IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/vm5rz.html
   My bibliography  Save this paper

Societal impact of novel corona virus (COVID ̶ 19 pandemic) in India

Author

Listed:
  • Kundu, Bhargabi
  • Bhowmik, Dipak

    (IIT Kanpur)

Abstract

The whole world is facing a big crisis due to the spreading of newly detected novel corona virus 2019 (COVID ̶ 19). A huge number of people have already been infected since last 4 months. People are thinking about the prevention of infected individuals, vaccine, medical treatment, and other precautions. The governments of most countries including India have already taken several measures like lockdown, social distancing, closure of schools, colleges, religious gatherings etc., to reduce its spreading. India is a developing country and most of the people are having below the standard income. So the lockdown in India has affected the poor and middle income group people. In this article, we will discuss in detail on the societal effects in India due to COVID ̶ 19 pandemic. The effects of health, essential commodities, Indian economy, domestic violence, politics, and psychology on society due to COVID ̶ 19 will be elaborated in detail. The aim of this research is to have a clear understanding of the present societal scenario during lockdown, which may help the government for better management and prevention of the disease.

Suggested Citation

  • Kundu, Bhargabi & Bhowmik, Dipak, 2020. "Societal impact of novel corona virus (COVID ̶ 19 pandemic) in India," SocArXiv vm5rz, Center for Open Science.
    • Handle: RePEc:osf:socarx:vm5rz
    DOI: 10.31219/osf.io/vm5rz
    as

    Download full text from publisher

    File URL: https://osf.io/download/5ea5b69b3854e200b769f565/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/vm5rz?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
    ---><---

    References listed on IDEAS

    as
    1. Fotios Petropoulos & Spyros Makridakis, 2020. "Forecasting the novel coronavirus COVID-19," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-8, March.
    Full references (including those not matched with items on IDEAS)

    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. Dante Miller & Jong-Min Kim, 2021. "Univariate and Multivariate Machine Learning Forecasting Models on the Price Returns of Cryptocurrencies," JRFM, MDPI, vol. 14(10), pages 1-10, October.
    2. Masum, Mohammad & Masud, M.A. & Adnan, Muhaiminul Islam & Shahriar, Hossain & Kim, Sangil, 2022. "Comparative study of a mathematical epidemic model, statistical modeling, and deep learning for COVID-19 forecasting and management," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    3. Das, Saikat & Bose, Indranil & Sarkar, Uttam Kumar, 2023. "Predicting the outbreak of epidemics using a network-based approach," European Journal of Operational Research, Elsevier, vol. 309(2), pages 819-831.
    4. Chakraborty, Tanujit & Ghosh, Indrajit, 2020. "Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    5. Emrah Gecili & Assem Ziady & Rhonda D Szczesniak, 2021. "Forecasting COVID-19 confirmed cases, deaths and recoveries: Revisiting established time series modeling through novel applications for the USA and Italy," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-11, January.
    6. Camacho, Carmen & Vasilakis, Chrysovalantis, 2023. "Transmissible Diseases, Vaccination and Inequality," IZA Discussion Papers 16504, Institute of Labor Economics (IZA).
    7. Paolo Berta & Paolo Paruolo & Stefano Verzillo & Pietro Giorgio Lovaglio, 2020. "A bivariate prediction approach for adapting the health care system response to the spread of COVID-19," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    8. Noureddine Ouerfelli & Narcisa Vrinceanu & Diana Coman & Adriana Lavinia Cioca, 2022. "Empirical Modeling of COVID-19 Evolution with High/Direct Impact on Public Health and Risk Assessment," IJERPH, MDPI, vol. 19(6), pages 1-13, March.
    9. Berta, P. & Lovaglio, P.G. & Paruolo, P. & Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand," Health, Econometrics and Data Group (HEDG) Working Papers 20/16, HEDG, c/o Department of Economics, University of York.
    10. Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2022. "Short-term forecasting of the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(2), pages 453-466.
    11. Semenoglou, Artemios-Anargyros & Spiliotis, Evangelos & Makridakis, Spyros & Assimakopoulos, Vassilios, 2021. "Investigating the accuracy of cross-learning time series forecasting methods," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1072-1084.
    12. Kathryn S Taylor & James W Taylor, 2022. "Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-25, March.
    13. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    14. Konstantinos Demertzis & Dimitrios Tsiotas & Lykourgos Magafas, 2020. "Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach Based on Complex Network Defined Splines," IJERPH, MDPI, vol. 17(13), pages 1-17, June.
    15. Khalid A. Kheirallah & Belal Alsinglawi & Abdallah Alzoubi & Motasem N. Saidan & Omar Mubin & Mohammed S. Alorjani & Fawaz Mzayek, 2020. "The Effect of Strict State Measures on the Epidemiologic Curve of COVID-19 Infection in the Context of a Developing Country: A Simulation from Jordan," IJERPH, MDPI, vol. 17(18), pages 1-11, September.
    16. Nathan H. Schumaker & Sydney M. Watkins, 2021. "Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA," Land, MDPI, vol. 10(4), pages 1-13, April.
    17. Michał Wieczorek & Jakub Siłka & Dawid Połap & Marcin Woźniak & Robertas Damaševičius, 2020. "Real-time neural network based predictor for cov19 virus spread," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-18, December.
    18. Torrealba-Rodriguez, O. & Conde-Gutiérrez, R.A. & Hernández-Javier, A.L., 2020. "Modeling and prediction of COVID-19 in Mexico applying mathematical and computational models," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    19. Jordan J Bird & Chloe M Barnes & Cristiano Premebida & Anikó Ekárt & Diego R Faria, 2020. "Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-20, October.
    20. Mohammad Amin Hariri-Ardebili, 2020. "Living in a Multi-Risk Chaotic Condition: Pandemic, Natural Hazards and Complex Emergencies," IJERPH, MDPI, vol. 17(16), pages 1-16, August.

    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:osf:socarx:vm5rz. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.