EXPLORING COVID-19 PANDEMIC INITIAL 2020 CURVE BASED ON STATISTICAL EVALUATION

Ibrar ul Hassan Akhtar ()
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Ibrar ul Hassan Akhtar: Department of Meteorology, COMSATS University Islamabad, Park Road, Tarlai Kalan, Islamabad 45550, Pakistan.

Acta Scientifica Malaysia (ASM), 2023, vol. 7, issue 1, 08-16

Abstract: This research was to explore CoVID-19 at initial stage of 2020 based on statistical techniques using probability density function (PDF), with different statistical measures, polynomial data fitting along with 30 day projections. The Covid-19 analysis was carried out only for highly affected countries along with six different regions and global level for 64 days covering period of January to March during 2020. It was found that infection and recovery rate for cases were ranged from 0 ‒ 9.89 and 0 ‒ 8.89% at global level, respectively. The PDF was observed highly positive skewed, leptokurtic, for confirmed cases representing 6620 daily mean infected population for confirmed cases. Countries of USA, Chinas, Spain, France, Italy, Iran, UK and Switzerland were eexpected to be most affected countries with minimum 0.100 million infected population. The projection errors for infection rate remained -78.8 to 49.0%. The curve of CoVID-19 and PDF (skewness and kurtosis) measures provided understanding of data shape and peak height.

Keywords: COVID-19; Time Series Analysis, Statistical Inferences, Public Health, Modeling (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnasm:v:7:y:2023:i:1:p:08-16

DOI: 10.26480/asm.01.2023.08.16

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