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Research Article
Yueheng Lan
Beijing University of Posts and Telecommunications
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In this paper, we construct a stochastic model of the 2019-nCoV transmission in a confi ned space, which gives a detailed account of the interaction between the spreading virus and mobile individuals. Di fferent aspects of the interaction at mesoscopic level, such as the human motion, the shedding and spreading of the virus, its contamination and invasion of the human body and the response of the human immune system, are touched upon in the model, thier relative importance during the course of infection being evaluated. The model provides a bridge linking the epidemic statistics to the physiological parameters of individuals and may serve a theoretical guidance for epidemic prevention and control.
Keywords
2019-nCoV, Stochastic Model,Epidemic prevention and control , Con fined space
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This is a preprint. It has not completed peer review.
Research Article
Yueheng Lan
Beijing University of Posts and Telecommunications
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 21 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epidemiology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
In this paper, we construct a stochastic model of the 2019-nCoV transmission in a confi ned space, which gives a detailed account of the interaction between the spreading virus and mobile individuals. Di fferent aspects of the interaction at mesoscopic level, such as the human motion, the shedding and spreading of the virus, its contamination and invasion of the human body and the response of the human immune system, are touched upon in the model, thier relative importance during the course of infection being evaluated. The model provides a bridge linking the epidemic statistics to the physiological parameters of individuals and may serve a theoretical guidance for epidemic prevention and control.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
This preprint is available for download as a PDF.
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