The Impact COVID-19 Pandemic on Coronary Heart Disease Deaths: Using Bayesian Lorenz Curve and Gini-Index Distribution

Abdulbari  Bener; Mustafa Hakan  Saldi; Zülfiye  Kuzu; Zekeriya  Nurkalem

doi:10.6000/1929-6029.2025.14.26

Authors

Abdulbari Bener Department of Biostatistics and Public Health, School of Medicine, Istanbul Medipol University, İstanbul, Turkey and Department of Evidence for Population Health Unit, School of Epidemiology and Health Sciences, The University of Manchester, Manchester, UK
Mustafa Hakan Saldi Department of Logistic Management, School of Medicine, Istanbul Medipol University, İstanbul, Turkey
Zülfiye Kuzu Department of Cardiology, School of Medicine, Health Sciences University, Kayseri State Hospital, Kayseri, Turkey https://orcid.org/0000-0001-5378-5516
Zekeriya Nurkalem Department of Cardiology, School of Medicine, Istanbul Medipol University, İstanbul, Turkey

DOI:

https://doi.org/10.6000/1929-6029.2025.14.26

Keywords:

Bayesian, Markov Chain and Monte Carlo (MCMC), Morbidity, Mortality, COVID-19, Lorenz Curve, Gini index

Abstract

Aim: The aim to investigate and assess role of COVID-19 on Coronary Heart Disease (CHD) mortality using Bayesian Lorenz Curve and associated Gini Index

Statistical Method: Bayesian estimation was applied to analyze CHD mortality rates, focusing on both gender and age group differences.

Application: A total of 341,467 patients were treated during 2-year period from 2020 to 2021during COVID-19 in Turkey. 195,413 females and 146,054 males were diagnosed and 155,211 deaths where 88,824 were males and 66,387 were females with CHD, and hence were studied to evaluate whether female gender was an independent predictor for poor prognosis.

Results: Mortality rates increase with age for females compared to males. The model suggests that males have higher risks or proportions across all groups compared to females, particularly in older age categories. The Lorenz curves for both genders show that a significant portion of deaths is concentrated in a relatively small subset of age groups, particularly older adults. The Gini Index regarding mortality for males is found to be 0.123 compared to value of 0.384 associated with female's age distribution. Meanwhile, the Gini Index regarding morbidity for males (0.146) and females (0.394) are very similar, suggesting that the patterns of inequality in morbidity distribution are comparable across genders.

Conclusion: The study highlights the effectiveness of empirical Bayesian techniques in estimating CHD-related COVID-19 mortality rates across Turkey. It suggests that such statistical methods can help allocate resources more efficiently to high-risk areas and to ensure fair resource distribution and healthcare interventions.

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