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-...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hibiscus
2020
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/87242/ http://psasir.upm.edu.my/id/eprint/87242/1/Prediction%20of%20cumulative%20death%20cases%20in%20Nigeria%20due%20to%20COVID.pdf |
| _version_ | 1848860396616679424 |
|---|---|
| author | Yahuza, Salihu Sabo, Ibrahim Alhaji Dan-Iya, Bilal Ibrahim Abd. Shukor, Mohd Yunus |
| author_facet | Yahuza, Salihu Sabo, Ibrahim Alhaji Dan-Iya, Bilal Ibrahim Abd. Shukor, Mohd Yunus |
| author_sort | Yahuza, Salihu |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T12:44:34Z |
| format | Article |
| id | upm-87242 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:44:34Z |
| publishDate | 2020 |
| publisher | Hibiscus |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/87242/ http://psasir.upm.edu.my/id/eprint/87242/ http://psasir.upm.edu.my/id/eprint/87242/ http://psasir.upm.edu.my/id/eprint/87242/1/Prediction%20of%20cumulative%20death%20cases%20in%20Nigeria%20due%20to%20COVID.pdf |