Your browser doesn't support javascript.
loading
Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan.
Yousaf, Muhammad; Zahir, Samiha; Riaz, Muhammad; Hussain, Sardar Muhammad; Shah, Kamal.
Afiliação
  • Yousaf M; Department of Statistics, Quaid-i-Azam University Islamabad 45320, Pakistan.
  • Zahir S; Department of Statistics, Quaid-i-Azam University Islamabad 45320, Pakistan.
  • Riaz M; Department of Statistics, Quaid-i-Azam University Islamabad 45320, Pakistan.
  • Hussain SM; Department of Mathematical Sciences, Balochistan University of Information Technology, Engineering and Management Sciences (BUITEMS), Quetta 87300, Pakistan.
  • Shah K; Department of Mathematics, University of Malakand, Chakdara Dir (L), KPK, Pakistan.
Chaos Solitons Fractals ; 138: 109926, 2020 Sep.
Article em En | MEDLINE | ID: mdl-32501377
ABSTRACT
In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) - Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Auto-Regressive Integrated Moving Average Model (ARIMA). The fitted forecasting models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan. Based on our model prediction the number of confirmed cases will be increased by 2.7 times, 95% prediction interval for the number of cases at the end of May 2020 = (5681 to 33079). There could be up to 500 deaths, 95% prediction interval = (168 to 885) and there could be eightfold increase in the number of recoveries, 95% prediction interval = (2391 to 16126). The forecasting results of COVID-19 are alarming for May in Pakistan. The health officials and government should adopt new strategies to control the pandemic from further spread until a proper treatment or vaccine is developed.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Chaos Solitons Fractals Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Paquistão

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Chaos Solitons Fractals Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Paquistão