Article: Modelling and forecasting of new cases, deaths and recover cases of COVID-19 by using Vector Autoregressive model in Pakistan.
2020 Volume 140, Page(s) 110189
Abstract: ... cases, deaths and recover cases for ten days. Our forecasted model results show maximum of 5,363/day new ... total deaths of 4,118. Vector Autoregressive time series models was used to forecast new daily confirmed ... to human life and economy. Pakistan is also severely effected by COVID-19 with 202,955 confirmed cases and ...
| Abstract | COVID-19 emerged in Wuhan, China in December 2019 has now spread around the world causes damage to human life and economy. Pakistan is also severely effected by COVID-19 with 202,955 confirmed cases and total deaths of 4,118. Vector Autoregressive time series models was used to forecast new daily confirmed cases, deaths and recover cases for ten days. Our forecasted model results show maximum of 5,363/day new cases with 95% confidence interval of 3,013-8,385 on 3rd of July, 167/day deaths with 95% confidence interval of 112-233 and maximum recoveries 4,016/day with 95% confidence interval of 2,182-6,405 in the next 10 days. The findings of this research may help government and other agencies to reshape their strategies according to the forecasted situation. As the data generating process is identified in terms of time series models, then it can be updated with the arrival of new data and provide forecasted scenario in future. |
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| Keywords | covid19 |
| Language | English |
| Publishing date | 2020-08-05 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2003919-0 |
| ISSN | 1873-2887 ; 0960-0779 |
| ISSN (online) | 1873-2887 |
| ISSN | 0960-0779 |
| DOI | 10.1016/j.chaos.2020.110189 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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