Infection Dynamics of Coronavirus Disease 2019 (Covid-19) Modeled with the Integration of the Eyring’s Rate Process Theory and Free Volume Concept
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Abstract
The Eyring’s rate process theory and free volume concept, two very popular theories in chemistry and physics fields, are employed to treat infectious disease transmissions. The susceptible individuals are assumed to move stochastically from one place to another. The virus particle transmission rate is assumed to obey the Eyring’s rate process theory and also controlled by how much free volume available in a system. The transmission process is considered to be a sequential chemical reaction, and the concentrations or fractions of four epidemiological compartments, the susceptible, the exposed, the infected, and the removed, can be derived and calculated. The obtained equations show that the basic reproduction number, R 0 , is not a constant, dependent on the volume fraction of virus particles, virus particle size, and virus particle packing structure, the energy barrier associated with susceptible individuals, and environment temperature. The developed models are applied to treat coronavirus disease 2019 (Covid-19) transmission and make predictions on peak time, peak infected, and R 0 . Our work provides a simple and straightforward approach to estimate how infection diseases evolve and how many people may be infected.
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SciScore for 10.1101/2020.02.26.20028571: (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 10.1101/2020.02.26.20028571: (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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