IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v39y2019i1d10.1007_s10669-018-9700-y.html
   My bibliography  Save this article

Structured decision-making for the management of a biological fieldable laboratory during outbreaks: a case for European Union Civil Protection Mechanism (EUCPM)

Author

Listed:
  • Olga Vybornova

    (Université Catholique de Louvain)

  • Jean-Luc Gala

    (Université Catholique de Louvain)

Abstract

Fast on-scene deployment of an analytical laboratory capacity to help contain an outbreak of infectious disease requires setting up an appropriate policy framework and a range of operating procedures to ensure efficient support to decision-making, as well as the optimal engagement and use of dedicated resources. This work focuses on fully autonomous deployment when the mobile capacity operators themselves need to make decisions and implement all the operational functions (OFs), from basic needs like provision of equipment, power supply, food and accommodation for the staff, to complicated procedures like logistics of transportation and supply chain. A model of the identity and structure of specific decision-making requirements for a generic deployment of laboratory capacities was built from the real experience during specific deployments of the operators and managers of the Belgian capacity Biological Light Fieldable Laboratory for Emergencies (B-LiFE). Self- and external assessments were conducted and lessons learned successively reviewed after each deployment by B-LiFE laboratory operators and managers and observers in the framework of European demonstration projects and joint exercises. The result was consolidated by integrating the assessment of European Commission-appointed certifiers during the certification procedure of B-LIFE as a self-sufficient module of the European Medical Corps, namely the European modules exercise “Modex” in April 2017 (Revinge, Sweden) followed by the “ModTTX 4” Table-top in May 2017 (Bruges, Belgium). A complete and updated set of Fieldable Laboratory operational functions is presented, including their contents, cross-links, inter-dependencies, information needs for implementation, and related decisions.

Suggested Citation

  • Olga Vybornova & Jean-Luc Gala, 2019. "Structured decision-making for the management of a biological fieldable laboratory during outbreaks: a case for European Union Civil Protection Mechanism (EUCPM)," Environment Systems and Decisions, Springer, vol. 39(1), pages 65-76, March.
  • Handle: RePEc:spr:envsyd:v:39:y:2019:i:1:d:10.1007_s10669-018-9700-y
    DOI: 10.1007/s10669-018-9700-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-018-9700-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10669-018-9700-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Balcik, Burcu & Beamon, Benita M. & Krejci, Caroline C. & Muramatsu, Kyle M. & Ramirez, Magaly, 2010. "Coordination in humanitarian relief chains: Practices, challenges and opportunities," International Journal of Production Economics, Elsevier, vol. 126(1), pages 22-34, July.
    2. Naor, Michael & Bernardes, Ednilson, 2016. "Self-Sufficient Healthcare Logistics Systems and Responsiveness: Ten Cases of Foreign Field Hospitals Deployed to Disaster Relief Supply Chains," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 9(1), July.
    3. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zachary A. Collier & James H. Lambert & Igor Linkov, 2019. "Modeling and analytics to address national and global scale challenges," Environment Systems and Decisions, Springer, vol. 39(1), pages 1-2, March.
    2. Mostafa Bentahir & Mamadou Diouldé Barry & Kekoura Koulemou & Jean-Luc Gala, 2022. "Providing On-Site Laboratory and Biosafety Just-In-Time Training Inside a Box-Based Laboratory during the West Africa Ebola Outbreak: Supporting Better Preparedness for Future Health Emergencies," IJERPH, MDPI, vol. 19(18), pages 1-13, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ben-Ammar, Oussama & Bettayeb, Belgacem & Dolgui, Alexandre, 2019. "Optimization of multi-period supply planning under stochastic lead times and a dynamic demand," International Journal of Production Economics, Elsevier, vol. 218(C), pages 106-117.
    2. Yang, Honglin & Zhuo, Wenyan & Shao, Lusheng & Talluri, Srinivas, 2021. "Mean-variance analysis of wholesale price contracts with a capital-constrained retailer: Trade credit financing vs. bank credit financing," European Journal of Operational Research, Elsevier, vol. 294(2), pages 525-542.
    3. Zhao, Na, 2019. "Managing interactive collaborative mega project supply chains under infectious risks," International Journal of Production Economics, Elsevier, vol. 218(C), pages 275-286.
    4. Li, Yongjian & Zhen, Xueping & Qi, Xiangtong & Cai, Gangshu (George), 2016. "Penalty and financial assistance in a supply chain with supply disruption," Omega, Elsevier, vol. 61(C), pages 167-181.
    5. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    6. Fan, Yingjie & Schwartz, Frank & Voß, Stefan, 2017. "Flexible supply chain planning based on variable transportation modes," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 654-666.
    7. Coskun, Abdullah & Elmaghraby, Wedad & Karaman, M. Muge & Salman, F. Sibel, 2019. "Relief aid stocking decisions under bilateral agency cooperation," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 147-165.
    8. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    9. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    10. Davis, Lauren B. & Samanlioglu, Funda & Qu, Xiuli & Root, Sarah, 2013. "Inventory planning and coordination in disaster relief efforts," International Journal of Production Economics, Elsevier, vol. 141(2), pages 561-573.
    11. Trapero, Juan R. & Cardós, Manuel & Kourentzes, Nikolaos, 2019. "Empirical safety stock estimation based on kernel and GARCH models," Omega, Elsevier, vol. 84(C), pages 199-211.
    12. Chakravarty, Amiya K., 2014. "Humanitarian relief chain: Rapid response under uncertainty," International Journal of Production Economics, Elsevier, vol. 151(C), pages 146-157.
    13. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2022. "Agility in humanitarian supply chain: an organizational information processing perspective and relational view," Annals of Operations Research, Springer, vol. 319(1), pages 559-579, December.
    14. Yingjie Fan & Frank Schwartz & Stefan Voß & David L. Woodruff, 2017. "Stochastic programming for flexible global supply chain planning," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 601-633, December.
    15. Adrian SOLOMON & Panagiotis KETIKIDIS & Felicia SIAVALAS, 2017. "Institutional Co-Creation Interfaces for Innovation Diffusion during Disaster Management," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 5(1), pages 77-95, March.
    16. Camilo Gomez & Andrés D. González & Hiba Baroud & Claudia D. Bedoya‐Motta, 2019. "Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1913-1929, September.
    17. Gerda Zigiene & Egidijus Rybakovas & Rimgaile Vaitkiene, 2020. "Challenges in Applying Artificial Intelligence for Supply Chain Risk Management," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 299-318.
    18. Svoboda, Josef & Minner, Stefan & Yao, Man, 2021. "Typology and literature review on multiple supplier inventory control models," European Journal of Operational Research, Elsevier, vol. 293(1), pages 1-23.
    19. Rameshwar Dubey & Tripti Singh & Omprakash K. Gupta, 2015. "Impact of Agility, Adaptability and Alignment on Humanitarian Logistics Performance: Mediating Effect of Leadership," Global Business Review, International Management Institute, vol. 16(5), pages 812-831, October.
    20. Ali, Syed Mithun & Rahman, Md. Hafizur & Tumpa, Tasmia Jannat & Moghul Rifat, Abid Ali & Paul, Sanjoy Kumar, 2018. "Examining price and service competition among retailers in a supply chain under potential demand disruption," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 40-47.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:39:y:2019:i:1:d:10.1007_s10669-018-9700-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.