Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study
Many countries are suffering from the COVID19 pandemic. The number of confirmed cases, recovered, and deaths are of concern to the countries having a high number of infected patients. Forecasting these parameters is a crucial way to control the spread of the disease and struggle with the pandemic. T...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-06-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022008660 |
| _version_ | 1811335010562605056 |
|---|---|
| author | Souad Larabi-Marie-Sainte Sawsan Alhalawani Sara Shaheen Khaled Mohamad Almustafa Tanzila Saba Fatima Nayer Khan Amjad Rehman |
| author_facet | Souad Larabi-Marie-Sainte Sawsan Alhalawani Sara Shaheen Khaled Mohamad Almustafa Tanzila Saba Fatima Nayer Khan Amjad Rehman |
| author_sort | Souad Larabi-Marie-Sainte |
| collection | DOAJ |
| description | Many countries are suffering from the COVID19 pandemic. The number of confirmed cases, recovered, and deaths are of concern to the countries having a high number of infected patients. Forecasting these parameters is a crucial way to control the spread of the disease and struggle with the pandemic. This study aimed at forecasting the number of cases and deaths in KSA using time-series and well-known statistical forecasting techniques including Exponential Smoothing and Linear Regression. The study is extended to forecast the number of cases in the main countries such that the US, Spain, and Brazil (having a large number of contamination) to validate the proposed models (Drift, SES, Holt, and ETS). The forecast results were validated using four evaluation measures. The results showed that the proposed ETS (resp. Drift) model is efficient to forecast the number of cases (resp. deaths). The comparison study, using the number of cases in KSA, showed that ETS (with RMSE reaching 18.44) outperforms the state-of-the art studies (with RMSE equal to 107.54). The proposed forecasting model can be used as a benchmark to tackle this pandemic in any country. |
| first_indexed | 2024-04-13T17:16:31Z |
| format | Article |
| id | doaj.art-745ba54713ab422a8633582b144056f0 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-13T17:16:31Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-745ba54713ab422a8633582b144056f02022-12-22T02:38:06ZengElsevierHeliyon2405-84402022-06-0186e09578Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case studySouad Larabi-Marie-Sainte0Sawsan Alhalawani1Sara Shaheen2Khaled Mohamad Almustafa3Tanzila Saba4Fatima Nayer Khan5Amjad Rehman6Department of Computer Science, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia; Corresponding author.Department of Computer Science, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaDepartment of Computer Science, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaDepartment of Information Sciences, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaArtificial Intelligence Data Analytics (AIDA) Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 12435, Saudi ArabiaDepartment of Information Sciences, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi ArabiaArtificial Intelligence Data Analytics (AIDA) Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 12435, Saudi ArabiaMany countries are suffering from the COVID19 pandemic. The number of confirmed cases, recovered, and deaths are of concern to the countries having a high number of infected patients. Forecasting these parameters is a crucial way to control the spread of the disease and struggle with the pandemic. This study aimed at forecasting the number of cases and deaths in KSA using time-series and well-known statistical forecasting techniques including Exponential Smoothing and Linear Regression. The study is extended to forecast the number of cases in the main countries such that the US, Spain, and Brazil (having a large number of contamination) to validate the proposed models (Drift, SES, Holt, and ETS). The forecast results were validated using four evaluation measures. The results showed that the proposed ETS (resp. Drift) model is efficient to forecast the number of cases (resp. deaths). The comparison study, using the number of cases in KSA, showed that ETS (with RMSE reaching 18.44) outperforms the state-of-the art studies (with RMSE equal to 107.54). The proposed forecasting model can be used as a benchmark to tackle this pandemic in any country.http://www.sciencedirect.com/science/article/pii/S2405844022008660COVID-19ForecastingDriftExponential smoothingHoltLinear regression |
| spellingShingle | Souad Larabi-Marie-Sainte Sawsan Alhalawani Sara Shaheen Khaled Mohamad Almustafa Tanzila Saba Fatima Nayer Khan Amjad Rehman Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study Heliyon COVID-19 Forecasting Drift Exponential smoothing Holt Linear regression |
| title | Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study |
| title_full | Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study |
| title_fullStr | Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study |
| title_full_unstemmed | Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study |
| title_short | Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study |
| title_sort | forecasting covid19 parameters using time series ksa usa spain and brazil comparative case study |
| topic | COVID-19 Forecasting Drift Exponential smoothing Holt Linear regression |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022008660 |
| work_keys_str_mv | AT souadlarabimariesainte forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT sawsanalhalawani forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT sarashaheen forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT khaledmohamadalmustafa forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT tanzilasaba forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT fatimanayerkhan forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy AT amjadrehman forecastingcovid19parametersusingtimeseriesksausaspainandbrazilcomparativecasestudy |