Khan, Muhammad Danyal (2020) Predictive modeling of COVID-19 death cases in Pakistan. Infectious Disease Modelling, 5. pp. 897-904. ISSN 2468-0427
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Abstract
Abstract
Background
The world is presently facing the challenges posed by COVID-19 (2019-nCoV), especially in the public health sector, and these challenges are dangerous to both health and life. The disease results in an acute respiratory infection that may result in pain and death. In Pakistan, the disease curve shows a vertical trend by almost 256K established cases of the diseases and 6035 documented death cases till August 5, 2020.
Objective
The primary purpose of this study is to provide the statistical model to predict the trend of COVID-19 death cases in Pakistan. The age and gender of COVID-19 victims were represented using a descriptive study.
Method
ology: Three regression models, which include Linear, logarithmic, and quadratic, were employed in this study for the modelling of COVID-19 death cases in Pakistan. These three models were compared based on R2, Adjusted R2, AIC, and BIC criterions. The data utilized for the modelling was obtained from the National Institute of Health of Pakistan from February 26, 2020 to August 5, 2020.
Conclusion
The finding deduced after the prediction modelling is that the rate of mortality would decrease by the end of October. The total number of deaths will reach its maximum point; then, it will gradually decrease. This indicates that the curve of total deaths will continue to be flat, i.e., it will shift to be constant, which is also the upper bound of the underlying function of absolute death.
| Item Type: | Article |
|---|---|
| Additional Information and Comments: | © 2020 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
| Faculty / Department: | Faculty of Business, Law and Criminology > School of Law and Criminology |
| Depositing User: | Danyal Khan |
| Date Deposited: | 02 May 2024 13:14 |
| Last Modified: | 02 May 2024 13:14 |
| URI: | https://hira.hope.ac.uk/id/eprint/4213 |
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