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原文連結
論文資訊
- 類型：已發表論文
- 日期：2025-06-02
摘要
數學 models have been used for about 30 years to improve our understanding of 病毒-host interaction, in particular during chronic infections. During the COVID-19 pandemic, these models have been used to provide insights into the natural history of acute SARS-CoV-2 infection, optimize antiviral treatment strategies, understand factors associated with 傳播, and optimize surveillance systems. The impact of modeling has been accelerated by the availability of unprecedented multidimensional 免疫 data from animal and human systems, which enhanced partnerships between experimentalists and theorists and led to exciting new modeling and 統計 developments. In this mini review, we examine the lessons learned from the COVID-19 pandemic and discuss the main insights provided by 數學 models of viral dynamics at the
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