COVID-19 Pandemic in Pakistan: Stages and Recommendations
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Abstract
We present a real-time forecast of COVID-19 in Pakistan that is important for decision-making to control the spread of the pandemic in the country. The study helps to develop an accurate plan to eradicate the COVID-19 by taking calculated steps at the appropriate time, that are crucial in the absence of a tested medicine. We use four phenomenological mathematical models, namely Discrete Exponential Growth model, the Discrete Generalized Growth model, the Discrete Generalized Logistic Growth, and Discrete Generalize Richards Growth model. Our analysis explains the important characteristics quantitatively. The study leads to understand COVID-19 pandemic in Pakistan in three evolutionary stages, and provides understanding to control its spread in the short time domain and in the long term domain. For the reason the study is helpful in devising the measures to handle the emerging threat of similar outbreaks in other countries.
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SciScore for 10.1101/2020.05.11.20098004: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2020.05.11.20098004: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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