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Why Do COVID-19 Fatality Rates Differ Across Countries? An Explorative Cross-country Study Based on Select Indicators

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  • Arindam Banik
  • Tirthankar Nag
  • Sahana Roy Chowdhury
  • Rajashri Chatterjee

Abstract

In this article, we analyse the factors that determine the fatality rates across 29 economies spread across both the developing and developed world. Recent emerging literature and expert opinions in popular media have indicated various factors that may explain cross-country difference in fatality rates. These factors range from access to public health infrastructure, BCG vaccination policies, demographic structure, restrictive policy interventions and the weather. In addition, articles are examining different kinds of fatality rates that can be explained. Progressing beyond fragmented databases and anecdotal evidence, we have developed a database for such factors, have explored various econometric models to test the explanatory power of these factors in explaining several kinds of fatality rates. Based on available data, our study reveals that factors such as public health system, population age structure, poverty level and BCG vaccination are powerful contributory factors in determining fatality rates. Interactions between factors such as poverty level and BCG vaccination provide interesting insights into the complex interplay of factors. Our analysis suggests that poor citizens’ access to the public healthcare system are worse in many countries irrespective of whether they are developed or developing countries.

Suggested Citation

  • Arindam Banik & Tirthankar Nag & Sahana Roy Chowdhury & Rajashri Chatterjee, 2020. "Why Do COVID-19 Fatality Rates Differ Across Countries? An Explorative Cross-country Study Based on Select Indicators," Global Business Review, International Management Institute, vol. 21(3), pages 607-625, June.
    • Handle: RePEc:sae:globus:v:21:y:2020:i:3:p:607-625
    DOI: 10.1177/0972150920929897
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    References listed on IDEAS

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    1. Jennifer Beam Dowd & Liliana Andriano & David M. Brazel & Valentina Rotondi & Per Block & Xuejie Ding & Yan Liu & Melinda C. Mills, 2020. "Demographic science aids in understanding the spread and fatality rates of COVID-19," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(18), pages 9696-9698, May.
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    Cited by:

    1. Das, Ramesh Chandra, 2020. "Forecasting incidences of COVID-19 using Box-Jenkins method for the period July 12-Septembert 11, 2020: A study on highly affected countries," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Munim Kumar Barai, 2021. "COVID 19 in South Asia and the Way Forward: An Introduction," South Asian Survey, , vol. 28(1), pages 7-19, March.
    3. Koppiahraj Karuppiah & Bathrinath Sankaranarayanan & Syed Mithun Ali, 2022. "Modeling Impacts of COVID-19 in Supply Chain Activities: A Grey-DEMATEL Approach," Sustainability, MDPI, vol. 14(21), pages 1-21, October.
    4. Lorenzo Pratici & Phillip McMinn Singer, 2021. "COVID-19 Vaccination: What Do We Expect for the Future? A Systematic Literature Review of Social Science Publications in the First Year of the Pandemic (2020–2021)," Sustainability, MDPI, vol. 13(15), pages 1-18, July.
    5. James Davies, 2021. "Economic Inequality and Covid-19 Death Rates in the First Wave, a Cross-Country Analysis," CESifo Working Paper Series 8957, CESifo.
    6. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," Papers 2110.10230, arXiv.org.
    7. Carolyn Chisadza & Matthew Clance & Rangan Gupta, 2021. "Government Effectiveness and the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    8. Ramesh Behl & Manit Mishra, 2020. "COVID-19 Lifecycle: Predictive Modelling of States in India," Global Business Review, International Management Institute, vol. 21(4), pages 883-891, August.
    9. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    10. Okafor, Luke & Yan, Eric, 2022. "Covid-19 vaccines, rules, deaths, and tourism recovery," Annals of Tourism Research, Elsevier, vol. 95(C).
    11. Giménez, Víctor & Prior, Diego & Thieme, Claudio & Tortosa-Ausina, Emili, 2024. "International comparisons of COVID-19 pandemic management: What can be learned from activity analysis techniques?," Omega, Elsevier, vol. 122(C).
    12. Anasuya Haldar & Narayan Sethi, 2021. "The Effect of Country-level Factors and Government Intervention on the Incidence of COVID-19," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 1(2), pages 1-4.

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