About: Analysis and Prediction of COVID-19 Pandemic in Pakistan using Time-dependent SIR Model

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Analysis and Prediction of COVID-19 Pandemic in Pakistan using Time-dependent SIR Model
Creator	Farooq, Muhammad Waqas, Muhammad Ahmad, Ashfaq Ahmad, Rashid
Source	ArXiv
abstract	The current outbreak is known as Coronavirus Disease or COVID-19 caused by the virus SAR-COV-2 which continues to wreak havoc across the globe. The World Health Organization (WHO) has declared the outbreak a Public Health Emergency of International Concern. In Pakistan, the spread of the virus is on the rise with the number of infected people and causalities rapidly increasing. In the absence of proper vaccination and treatment, to reduce the number of infections and casualties, the only option so far is to educate people regarding preventive measures and to enforce countrywide lock-down. Any strategy about the preventive measures needs to be based upon detailed analysis of the COVID-19 outbreak and accurate scientific predictions. In this paper, we conduct mathematical and numerical analysis to come up with reliable and accurate predictions of the outbreak in Pakistan. The time-dependent Susceptible-Infected-Recovered (SIR) model is used to fit the data and provide future predictions. The turning point of the peak of the pandemic is defined as the day when the transmission rate becomes less than the recovering rate. We have predicted that the outbreak will reach its maximum peak occurring from late May to 9 June with unrecovered number of Infectives in the range 20000-47000 and the cumulative number of infected cases in the range of 57500-153100. The number of Infectives will remain at the lower end in the lock-down scenario but can rapidly double or triple if the spread of the epidemic is not curtailed and localized. The uncertainty on single day projection in our analysis after April 15 is found to be within 5/%.
has issue date	2020-05-05(xsd:dateTime)
has license	arxiv
sha1sum (hex)	b98364ed9cb505e44d8cff50fe29f0287458cf9e
resource representing a document's title	Analysis and Prediction of COVID-19 Pandemic in Pakistan using Time-dependent SIR Model
resource representing a document's body	covid:b98364ed9cb505e44d8cff50fe29f0287458cf9e#body_text
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