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Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection.
Chakravarty, Aranyak; Panchagnula, Mahesh V; Patankar, Neelesh A.
  • Chakravarty A; School of Nuclear Studies and Application, Jadavpur University, Kolkata, India.
  • Panchagnula MV; Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
  • Patankar NA; Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.
Front Physiol ; 14: 1073165, 2023.
Article in English | MEDLINE | ID: covidwho-2239626
ABSTRACT
Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung-which may cause a severe infection-is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5-7 days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Vaccines Language: English Journal: Front Physiol Year: 2023 Document Type: Article Affiliation country: Fphys.2023.1073165

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Vaccines Language: English Journal: Front Physiol Year: 2023 Document Type: Article Affiliation country: Fphys.2023.1073165