Program in Computational Science, The University of Texas at El Paso, El Paso, TX 79968-0514, USA.
Math Biosci Eng. 2011 Jan;8(1):183-97. doi: 10.3934/mbe.2011.8.183.
A discrete time Susceptible - Asymptomatic - Infectious - Treated - Recovered (SAITR) model is introduced in the context of influenza transmission. We evaluate the potential effect of control measures such as social distancing and antiviral treatment on the dynamics of a single outbreak. Optimal control theory is applied to identify the best way of reducing morbidity and mortality at a minimal cost. The problem is solved by using a discrete version of Pontryagin's maximum principle. Numerical results show that dual strategies have stronger impact in the reduction of the final epidemic size.
本文提出了一个离散时间的易感-无症状-感染-治疗-恢复（SAITR）模型，用于流感传播的研究。我们评估了社交距离和抗病毒治疗等控制措施对单一疫情动态的潜在影响。最优控制理论被用于确定在最小成本下降低发病率和死亡率的最佳方法。该问题通过使用庞特里亚金极大值原理的离散版本得到解决。数值结果表明，双重策略在减少最终疫情规模方面具有更强的影响力。
