Authors | Massoud Sokouti-Ramin Sadeghi-Saeid Pashazadeh-Saeid Eslami-Mohsen Sokouti-Morteza Ghojazadeh-Babak Sokouti |
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Journal | Archives of Medical Research |
Presented by | University of Tabriz |
Page number | 458-463 |
Serial number | 5 |
Volume number | 51 |
Paper Type | Full Paper |
Published At | 2020-06-19 |
Journal Grade | ISI (WOS) |
Journal Type | Typographic |
Journal Country | United States |
Abstract
COVID-19 is a novel coronavirus that was reported by the world health organization in late December 2019. As an unexplained respiratory disease epidemic, which is similar to respiratory syndrome coronavirus SARS-CoV, it rapidly spread all over the world. The study aims to compare several parameters of COVID-19 and SARS-CoV infectious diseases in terms of incidence, mortality, and recovery rates. The publicly available dataset Worldometer (extracted on April 5, 2020) confirmed by WHO report was available for meta-analysis purposes using the Meta-MUMS tool. And, the reported outcomes of the analysis used a random-effects model to evaluate the event rate, and risk ratios thorough subgroup analysis forest plots. Seventeen countries for COVID-19 and eight countries of SARS infections, including COVID-19 group n = 1124243, and SARS-CoV group n = 8346, were analyzed. In this meta-analysis, a random effect model of relations of incidence, mortality, and recovery rates of COVID-19 and SARS world infections were determined. The meta-analysis and forest plots of two viral world infections showed that the incidence rate of COVID-19 infection is more than SARS infections, while recovery and mortality event rates of SARS-CoV are more than COVID-19 infection. And subgroup analysis showed that the mortality and recovery rates were higher in both SARS-CoV wand COVID-19 in comparison to incidence and mortality rates, respectively. In conclusion, the meta-analysis approach on the abovementioned dataset revealed the epidemiological and statistical analyses for comparing COVID-19 and SARS-CoV outbreaks.
tags: COVID-19, SARS-CoV, Meta-analysis, Meta-MUMS, Epidemiology