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The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods

Year 2024, Volume: 22 Issue: 1, 49 - 58, 26.04.2024

Deniz Erdal Burcu Ecem Uğuz Caferi Tayyar Şaşmaz

https://doi.org/10.20518/tjph.1357153

Abstract

Objective: The aim of this study is to evaluate the correlation between the incidence case/death rate of coronavirus disease 2019 (COVID-19) and some variables of the countries.
Methods: This research is an Ecological study. We analyzed the association of COVID‐19 incidence of cases/deaths with population rates over 65, Gini index, GDP per capita (current US$), burden of disease (DALYs-2019), literacy rate of over 15 years old, Coefficient of Variation (CV) of caloric intake, prevalence of obesity among adults, total COVID-19 vaccine doses administered per 100 people, and total tests conducted (per 1M). Furthermore, we analyzed the data on COVID-19 incidence of cases/death in the cross-sectionally for three periods: Alpha-Beta-Gamma, Delta and Omicron periods. Spearman correlation test was used for statistical analysis.
Results: Positive correlations were found in COVID-19 cumulative incidence of cases/deaths (per 1M), and population rates over 65, GDP (per capita), lliteracy rate of individuals over 15 years old, prevalence of obesity among adults, and total COVID-19 vaccine doses administered per 100 people. On the other hand, negative correlations were found with DALYs, Coefficient of Variation (CV) of caloric intake and Gini index. When the variant periods of COVID-19 were examined respectively (Alpha-Beta-Gamma, Delta and Omicron), the positive correlations and the negative correlations were further increased during the Omicron period.
Conclusion: It is recommended to consider the demographic and socioeconomic characteristics of the countries, as well as the characteristics of the disease agent, for the prevention and control of potential future pandemics.Keywords: COVİD-19, DALYs, aged, obesity, vaccine, correlation study

Keywords

COVID-19 DALYs Aged Obesity Correlation Study

Ethical Statement

Ethics committee approval was not obtained as this eco-logical type research was conducted with open data.

Supporting Institution

No funding support

Thanks

Thanks to Sevim Yılmaz for translation support.

References

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  • The World Bank. Gini index [Online]. Available at: https://data.worldbank.org/indicator/SI.POV.GINI. Accessed March 13 2023
  • Our World in Data. Obesity [Online]. Available at: https://ourworldindata.org/obesity. Accessed March 11 2023
  • Our World in Data. What is undernourishment and how is it measured? [Online]. Available at: https://ourworldindata.org/undernourishment-definition. Accessed March 17 2023
  • Our World in Data. Food Supply [Online]. Available at: https://ourworldindata.org/food-supply. Accessed March 17 2023
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  • Sachs JD, Karim SSA, Aknin L, et all. The Lancet Commission on lessons for the future from the COVID-19 pandemic. The Lancet. 2022 Oct;400(10359):1224–1280.
  • Our World in Data. Share of total disease burden by cause, World, 2019 [Online]. Available at: https://ourworldindata.org/grapher/share-of-total-disease-burden-by-cause. Accessed January 11 2023
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  • Dalsania AK, Fastiggi MJ, Kahlam A, et all. The Relationship Between Social Determinants of Health and Racial Disparities in COVID-19 Mortality. J Racial Ethn Health Disparities. 2022 Feb 5;9(1):288–295.
  • Mulenga LB, Hines JZ, Fwoloshi S, et all. Prevalence of SARS-CoV-2 in six districts in Zambia in July, 2020: a cross-sectional cluster sample survey. Lancet Glob Health. 2021 Jun;9(6):e773–e781.
  • Nkuba AN, Makiala SM, Guichet E, et all. High Prevalence of Anti–Severe Acute Respiratory Syndrome Coronavirus 2 (Anti–SARS-CoV-2) Antibodies After the First Wave of Coronavirus Disease 2019 (COVID-19) in Kinshasa, Democratic Republic of the Congo: Results of a Cross-sectional Household-Based Survey. Clinical Infectious Diseases. 2022 Mar 9;74(5):882–890.
  • Mandolo J, Msefula J, Henrion MYR, et all. SARS-CoV-2 exposure in Malawian blood donors: an analysis of seroprevalence and variant dynamics between January 2020 and July 2021. BMC Med. 2021 Dec 19;19(1):303.
  • Adetifa IMO, Uyoga S, Gitonga JN, et all. Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya. Nat Commun. 2021 Jun 25;12(1):3966.
  • Our World in Data. Median age, 1950 to 2100 [Online]. Available at: https://ourworldindata.org/grapher/median-age?tab=table. Accessed March 7 2023
  • Pardhan S, Drydakis N. Associating the Change in New COVID-19 Cases to GDP per Capita in 38 European Countries in the First Wave of the Pandemic. Front Public Health. 2021 Jan 20;8.
  • Bouba Y, Tsinda EK, Fonkou MDM, Mmbando GS, Bragazzi NL, Kong JD. The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis. Front Public Health. 2021 Oct 21;9.
  • Cifuentes-Faura J. COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables. Int J Environ Res Public Health. 2021 Jun 27;18(13):6900.
  • Azarpazhooh MR, Morovatdar N, Avan A, et all. COVID-19 Pandemic and Burden of Non-Communicable Diseases: An Ecological Study on Data of 185 Countries. J Stroke Cerebrovasc Dis. 2020 Sep;29(9):105089. PMID: 32807484
  • Burki T. Global COVID-19 vaccine inequity. Lancet Infect Dis. 2021 Jul;21(7):922–923. PMID: 34174236
  • Mathieu E, Ritchie H, Ortiz-Ospina E, et all. A global database of COVID-19 vaccinations. Nat Hum Behav. 2021 May 10;5(7):947–953.
  • Muttappallymyalil J, Chandrasekhar Nair S, Changerath R, Sreejith A, Manda S, Sreedharan J. Vaccination Rate and Incidence of COVID-19 and Case Fatality Rate (CFR): A Correlational Study Using Data From 2019 to 2021. Cureus. 2022 Aug;14(8):e28210. PMID: 36158447
  • Institute for Health Metrics and Evaluation. COVID-19 vaccine efficacy summary [Online]. Available at: https://www.healthdata.org/covid/COVID-19-vaccine-efficacy-summary. Accessed March 17 2023
  • Nair SC, Gasmelseed HI, Khan AA, et all. Assessment of mortality from COVID-19 in a multicultural multi-ethnic patient population. BMC Infect Dis. 2021 Dec 29;21(1):1115.
  • Alimohamadi Y, Tola HH, Abbasi-Ghahramanloo A, Janani M, Sepandi M. Case fatality rate of COVID-19: a systematic review and meta-analysis. J Prev Med Hyg. 2021 Jun;62(2):E311–E320. PMID: 34604571
  • Goldstein JR, Lee RD. Demographic perspectives on the mortality of COVID-19 and other epidemics. Proceedings of the National Academy of Sciences. 2020 Sep 8;117(36):22035–22041.

Year 2024, Volume: 22 Issue: 1, 49 - 58, 26.04.2024

Deniz Erdal Burcu Ecem Uğuz Caferi Tayyar Şaşmaz

https://doi.org/10.20518/tjph.1357153

Abstract

References

  • WHO. WHO Coronavirus (COVID-19) Dashboard With Vaccination Data [Online]. Available at: https://covid19.who.int. Accessed March 1 2023
  • CDC. People with Certain Medical Conditions [Online]. Available at: https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html#print. Accessed March 3 2023
  • Yanez ND, Weiss NS, Romand JA, Treggiari MM. COVID-19 mortality risk for older men and women. BMC Public Health. 2020 Dec 19;20(1):1742.
  • Sawadogo W, Tsegaye M, Gizaw A, Adera T. Overweight and obesity as risk factors for COVID-19-associated hospitalisations and death: systematic review and meta-analysis. BMJ Nutr Prev Health. 2022 Jun;5(1):10–18.
  • Bor J, Cohen GH, Galea S. Population health in an era of rising income inequality: USA, 1980-2015. Lancet. 2017 Apr 8;389(10077):1475–1490. PMID: 28402829
  • Kondo N, Sembajwe G, Kawachi I, van Dam RM, Subramanian S V, Yamagata Z. Income inequality, mortality, and self rated health: meta-analysis of multilevel studies. BMJ. 2009 Nov 10;339(nov10 2):b4471–b4471.
  • Ferreira FHG, Sterck O, Mahler DG, Decerf B. Death and Destitution: The Global Distribution of Welfare Losses from the COVID-19 Pandemic. LSE Public Policy Review. LSE Press; 2021 May 3;1(4):2.
  • Oshakbayev K, Zhankalova Z, Gazaliyeva M, et all. Association between COVID-19 morbidity, mortality, and gross domestic product, overweight/ obesity, non-communicable diseases, vaccination rate: A cross-sectional study. J Infect Public Health. 2022 Feb;15(2):255–260.
  • The World Bank. Indicators [Online]. Available at: https://data.worldbank.org/indicator. Accessed January 11 2023
  • Our World in Data [Online]. Available at: https://ourworldindata.org/. Accessed January 15 2023
  • COVID - Coronavirus Statistics - Worldometer [Online]. Available at: https://www.worldometers.info/coronavirus/. Accessed January 16 2023
  • WHO. Updated working definitions and primary actions for SARSCoV2 variants [Online]. Available at: https://www.who.int/publications/m/item/historical-working-definitions-and-primary-actions-for-sars-cov-2-variants. Accessed March 1 2023
  • Our World in Data. Burden of disease [Online]. Available at: https://ourworldindata.org/burden-of-disease. Accessed March 11 2023
  • Our World in Data. Economic Growth [Online].Available at: https://ourworldindata.org/economic-growth. Accessed March 13 2023
  • The World Bank. Gini index [Online]. Available at: https://data.worldbank.org/indicator/SI.POV.GINI. Accessed March 13 2023
  • Our World in Data. Obesity [Online]. Available at: https://ourworldindata.org/obesity. Accessed March 11 2023
  • Our World in Data. What is undernourishment and how is it measured? [Online]. Available at: https://ourworldindata.org/undernourishment-definition. Accessed March 17 2023
  • Our World in Data. Food Supply [Online]. Available at: https://ourworldindata.org/food-supply. Accessed March 17 2023
  • Our World in Data. Human Development Index (HDI) [Online]. Available at: https://ourworldindata.org/human-development-index. Accessed March 17 2023
  • The World Bank. Population ages 65 and above (% of total population) [Online]. Available at: https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS. Accessed January 11 2023
  • Sachs JD, Karim SSA, Aknin L, et all. The Lancet Commission on lessons for the future from the COVID-19 pandemic. The Lancet. 2022 Oct;400(10359):1224–1280.
  • Our World in Data. Share of total disease burden by cause, World, 2019 [Online]. Available at: https://ourworldindata.org/grapher/share-of-total-disease-burden-by-cause. Accessed January 11 2023
  • Magesh S, John D, Li WT, et all. Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status. JAMA Netw Open. 2021 Nov 11;4(11):e2134147.
  • Dalsania AK, Fastiggi MJ, Kahlam A, et all. The Relationship Between Social Determinants of Health and Racial Disparities in COVID-19 Mortality. J Racial Ethn Health Disparities. 2022 Feb 5;9(1):288–295.
  • Mulenga LB, Hines JZ, Fwoloshi S, et all. Prevalence of SARS-CoV-2 in six districts in Zambia in July, 2020: a cross-sectional cluster sample survey. Lancet Glob Health. 2021 Jun;9(6):e773–e781.
  • Nkuba AN, Makiala SM, Guichet E, et all. High Prevalence of Anti–Severe Acute Respiratory Syndrome Coronavirus 2 (Anti–SARS-CoV-2) Antibodies After the First Wave of Coronavirus Disease 2019 (COVID-19) in Kinshasa, Democratic Republic of the Congo: Results of a Cross-sectional Household-Based Survey. Clinical Infectious Diseases. 2022 Mar 9;74(5):882–890.
  • Mandolo J, Msefula J, Henrion MYR, et all. SARS-CoV-2 exposure in Malawian blood donors: an analysis of seroprevalence and variant dynamics between January 2020 and July 2021. BMC Med. 2021 Dec 19;19(1):303.
  • Adetifa IMO, Uyoga S, Gitonga JN, et all. Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya. Nat Commun. 2021 Jun 25;12(1):3966.
  • Our World in Data. Median age, 1950 to 2100 [Online]. Available at: https://ourworldindata.org/grapher/median-age?tab=table. Accessed March 7 2023
  • Pardhan S, Drydakis N. Associating the Change in New COVID-19 Cases to GDP per Capita in 38 European Countries in the First Wave of the Pandemic. Front Public Health. 2021 Jan 20;8.
  • Bouba Y, Tsinda EK, Fonkou MDM, Mmbando GS, Bragazzi NL, Kong JD. The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis. Front Public Health. 2021 Oct 21;9.
  • Cifuentes-Faura J. COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables. Int J Environ Res Public Health. 2021 Jun 27;18(13):6900.
  • Azarpazhooh MR, Morovatdar N, Avan A, et all. COVID-19 Pandemic and Burden of Non-Communicable Diseases: An Ecological Study on Data of 185 Countries. J Stroke Cerebrovasc Dis. 2020 Sep;29(9):105089. PMID: 32807484
  • Burki T. Global COVID-19 vaccine inequity. Lancet Infect Dis. 2021 Jul;21(7):922–923. PMID: 34174236
  • Mathieu E, Ritchie H, Ortiz-Ospina E, et all. A global database of COVID-19 vaccinations. Nat Hum Behav. 2021 May 10;5(7):947–953.
  • Muttappallymyalil J, Chandrasekhar Nair S, Changerath R, Sreejith A, Manda S, Sreedharan J. Vaccination Rate and Incidence of COVID-19 and Case Fatality Rate (CFR): A Correlational Study Using Data From 2019 to 2021. Cureus. 2022 Aug;14(8):e28210. PMID: 36158447
  • Institute for Health Metrics and Evaluation. COVID-19 vaccine efficacy summary [Online]. Available at: https://www.healthdata.org/covid/COVID-19-vaccine-efficacy-summary. Accessed March 17 2023
  • Nair SC, Gasmelseed HI, Khan AA, et all. Assessment of mortality from COVID-19 in a multicultural multi-ethnic patient population. BMC Infect Dis. 2021 Dec 29;21(1):1115.
  • Alimohamadi Y, Tola HH, Abbasi-Ghahramanloo A, Janani M, Sepandi M. Case fatality rate of COVID-19: a systematic review and meta-analysis. J Prev Med Hyg. 2021 Jun;62(2):E311–E320. PMID: 34604571
  • Goldstein JR, Lee RD. Demographic perspectives on the mortality of COVID-19 and other epidemics. Proceedings of the National Academy of Sciences. 2020 Sep 8;117(36):22035–22041.
There are 40 citations in total.

Details

Primary Language English
Subjects Health Services and Systems (Other)
Journal Section Original Research
Authors

Deniz Erdal 0000-0001-7721-0653

Burcu Ecem Uğuz 0000-0002-1356-541X

Caferi Tayyar Şaşmaz 0000-0002-3923-570X

Early Pub Date April 20, 2024
Publication Date April 26, 2024
Submission Date September 8, 2023
Acceptance Date February 16, 2024
Published in Issue Year 2024 Volume: 22 Issue: 1

Cite

APA Erdal, D., Uğuz, B. E., & Şaşmaz, C. T. (2024). The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods. Turkish Journal of Public Health, 22(1), 49-58. https://doi.org/10.20518/tjph.1357153
AMA Erdal D, Uğuz BE, Şaşmaz CT. The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods. TJPH. April 2024;22(1):49-58. doi:10.20518/tjph.1357153
Chicago Erdal, Deniz, Burcu Ecem Uğuz, and Caferi Tayyar Şaşmaz. “The Evaluation of the Correlation Between Some Variables of the Countries and COVID-19 Incidence of Cases and Deaths in Different Variant Periods”. Turkish Journal of Public Health 22, no. 1 (April 2024): 49-58. https://doi.org/10.20518/tjph.1357153.
EndNote Erdal D, Uğuz BE, Şaşmaz CT (April 1, 2024) The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods. Turkish Journal of Public Health 22 1 49–58.
IEEE D. Erdal, B. E. Uğuz, and C. T. Şaşmaz, “The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods”, TJPH, vol. 22, no. 1, pp. 49–58, 2024, doi: 10.20518/tjph.1357153.
ISNAD Erdal, Deniz et al. “The Evaluation of the Correlation Between Some Variables of the Countries and COVID-19 Incidence of Cases and Deaths in Different Variant Periods”. Turkish Journal of Public Health 22/1 (April 2024), 49-58. https://doi.org/10.20518/tjph.1357153.
JAMA Erdal D, Uğuz BE, Şaşmaz CT. The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods. TJPH. 2024;22:49–58.
MLA Erdal, Deniz et al. “The Evaluation of the Correlation Between Some Variables of the Countries and COVID-19 Incidence of Cases and Deaths in Different Variant Periods”. Turkish Journal of Public Health, vol. 22, no. 1, 2024, pp. 49-58, doi:10.20518/tjph.1357153.
Vancouver Erdal D, Uğuz BE, Şaşmaz CT. The evaluation of the correlation between some variables of the countries and COVID-19 incidence of cases and deaths in different variant periods. TJPH. 2024;22(1):49-58.
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