Markovian Random Walk Modeling and Visualization of the Epidemic Spread of COVID-19
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Abstract
The epidemic spread of CoVID-19 has resulted in confirmed cases of viral respiratory illness in more than 1.4 million people around the world as of April 7 th , 2020 [1]. However, different regions have experienced the spread of this disease differently. Here, we develop a Markovian random-walk spatial extension of a quarantine-enhanced SIR model to measure, visualize and forecast the effect of susceptible population density, testing rate, and social distancing and quarantine policies on epidemic spreading. The model is used to simulate the spread of CoVID-19 in the regions of Hubei, China; South Korea; Iran; and Spain. The model allows for evaluating the results of different policies both quantitatively and visually as means of better understanding and controlling the spread of the disease.
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SciScore for 10.1101/2020.04.12.20062927: (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: Thank you for sharing your code and data.
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 rtransp…SciScore for 10.1101/2020.04.12.20062927: (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: Thank you for sharing your code and data.
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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