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Geographic Distribution of Excess Mortality Rate duo to COVID-19 in Iranian Population: An Ecological Study
Publication year - 2021
Publication title -
iranian red crescent medical journal
Language(s) - English
Resource type - Journals
ISSN - 2074-1804
DOI - 10.32592/ircmj.2021.23.11.1208
Subject(s) - covid-19 , demography , china , geography , pandemic , distribution (mathematics) , mortality rate , ecological study , population , medicine , socioeconomics , environmental health , outbreak , disease , virology , mathematical analysis , mathematics , archaeology , sociology , infectious disease (medical specialty)
COVID-19 has raised world concern since it emerged in Wuhan, China in December 2019. The direct and indirect death rates in the world and in Iran have increased significantly after the occurrence of this pandemic in the world.Objective: In this study EMR estimated by Multilevel Poison Regression then this estimation compared to the historical trends, to obtain total death related to the COVID-19 in addtion the geographic distribution of EMR has been presented for Iran country.Materials and Methods: All-cause mortality count of each province of Iran from March 21, 2013 to June 20, 2020 downloaded from National Organizationfor Civil Registration (NOCR). The data from spring of 2020 (March 20, 2020 to June 20, 2020) remove from data and then the multilevel poison model has been used to estimate all-cause mortality in spring 2020 then excess mortality attributable to COVID-19 (the difference between the numberof registered and expected deaths) has been calculated.Results: The results of this study showed that Iran’s EMR in spring 2020 was 23% (Male=25%, Female=21%). More result also showed that four category low (EMR≤5%, n=3), moderate (5 %< EMR<20%, n=10), high (20 %< EMR<40%, n=16) and very high (40≤EMR, n=2) EMR.Conclusion: Due to the diverse EMR in different provinces of Iran, the type of management of provinces with low and moderate EMR can be used as a suitable model to control EMR in provinces with high and very high EMR.

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