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Optimisation of Healthcare Supply Chain Models to Enable Decision Making During a Pandemic

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Proceedings of Eighth International Congress on Information and Communication Technology (ICICT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 696))

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Abstract

The world is slowly recovering from the worst pandemic after the 1918–1920 influenza pandemic. The Corona Virus Disease 2019 (COVID-19) is a highly infectious virus that spread across the entire world in just under three months. All economic activities and healthcare supply chains were disrupted, resulting in poor decision making and inadequate knowledge to fight the pandemic. The healthcare supply chain models and systems failed to handle the impact and shock caused by the pandemic. Healthcare institutions were overwhelmed by a high number of sick and dying patients, governments struggled to source adequate personal protective equipment, clothing and medical drugs that were required to contain the deadly virus. This study was conducted to investigate the possibility of optimising the healthcare supply chain models to support management decision making during a pandemic. The study applied a systematic literature review and a case study to simulate an optimised supply chain model and determine its capability to enable decision making during a pandemic.

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Acknowledgements

The research reported in this article was supported by the South African Department of Science and Innovation (DSI) and the South African Medical Research Council (SAMRC) under BRICS JAF #2020/33. The content and findings reported or illustrated herein are the sole deduction, view and responsibility of the researcher/s and do not reflect the official position and sentiments of the funders.

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Authors and Affiliations

  1. University of Pretoria, Pretoria, South Africa

    George Maramba, Hanlie Smuts, Funmi Adebesin, Marie Hattingh & Tendani Mawela

Authors
  1. George Maramba
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  2. Hanlie Smuts
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  3. Funmi Adebesin
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  4. Marie Hattingh
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  5. Tendani Mawela
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Corresponding author

Correspondence to George Maramba .

Editor information

Editors and Affiliations

  1. Department of Design Engineering and Mathematics, Middlesex University London, London, UK

    Xin-She Yang

  2. Department of Biomedical Engineering, University of Reading, England, UK

    R. Simon Sherratt

  3. Department of Computer Science and Engineering, Techno International Newtown, Chakpachuria, West Bengal, India

    Nilanjan Dey

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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Maramba, G., Smuts, H., Adebesin, F., Hattingh, M., Mawela, T. (2024). Optimisation of Healthcare Supply Chain Models to Enable Decision Making During a Pandemic. In: Yang, XS., Sherratt, R.S., Dey, N., Joshi, A. (eds) Proceedings of Eighth International Congress on Information and Communication Technology. ICICT 2023. Lecture Notes in Networks and Systems, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-99-3236-8_31

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  • DOI: https://doi.org/10.1007/978-981-99-3236-8_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-3235-1

  • Online ISBN: 978-981-99-3236-8

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