Excess deaths during the COVID-19 pandemic in Iran

Abstract

Background

The actual number of deaths during the COVID-19 pandemic is expected to be higher than the reported deaths. We aimed to estimate the number of deaths in Iran during the COVID-19 pandemic from December 22, 2019 to March 20, 2022.

Methods

We compared the number of age- and sex-specific deaths reported by Iran’s Bureau of Vital Statistics with the predicted deaths estimated using an improved Lee-Carter model. We estimated the number of all-cause excess deaths in three scenarios, including the baseline scenario (without any undercounting of deaths) and 4% and 8% undercounting of all-cause deaths.

Results

We estimated 282,378 (95% confidence intervals [CI]: 225,439; 341,951) excess deaths in the baseline model. This number was 303,148 (95% CI: 246,417; 357,823) and 308,486 (95% CI: 250,607; 364,417) in the 4% and 8% scenarios, respectively. During the same period, Iran reported 139,610 deaths as being directly related to COVID-19. The ratio of reported COVID-19 deaths to total excess deaths ranged from 45.2% to 49.4% in the various scenarios. Most excess deaths occurred in the baseline scenario in males (157,552 [95% CI: 125,142; 191,265]) and those aged ≥75 years (102,369 [95% CI: 93,894; 111,188]).

Conclusions

The reported number of COVID-19 deaths was less than half of Iran’s estimated number of excess deaths. The results of this study will be helpful for health policymakers’ planning, and call for strengthening the timeliness and accuracy of Iran’s death registration systems, planning for more accurate monitoring of epidemics, and planning to provide support services for survivors’ families.

Keywords:

• COVID-19
• excess death
• Lee-Carter model
• Iran

Ethical issues

The proposal of the present study was approved by the ethics committee of Kerman University of Medical Sciences, Kerman, Iran (reference 98001239). The Ethical approval code is IR.KMU.REC.1398.735.

Disclosure statement

The authors declare no conflict of interest, real or perceived.

Additional information

Funding

This work was supported by the International COVID-19 Modelling (CoMo) Consortium. The CoMo Consortium was supported by the Oxford University COVID-19 Research Response Fund (ref: 0009280). Lisa White is funded by the Li Ka Shing Foundation. Mohammad Karamouzian is supported by a Banting Postdoctoral Fellowship.