ArticleComputational and mathematical methods in medicine2022
COVID-19 Pandemic Data Modeling in Pakistan Using Time-Series SIR.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Article
- Antimicrobial Dispensing Practices during COVID-19 and the Implications for Pakistan.Antibiotics (Basel, Switzerland) · 2023Article
- Short-Term Forecasting of Monkeypox Cases Using a Novel Filtering and Combining Technique.Diagnostics (Basel, Switzerland) · 2023Article
- Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases.Frontiers in artificial intelligence · 2023Article
- Race Against the Clock: On the Transmission Dynamics of COVID-19 in Africa [Letter].Clinical epidemiology · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.