious disease dynamics. However, these models typically assume that populations are homogeneously mixed, ignoring possible variations in disease prevalence due to spatial heterogeneity. To address this issue, reaction-diffusion models have been proposed as an alternative approach to modeling spatially continuous populations in which individuals move in a diffusive manner.
View Article and Find Full Text PDFMed Image Anal
December 2024
Department of Mathematics, University of California Irvine, USA; Department of Biomedical Engineering, University of California Irvine, USA. Electronic address:
Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understanding tumor growth dynamics and designing personalized radiotherapy treatment plans. Mathematical models of GBM growth can complement the data in the prediction of spatial distributions of tumor cells. However, this requires estimating patient-specific parameters of the model from clinical data, which is a challenging inverse problem due to limited temporal data and the limited time between imaging and diagnosis.
View Article and Find Full Text PDFMath Biosci Eng
November 2024
School of Mathematics and Physics, Yancheng Institute of Technology, Yancheng 224003, China.
A vegetation model composed of water and plants was proposed by introducing a weighted graph Laplacian operator into the reaction-diffusion dynamics. We showed the global existence and uniqueness of the solution via monotone iterative sequence. The parameter space of Turing patterns for plant behavior is obtained based on the analysis of the eigenvalues of the Laplacian of weighted graph, while the amplitude equation determining the stability of Turing patterns is obtained by weakly nonlinear analysis.
View Article and Find Full Text PDFMath Biosci Eng
November 2024
Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, Villeurbanne 69622, France.
The process of viral infection spreading in tissues was influenced by various factors, including virus replication within host cells, transportation, and the immune response. Reaction-diffusion systems provided a suitable framework for examining this process. In this work, we studied a nonlocal reaction-diffusion system of equations that modeled the distribution of viruses based on their genotypes and their interaction with the immune response.
View Article and Find Full Text PDFPhys Rev E
November 2024
Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska 68588, USA.
We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±1/2 defects. The enabling term is analogous to polarization charge density seen in dielectric materials.
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