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Novel COVID-19 Mortality Rate Prediction (MRP) Model for India Using Regression Model With Optimized Hyperparameter

Novel COVID-19 Mortality Rate Prediction (MRP) Model for India Using Regression Model With Optimized Hyperparameter
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Author(s): Dhamodharavadhani S. (Periyar University, Salem, India) and R. Rathipriya (Periyar University, Salem, India)
Copyright: 2021
Volume: 23
Issue: 4
Pages: 12
Source title: Journal of Cases on Information Technology (JCIT)
Editor(s)-in-Chief: Andrew Borchers (Lipscomb University, USA)
DOI: 10.4018/JCIT.20211001.oa1

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Abstract

The main objective of this study is to estimate the future COVID-19 mortality rate for India using COVID-19 mortality rate models from different countries. Here, the regression method with the optimal hyperparameter is used to build these models. In the literature, numerous mortality models for infectious diseases have been proposed, most of which predict future mortality by extending one or more disease-related attributes or parameters. But most of these models predict mortality rates from historical data. In this paper, the Gaussian process regression model with the optimal hyperparameter is used to develop the COVID-19 mortality rate prediction (MRP) model. Five different MRP models have been built for the U.S., Italy, Germany, Japan, and India. The results show that Germany has the lowest death rate in 2000 plus COVID-19 confirmed cases. Therefore, if India follows the strategy pursued by Germany, India will control the COVID-19 mortality rate even in the increase of confirmed cases.

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