Trend Analysis and Predictions of Coronavirus Disease 2019 in Ethiopia.


Journal

Journal of research in health sciences
ISSN: 2228-7809
Titre abrégé: J Res Health Sci
Pays: Iran
ID NLM: 101480094

Informations de publication

Date de publication:
12 Aug 2021
Historique:
received: 10 06 2021
accepted: 06 08 2021
revised: 06 08 2021
entrez: 26 10 2021
pubmed: 27 10 2021
medline: 29 10 2021
Statut: epublish

Résumé

Coronavirus Disease 2019 (COVID-19) is affecting both lives of millions of people and the global economy of the world day by day. This study aimed to determine the trend of COVID-19 and its predictions in Ethiopia. This study was conducted based on a time series design. The required data were collected from the Ethiopian COVID-19 monitoring platform beginning from the onset of the disease in the country until March 28, 2021. Furthermore, the auto-regressive integrated moving average models were used on daily-based time series. The Poisson and Negative Binomial regression were also employed to notice the effects of months on the transmission and disease-related human deaths. The mean daily infection and death of COVID-19 in Ethiopia were 533.47±466.62 and 7.45±6.72, respectively. The peaks of infection and deaths in this country were in March, 2021, and August, 2020. In addition, the trend of daily new deaths (P=0.000) and infection (P=0.000) was significantly increasing. It is expected that around 10 million (8.6%) and 138,084.64 (0.12%) Ethiopians will be infected and die, respectively. The disease transmission and deaths vary from day to day and month to month. The highest peaks of COVID-19 infection and death were in March 2021 and August 2020. For the next end of August 2021, the COVID-19 daily new infection, new death, total case, and total death are expected to be increased. If this epidemic disease is not controlled, Ethiopia will face a severe shortage of hospitals, and the outbreak even becomes worse.

Sections du résumé

BACKGROUND BACKGROUND
Coronavirus Disease 2019 (COVID-19) is affecting both lives of millions of people and the global economy of the world day by day. This study aimed to determine the trend of COVID-19 and its predictions in Ethiopia.
STUDY DESIGN METHODS
This study was conducted based on a time series design.
METHODS METHODS
The required data were collected from the Ethiopian COVID-19 monitoring platform beginning from the onset of the disease in the country until March 28, 2021. Furthermore, the auto-regressive integrated moving average models were used on daily-based time series. The Poisson and Negative Binomial regression were also employed to notice the effects of months on the transmission and disease-related human deaths.
RESULTS RESULTS
The mean daily infection and death of COVID-19 in Ethiopia were 533.47±466.62 and 7.45±6.72, respectively. The peaks of infection and deaths in this country were in March, 2021, and August, 2020. In addition, the trend of daily new deaths (P=0.000) and infection (P=0.000) was significantly increasing. It is expected that around 10 million (8.6%) and 138,084.64 (0.12%) Ethiopians will be infected and die, respectively.
CONCLUSION CONCLUSIONS
The disease transmission and deaths vary from day to day and month to month. The highest peaks of COVID-19 infection and death were in March 2021 and August 2020. For the next end of August 2021, the COVID-19 daily new infection, new death, total case, and total death are expected to be increased. If this epidemic disease is not controlled, Ethiopia will face a severe shortage of hospitals, and the outbreak even becomes worse.

Identifiants

pubmed: 34698657
pii: 6945
doi: 10.34172/jrhs.2021.59
pmc: PMC8957680
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e00523

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Auteurs

Abiyot Negash Terefe (AN)

Jimma University, College of Natural Sciences, Department of Statistics, Jimma, Oromia, Ethiopia. abiyotnegash@yahoo.com.

Samuel Getachew Zewudie (SG)

Mizan-Tepi University, College of Natural and Computational Sciences, Department of Biology, Tepi, Ethiopia.

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Classifications MeSH