Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model
Purpose – As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epi...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Emerald Publishing
2025-01-01
|
| Series: | Applied Computing and Informatics |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/ACI-09-2020-0059/full/pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832583464392589312 |
|---|---|
| author | Gopi Battineni Nalini Chintalapudi Francesco Amenta |
| author_facet | Gopi Battineni Nalini Chintalapudi Francesco Amenta |
| author_sort | Gopi Battineni |
| collection | DOAJ |
| description | Purpose – As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epidemic models to predict the disease severity with national wide data. Design/methodology/approach – In this study, the authors considered COVID-19 daily infection data four most COVID-19 affected nations (such as the USA, Brazil, India and Russia) to conduct 60-day forecasting of total infections. To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model. Findings – Results highlighted that by late September, the estimated outbreak can reach 7.56, 4.65, 3.01 and 1.22 million cases in the USA, Brazil, India and Russia, respectively. The authors found some underestimation and overestimation of daily cases, and the linear model of actual vs predicted cases found a p-value (<2.2e-16) lower than the R2 value of 0.995. Originality/value – In this paper, the authors adopted the Fb-Prophet ML model because it can predict the epidemic trend and derive an epidemic curve. |
| format | Article |
| id | doaj-art-3e9a3549dc2b4ec19a9941286ef87346 |
| institution | Kabale University |
| issn | 2634-1964 2210-8327 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Applied Computing and Informatics |
| spelling | doaj-art-3e9a3549dc2b4ec19a9941286ef873462025-01-28T12:19:18ZengEmerald PublishingApplied Computing and Informatics2634-19642210-83272025-01-01211/221110.1108/ACI-09-2020-0059Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning modelGopi Battineni0Nalini Chintalapudi1Francesco Amenta2Telemedicine and Telepharmacy Center, School of Medicinal Products and Health Sciences, University of Camerino, Camerino, ItalyTelemedicine and Telepharmacy Center, School of Medicinal Products and Health Sciences, University of Camerino, Camerino, ItalyTelemedicine and Telepharmacy Center, School of Medicinal Products and Health Sciences, University of Camerino, Camerino, ItalyPurpose – As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epidemic models to predict the disease severity with national wide data. Design/methodology/approach – In this study, the authors considered COVID-19 daily infection data four most COVID-19 affected nations (such as the USA, Brazil, India and Russia) to conduct 60-day forecasting of total infections. To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model. Findings – Results highlighted that by late September, the estimated outbreak can reach 7.56, 4.65, 3.01 and 1.22 million cases in the USA, Brazil, India and Russia, respectively. The authors found some underestimation and overestimation of daily cases, and the linear model of actual vs predicted cases found a p-value (<2.2e-16) lower than the R2 value of 0.995. Originality/value – In this paper, the authors adopted the Fb-Prophet ML model because it can predict the epidemic trend and derive an epidemic curve.https://www.emerald.com/insight/content/doi/10.1108/ACI-09-2020-0059/full/pdfCOVID-19 pandemicWorst-hit nationsInfection ratesFb-ProphetSeasonal modeling |
| spellingShingle | Gopi Battineni Nalini Chintalapudi Francesco Amenta Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model Applied Computing and Informatics COVID-19 pandemic Worst-hit nations Infection rates Fb-Prophet Seasonal modeling |
| title | Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model |
| title_full | Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model |
| title_fullStr | Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model |
| title_full_unstemmed | Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model |
| title_short | Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by Fb-Prophet machine learning model |
| title_sort | forecasting of covid 19 epidemic size in four high hitting nations usa brazil india and russia by fb prophet machine learning model |
| topic | COVID-19 pandemic Worst-hit nations Infection rates Fb-Prophet Seasonal modeling |
| url | https://www.emerald.com/insight/content/doi/10.1108/ACI-09-2020-0059/full/pdf |
| work_keys_str_mv | AT gopibattineni forecastingofcovid19epidemicsizeinfourhighhittingnationsusabrazilindiaandrussiabyfbprophetmachinelearningmodel AT nalinichintalapudi forecastingofcovid19epidemicsizeinfourhighhittingnationsusabrazilindiaandrussiabyfbprophetmachinelearningmodel AT francescoamenta forecastingofcovid19epidemicsizeinfourhighhittingnationsusabrazilindiaandrussiabyfbprophetmachinelearningmodel |