Nithish Ragav, N (2021) Mathematical Models for Predicting Covid-19 Pandemic: A Review. Journal of Physics: Conference Series, 1797 (1). 012009. ISSN 1742-6588
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Abstract
The catastrophic outbreak of the Novel Corona virus (Covid-19) has brought to light, the significance of reliable predictive mathematical models. The results from such models greatly affect the use of non-pharmaceutical intervention measures, management of medical resources and understanding risk factors. This paper compares popular mathematical models based on their predictive capabilities, practical validity, presumptions and drawbacks. The paper focuses on popular techniques in use for the predictive modeling of the Covid-19 epidemic. The paper covers the Gaussian Model, SIRD, SEIRD and the latest θ-SEIHRD techniques used for predictive modeling of epidemics.
Item Type: | Article |
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Subjects: | C Computer Science and Engineering > Data Mining |
Divisions: | Electrical and Electronics Engineering |
Depositing User: | Users 5 not found. |
Date Deposited: | 23 Apr 2024 09:30 |
Last Modified: | 23 Apr 2024 09:30 |
URI: | https://ir.psgitech.ac.in/id/eprint/408 |