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Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models

In this paper, we present various growth models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in fitting and evaluating the COVID-19 epidemic pattern as of 15 July 2020 in the form of the total number of SARS-...

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Main Authors: Yahuza, Salihu, Sabo, Ibrahim Alhaji, Dan-Iya, Bilal Ibrahim, Abd. Shukor, Mohd Yunus
Format: Article
Language:English
Published: Hibiscus 2020
Online Access:http://psasir.upm.edu.my/id/eprint/87242/1/Prediction%20of%20cumulative%20death%20cases%20in%20Nigeria%20due%20to%20COVID.pdf
http://psasir.upm.edu.my/id/eprint/87242/
https://journal.hibiscuspublisher.com/index.php/BESSM/article/view/528
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spelling my.upm.eprints.872422022-01-20T08:46:59Z http://psasir.upm.edu.my/id/eprint/87242/ Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models Yahuza, Salihu Sabo, Ibrahim Alhaji Dan-Iya, Bilal Ibrahim Abd. Shukor, Mohd Yunus In this paper, we present various growth models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in fitting and evaluating the COVID-19 epidemic pattern as of 15 July 2020 in the form of the total number of SARS-CoV-2 deaths in Nigeria. The MMF model was found to be the best model having the highest adjusted R2 value and lowest RMSE value. The values for the Accuracy and Bias Factors were near unity (1.0). The parameters derived from the MMF model include maximum growth rate (log) of 0.02 (95% CI from 0.02 to 0.03), curve constant (d) that affects the infection point of 1.61 (95% CI from 1.42 to 1.79) and maximal total number of death cases (Ymax) of 1,717 (95% CI from 1,428 to 2,123). The model estimated that the total number of death cases for Nigeria on the coming 15th of August and 15th of September 2020 were 940 (95% CI of 847 to 1,043) and 1,101 (95% CI of 968 to 1,252), respectively. The predictive ability of the model employed in this study is a powerful tool for epidemiologist to monitor and assess the severity of COVID-19 in Nigeria in months to come. However, like any other model, these values need to be taken with caution because of the COVID-19 uncertainty situation locally and globally. Hibiscus 2020-07-31 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87242/1/Prediction%20of%20cumulative%20death%20cases%20in%20Nigeria%20due%20to%20COVID.pdf Yahuza, Salihu and Sabo, Ibrahim Alhaji and Dan-Iya, Bilal Ibrahim and Abd. Shukor, Mohd Yunus (2020) Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models. Bulletin of Environmental Science & Sustainable Management, 4 (1). 20 - 24. ISSN 2716-5353 https://journal.hibiscuspublisher.com/index.php/BESSM/article/view/528 10.54987/bessm.v4i1.528
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In this paper, we present various growth models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in fitting and evaluating the COVID-19 epidemic pattern as of 15 July 2020 in the form of the total number of SARS-CoV-2 deaths in Nigeria. The MMF model was found to be the best model having the highest adjusted R2 value and lowest RMSE value. The values for the Accuracy and Bias Factors were near unity (1.0). The parameters derived from the MMF model include maximum growth rate (log) of 0.02 (95% CI from 0.02 to 0.03), curve constant (d) that affects the infection point of 1.61 (95% CI from 1.42 to 1.79) and maximal total number of death cases (Ymax) of 1,717 (95% CI from 1,428 to 2,123). The model estimated that the total number of death cases for Nigeria on the coming 15th of August and 15th of September 2020 were 940 (95% CI of 847 to 1,043) and 1,101 (95% CI of 968 to 1,252), respectively. The predictive ability of the model employed in this study is a powerful tool for epidemiologist to monitor and assess the severity of COVID-19 in Nigeria in months to come. However, like any other model, these values need to be taken with caution because of the COVID-19 uncertainty situation locally and globally.
format Article
author Yahuza, Salihu
Sabo, Ibrahim Alhaji
Dan-Iya, Bilal Ibrahim
Abd. Shukor, Mohd Yunus
spellingShingle Yahuza, Salihu
Sabo, Ibrahim Alhaji
Dan-Iya, Bilal Ibrahim
Abd. Shukor, Mohd Yunus
Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
author_facet Yahuza, Salihu
Sabo, Ibrahim Alhaji
Dan-Iya, Bilal Ibrahim
Abd. Shukor, Mohd Yunus
author_sort Yahuza, Salihu
title Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
title_short Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
title_full Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
title_fullStr Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
title_full_unstemmed Prediction of cumulative death cases in Nigeria due to COVID-19 using mathematical models
title_sort prediction of cumulative death cases in nigeria due to covid-19 using mathematical models
publisher Hibiscus
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/87242/1/Prediction%20of%20cumulative%20death%20cases%20in%20Nigeria%20due%20to%20COVID.pdf
http://psasir.upm.edu.my/id/eprint/87242/
https://journal.hibiscuspublisher.com/index.php/BESSM/article/view/528
_version_ 1724075498794909696
score 13.211869

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