COVID-19 Pandemic Data Modeling in Pakistan Using Time-Series SIR

Abstract

Pakistan is currently facing the fourth wave of the deadly coronavirus, which was first reported in Wuhan, China, in December 2019. This work utilizes the epidemiological models to analyze Pakistan’s COVID-19 data. The basic susceptible, infected, and recovered (SIR) model is studied assuming Bayesian and time-series SIR (tSIR) approaches. Many studies have been conducted from different perspectives, but to the best of our knowledge, no study is available using the SIR models for Pakistan. The coronavirus incubation period has been set to 14 days across the globe; however, this study noticed that the assumption of 14 days is not suitable for Pakistan’s data. Furthermore, on the basis of R 0 , we infer that COVID-19 is not a pandemic in Pakistan, as it was in other nations, such as the United States, India, Brazil, and Italy, among others. We attribute this to the best strategy adopted by the Government of Pakistan to minimize the burden of COVID-19 cases in Pakistani hospitals. It is also noticed that the posterior-based SIR (pSIR) model with uniform prior to R 0 and Poisson distribution (of log-likelihood) provides better results as compared to other distributions. From time-series SIR (tSIR), we observed that the value of the reporting rate ρ is less than 1 which means that cases are underreported.

Predicting COVID-19 Pandemic Endpoint in Some Sub-Saharan African and European Countries

“…This study has a number of limitations, for instance, we avoided social distancing and the use of machine learning. Bayesian analysis as in Taimoor et al [8] with SIR model would be considered in our modified paper to determine the endpoints of contagious diseases.…”

“…Several researchers have adopted an individual-level strategy that looks for the overall average equilibrium [5][6][7], where individuals may choose their contact rate and are motivated by various initiatives to compare the overall average equilibrium to a socially optimum approach. Additionally, data-based strategies like those in [8][9][10][11] have offered intriguing insights into the effectiveness of stay-athome directives and target lock downs. Further theoretical research on COVID-19 [12][13][14][15][16][17] has indeed been helpful in understanding the dynamics of transmission and the potential role of various effective interventions, like mitigation and suppression to slow down the epidemic's spread, the demand for health precautions to maintain those who are prone to various risks from infections, the number of infective cases to the low level, enforcing lockdown on regions of highly infective cases, home isolation of suspected cases, and home quarantine.…”

Race Against the Clock: On the Transmission Dynamics of COVID-19 in Africa [Letter]

“…3 The R 0 reported for Pakistan was approximately 1.05. 4 Lessons that can be learned from Pakistan’s response to the pandemic include full as well as smart lockdowns, awareness campaigns, quarantines and contact-tracing, and organization of screening camps with mass-testing. 4 …”

“…3 The R 0 reported for Pakistan was approximately 1.05. 4 Lessons that can be learned from Pakistan's response to the pandemic include full as well as smart lockdowns, awareness campaigns, quarantines and contact-tracing, and organization of screening camps with mass-testing. 4 The authors informed that host defense response against the virus is influenced by vaccination against SARS-CoV-2, presence of co-morbids, age, and previous infection.…”

“…4 Lessons that can be learned from Pakistan's response to the pandemic include full as well as smart lockdowns, awareness campaigns, quarantines and contact-tracing, and organization of screening camps with mass-testing. 4 The authors informed that host defense response against the virus is influenced by vaccination against SARS-CoV-2, presence of co-morbids, age, and previous infection. Moreover, nutritional status is also a major factor of the host's immune response, more importantly since African nations are poverty-stricken.In the SIMCR model, the authors have considered the susceptible and the infected groups.…”