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原文連結
論文資訊
- 類型：已發表論文
- 日期：2021-05-19
摘要
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 免疫 response are challenging to study in vivo, we developed Spatial 免疫 Model of Corona病毒 (SIMCoV), a scalable 計算 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 that spatially dispersed infections lead to increased viral loads. The model 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 pat
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