IDEAS home Printed from https://ideas.repec.org/a/igg/jsda00/v11y2022i1p1-16.html
   My bibliography  Save this article

Fuzzy Modelling of Clinical and Epidemiological Factors for COVID-19

Author

Listed:
  • Poonam Mittal

    (J C Bose University of science and Technology, YMCA, Faridabad, India)

  • Monika Mangla

    (Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India)

  • Nonita Sharma

    (Department of Information Technology, Indira Gandhi Delhi Technical University for Women, New Delhi, India)

  • Reena

    (Dr. B. R. Ambedkar National Institute of Technology, India)

  • Suneeta Satpathy

    (Faculty of Emerging Technology, Sri Sri University, Cuttack, India)

  • Sachi Nandan Mohanty

    (School of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, India)

Abstract

During this pandemic outbreak of COVID-19, the whole world is getting severely affected in respect of population health and economy. This novel virus has brought the whole world including the most developed countries to a standstill in a very short span like never before. The prime reason for this unexpected outburst of COVID-19 is lack of effective medicine and lack of proper understanding of the influencing factors. Here, the authors aim to find the effect of epidemiological factors that influence its spread using a fuzzy approach. For the same, a total of nine factors have been considered which are classified into risk and preventive factors. This fuzzy model supports to understand and evaluate the impact of these factors on the spread of COVID-19. Also, the model establishes a basis for understanding the effect of risk factors on preventive factors and vice versa. It is worth mentioning that this is the first attempt to analyze the effect of clinical and epidemiological factors with respect to COVID-19 using a fuzzy approach.

Suggested Citation

  • Poonam Mittal & Monika Mangla & Nonita Sharma & Reena & Suneeta Satpathy & Sachi Nandan Mohanty, 2022. "Fuzzy Modelling of Clinical and Epidemiological Factors for COVID-19," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 11(1), pages 1-16, January.
    • Handle: RePEc:igg:jsda00:v:11:y:2022:i:1:p:1-16
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSDA.307566
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jsda00:v:11:y:2022:i:1:p:1-16. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.