Analysis and Prediction of COVID-19 Pandemic in Pakistan using Time-dependent SIR Model
Muhammad Waqas, Muhammad Farooq, Rashid Ahmad, Ashfaq Ahmad

TL;DR
This paper uses a time-dependent SIR model to analyze and predict the COVID-19 outbreak in Pakistan, providing estimates of peak timing, infection numbers, and the impact of lockdown measures.
Contribution
It applies a time-dependent SIR model to accurately forecast COVID-19 outbreak dynamics in Pakistan, including peak timing and infection estimates.
Findings
Peak expected between late May and 9 June
Infective cases range from 20,000 to 47,000 at peak
Lockdown reduces infective numbers significantly
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…
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Taxonomy
TopicsCOVID-19 epidemiological studies · COVID-19 Pandemic Impacts · COVID-19 diagnosis using AI
