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A metapopulation model for the population dynamics of anopheles mosquito

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  • Mann Manyombe, M.L.
  • Tsanou, B.
  • Mbang, J.
  • Bowong, S.

Abstract

A more robust assessment of malaria control will come from a better understanding of the distribution and connectivity of breeding and blood feeding sites. Spatial heterogeneity of mosquito resources, such as hosts and breeding sites, affects mosquito dispersal behavior. This paper analyzes and simulates the spreading of anopheles mosquito on a complex metapopulation, that is, networks of populations connected by migratory flows whose configurations are described in terms of connectivity distribution of nodes (patches) and the conditional probabilities of connections between nodes. We examine the impacts of vector dispersal on the persistence and extinction of a mosquito population in both homogeneous and heterogeneous landscapes. For uncorrelated networks in a homogeneous landscape, we derive an explicit formula of the basic offspring number R0(m). Using the theory of monotone operators, we obtain sufficient conditions for the global asymptotic stability of equilibria. Precisely, the value 1 of the basic offspring number is a forward bifurcation for the dynamics of anopheles mosquito, with the trivial (mosquito-free) equilibrium point being globally asymptotically stable (GAS) when R0(m)≤1, and one stable nontrivial (mosquito-persistent) equilibrium point being born with well determined basins of attraction when R0(m)>1. Theoretical results are numerically supported and the impact of the migration of mosquitoes are discussed through global sensitivity analysis and numerical simulations.

Suggested Citation

  • Mann Manyombe, M.L. & Tsanou, B. & Mbang, J. & Bowong, S., 2017. "A metapopulation model for the population dynamics of anopheles mosquito," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 71-91.
    • Handle: RePEc:eee:apmaco:v:307:y:2017:i:c:p:71-91
    DOI: 10.1016/j.amc.2017.02.039
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    References listed on IDEAS

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    1. Wang, Yi & Cao, Jinde & Alofi, Abdulaziz & AL-Mazrooei, Abdullah & Elaiw, Ahmed, 2015. "Revisiting node-based SIR models in complex networks with degree correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 75-88.
    2. Wang, Yi & Cao, Jinde & Sun, Gui-Quan & Li, Jing, 2014. "Effect of time delay on pattern dynamics in a spatial epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 137-148.
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    Cited by:

    1. Huang, Chengdai & Li, Huan & Cao, Jinde, 2019. "A novel strategy of bifurcation control for a delayed fractional predator–prey model," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 808-838.

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