{"title":"A hybrid Lagrangian-Eulerian model for vector-borne diseases.","authors":"Daozhou Gao, Xiaoyan Yuan","doi":"10.1007/s00285-024-02109-5","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, a multi-patch and multi-group vector-borne disease model is proposed to study the effects of host commuting (Lagrangian approach) and/or vector migration (Eulerian approach) on disease spread. We first define the basic reproduction number of the model, <math><msub><mi>R</mi> <mn>0</mn></msub> </math> , which completely determines the global dynamics of the model system. Namely, if <math> <mrow><msub><mi>R</mi> <mn>0</mn></msub> <mo>≤</mo> <mn>1</mn></mrow> </math> , then the disease-free equilibrium is globally asymptotically stable, and if <math> <mrow><msub><mi>R</mi> <mn>0</mn></msub> <mo>></mo> <mn>1</mn></mrow> </math> , then there exists a unique endemic equilibrium which is globally asymptotically stable. Then, we show that the basic reproduction number has lower and upper bounds which are independent of the host residence times matrix and the vector migration matrix. In particular, nonhomogeneous mixing of hosts and vectors in a homogeneous environment generally increases disease persistence and the basic reproduction number of the model attains its minimum when the distributions of hosts and vectors are proportional. Moreover, <math><msub><mi>R</mi> <mn>0</mn></msub> </math> can also be estimated by the basic reproduction numbers of disconnected patches if the environment is homogeneous. The optimal vector control strategy is obtained for a special scenario. In the two-patch and two-group case, we numerically analyze the dependence of the basic reproduction number and the total number of infected people on the host residence times matrix and illustrate the optimal vector control strategy in homogeneous and heterogeneous environments.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11189357/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s00285-024-02109-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a multi-patch and multi-group vector-borne disease model is proposed to study the effects of host commuting (Lagrangian approach) and/or vector migration (Eulerian approach) on disease spread. We first define the basic reproduction number of the model, , which completely determines the global dynamics of the model system. Namely, if , then the disease-free equilibrium is globally asymptotically stable, and if , then there exists a unique endemic equilibrium which is globally asymptotically stable. Then, we show that the basic reproduction number has lower and upper bounds which are independent of the host residence times matrix and the vector migration matrix. In particular, nonhomogeneous mixing of hosts and vectors in a homogeneous environment generally increases disease persistence and the basic reproduction number of the model attains its minimum when the distributions of hosts and vectors are proportional. Moreover, can also be estimated by the basic reproduction numbers of disconnected patches if the environment is homogeneous. The optimal vector control strategy is obtained for a special scenario. In the two-patch and two-group case, we numerically analyze the dependence of the basic reproduction number and the total number of infected people on the host residence times matrix and illustrate the optimal vector control strategy in homogeneous and heterogeneous environments.
本文提出了一个多斑块和多群体病媒传播疾病模型,以研究宿主通勤(拉格朗日方法)和/或病媒迁移(欧拉方法)对疾病传播的影响。我们首先定义了模型的基本繁殖数 R 0,它完全决定了模型系统的全局动态。也就是说,如果 R 0 ≤ 1,则无疾病平衡是全局渐近稳定的;如果 R 0 > 1,则存在一个全局渐近稳定的唯一流行平衡。然后,我们证明了基本繁殖数具有下限和上限,它们与宿主居住时间矩阵和矢量迁移矩阵无关。特别是,宿主和载体在均质环境中的非均质混合通常会增加疾病的持续性,当宿主和载体的分布成比例时,模型的基本繁殖数达到最小值。此外,如果环境是均质的,R 0 也可以通过互不相连的斑块的基本繁殖数来估算。在特殊情况下,可以获得最佳载体控制策略。在两个斑块和两个群体的情况下,我们数值分析了基本繁殖数和感染总人数对宿主居住时间矩阵的依赖关系,并说明了同质和异质环境下的最优向量控制策略。