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Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators
The coronavirus (COVID-19) disease outbreak was a public health emergency of international concern which eventually evolved into a pandemic. Nigeria was locked down in March, 2020 as the country battled to contain the spread of the disease. By August 2020, phase-by-phase easing of the lockdown was c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341373/ https://www.ncbi.nlm.nih.gov/pubmed/34397825 http://dx.doi.org/10.1097/MD.0000000000026776 |
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author | Chigbu, Baptista C. Edikpa, Edith C. Onu, Eucharia A. Nwabueze, Akachukwu I. Aneke, Mary C. Vita-Agundu, Uche C. Adepoju, Esther B. |
author_facet | Chigbu, Baptista C. Edikpa, Edith C. Onu, Eucharia A. Nwabueze, Akachukwu I. Aneke, Mary C. Vita-Agundu, Uche C. Adepoju, Esther B. |
author_sort | Chigbu, Baptista C. |
collection | PubMed |
description | The coronavirus (COVID-19) disease outbreak was a public health emergency of international concern which eventually evolved into a pandemic. Nigeria was locked down in March, 2020 as the country battled to contain the spread of the disease. By August 2020, phase-by-phase easing of the lockdown was commenced and university students will soon return for academic activities. This study undertakes some epidemiological analysis of the Nigerian COVID-19 data to help the government and university administrators make informed decisions on the safety of personnel and students. The COVID-19 data on confirmed cases, deaths, and recovered were obtained from the website of the Nigerian Centre for Disease Control (NCDC) from April 2, 2020 to August 24, 2020. The infection rate, prevalence, ratio, cause-specific death rate, and case recovery rate were used to evaluate the epidemiological characteristics of the pandemic in Nigeria. Exponential smoothing was adopted in modeling the time series data and forecasting the pandemic in Nigeria up to January 31, 2021. The results indicated that the pandemic had infection rate of at most 3 infections per 1 million per day from April to August 2020. The death rate was 5 persons per 1 million during the period of study while recovery rate was 747 persons per 1000 infections. Analysis of forecast data showed steady but gradual decrease in the daily infection rate and death rate and substantial increase in the recovery rate, 975 recoveries per 1000 infections. In general, the epidemiological attributes of the pandemic from the original data and the forecast data indicated optimism in the decrease in the rate of infection and death in the future. Moreover, the infection rate, prevalence and death rate in January 2021 coincided with the predictions based on the analysis. Therefore, the Nigerian government is encouraged to allow universities in the country to reopen while university administrators set up the necessary protocols for strict adherence to safety measures. |
format | Online Article Text |
id | pubmed-8341373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-83413732021-08-07 Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators Chigbu, Baptista C. Edikpa, Edith C. Onu, Eucharia A. Nwabueze, Akachukwu I. Aneke, Mary C. Vita-Agundu, Uche C. Adepoju, Esther B. Medicine (Baltimore) 4900 The coronavirus (COVID-19) disease outbreak was a public health emergency of international concern which eventually evolved into a pandemic. Nigeria was locked down in March, 2020 as the country battled to contain the spread of the disease. By August 2020, phase-by-phase easing of the lockdown was commenced and university students will soon return for academic activities. This study undertakes some epidemiological analysis of the Nigerian COVID-19 data to help the government and university administrators make informed decisions on the safety of personnel and students. The COVID-19 data on confirmed cases, deaths, and recovered were obtained from the website of the Nigerian Centre for Disease Control (NCDC) from April 2, 2020 to August 24, 2020. The infection rate, prevalence, ratio, cause-specific death rate, and case recovery rate were used to evaluate the epidemiological characteristics of the pandemic in Nigeria. Exponential smoothing was adopted in modeling the time series data and forecasting the pandemic in Nigeria up to January 31, 2021. The results indicated that the pandemic had infection rate of at most 3 infections per 1 million per day from April to August 2020. The death rate was 5 persons per 1 million during the period of study while recovery rate was 747 persons per 1000 infections. Analysis of forecast data showed steady but gradual decrease in the daily infection rate and death rate and substantial increase in the recovery rate, 975 recoveries per 1000 infections. In general, the epidemiological attributes of the pandemic from the original data and the forecast data indicated optimism in the decrease in the rate of infection and death in the future. Moreover, the infection rate, prevalence and death rate in January 2021 coincided with the predictions based on the analysis. Therefore, the Nigerian government is encouraged to allow universities in the country to reopen while university administrators set up the necessary protocols for strict adherence to safety measures. Lippincott Williams & Wilkins 2021-08-06 /pmc/articles/PMC8341373/ /pubmed/34397825 http://dx.doi.org/10.1097/MD.0000000000026776 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | 4900 Chigbu, Baptista C. Edikpa, Edith C. Onu, Eucharia A. Nwabueze, Akachukwu I. Aneke, Mary C. Vita-Agundu, Uche C. Adepoju, Esther B. Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title | Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title_full | Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title_fullStr | Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title_full_unstemmed | Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title_short | Analysis and forecasting of confirmed, death, and recovered cases of COVID-19 infections in Nigeria: Implications for university administrators |
title_sort | analysis and forecasting of confirmed, death, and recovered cases of covid-19 infections in nigeria: implications for university administrators |
topic | 4900 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341373/ https://www.ncbi.nlm.nih.gov/pubmed/34397825 http://dx.doi.org/10.1097/MD.0000000000026776 |
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