Serra Nicola, Di Carlo Paola, Rea Teresa, Sergi Consolato M
Departments of Public Health, University Federico II of Naples, 80131 Naples, Italy.
Department of Health Promotion, Maternal-Childhood, Internal Medicine of Excellence "G. D'Alessandro," PROMISE, University of Palermo, Palermo 90127, Italy.
Phys Fluids (1994). 2021 Apr;33(4):041903. doi: 10.1063/5.0044061. Epub 2021 Apr 12.
Viral immune evasion by sequence variation is a significant barrier to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine design and coronavirus disease-2019 diffusion under lockdown are unpredictable with subsequent waves. Our group has developed a computational model rooted in physics to address this challenge, aiming to predict the fitness landscape of SARS-CoV-2 diffusion using a variant of the bidimensional Ising model (2DIMV) connected seasonally. The 2DIMV works in a closed system composed of limited interaction subjects and conditioned by only temperature changes. Markov chain Monte Carlo method shows that an increase in temperature implicates reduced virus diffusion and increased mobility, leading to increased virus diffusion.
通过序列变异进行病毒免疫逃逸是严重急性呼吸综合征冠状病毒2（SARS-CoV-2）疫苗设计的重大障碍，而在封锁措施下2019冠状病毒病的传播具有不可预测性，后续还会出现多波疫情。我们团队开发了一种基于物理学的计算模型来应对这一挑战，旨在使用季节性连接的二维伊辛模型变体（2DIMV）预测SARS-CoV-2传播的适应性景观。2DIMV在一个由有限相互作用主体组成的封闭系统中运行，仅受温度变化影响。马尔可夫链蒙特卡罗方法表明，温度升高意味着病毒传播减少和流动性增加，从而导致病毒传播增加。
