Statistical Evaluation of Infant Mortality, COVID-19, and Tuberculosis in Iraq

Authors

  • Dler H. Kadir (1) Department of Statistics and Informatics, College of Administration and Economics, Salahaddin University-Erbil, Erbil, Kurdistan Region - F.R. Iraq; (2) Department of Business Administration, Cihan University-Erbil, Erbil, Kurdistan Region - F.R. Iraq https://orcid.org/0000-0002-1254-721X

DOI:

https://doi.org/10.14500/aro.13066

Keywords:

Binary Logistic Regression, Infant mortality, Tuberculosis, COVID-19, One-way ANOVA

Abstract

A part of this study investigates the factors associated with infant death in Iraq based on the multiple indicator cluster survey round sex survey dataset. Furthermore, the other part of this study is to investigate the potential association between the COVID-19 pandemic and tuberculosis (TB) cases, consisting of 1381 TB patients recorded over 4 years (2019–2022) at Iraq TB hospitals. The methodology adapted for analyzing is known as binary logistic regression for predicting the probability of determinants that are related to infant death and its component periods in the region. Furthermore, we used TB cases in 2019 as a control group and baseline for comparison. To determine statistically significant differences in average TB cases between groups, we employed one-way analysis of variance with post hoc multiple comparisons. We analyzed TB case frequency by quarter. Our findings reveal a statistically significant increase in TB cases during the second and third quarters of 2022, coinciding with the decline of COVID-19 cases in the region. This suggests a stronger overall TB incidence after the pandemic’s peak compared to pre pandemic levels in 2020. These findings are highly beneficial for the fields of public health, epidemiology, and health policy-making. In practice, this analysis applies to strategic resource allocation and the design of targeted maternal-child health interventions. It helps policymakers identify high-risk demographic groups to reduce infant mortality and enables health systems to address the resurgence of neglected infectious diseases like TB.

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Author Biography

Dler H. Kadir, (1) Department of Statistics and Informatics, College of Administration and Economics, Salahaddin University-Erbil, Erbil, Kurdistan Region - F.R. Iraq; (2) Department of Business Administration, Cihan University-Erbil, Erbil, Kurdistan Region - F.R. Iraq

Dler H. Kadir is an Assistant Professor at the Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Iraq. He received his B.Sc. degree in Statistics from Salahaddin University-Erbil, his M.Sc. degree in Statistics from the University of Sulaymaniyah, Iraq, and his Ph.D. degree in Probability and Statistics from the University of Sheffield, UK. His research interests include Bayesian inference, MCMC, and statistical modeling. Dr. Kadir is a member of the Kurdistan Economic Syndicate.

References

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Published

2026-10-18

How to Cite

Kadir, D. H. (2026) “Statistical Evaluation of Infant Mortality, COVID-19, and Tuberculosis in Iraq”, ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 14(2), pp. 104–111. doi: 10.14500/aro.13066.

Issue

Vol. 14 No. 2 (2026): Edition Twenty Seven

Section

Articles

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Copyright (c) 2026 Dler H. Kadir

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Received 2026-06-16
Accepted 2026-09-15
Published 2026-10-18

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