Predicting COVID-19 outbreak in India using modified SIRD model
In this paper, the existing Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiologic process model is modified for forecasting the coronavirus effect in India. The data from India was studied for weekly fatalities, weekly infected, weekly recovered, new cases, infected and recovere...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Applied Mathematics in Science and Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/27690911.2024.2305191 |
| _version_ | 1797333472102055936 |
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| author | Sakshi Shringi Harish Sharma Pushpa Narayan Rathie Jagdish Chand Bansal Atulya Nagar Daya Lal Suthar |
| author_facet | Sakshi Shringi Harish Sharma Pushpa Narayan Rathie Jagdish Chand Bansal Atulya Nagar Daya Lal Suthar |
| author_sort | Sakshi Shringi |
| collection | DOAJ |
| description | In this paper, the existing Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiologic process model is modified for forecasting the coronavirus effect in India. The data from India was studied for weekly fatalities, weekly infected, weekly recovered, new cases, infected and recovered individuals, Reproductive Number [Formula: see text], recovery rate, death rate, and coefficient of transmission from 30 January 2020 to 31 July 2021. SARS Coronavirus 2 (SARS-CoV-2) is the Covid strain that causes Covid sickness (COVID-19), a respiratory ailment that triggered the outbreak of COVID-19 at the beginning of December 2019. We aim to provide a hybrid SIRD model for predicting the COVID-19 outbreak. In the proposed method, to improve the exploration ability of the Grey Wolf Optimizer (GWO) or to avoid stagnation in the swarm, a modified Grey Wolf Optimization Algorithm is used to optimize the initial value of Infected individuals. The modified SIRD model is further applied to get the predicted values. The data is examined on weekly basis to prevent noise. Depending on the fact, that the precise mode of transmission is highly dependent on how and when different precautions such as isolation, confinement, and other preventative measures were implemented, we put together our projections concerning satisfactory speculations based on genuine realities. The experimental results show the various trends observed in the pandemic in terms of number of peaks, increasing trend, decreasing trend, and continuous trend for infected individuals, weekly change in number of cases, weekly deaths, weekly infected, and weekly recoeverd cases of Covid-19. The proposed modified SIRD model could be a valuable tool for assessing the impact of government measures on COVID-19 outbreak. |
| first_indexed | 2024-03-08T08:04:21Z |
| format | Article |
| id | doaj.art-28c270a16afa447bbd346cbaeefcd617 |
| institution | Directory Open Access Journal |
| issn | 2769-0911 |
| language | English |
| last_indexed | 2024-03-08T08:04:21Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Mathematics in Science and Engineering |
| spelling | doaj.art-28c270a16afa447bbd346cbaeefcd6172024-02-02T11:17:40ZengTaylor & Francis GroupApplied Mathematics in Science and Engineering2769-09112024-12-0132110.1080/27690911.2024.2305191Predicting COVID-19 outbreak in India using modified SIRD modelSakshi Shringi0Harish Sharma1Pushpa Narayan Rathie2Jagdish Chand Bansal3Atulya Nagar4Daya Lal Suthar5Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, Rajasthan, IndiaDepartment of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, IndiaDepartment of Statistics, University of Brasilia, Brasilia, BrazilDepartment of Mathematics, South Asian University, New Delhi, IndiaSchool of Mathematics, Computer Science and Engineering, Liverpool Hope University, UKDepartment of Mathematics, Wollo University, Dessie, EthiopiaIn this paper, the existing Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiologic process model is modified for forecasting the coronavirus effect in India. The data from India was studied for weekly fatalities, weekly infected, weekly recovered, new cases, infected and recovered individuals, Reproductive Number [Formula: see text], recovery rate, death rate, and coefficient of transmission from 30 January 2020 to 31 July 2021. SARS Coronavirus 2 (SARS-CoV-2) is the Covid strain that causes Covid sickness (COVID-19), a respiratory ailment that triggered the outbreak of COVID-19 at the beginning of December 2019. We aim to provide a hybrid SIRD model for predicting the COVID-19 outbreak. In the proposed method, to improve the exploration ability of the Grey Wolf Optimizer (GWO) or to avoid stagnation in the swarm, a modified Grey Wolf Optimization Algorithm is used to optimize the initial value of Infected individuals. The modified SIRD model is further applied to get the predicted values. The data is examined on weekly basis to prevent noise. Depending on the fact, that the precise mode of transmission is highly dependent on how and when different precautions such as isolation, confinement, and other preventative measures were implemented, we put together our projections concerning satisfactory speculations based on genuine realities. The experimental results show the various trends observed in the pandemic in terms of number of peaks, increasing trend, decreasing trend, and continuous trend for infected individuals, weekly change in number of cases, weekly deaths, weekly infected, and weekly recoeverd cases of Covid-19. The proposed modified SIRD model could be a valuable tool for assessing the impact of government measures on COVID-19 outbreak.https://www.tandfonline.com/doi/10.1080/27690911.2024.2305191COVID-19epidemiologygrey wolf optimizerreproductive number92-1065K10 |
| spellingShingle | Sakshi Shringi Harish Sharma Pushpa Narayan Rathie Jagdish Chand Bansal Atulya Nagar Daya Lal Suthar Predicting COVID-19 outbreak in India using modified SIRD model Applied Mathematics in Science and Engineering COVID-19 epidemiology grey wolf optimizer reproductive number 92-10 65K10 |
| title | Predicting COVID-19 outbreak in India using modified SIRD model |
| title_full | Predicting COVID-19 outbreak in India using modified SIRD model |
| title_fullStr | Predicting COVID-19 outbreak in India using modified SIRD model |
| title_full_unstemmed | Predicting COVID-19 outbreak in India using modified SIRD model |
| title_short | Predicting COVID-19 outbreak in India using modified SIRD model |
| title_sort | predicting covid 19 outbreak in india using modified sird model |
| topic | COVID-19 epidemiology grey wolf optimizer reproductive number 92-10 65K10 |
| url | https://www.tandfonline.com/doi/10.1080/27690911.2024.2305191 |
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