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Simulation Models for Genetic Control Alternatives

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Mathematical Analysis of Decision Problems in Ecology

Part of the book series: Lecture Notes in Biomathematics ((LNBM,volume 5))

Abstract

The problems in relation to the use of pesticides (e.g. environmental pollution, selection of resistant strains) have stimulated research in genetical methods of control and/or eradication of pest and vector populations. These methods aim at reducing the fertility by releasing either sterile males or strains with translocations. The paper surveys the mathematical models describing the various genetical control methods and predicting the outcomes of specified release strategies. It is shown that success and failure depend crucially on the density-dependent mechanism that regulates the natural population densities. Computer simulations allow us to optimize the timing of the releases in relation to the seasonal pattern of the carrying capacity of the environment. Particular reference is made to the genetic control of mosquito vector populations. In practice, the release of partially fertile males and even females together with the sterile males cannot be avoided. Under certain assumptions it can be shown that the release ratios have to be between certain boundaries in order to achieve population reduction. Transmission models help to assess the effects of a certain reduction in vector density on the transmission of the disease.

The author is grateful to Dr. C. B. Cuellar and Dr. C. F. Curtis for stimulating discussions, and to Mr. A. Thomas for the programming in relation to the Tables.

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References

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© 1975 Springer-Verlag Berlin · Heidelberg

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Dietz, K. (1975). Simulation Models for Genetic Control Alternatives. In: Charnes, A., Lynn, W.R. (eds) Mathematical Analysis of Decision Problems in Ecology. Lecture Notes in Biomathematics, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80924-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-80924-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-07188-4

  • Online ISBN: 978-3-642-80924-8

  • eBook Packages: Springer Book Archive

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