This article is a Preprint
Preprints are preliminary research reports that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preprints posted online allow authors to receive rapid feedback and the entire scientific community can appraise the work for themselves and respond appropriately. Those comments are posted alongside the preprints for anyone to read them and serve as a post publication assessment.
In Silico Modeling of Virus Particle Propagation and Infectivity along the Respiratory Tract: A Case Study for SARS-COV-2 (preprint)
biorxiv; 2020.
Preprint
in English
| bioRxiv | ID: ppzbmed-10.1101.2020.08.20.259242
ABSTRACT
Respiratory viruses including Respiratory syncytial virus (RSV), influenza virus and cornaviruses such as Middle Eastern respiratory virus (MERS) and SARS-CoV-2 infect and cause serious and sometimes fatal disease in thousands of people annually. It is critical to understand virus propagation dynamics within the respiratory system because new insights will increase our understanding of virus pathogenesis and enable infection patterns to be more predictable in vivo, which will enhance targeting of vaccines and drug delivery. This study presents a computational model of virus propagation within the respiratory tract network. The model includes the generation network branch structure of the respiratory tract, biophysical and infectivity properties of the virus, as well as air flow models that aid the circulation of the virus particles. The model can also consider the impact of the immune response aim to inhibit virus replication and spread. The model was applied to the SARS-CoV-2 virus by integrating data on its life-cycle, as well as density of Angiotensin Converting Enzyme (ACE2) expressing cells along the respiratory tract network. Using physiological data associated with the respiratory rate and virus load that is inhaled, the model can improve our understanding of the concentration and spatiotemporal dynamics of virus.
Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Main subject:
Respiratory Syncytial Virus Infections
/
Severe Acute Respiratory Syndrome
Language:
English
Year:
2020
Document Type:
Preprint
Similar
MEDLINE
...
LILACS
LIS