Research Article - Journal of RNA and Genomics (2021) Volume 0, Issue 0

Regression Models for Predictions of COVID-19 New Cases and New Deaths Based on May/June Data in Ethiopia

Background: As of 15 June 2020, we have 7,984,067 total COVID-19 cases, globally and 435,181 total deaths. Ethiopia was ranked 2nd and 15th in the table by 176 new cases and by 3,521 total new cases from African countries.

Objectives: This study aimed to predict COVID-19 new cases and new deaths based on May/June data in Ethiopia using the regression model.

Methods: In this study, I used Pearson’s correlation analysis and the linear regression model to predict COVID-19 new cases and new deaths based on the available data from 12th May to 10th June 2020 in Ethiopia.

Results: There was a significant positive correlation between COVID-19 new cases and new deaths with different related variables. In the regression models, the simple linear regression model was a better fit for the data of COVID-19 new cases and new deaths than as compared with quadratic and cubic regression models. In the multiple linear regression models, variables such as the number of days, the number of new laboratory tests, and the number of new cases from AA city significantly predicted the COVID-19 new cases. In this model, the number of days and new recoveries significantly predicted new deaths of COVID-19. The number of days, daily laboratory tests, and new cases from Addis Ababa city significantly predicted new COVID-19 cases, and the number of days and new recoveries significantly predicted new deaths from COVID-19.

Discussion: Ethiopian government, Ministry of Health, and Addis Ababa city administrative should give more awareness and protections for societies, and they should open again more COVID-19 laboratory testing centers.

Author(s): Alemayehu Argawu

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