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Modeling insights into SARS-CoV-2 respiratory tract infections prior to immune protection.
Chen, Alexander; Wessler, Timothy; Daftari, Katherine; Hinton, Kameryn; Boucher, Richard C; Pickles, Raymond; Freeman, Ronit; Lai, Samuel K; Forest, M Gregory.
  • Chen A; Department of Mathematics, CSU Dominguez Hills, Carson, California.
  • Wessler T; Department of Mathematics, UNC Chapel Hill, Chapel Hill, North Carolina. Electronic address: tswessler@gmail.com.
  • Daftari K; Department of Mathematics, UNC Chapel Hill, Chapel Hill, North Carolina.
  • Hinton K; Department of Applied Physical Sciences, UNC Chapel Hill, Chapel Hill, North Carolina.
  • Boucher RC; Marsico Lung Institute, UNC Chapel Hill, Chapel Hill, North Carolina.
  • Pickles R; Marsico Lung Institute, UNC Chapel Hill, Chapel Hill, North Carolina; Department of Microbiology and Immunology, UNC Chapel Hill, Chapel Hill, North Carolina.
  • Freeman R; Department of Applied Physical Sciences, UNC Chapel Hill, Chapel Hill, North Carolina.
  • Lai SK; Department of Microbiology and Immunology, UNC Chapel Hill, Chapel Hill, North Carolina; Joint Department of Biomedical Engineering, UNC Chapel Hill and NC State University, Chapel Hill and Raleigh, North Carolina; Division of Pharmacoengineering and Molecular Pharmaceutics, Eshelman School of Pharm
  • Forest MG; Department of Mathematics, UNC Chapel Hill, Chapel Hill, North Carolina; Department of Applied Physical Sciences, UNC Chapel Hill, Chapel Hill, North Carolina; Joint Department of Biomedical Engineering, UNC Chapel Hill and NC State University, Chapel Hill and Raleigh, North Carolina. Electronic add
Biophys J ; 121(9): 1619-1631, 2022 05 03.
Article in English | MEDLINE | ID: covidwho-1767943
ABSTRACT
Mechanistic insights into human respiratory tract (RT) infections from SARS-CoV-2 can inform public awareness as well as guide medical prevention and treatment for COVID-19 disease. Yet the complexity of the RT and the inability to access diverse regions pose fundamental roadblocks to evaluation of potential mechanisms for the onset and progression of infection (and transmission). We present a model that incorporates detailed RT anatomy and physiology, including airway geometry, physical dimensions, thicknesses of airway surface liquids (ASLs), and mucus layer transport by cilia. The model further incorporates SARS-CoV-2 diffusivity in ASLs and best-known data for epithelial cell infection probabilities, and, once infected, duration of eclipse and replication phases, and replication rate of infectious virions. We apply this baseline model in the absence of immune protection to explore immediate, short-term outcomes from novel SARS-CoV-2 depositions onto the air-ASL interface. For each RT location, we compute probability to clear versus infect; per infected cell, we compute dynamics of viral load and cell infection. Results reveal that nasal infections are highly likely within 1-2 days from minimal exposure, and alveolar pneumonia occurs only if infectious virions are deposited directly into alveolar ducts and sacs, not via retrograde propagation to the deep lung. Furthermore, to infect just 1% of the 140 m2 of alveolar surface area within 1 week, either 103 boluses each with 106 infectious virions or 106 aerosols with one infectious virion, all physically separated, must be directly deposited. These results strongly suggest that COVID-19 disease occurs in stages a nasal/upper RT infection, followed by self-transmission of infection to the deep lung. Two mechanisms of self-transmission are persistent aspiration of infected nasal boluses that drain to the deep lung and repeated rupture of nasal aerosols from infected mucosal membranes by speaking, singing, or cheering that are partially inhaled, exhaled, and re-inhaled, to the deep lung.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies Limits: Humans Language: English Journal: Biophys J Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies Limits: Humans Language: English Journal: Biophys J Year: 2022 Document Type: Article