Evidence map›Paper›PMID 40767191›Full record

ArticleInternational journal of health policy and management2025

All-Cause and Cause-Specific Excess Mortality During the First Two Years of the COVID-19 Pandemic in North-East of Iran: Reiterating the Significance of High-Quality Healthcare Systems.

Seyedeh Vajiheh Kazemian, Maliheh Dadgarmoghaddam, Hamed Tabesh, Amirreza Khajedaluee, Mohammad Khajedaluee

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Article in International journal of health policy and management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Seyedeh Vajiheh KazemianCommunity Medicine Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0003-4580-9463
Maliheh DadgarmoghaddamCommunity Medicine Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0002-4797-8714
Hamed TabeshDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0003-3081-0488
Amirreza KhajedalueeSinus and Surgical Endoscopic Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0002-1314-2337
Mohammad KhajedalueeCommunity Medicine Department, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0001-6275-4455

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExcess mortality provides a comprehensive measure to assess the true impact of the disease on mortality rates. This study aimed to quantify excess mortality attributable to COVID-19 in northeastern Iran during the pandemic period (2020-2022).

methodsThis population-based cross-sectional study utilized population and mortality data extracted from electronic systems linked to Mashhad University of Medical Sciences (MUMS). Data analysis was conducted using R Version 4.3.3. A log-linear model was employed to predict expected deaths during the two-year pandemic period, incorporating predictor variables such as the year of interest, the presence of COVID-19, and the population size for each respective year. Excess deaths were calculated as the difference between the expected and observed mortality. Furthermore, by considering the confirmed deaths directly attributed to COVID-19 and the difference between these and the excess deaths, the number of indirect deaths during the pandemic was determined.

resultsThe total count of recorded deaths from all causes exceeded the expected deaths by 31.15% (6750 cases) in the first year and 44.74% (10 078 cases) in the second year. The excess deaths were 1.48 and 1.79 times greater than the official reports of COVID-19 for the first and second years, respectively. It was also found that men experienced increased rates of excess deaths in each of the two years. Moreover, urban residents experienced higher rates of excess death in the same years. Based on cause-specific excess mortality, following infectious diseases, cardiovascular diseases (CVDs) accounted for the largest proportion of excess deaths in both years of the pandemic.

conclusionThe overall mortality burden during the COVID-19 pandemic exceeded the official reports, highlighting the undercounting of the number of direct effects and emphasizing the significance of indirect effects. These findings underscore the importance of preparedness and organization of healthcare systems prior to a pandemic.

Indexed as

COVID-19MortalityQuality of Health CareAdolescentAdultAgedCause of DeathCross-Sectional StudiesFemaleHumansIranMaleMiddle AgedPandemicsSARS-CoV-2Young AdultAll-Cause Excess DeathsAll-Cause Excess MortalityCause-Specific Excess DeathCause-Specific Excess MortalityCOVID-19 PandemicIran

Identifiers

PMID40767191
PMCPMC12257195

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.