Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India
The global explosion of the COVID-19 pandemic has created worldwide unprecedented health and economic challenges which stimulated one of the biggest annual migrations globally. In the Indian context, even after proactive decisions taken by the Government, the continual growth of COVID-19 raises ques...
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| Format: | Article |
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MDPI AG
2021-01-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/2/127 |
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| author | Himanshu Gupta Saurav Kumar Drishti Yadav Om Prakash Verma Tarun Kumar Sharma Chang Wook Ahn Jong-Hyun Lee |
| author_facet | Himanshu Gupta Saurav Kumar Drishti Yadav Om Prakash Verma Tarun Kumar Sharma Chang Wook Ahn Jong-Hyun Lee |
| author_sort | Himanshu Gupta |
| collection | DOAJ |
| description | The global explosion of the COVID-19 pandemic has created worldwide unprecedented health and economic challenges which stimulated one of the biggest annual migrations globally. In the Indian context, even after proactive decisions taken by the Government, the continual growth of COVID-19 raises questions regarding its extent and severity. The present work utilizes the susceptible-infected-recovered-death (SIRD) compartment model for parameter estimation and fruitful prediction of COVID-19. Further, various optimization techniques such as particle swarm optimization (PSO), gradient (G), pattern search (PS) and their hybrid are employed to solve the considered model. The simulation study endorse the efficiency of PSO (with or without G) and G+PS+G over other techniques for ongoing pandemic assessment. The key parametric values including characteristic time of infection and death and reproduction number have been estimated as 60 days, 67 days and 4.78 respectively by utilizing the optimum results. The model assessed that India has passed its peak duration of COVID-19 with more than 81% recovery and only a 1.59% death rate. The short duration analysis (15 days) of obtained results against reported data validates the effectiveness of the developed models for ongoing pandemic assessment. |
| first_indexed | 2024-03-09T05:31:38Z |
| format | Article |
| id | doaj.art-bb899c135a58474a83b27b70cfdddfba |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T05:31:38Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-bb899c135a58474a83b27b70cfdddfba2023-12-03T12:32:27ZengMDPI AGElectronics2079-92922021-01-0110212710.3390/electronics10020127Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of IndiaHimanshu Gupta0Saurav Kumar1Drishti Yadav2Om Prakash Verma3Tarun Kumar Sharma4Chang Wook Ahn5Jong-Hyun Lee6Department of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Jalandhar 144011, IndiaDepartment of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Jalandhar 144011, IndiaDepartment of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Jalandhar 144011, IndiaDepartment of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Jalandhar 144011, IndiaDepartment of Computer Science and Engineering, Shobhit University Gangoh, Saharanpur 247341, IndiaAI Graduate School, Gwangju Institute of Science and Technology, Gwangju 61005, KoreaResearch Center for Convergence, Sungkyunkwan University, Suwon 16419, KoreaThe global explosion of the COVID-19 pandemic has created worldwide unprecedented health and economic challenges which stimulated one of the biggest annual migrations globally. In the Indian context, even after proactive decisions taken by the Government, the continual growth of COVID-19 raises questions regarding its extent and severity. The present work utilizes the susceptible-infected-recovered-death (SIRD) compartment model for parameter estimation and fruitful prediction of COVID-19. Further, various optimization techniques such as particle swarm optimization (PSO), gradient (G), pattern search (PS) and their hybrid are employed to solve the considered model. The simulation study endorse the efficiency of PSO (with or without G) and G+PS+G over other techniques for ongoing pandemic assessment. The key parametric values including characteristic time of infection and death and reproduction number have been estimated as 60 days, 67 days and 4.78 respectively by utilizing the optimum results. The model assessed that India has passed its peak duration of COVID-19 with more than 81% recovery and only a 1.59% death rate. The short duration analysis (15 days) of obtained results against reported data validates the effectiveness of the developed models for ongoing pandemic assessment.https://www.mdpi.com/2079-9292/10/2/127COVID-19compartment modelingepidemiologypredictive modelingoptimizationparticle swarm optimization |
| spellingShingle | Himanshu Gupta Saurav Kumar Drishti Yadav Om Prakash Verma Tarun Kumar Sharma Chang Wook Ahn Jong-Hyun Lee Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India Electronics COVID-19 compartment modeling epidemiology predictive modeling optimization particle swarm optimization |
| title | Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India |
| title_full | Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India |
| title_fullStr | Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India |
| title_full_unstemmed | Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India |
| title_short | Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic—A Case Study of India |
| title_sort | data analytics and mathematical modeling for simulating the dynamics of covid 19 epidemic a case study of india |
| topic | COVID-19 compartment modeling epidemiology predictive modeling optimization particle swarm optimization |
| url | https://www.mdpi.com/2079-9292/10/2/127 |
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