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Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model

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  • Shami, Labib
  • Lazebnik, Teddy

Abstract

Mankind has struggled with pathogens throughout history. In this context, the contribution of vaccines to the continued economic and social prosperity of humanity is enormous, but it is constantly threatened by the development of vaccine-resistant strains of the pathogen. In this study, we investigate the usage of genomic sequencing tests to detect new strains of a pathogen in a multi-strain pandemic scenario using a mathematical–epidemiological–genomic–economic model. Our model provides a theoretical framework to explore the influence of an extensive number of pharmaceutical interventions in a dynamic multi-strain pandemic. Specifically, we show that while a genomic sequence testing policy can be both economically and epidemiologically efficient, a random sample of the population provides sub-optimal results. Moreover, we demonstrate that the optimal policy is sensitive to the social and economic settings of the population, and provide a machine learning based model that offers a solution to these challenges.

Suggested Citation

  • Shami, Labib & Lazebnik, Teddy, 2022. "Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
  • Handle: RePEc:eee:chsofr:v:165:y:2022:i:p2:s0960077922010025
    DOI: 10.1016/j.chaos.2022.112823
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    References listed on IDEAS

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    Cited by:

    1. Lazebnik, Teddy, 2023. "Computational applications of extended SIR models: A review focused on airborne pandemics," Ecological Modelling, Elsevier, vol. 483(C).
    2. Lazebnik, Teddy & Shami, Labib & Bunimovich-Mendrazitsky, Svetlana, 2023. "Intervention policy influence on the effect of epidemiological crisis on industry-level production through input–output networks," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

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    More about this item

    Keywords

    SIR model; Genetic algorithm; Multi-strain pandemic model; Epidemiological–economic modeling; Genomic testing; Dynamical systems;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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