利用活性布朗粒子研究传染的微观动力学：普适标度与受保护程度控制的传播
Microscopic dynamics of contagion using active Brownian particles: universal scaling and propagation controlled by protection
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中文总结 AI 辅助
该研究利用活性布朗粒子模型，发现受保护个体比例约30%为传染状态的交叉阈值，低于阈值时最大传染速率遵循普适标度，高于阈值时保护成为主导控制机制，为疫情动力学研究提供了新框架。
中文摘要 AI 辅助
理解个体保护措施与种群密度如何影响疫情传播，仍是流行病学的核心挑战。经典仓室模型虽能成功描述疫情的时间演化，但未明确考虑个体的微观运动与空间组织。本研究采用基于智能体的活性布朗粒子（Active Brownian Particles, ABPs）模型探究传染动力学，其中自驱动智能体通过局部接触相互作用，且设定了一定比例的受保护个体。通过系统改变受保护个体比例与种群密度，研究人员识别出两种不同的传染状态，二者由约30%的交叉保护水平分隔。低于该阈值时，最大传染速率遵循普适标度ν_max∝φ^(1/2)，表明疾病传播主要由相遇频率决定；高于该阈值时，普适标度消失，保护成为控制疫情传播的主导机制，且在低密度种群中抑制效果最强。这些结果表明，微观活性物质模型为研究超越完全混合种群模型假设的疫情动力学提供了强大框架，揭示了空间组织与个体保护如何共同决定传染动力学。
英文摘要
Understanding how individual protection and population density influence epidemic spreading remains a central challenge in epidemiology. While classical compartmental models successfully describe the temporal evolution of epidemics, they do not explicitly account for the microscopic motion and spatial organisation of individuals. Here, we investigate contagion dynamics using an agent-based model of Active Brownian Particles (ABPs), where self-propelled agents interact through local contact and a prescribed fraction of the population is protected. By systematically varying the protected-agent fraction and the population density, we identify two distinct contagion regimes separated by a crossover protection of approximately $30\%$. Below this threshold, the maximum contagion rate follows the universal scaling $ν_{\mathrm{max}}\proptoϕ^{1/2}$, indicating that disease transmission is governed primarily by frequency of encounters. Above the threshold, universal scaling is lost and protection becomes the dominant mechanism controlling epidemic spreading, with the strongest suppression occurring in low-density populations. These results demonstrate that microscopic active-matter models provide a powerful framework for investigating epidemic dynamics beyond the assumptions of well-mixed population models and reveal how spatial organisation and individual protection jointly determine contagion dynamics.
发表机构
- Universidad de Guanajuato（瓜纳华托大学）
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