ArticlePLoS computational biology2021
Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- Spatial Immune Model of Alveolar Lung Infection (SIMALI) Identifies Structural Determinants of Lung Inflammation.Research square · 2026Article
- Multimodal data integration to determine viral and innate immune kinetics in human airway epithelium.PLoS computational biology · 2026Article
- Bigger is faster in the adaptive immune response.Scientific reports · 2025Article
- Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025Article
- Viral Dynamic Models During COVID-19: Are We Ready for the Next Pandemic?CPT: pharmacometrics & systems pharmacology · 2025Review
- A biomathematical model of SARS-CoV-2 in Syrian hamsters.Scientific reports · 2024Article
- Quantitatively Mapping Immune Control during Influenza.Current opinion in systems biology · 2024Article
- Vaccine and antiviral drug promise for preventing post-acute sequelae of COVID-19, and their combination for its treatment.Frontiers in immunology · 2024Article
- Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review.Microorganisms · 2023Review
- An agent-based modeling approach for lung fibrosis in response to COVID-19.PLoS computational biology · 2023Article
- Influence of cell type specific infectivity and tissue composition on SARS-CoV-2 infection dynamics within human airway epithelium.PLoS computational biology · 2023Article
- Topological data analysis of antibody dynamics of severe and non-severe patients with COVID-19.Mathematical biosciences · 2023Article
- Modeling identifies variability in SARS-CoV-2 uptake and eclipse phase by infected cells as principal drivers of extreme variability in nasal viral load in the 48 h post infection.Journal of theoretical biology · 2023Article
- Antibody protection from SARS-CoV-2 respiratory tract exposure and infection.Journal of theoretical biology · 2023Article
- The two-stage molecular scenery of SARS-CoV-2 infection with implications to disease severity: An in-silico quest.Frontiers in immunology · 2023Article
- A hybrid discrete-continuum model of immune responses to SARS-CoV-2 infection in the lung alveolar region, with a focus on interferon induced innate response.Journal of theoretical biology · 2022Article
- Article
- Modeling insights into SARS-CoV-2 respiratory tract infections prior to immune protection.Biophysical journal · 2022Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.