IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v85y2023ics0038012122002531.html
   My bibliography  Save this article

Identifying and prioritizing resilient health system units to tackle the COVID-19 pandemic

Author

Listed:
  • Adabavazeh, Nazila
  • Nikbakht, Mehrdad
  • Tirkolaee, Erfan Babaee

Abstract

Since human health greatly depends on a healthy and risk-free social environment, it is very important to have a concept to focus on improving epidemiology capacity and potential along with economic perspectives as a very influential factor in the future of societies. Through responsible behavior during an epidemic crisis, the health system units can be utilized as a suitable platform for sustainable development. This study employs the Best-Worst Method (BWM) in order to develop a system for identifying and ranking health system units with understanding the nature of the epidemic to help the World Health Organization (WHO) in recognizing the capabilities of resilient health system units. The purpose of this study is to identify and prioritize the resilient health system units for dealing with Coronavirus. The statistical population includes 215 health system units in the world and the opinions of twenty medical experts are also utilized as an informative sample to localize the conceptual model of the study and answer the research questionnaires. The resilient health system units of the world are identified and prioritized based on the statistics of “Total Cases”, “Total Recovered”, “Total Deaths”, “Active Cases”, “Serious”, “Total Tests” and “Day of Infection”. The present descriptive cross-sectional study is conducted on Worldometer data of COVID-19 during the period of 17 July 2020 at 8:33 GMT. According to the results, the factors of “Total Cases”, “Total Deaths”, “Serious”, “Active Cases”, “Total Recovered”, “Total Tests” and “Day of Infection” are among the most effective ones, respectively, in order to have a successful and optimal performance during a crisis. The attention of health system units to the identified important factors can improve the performance of epidemiology system. The WHO should pay more attention to low-resilience health system units in terms of promoting the health culture in crisis management of common viruses. Considering the importance of providing health services as well as their significant effect on the efficiency of the world health system, especially in critical situations, resilience analysis with the possibility of comparison and ranking can be an important step to continuously improve the performance of health system units.

Suggested Citation

  • Adabavazeh, Nazila & Nikbakht, Mehrdad & Tirkolaee, Erfan Babaee, 2023. "Identifying and prioritizing resilient health system units to tackle the COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:soceps:v:85:y:2023:i:c:s0038012122002531
    DOI: 10.1016/j.seps.2022.101452
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012122002531
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2022.101452?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. Karasan, Ali & Erdogan, Melike & Cinar, Melih, 2022. "Healthcare service quality evaluation: An integrated decision-making methodology and a case study," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    2. Ankan Bhaumik & Sankar Kumar Roy & Gerhard Wilhelm Weber, 2020. "Hesitant interval-valued intuitionistic fuzzy-linguistic term set approach in Prisoners’ dilemma game theory using TOPSIS: a case study on Human-trafficking," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 797-816, June.
    3. Dragan Pamučar & Fatih Ecer & Goran Cirovic & Melfi A. Arlasheedi, 2020. "Application of Improved Best Worst Method (BWM) in Real-World Problems," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    4. Kok Fong See & Siew Hwa Yen, 2018. "Does happiness matter to health system efficiency? A performance analysis," Health Economics Review, Springer, vol. 8(1), pages 1-10, December.
    5. Daryosh Mohamadi Janaki & Abolfazl Mirzazadeh & Mehdi Mohamadi Janaki, 2019. "Reducing barriers to the implementation of strategic management by providing improved strategies: using fuzzy QFD applied to Petropars Company," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 31(4), pages 535-557.
    6. Billy Fleming, 2015. "The Resilience Dividend: Being Strong in a World Where Things Go Wrong , by Judith Rodin; and The Social Roots of Risk: Producing Disasters, Promoting Resilience , by Kathleen Tierney," Journal of the American Planning Association, Taylor & Francis Journals, vol. 81(4), pages 316-317, October.
    7. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    8. Alper Çevik & Gerhard-Wilhelm Weber & B. Murat Eyüboğlu & Kader Karlı Oğuz, 2017. "Voxel-MARS: a method for early detection of Alzheimer’s disease by classification of structural brain MRI," Annals of Operations Research, Springer, vol. 258(1), pages 31-57, November.
    9. Garcia-Lacalle, Javier & Martin, Emilio, 2010. "Rural vs urban hospital performance in a 'competitive' public health service," Social Science & Medicine, Elsevier, vol. 71(6), pages 1131-1140, September.
    10. Ocampo, Lanndon & Yamagishi, Kafferine, 2020. "Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    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. Rini & Priyamvada, 2023. "COVID-19 challenge: optimizing investment in service and promotional effort with pricing strategy for sustainability in new normal," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1218-1229, September.
    2. Nandi, Sandip & Granata, Giuseppe & Jana, Subrata & Ghorui, Neha & Mondal, Sankar Prasad & Bhaumik, Moumita, 2023. "Evaluation of the treatment options for COVID-19 patients using generalized hesitant fuzzy- multi criteria decision making techniques," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    3. Kochakkashani, Farid & Kayvanfar, Vahid & Haji, Alireza, 2023. "Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

    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. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    2. Xiao-Kang Wang & Wen-Hui Hou & Chao Song & Min-Hui Deng & Yong-Yi Li & Jian-Qiang Wang, 2021. "BW-MaxEnt: A Novel MCDM Method for Limited Knowledge," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    3. Jurgita Kuizinaitė & Mangirdas Morkūnas & Artiom Volkov, 2023. "Assessment of the Most Appropriate Measures for Mitigation of Risks in the Agri-Food Supply Chain," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    4. Du, Puliang & Zhou, Bo & Yang, Miaoheng, 2024. "Carbon emission reduction contribution analysis of electricity enterprises in urban green development: A quantum spherical fuzzy sets-based decision framework," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    5. Shorabeh, Saman Nadizadeh & Firozjaei, Hamzeh Karimi & Firozjaei, Mohammad Karimi & Jelokhani-Niaraki, Mohammadreza & Homaee, Mehdi & Nematollahi, Omid, 2022. "The site selection of wind energy power plant using GIS-multi-criteria evaluation from economic perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Muhammet Deveci & Raghunathan Krishankumar & Ilgin Gokasar & Rumeysa Tuna Deveci, 2023. "Prioritization of healthcare systems during pandemics using Cronbach’s measure based fuzzy WASPAS approach," Annals of Operations Research, Springer, vol. 328(1), pages 279-307, September.
    7. Wan-Chi Jackie Hsu & Huai-Wei Lo & Chin-Cheng Yang, 2021. "The Formulation of Epidemic Prevention Work of COVID-19 for Colleges and Universities: Priorities and Recommendations," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    8. Alptekin Ulutaş & Ayşe Topal & Dragan Pamučar & Željko Stević & Darjan Karabašević & Gabrijela Popović, 2022. "A New Integrated Multi-Criteria Decision-Making Model for Sustainable Supplier Selection Based on a Novel Grey WISP and Grey BWM Methods," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    9. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    10. Junnan Wu & Xin Liu & Dianqi Pan & Yichen Zhang & Jiquan Zhang & Kai Ke, 2023. "Research on Safety Evaluation of Municipal Sewage Treatment Plant Based on Improved Best-Worst Method and Fuzzy Comprehensive Method," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    11. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    12. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    13. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    14. Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1778-1798, October.
    15. Dilupa Nakandala & Yung Po Tsang & Henry Lau & Carman Ka Man Lee, 2022. "An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    16. Martín-García, Jaime & Gómez-Limón, José A. & Arriaza, Manuel, 2024. "Conversion to organic farming: Does it change the economic and environmental performance of fruit farms?," Ecological Economics, Elsevier, vol. 220(C).
    17. Zeng, Shouzhen & Zhou, Jiamin & Zhang, Chonghui & Merigó, José M., 2022. "Intuitionistic fuzzy social network hybrid MCDM model for an assessment of digital reforms of manufacturing industry in China," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    18. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    19. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    20. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).

    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:eee:soceps:v:85:y:2023:i:c:s0038012122002531. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.