IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v151y2021ics0960077921005944.html
   My bibliography  Save this article

Clustering of countries for COVID-19 cases based on disease prevalence, health systems and environmental indicators

Author

Listed:
  • Rizvi, Syeda Amna
  • Umair, Muhammad
  • Cheema, Muhammad Aamir

Abstract

The coronavirus has a high basic reproduction number (R0) and has caused the global COVID-19 pandemic. Governments are implementing lockdowns that are leading to economic fallout in many countries. Policy makers can take better decisions if provided with the indicators connected with the disease spread. This study is aimed to cluster the countries using social, economic, health and environmental related metrics affecting the disease spread so as to implement the policies to control the widespread of disease. Thus, countries with similar factors can take proactive steps to fight against the pandemic. The data is acquired for 79 countries and 18 different feature variables (the factors that are associated with COVID-19 spread) are selected. Pearson Product Moment Correlation Analysis is performed between all the feature variables with cumulative death cases and cumulative confirmed cases individually to get an insight of relation of these factors with the spread of COVID-19. Unsupervised k-means algorithm is used and the feature set includes economic, environmental indicators and disease prevalence along with COVID-19 variables. The learning model is able to group the countries into 4 clusters on the basis of relation with all 18 feature variables. We also present an analysis of correlation between the selected feature variables, and COVID-19 confirmed cases and deaths. Prevalence of underlying diseases shows strong correlation with COVID-19 whereas environmental health indicators are weakly correlated with COVID-19.

Suggested Citation

  • Rizvi, Syeda Amna & Umair, Muhammad & Cheema, Muhammad Aamir, 2021. "Clustering of countries for COVID-19 cases based on disease prevalence, health systems and environmental indicators," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921005944
    DOI: 10.1016/j.chaos.2021.111240
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921005944
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.111240?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. Malki, Zohair & Atlam, El-Sayed & Hassanien, Aboul Ella & Dagnew, Guesh & Elhosseini, Mostafa A. & Gad, Ibrahim, 2020. "Association between weather data and COVID-19 pandemic predicting mortality rate: Machine learning approaches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Faye Chan & Susana Adamo & Pamela Coxson & Lee Goldman & Dongfeng Gu & Dong Zhao & Chung-Shiuan Chen & Jiang He & Valentina Mara & Andrew Moran, 2012. "Projected impact of urbanization on cardiovascular disease in china," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(5), pages 849-854, October.
    3. Fynnwin Prager & Dan Wei & Adam Rose, 2017. "Total Economic Consequences of an Influenza Outbreak in the United States," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 4-19, January.
    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. Cerqueti, Roy & Ficcadenti, Valerio, 2022. "Combining rank-size and k-means for clustering countries over the COVID-19 new deaths per million," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    2. Joanna Brzyska & Izabela Szamrej-Baran, 2021. "Classification of the EU Countries According to the Vulnerability of their Economies to the Impact of COVID-19 Pandemic," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 967-978.
    3. Saleem, Farhan & Hina, Saadia & Ullah, Irfan & Habib, Ammara & Hina, Alina & Ilyas, Sana & Hamid, Muhammad, 2024. "Impacts of irregular and strategic lockdown on air quality over Indo-Pak Subcontinent: Pre-to-post COVID-19 analysis," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    4. Alexandra-Mădălina Țăran & Lavinia Mustea & Sorana Vătavu & Oana-Ramona Lobonț & Magda-Mihaela Luca, 2022. "Challenges and Drawbacks of the EU Medical System Generated by the COVID-19 Pandemic in the Field of Health Systems’ Digitalization," IJERPH, MDPI, vol. 19(9), pages 1-26, April.

    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. Don Pagach & Monika Wieczorek-Kosmala, 2020. "The Challenges and Opportunities for ERM Post-COVID-19: Agendas for Future Research," JRFM, MDPI, vol. 13(12), pages 1-10, December.
    2. Trey Malone & K. Aleks Schaefer & Felicia Wu, 2021. "The Razor's Edge of “Essential” Labor in Food and Agriculture," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(1), pages 368-381, March.
    3. Jorge Enrique Horbath Corredor, 2021. "La probabilidad de contagio y deceso por COVID-19 en pacientes indígenas y no indígenas iniciando la pandemia en México," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, vol. 40(72), pages 205-232, July.
    4. Shimaa Elkomy & Tim Jackson, 2024. "Health resilience and the global pandemic: The effect of social conditions on the COVID‐19 mortality rate," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(5), pages 2342-2371, July.
    5. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    6. Prager, Fynnwin & Rhoads, Mohja & Martínez, Jose N., 2022. "The COVID-19 economic shutdown and the future of flexible workplace practices in the South Bay region of Los Angeles County," Transport Policy, Elsevier, vol. 125(C), pages 241-255.
    7. Doran, Áine & Colvin, Christopher L. & McLaughlin, Eoin, 2024. "What can we learn from historical pandemics? A systematic review of the literature," Social Science & Medicine, Elsevier, vol. 342(C).
    8. Ilan Noy & Nguyen Doan & Benno Ferrarini & Donghyun Park, 2020. "Measuring the Economic Risk of COVID‐19," Global Policy, London School of Economics and Political Science, vol. 11(4), pages 413-423, September.
    9. Linn Svegrup & Jonas Johansson & Henrik Hassel, 2019. "Integration of Critical Infrastructure and Societal Consequence Models: Impact on Swedish Power System Mitigation Decisions," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1970-1996, September.
    10. Ilan Noy & Nguyen Doan & Benno Ferrarini & Donghyun Park, 2019. "Measuring the Economic Risk of Epidemics," CESifo Working Paper Series 8016, CESifo.
    11. Francis Tuluri & Reddy Remata & Wilbur L. Walters & Paul. B. Tchounwou, 2022. "Application of Machine Learning to Study the Association between Environmental Factors and COVID-19 Cases in Mississippi, USA," Mathematics, MDPI, vol. 10(6), pages 1-9, March.
    12. Patrice Rélouendé Zidouemba & Somlanare Romuald Kinda & Idrissa Mohamed Ouedraogo, 2020. "Could Covid-19 Worsen Food Insecurity in Burkina Faso?," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(5), pages 1379-1401, December.
    13. Walmsley, Terrie & Rose, Adam & John, Richard & Wei, Dan & Hlávka, Jakub P. & Machado, Juan & Byrd, Katie, 2023. "Macroeconomic consequences of the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 120(C).
    14. Das, Ayan Kumar & Kalam, Sidra & Kumar, Chiranjeev & Sinha, Ditipriya, 2021. "TLCoV- An automated Covid-19 screening model using Transfer Learning from chest X-ray images," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    15. Klas Kellerborg & Werner Brouwer & Pieter Baal, 2020. "Costs and benefits of interventions aimed at major infectious disease threats: lessons from the literature," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(9), pages 1329-1350, December.
    16. Ilan Noy & Tomáš Uher, 2022. "Economic consequences of pre-COVID-19 epidemics: a literature review," Chapters, in: Mark Skidmore (ed.), Handbook on the Economics of Disasters, chapter 7, pages 117-133, Edward Elgar Publishing.
    17. Wang, Mingzhao & Fu, Zuntao, 2022. "A new method of nonlinear causality detection: Reservoir computing Granger causality," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    18. Betarelli Junior, Admir Antonio & Faria, Weslem Rodrigues & Proque, Andressa Lemes & Perobelli, Fernando Salgueiro & de Almeida Vale, Vinicius, 2021. "COVID-19, public agglomerations and economic effects: Assessing the recovery time of passenger transport services in Brazil," Transport Policy, Elsevier, vol. 110(C), pages 254-272.
    19. Yu-Tse Tsan & Endah Kristiani & Po-Yu Liu & Wei-Min Chu & Chao-Tung Yang, 2022. "In the Seeking of Association between Air Pollutant and COVID-19 Confirmed Cases Using Deep Learning," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    20. Delin Meng & Jun Xu & Jijun Zhao, 2021. "Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-16, December.

    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:chsofr:v:151:y:2021:i:c:s0960077921005944. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.