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Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan
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 f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247520/ https://www.ncbi.nlm.nih.gov/pubmed/32501377 http://dx.doi.org/10.1016/j.chaos.2020.109926 |
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author | Yousaf, Muhammad Zahir, Samiha Riaz, Muhammad Hussain, Sardar Muhammad Shah, Kamal |
author_facet | Yousaf, Muhammad Zahir, Samiha Riaz, Muhammad Hussain, Sardar Muhammad Shah, Kamal |
author_sort | Yousaf, Muhammad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7247520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72475202020-05-26 Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan Yousaf, Muhammad Zahir, Samiha Riaz, Muhammad Hussain, Sardar Muhammad Shah, Kamal Chaos Solitons Fractals Article 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. Elsevier Ltd. 2020-09 2020-05-25 /pmc/articles/PMC7247520/ /pubmed/32501377 http://dx.doi.org/10.1016/j.chaos.2020.109926 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Yousaf, Muhammad Zahir, Samiha Riaz, Muhammad Hussain, Sardar Muhammad Shah, Kamal Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title | Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title_full | Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title_fullStr | Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title_full_unstemmed | Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title_short | Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan |
title_sort | statistical analysis of forecasting covid-19 for upcoming month in pakistan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247520/ https://www.ncbi.nlm.nih.gov/pubmed/32501377 http://dx.doi.org/10.1016/j.chaos.2020.109926 |
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